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Huang Y, Ren S, Yang Q. Efficacy and Safety of Excision Combination Therapies for Earlobe Keloids: A Systematic Review and Meta-analysis. Aesthetic Plast Surg 2024; 48:2757-2770. [PMID: 38789810 DOI: 10.1007/s00266-024-04092-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Accepted: 04/15/2024] [Indexed: 05/26/2024]
Abstract
BACKGROUND Different combinations of excision and adjuvant therapies have been applied to improve outcomes for earlobe keloids, though evidence in this field is still lacking. OBJECTIVES This study sought to systematically investigate efficacy and safety of these treatments. METHODS We conducted a systematic search on PubMed, Embase, Web of Science, and Cochrane Library to find all relevant studies. Meta-analysis of recurrence rates (RRs) and adverse event rates with 95% confidence intervals, and individual participants data (IPD) were calculated for each intervention when possible. Otherwise, narrative syntheses were performed. RESULTS A total of 85 articles, covering 23 treatments for earlobe keloids, were included, indicating a preference for multiple combination therapy. The estimated RRs for 6 interventions (i.e., excision monotherapy, combinations of excision with imiquimod, pressure therapy, radiotherapy, steroids, and steroids with pressure therapy) appeared to be comparable. Electron radiotherapy was found to have potential advantages over X-ray treatment, contributing to the observed heterogeneity. Further meta-analysis using IPD revealed that both combination therapies of excision plus steroid therapy (p=0.003) and excision plus radiotherapy (p=0.003) yielded better recurrence-free survival compared to excision alone. The median recurrence-free interval for combination therapy was 10 months. Adverse event rates were similar among different intervention groups. CONCLUSIONS This study suggests that combining excision with radiotherapy or perioperative steroid therapy has the potential to improve prognosis of earlobe keloids without increasing the risk of adverse events. Overall evaluation of patients' conditions and further studies with sufficient follow-up are warranted for clinical practice. LEVEL OF EVIDENCE IV This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .
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Affiliation(s)
- Ying Huang
- Department of Comprehensive Plastic Surgery, Plastic Surgery Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Badachu Road 33, Beijing, People's Republic of China
| | - Shuofang Ren
- Department of Cardiac Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China
| | - Qinghua Yang
- Department of Comprehensive Plastic Surgery, Plastic Surgery Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Badachu Road 33, Beijing, People's Republic of China.
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Fouad K, Vavrek R, Surles-Zeigler MC, Huie JR, Radabaugh HL, Gurkoff GG, Visser U, Grethe JS, Martone ME, Ferguson AR, Gensel JC, Torres-Espin A. A practical guide to data management and sharing for biomedical laboratory researchers. Exp Neurol 2024; 378:114815. [PMID: 38762093 DOI: 10.1016/j.expneurol.2024.114815] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2023] [Revised: 05/13/2024] [Accepted: 05/14/2024] [Indexed: 05/20/2024]
Abstract
Effective data management and sharing have become increasingly crucial in biomedical research; however, many laboratory researchers lack the necessary tools and knowledge to address this challenge. This article provides an introductory guide into research data management (RDM), and the importance of FAIR (Findable, Accessible, Interoperable, and Reusable) data-sharing principles for laboratory researchers produced by practicing scientists. We explore the advantages of implementing organized data management strategies and introduce key concepts such as data standards, data documentation, and the distinction between machine and human-readable data formats. Furthermore, we offer practical guidance for creating a data management plan and establishing efficient data workflows within the laboratory setting, suitable for labs of all sizes. This includes an examination of requirements analysis, the development of a data dictionary for routine data elements, the implementation of unique subject identifiers, and the formulation of standard operating procedures (SOPs) for seamless data flow. To aid researchers in implementing these practices, we present a simple organizational system as an illustrative example, which can be tailored to suit individual needs and research requirements. By presenting a user-friendly approach, this guide serves as an introduction to the field of RDM and offers practical tips to help researchers effortlessly meet the common data management and sharing mandates rapidly becoming prevalent in biomedical research.
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Affiliation(s)
- K Fouad
- Department of Physical Therapy, Faculty of Rehabilitation Medicine, University of Alberta, Edmonton, AB, Canada.
| | - R Vavrek
- Department of Physical Therapy, Faculty of Rehabilitation Medicine, University of Alberta, Edmonton, AB, Canada
| | - M C Surles-Zeigler
- Department of Neuroscience, University of California, San Diego, La Jolla, CA, United States
| | - J R Huie
- Department of Neurosurgery, Brain and Spinal Injury Center, Weill Institutes for Neurosciences, University of California, San Francisco, San Francisco, CA, United States; San Francisco Veterans Affairs Healthcare System, San Francisco, CA, United States
| | - H L Radabaugh
- Department of Neurosurgery, Brain and Spinal Injury Center, Weill Institutes for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - G G Gurkoff
- Center for Neuroscience, University of California Davis, Davis, CA, United States; Department of Neurological Surgery, University of California Davis, Davis, CA, United States; Northern California Veterans Affairs Healthcare System, Martinez, CA, United States
| | - U Visser
- Department of Computer Science, University of Miami, Coral Gables, FL, United States
| | - J S Grethe
- Department of Neuroscience, University of California, San Diego, La Jolla, CA, United States
| | - M E Martone
- Department of Neuroscience, University of California, San Diego, La Jolla, CA, United States; San Francisco Veterans Affairs Healthcare System, San Francisco, CA, United States
| | - A R Ferguson
- Department of Neurosurgery, Brain and Spinal Injury Center, Weill Institutes for Neurosciences, University of California, San Francisco, San Francisco, CA, United States; San Francisco Veterans Affairs Healthcare System, San Francisco, CA, United States
| | - J C Gensel
- Spinal Cord and Brain Injury Research Center and Department of Physiology, University of Kentucky College of Medicine, Lexington, KY, United States.
| | - A Torres-Espin
- Department of Physical Therapy, Faculty of Rehabilitation Medicine, University of Alberta, Edmonton, AB, Canada; Department of Neurosurgery, Brain and Spinal Injury Center, Weill Institutes for Neurosciences, University of California, San Francisco, San Francisco, CA, United States; School of Public Health Sciences, University of Waterloo, Waterloo, ON, Canada.
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Patabendige M, Chan F, Vayssiere C, Ehlinger V, Van Gemund N, le Cessie S, Prager M, Marions L, Rozenberg P, Chevret S, Young DC, Le Roux PA, Gregson S, Waterstone M, Rolnik DL, Mol BW, Li W. Vaginal misoprostol versus vaginal dinoprostone for cervical ripening and induction of labour: An individual participant data meta-analysis of randomised controlled trials. BJOG 2024; 131:1167-1180. [PMID: 38425020 DOI: 10.1111/1471-0528.17794] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Revised: 02/08/2024] [Accepted: 02/09/2024] [Indexed: 03/02/2024]
Abstract
BACKGROUND Induction of labour (IOL) is common practice and different methods carry different effectiveness and safety profiles. OBJECTIVES To compare the effectiveness, and maternal and perinatal safety outcomes of IOL with vaginal misoprostol versus vaginal dinoprostone using individual participant data from randomised clinical trials. SEARCH STRATEGY The following databases were searched from inception to March 2023: CINAHL Plus, ClinicalTrials.gov, Cochrane Pregnancy and Childbirth Group Trial Register, Ovid Embase, Ovid Emcare, Ovid MEDLINE, Scopus and the World Health Organization (WHO) International Clinical Trials Registry Platform (ICTRP). SELECTION CRITERIA Randomised controlled trials (RCTs), with viable singleton gestation, no language restrictions, and all published and unpublished data. DATA COLLECTION AND ANALYSIS An individual participant data meta-analysis was carried out. MAIN RESULTS Ten of 52 eligible trials provided individual participant data, of which two were excluded after checking data integrity. The remaining eight trials compared low-dose vaginal misoprostol versus dinoprostone, including 4180 women undergoing IOL, which represents 32.8% of all participants in the published RCTs. Of these, 2077 were assigned to low-dose vaginal misoprostol and 2103 were assigned to vaginal dinoprostone. Compared with vaginal dinoprostone, low-dose vaginal misoprostol had a comparable rate of vaginal birth. Composite adverse perinatal outcomes did not differ between the groups. Compared with vaginal dinoprostone, composite adverse maternal outcomes were significantly lower with low-dose vaginal misoprostol (aOR 0.80, 95% CI 0.65-0.98, P = 0.03, I2 = 0%). CONCLUSIONS Low-dose vaginal misoprostol and vaginal dinoprostone for IOL are comparable in terms of effectiveness and perinatal safety. However, low-dose vaginal misoprostol is likely to lead to a lower rate of composite adverse maternal outcomes than vaginal dinoprostone.
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Affiliation(s)
- Malitha Patabendige
- Department of Obstetrics and Gynaecology, Monash Medical Centre, Monash University, Clayton, Victoria, Australia
- Ministry of Health, Colombo, Sri Lanka
- Monash Health - Casey Hospital, Berwick, Victoria, Australia
| | - Fei Chan
- Department of Obstetrics and Gynaecology, Monash Medical Centre, Monash University, Clayton, Victoria, Australia
| | - Christophe Vayssiere
- Centre for Epidemiology and Research in Population Health (CERPOP), UMR1295, Toulouse University, Inserm, Paul Sabatier University, Toulouse, France
- Department of Obstetrics and Gynaecology, Paule de Viguier Hospital, Toulouse University Hospital, Toulouse, France
| | - Virginie Ehlinger
- Centre for Epidemiology and Research in Population Health (CERPOP), UMR1295, Toulouse University, Inserm, Paul Sabatier University, Toulouse, France
| | - Nicolette Van Gemund
- Department of Obstetrics and Gynaecology, Franciscus Gasthuis, Rotterdam, the Netherlands
| | - Saskia le Cessie
- Department of Biomedical Data Sciences, Leiden University Medical Centre, Leiden, the Netherlands
| | - Martina Prager
- Division of Obstetrics and Gynaecology, Department of Women's and Children's Health, Karolinska University Hospital, Karolinska Institutet, Stockholm, Sweden
| | - Lena Marions
- Division of Obstetrics and Gynaecology, Department of Women's and Children's Health, Karolinska University Hospital, Karolinska Institutet, Stockholm, Sweden
| | - Patrick Rozenberg
- Department of Gynaecology and Obstetrics, Poissy Hospital, University Paris V, Paris, France
| | - Sylvie Chevret
- Department of Biostatistics, Hopital Saint-Louis, University Paris VII, INSERM, Paris, France
| | - David C Young
- Department of Obstetrics and Gynaecology, Dalhousie University, Halifax, Nova Scotia, Canada
- IWK Health Centre, Halifax, Nova Scotia, Canada
| | - Paul A Le Roux
- Department of Obstetrics and Gynaecology, University of Cape Town, Cape Town, South Africa
| | - Sarah Gregson
- Maternity Unit, Queen Mary's Sidcup NHS Trust, Kent, UK
| | | | - Daniel L Rolnik
- Department of Obstetrics and Gynaecology, Monash Medical Centre, Monash University, Clayton, Victoria, Australia
| | - Ben W Mol
- Department of Obstetrics and Gynaecology, Monash Medical Centre, Monash University, Clayton, Victoria, Australia
| | - Wentao Li
- Department of Obstetrics and Gynaecology, Monash Medical Centre, Monash University, Clayton, Victoria, Australia
- National Perinatal Epidemiology and Statistics Unit (NPESU), Centre for Big Data Research in Health, and School of Clinical Medicine, Faculty of Medicine, University of New South Wales, Sydney, Australia
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Dugan C, Peeling P, Burden R, Richards T. Efficacy of iron supplementation on physical capacity in non-anaemic iron-deficient individuals: protocol for an individual patient data meta-analysis. Syst Rev 2024; 13:182. [PMID: 39010146 PMCID: PMC11247796 DOI: 10.1186/s13643-024-02559-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/06/2023] [Accepted: 05/13/2024] [Indexed: 07/17/2024] Open
Abstract
BACKGROUND A deficiency in iron stores is associated with various adverse health complications, which, if left untreated, can progress to states of anaemia, whereby there is significant detriment to an individual's work capacity and quality of life due to compromised erythropoiesis. The most common methods employed to treat an iron deficiency include oral iron supplementation and, in persistent and/or unresponsive cases, intravenous iron therapy. The efficacy of these treatments, particularly in states of iron deficiency without anaemia, is equivocal. Indeed, both randomised control trials and aggregate data meta-analyses have produced conflicting evidence. Therefore, this study aims to assess the efficacy of both oral and intravenous iron supplementation on physical capacity, quality of life, and fatigue scores in iron-deficient non-anaemic individuals using individual patient data (IPD) meta-analysis techniques. METHODS All potential studies, irrespective of design, will be sourced through systematic searches on the following databases: Cochrane Central Register of Controlled Trials, MEDLINE Ovid, Embase Ovid, Web of Science: Science Citation Index Expanded, Web of Science: Conference Proceedings Citation Index-Science, ClinicalTrials.gov, and World Health Organization (WHO) International Clinical Trials Registry Platform. Individual patient data from all available trials will be included and subsequently analysed in a two-stage approach. Predetermined subgroup and sensitivity analyses will be employed to further explain results. DISCUSSION The significance of this IPD meta-analysis is one of consolidating a clear consensus to better inform iron-deficient individuals of the physiological response associated with iron supplementation. The IPD approach, to the best of our knowledge, is novel for this research topic. As such, the findings will significantly contribute to the current body of evidence. SYSTEMATIC REVIEW REGISTRATION PROSPERO CRD42020191739.
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Affiliation(s)
- Cory Dugan
- School of Human Sciences, University of Western Australia, Perth, Australia.
| | - Peter Peeling
- School of Human Sciences, University of Western Australia, Perth, Australia
| | - Richard Burden
- National Centre for Sport and Exercise Medicine, School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK
| | - Toby Richards
- Division of Surgery, University of Western Australia, Perth, Australia
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Bonofiglio F. Survival Analysis Without Sharing of Individual Patient Data by Using a Gaussian Copula. Pharm Stat 2024. [PMID: 38973072 DOI: 10.1002/pst.2415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 03/10/2024] [Accepted: 06/11/2024] [Indexed: 07/09/2024]
Abstract
Cox regression and Kaplan-Meier estimations are often needed in clinical research and this requires access to individual patient data (IPD). However, IPD cannot always be shared because of privacy or proprietary restrictions, which complicates the making of such estimations. We propose a method that generates pseudodata replacing the IPD by only sharing non-disclosive aggregates such as IPD marginal moments and a correlation matrix. Such aggregates are collected by a central computer and input as parameters to a Gaussian copula (GC) that generates the pseudodata. Survival inferences are computed on the pseudodata as if it were the IPD. Using practical examples we demonstrate the utility of the method, via the amount of IPD inferential content recoverable by the GC. We compare GC to a summary-based meta-analysis and an IPD bootstrap distributed across several centers. Other pseudodata approaches are also considered. In the empirical results, GC approximates the utility of the IPD bootstrap although it might yield more conservative inferences and it might have limitations in subgroup analyses. Overall, GC avoids many legal problems related to IPD privacy or property while enabling approximation of common IPD survival analyses otherwise difficult to conduct. Sharing more IPD aggregates than is currently practiced could facilitate "second purpose"-research and relax concerns regarding IPD access.
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Affiliation(s)
- Federico Bonofiglio
- Evidence and Value Generation Team, Veramed GmbH, Frankfurt am Main, Germany
- Veramed Ltd, Twickenham, UK
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Van Hoogenhuijze N, Broekmans F. Reply. How much evidence is needed to stop calling endometrial scratching 'controversial'? Hum Reprod Update 2024:dmae019. [PMID: 38908021 DOI: 10.1093/humupd/dmae019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2024] [Indexed: 06/24/2024] Open
Affiliation(s)
- Nienke Van Hoogenhuijze
- Department of Gynaecology & Reproductive Medicine, University Medical Centre Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Frank Broekmans
- Department of Gynaecology & Reproductive Medicine, University Medical Centre Utrecht, Utrecht University, Utrecht, the Netherlands
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7
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Moore H, Pereira B, Fillon A, Miguet M, Masurier J, Beaulieu K, Finlayson G, Thivel D. The association between obesity severity and food reward in adolescents with obesity: a one-stage individual participant data meta-analysis. Eur J Nutr 2024; 63:1241-1255. [PMID: 38376518 DOI: 10.1007/s00394-024-03348-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Accepted: 01/20/2024] [Indexed: 02/21/2024]
Abstract
BACKGROUND Food reward and cue reactivity have been linked prospectively to problematic eating behaviours and excess weight gain in adults and children. However, evidence to date in support of an association between degree of adiposity and food reward is tenuous. A non-linear relationship between reward sensitivity and obesity degree has been previously proposed, suggesting a peak is reached in mild obesity and decreases in more severe obesity in a quadratic fashion. OBJECTIVE To investigate and characterise in detail the relationship between obesity severity, body composition, and explicit and implicit food reward in adolescents with obesity. METHODS Data from seven clinical trials in adolescents with obesity were aggregated and analysed in an independent participant data meta-analysis. Linear and curvilinear relationships between the degree of obesity and explicit and implicit reward for sweet and high fat foods were tested in fasted and fed states with BMI-z score as a continuous and discrete predictor using clinically recognised partitions. RESULTS Although positive associations between obesity severity and preference for high-fat (i.e. energy dense) foods were observed when fasted, none reached significance in either analysis. Conversely, adiposity was reliably associated with lower reward for sweet, particularly when measured as implicit wanting (p = 0.012, ηp2 = 0.06), independent of metabolic state. However, this significant association was only observed in the linear model. Fat distribution was consistently associated with explicit and implicit preference for high-fat foods. CONCLUSIONS A limited relationship was demonstrated between obesity severity and food reward in adolescents, although a lower preference for sweet could be a signal of severe obesity in a linear trend. Obesity is likely a heterogenous condition associated with multiple potential phenotypes, which metrics of body composition may help define. CLINICAL TRIAL REGISTRATIONS NCT02925572: https://classic. CLINICALTRIALS gov/ct2/show/NCT02925572 . NCT03807609: https://classic. CLINICALTRIALS gov/ct2/show/NCT03807609 . NCT03742622: https://classic. CLINICALTRIALS gov/ct2/show/NCT03742622 . NCT03967782: https://classic. CLINICALTRIALS gov/ct2/show/NCT03967782 . NCT03968458: https://classic. CLINICALTRIALS gov/ct2/show/NCT03968458 . NCT04739189: https://classic. CLINICALTRIALS gov/ct2/show/NCT04739189 . NCT05365685: https://www. CLINICALTRIALS gov/study/NCT05365685?tab=history .
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Affiliation(s)
- Halim Moore
- EA 3533, Laboratory of the Metabolic Adaptations to Exercise Under Physiological and Pathological Conditions (AME2P), CRNH Auvergne, Clermont Auvergne University, 3 Rue de La Chebarde, 63170, Clermont-Ferrand, Aubière, France.
| | - Bruno Pereira
- Unit of Biostatistics (DRCI), Clermont-Ferrand University Hospital, Clermont-Ferrand, France
| | - Alicia Fillon
- EA 3533, Laboratory of the Metabolic Adaptations to Exercise Under Physiological and Pathological Conditions (AME2P), CRNH Auvergne, Clermont Auvergne University, 3 Rue de La Chebarde, 63170, Clermont-Ferrand, Aubière, France
- Observatoire National de l'Activité Physique et de la Sédentarité (ONAPS), Faculty of Medicine, Clermont Auvergne University, Clermont-Ferrand, France
| | - Maud Miguet
- Laboratoire CIAMS Complexité, Innovation, Activités Motrices et Sportives, Fédération SAPRéM, 2 Allée du Château, 45062, Orléans Cedex 2, France
- Department of Surgical Sciences, Functional Pharmacology and Neuroscience, Uppsala University, Uppsala, Sweden
| | - Julie Masurier
- Nutrition Obesity Clincal Center UGECAM, Clermont-Ferrand, France
| | - Kristine Beaulieu
- Appetite Control and Energy Balance Research Group, School of Psychology, Faculty of Medicine and Health, University of Leeds, Leeds, West Yorkshire, UK
| | - Graham Finlayson
- Appetite Control and Energy Balance Research Group, School of Psychology, Faculty of Medicine and Health, University of Leeds, Leeds, West Yorkshire, UK
| | - David Thivel
- EA 3533, Laboratory of the Metabolic Adaptations to Exercise Under Physiological and Pathological Conditions (AME2P), CRNH Auvergne, Clermont Auvergne University, 3 Rue de La Chebarde, 63170, Clermont-Ferrand, Aubière, France
- Observatoire National de l'Activité Physique et de la Sédentarité (ONAPS), Faculty of Medicine, Clermont Auvergne University, Clermont-Ferrand, France
- International Research Chair Health in Motion, Clermont Auvergne University Foundation, Clermont-Ferrand, France
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Moutchia J, McClelland RL, Al-Naamani N, Appleby DH, Holmes JH, Minhas J, Mazurek JA, Palevsky HI, Ventetuolo CE, Kawut SM. Pulmonary arterial hypertension treatment: an individual participant data network meta-analysis. Eur Heart J 2024; 45:1937-1952. [PMID: 38416633 PMCID: PMC11143388 DOI: 10.1093/eurheartj/ehae049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 11/20/2023] [Accepted: 01/18/2024] [Indexed: 03/01/2024] Open
Abstract
BACKGROUND AND AIMS Effective therapies that target three main signalling pathways are approved to treat pulmonary arterial hypertension (PAH). However, there are few large patient-level studies that compare the effectiveness of these pathways. The aim of this analysis was to compare the effectiveness of the treatment pathways in PAH and to assess treatment heterogeneity. METHODS A network meta-analysis was performed using individual participant data of 6811 PAH patients from 20 Phase III randomized clinical trials of therapy for PAH that were submitted to the US Food and Drug Administration. Individual drugs were grouped by the following treatment pathways: endothelin, nitric oxide, and prostacyclin pathways. RESULTS The mean (±standard deviation) age of the sample was 49.2 (±15.4) years; 78.4% were female, 59.7% had idiopathic PAH, and 36.5% were on background PAH therapy. After covariate adjustment, targeting the endothelin + nitric oxide pathway {β: 43.7 m [95% confidence interval (CI): 32.9, 54.4]}, nitric oxide pathway [β: 29.4 m (95% CI: 22.6, 36.3)], endothelin pathway [β: 25.3 m (95% CI: 19.8, 30.8)], and prostacyclin pathway [oral/inhaled β: 19.1 m (95% CI: 14.2, 24.0), intravenous/subcutaneous β: 24.4 m (95% CI: 15.1, 33.7)] significantly increased 6 min walk distance at 12 or 16 weeks compared with placebo. Treatments also significantly reduced the likelihood of having clinical worsening events. There was significant heterogeneity of treatment effects by age, body mass index, hypertension, diabetes, and coronary artery disease. CONCLUSIONS Drugs targeting the three traditional treatment pathways significantly improve outcomes in PAH, with significant treatment heterogeneity in patients with some comorbidities. Randomized clinical trials are warranted to identify the most effective treatment strategies in a personalized approach.
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Affiliation(s)
- Jude Moutchia
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Robyn L McClelland
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, USA
| | - Nadine Al-Naamani
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Dina H Appleby
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - John H Holmes
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jasleen Minhas
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jeremy A Mazurek
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Harold I Palevsky
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Corey E Ventetuolo
- Department of Medicine and Health Services, Policy and Practice, Brown University, Providence, RI, USA
| | - Steven M Kawut
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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9
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Anawalt BD. The Relationship of Sex Steroid Hormones and Clinical Outcomes Is Complex. Ann Intern Med 2024; 177:826-827. [PMID: 38739925 DOI: 10.7326/m24-0875] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/16/2024] Open
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10
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Amin-Esmaeili M, Farokhnia M, Susukida R, Leggio L, Johnson RM, Crum RM, Mojtabai R. Reduced drug use as an alternative valid outcome in individuals with stimulant use disorders: Findings from 13 multisite randomized clinical trials. Addiction 2024; 119:833-843. [PMID: 38197836 PMCID: PMC11009085 DOI: 10.1111/add.16409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Accepted: 11/10/2023] [Indexed: 01/11/2024]
Abstract
BACKGROUND AND AIMS Total abstinence has historically been the goal of treatment for substance use disorders; however, there is a growing recognition of the health benefits associated with reduced use as a harm reduction measure in stimulant use disorders treatment. We aimed to assess the validity of reduced stimulant use as an outcome measure in randomized controlled trials (RCTs) of pharmacological interventions for stimulant use disorder. DESIGN We conducted a secondary analysis of a pooled dataset of 13 RCTs. SETTING AND PARTICIPANTS Participants were individuals seeking treatment for cocaine or methamphetamine use disorders (N = 2062) in a wide range of treatment facilities in the United States. MEASUREMENTS We validated reduced stimulant use against a set of clinical indicators drawn from harmonized measurements, including severity of problems caused by drug use, comorbid depression, global severity of substance use and improvement, severity of drug-seeking behavior, craving and high-risk behaviors, all assessed at the end of the trial, as well as follow-up urine toxicology. A series of mixed effect regression models was conducted to validate reduction in frequency of use against no reduction in use and abstinence. FINDINGS More participants reduced frequency of primary drug use than achieved abstinence (18.0% vs. 14.2%, respectively). Reduced use was significantly associated with decreases in craving for the primary drug [60.1%, 95% confidence interval (CI) = 54.3%-64.7%], drug seeking behaviors (41.0%, 95% CI = 36.6%-45.7%), depression severity (39.9%, 95% CI = 30.9%-48.3%), as well as multiple measures of global improvement in psychosocial functioning and severity of drug-related problems, albeit less strongly so than abstinence. Moreover, reduced use was associated with sustained clinical benefit at follow-up, as confirmed by negative urine tests (adjusted odds ratio compared with those with no reduction in use: 0.50, 95% CI = 0.35-0.71). CONCLUSION Reduced frequency of stimulant use appears to be associated with meaningful improvement in various clinical indicators of recovery. Assessment of reduced use, in addition to abstinence, could broaden the scope of outcomes measured in randomized controlled trials of stimulant use disorders and facilitate the development of more diverse treatment approaches.
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Affiliation(s)
- Masoumeh Amin-Esmaeili
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Iranian National Center for Addiction Studies (INCAS), Tehran University of Medical Sciences, Tehran, Iran
| | - Mehdi Farokhnia
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Clinical Psychoneuroendocrinology and Neuropsychopharmacology Section, Translational Addiction Medicine Branch, National Institute on Drug Abuse Intramural Research Program and National Institute on Alcohol Abuse and Alcoholism Division of Intramural Clinical and Biological Research, National Institutes of Health, Baltimore, MD, USA
| | - Ryoko Susukida
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Lorenzo Leggio
- Clinical Psychoneuroendocrinology and Neuropsychopharmacology Section, Translational Addiction Medicine Branch, National Institute on Drug Abuse Intramural Research Program and National Institute on Alcohol Abuse and Alcoholism Division of Intramural Clinical and Biological Research, National Institutes of Health, Baltimore, MD, USA
- Medication Development Program, National Institute on Drug Abuse Intramural Research Program, National Institutes of Health, Baltimore, MD, USA
- Center for Alcohol and Addiction Studies, Department of Behavioral and Social Sciences, Brown University, Providence, RI, USA
- Division of Addiction Medicine, Department of Medicine, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Renee M Johnson
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Rosa M Crum
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Ramin Mojtabai
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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11
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Stogiannis D, Siannis F, Androulakis E. Heterogeneity in meta-analysis: a comprehensive overview. Int J Biostat 2024; 20:169-199. [PMID: 36961993 DOI: 10.1515/ijb-2022-0070] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Accepted: 02/10/2023] [Indexed: 03/26/2023]
Abstract
In recent years, meta-analysis has evolved to a critically important field of Statistics, and has significant applications in Medicine and Health Sciences. In this work we briefly present existing methodologies to conduct meta-analysis along with any discussion and recent developments accompanying them. Undoubtedly, studies brought together in a systematic review will differ in one way or another. This yields a considerable amount of variability, any kind of which may be termed heterogeneity. To this end, reports of meta-analyses commonly present a statistical test of heterogeneity when attempting to establish whether the included studies are indeed similar in terms of the reported output or not. We intend to provide an overview of the topic, discuss the potential sources of heterogeneity commonly met in the literature and provide useful guidelines on how to address this issue and to detect heterogeneity. Moreover, we review the recent developments in the Bayesian approach along with the various graphical tools and statistical software that are currently available to the analyst. In addition, we discuss sensitivity analysis issues and other approaches of understanding the causes of heterogeneity. Finally, we explore heterogeneity in meta-analysis for time to event data in a nutshell, pointing out its unique characteristics.
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Affiliation(s)
| | - Fotios Siannis
- Department of Mathematics, National and Kapodistrian University, Athens, Greece
| | - Emmanouil Androulakis
- Mathematical Modeling and Applications Laboratory, Section of Mathematics, Hellenic Naval Academy, Piraeus, Greece
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12
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Hobeika C, Ronot M, Guiu B, Ferraioli G, Iijima H, Tada T, Lee DH, Kuroda H, Lee YH, Lee JM, Kim SY, Cassinotto C, Maiocchi L, Raimondi A, Nishimura T, Kumada T, Kwon EY, Jang JK, Correas JM, Valla D, Vilgrain V, Dioguardi Burgio M. Ultrasound-based steatosis grading system using 2D-attenuation imaging: An individual patient data meta-analysis with external validation. Hepatology 2024:01515467-990000000-00856. [PMID: 38652643 DOI: 10.1097/hep.0000000000000895] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Accepted: 03/07/2024] [Indexed: 04/25/2024]
Abstract
BACKGROUND AND AIMS Noninvasive tools assessing steatosis, such as ultrasonography-based 2D-attenuation imaging (ATI), are needed to tackle the worldwide burden of steatotic liver disease. This one-stage individual patient data (IPD) meta-analysis aimed to create an ATI-based steatosis grading system. APPROACH AND RESULTS A systematic review (EMBASE + MEDLINE, 2018-2022) identified studies, including patients with histologically or magnetic resonance imaging proton-density fat fraction (MRI-PDFF)-verified ATI for grading steatosis (S0 to S3). One-stage IPD meta-analyses were conducted using generalized mixed models with a random study-specific intercept. Created ATI-based steatosis grading system (aS0 to aS3) was externally validated on a prospective cohort of patients with type 2 diabetes and metabolic dysfunction-associated steatotic liver disease (n=174, histologically and MRI-PDFF-verified steatosis). Eleven enrolled studies included 1374 patients, classified into S0, S1, S2, and S3 in 45.4%, 35.0%, 9.3%, and 10.3% of the cases. ATI was correlated with histological steatosis ( r = 0.60; 95% CI: 0.52, 0.67; p < 0.001) and MRI-PDFF ( r = 0.70; 95% CI: 0.66, 0.73; p < 0.001) but not with liver stiffness ( r = 0.03; 95% CI: -0.04, 0.11, p = 0.343). Steatosis grade was an independent factor associated with ATI (coefficient: 0.24; 95% CI: [0.22, 0.26]; p < 0.001). ATI marginal means within S0, S1, S2, and S3 subpopulations were 0.59 (95% CI: [0.58, 0.61]), 0.69 (95% CI [0.67, 0.71]), 0.78 (95% CI: [0.76, 0.81]), and 0.85 (95% CI: [0.83, 0.88]) dB/cm/MHz; all contrasts between grades were significant ( p < 0.0001). Three ATI thresholds were calibrated to create a new ATI-based steatosis grading system (aS0 to aS3, cutoffs: 0.66, 0.73, and 0.81 dB/cm/MHz). Its external validation showed Obuchowski measures of 0.84 ± 0.02 and 0.82 ± 0.02 with histologically based and MRI-PDFF-based references. CONCLUSIONS ATI is a reliable, noninvasive marker of steatosis. This validated ATI-based steatosis grading system could be valuable in assessing patients with metabolic dysfunction-associated steatotic liver disease.
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Affiliation(s)
- Christian Hobeika
- Department of HPB Surgery and Liver Transplantation, AP-HP, Hôpital Beaujon, Clichy, France
- Université Paris Cité, Inserm, CArcinose Péritoine Paris-Technologies, Paris, France
- Ajmera Transplant Centre, Toronto General Hospital, University Health Network, Toronto, Ontario, Canada
| | - Maxime Ronot
- Department of Radiology, Hôpital Beaujon, AP-HP.Nord, Clichy, France
- Université Paris Cité, Inserm, Centre de recherche sur l'inflammation, Paris, France
| | - Boris Guiu
- Department of Radiology, St-Eloi University Hospital, Montpellier, France
| | - Giovanna Ferraioli
- Dipartimento di Scienze Clinico-Chirurgiche, Diagnostiche e Pediatriche, University of Pavia, Pavia, Italy
| | - Hiroko Iijima
- Department of Internal Medicine, Division of Gastroenterology and Hepatology, Hyogo Medical University, Hyogo, Japan
| | - Toshifumi Tada
- Department of Internal Medicine, Japanese Red Cross Society Himeji Hospital, Hyogo, Japan
| | - Dong Ho Lee
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Hidekatsu Kuroda
- Department of Internal Medicine, Division of Gastroenterology and Hepatology, Iwate Medical University, Iwate, Japan
| | - Young Hwan Lee
- Department of Radiology, Wonkwang University School of Medicine and Hospital, Iksan, Korea
| | - Jeong Min Lee
- Department of Radiology, Seoul National University Hospital and Seoul National University College of Medicine, Seoul, Korea
| | - So Yeon Kim
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | | | - Laura Maiocchi
- Ultrasound Unit, Dipartimento Servizi Diagnostici e per Immagini Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Ambra Raimondi
- Dipartimento di Scienze Clinico-Chirurgiche, Diagnostiche e Pediatriche, University of Pavia, Pavia, Italy
- Ultrasound Unit, Dipartimento Servizi Diagnostici e per Immagini Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Takashi Nishimura
- Department of Internal Medicine, Division of Gastroenterology and Hepatology, Hyogo Medical University, Hyogo, Japan
| | - Takashi Kumada
- Department of Nursing, Gifu Kyoritsu University, Gifu, Japan
| | - Eun Young Kwon
- Department of Radiology, Wonkwang University School of Medicine and Hospital, Iksan, Korea
| | - Jong Keon Jang
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Jean-Michel Correas
- AP-HP, Hôpital Necker Enfants Malades, Service d'Imagerie Adulte, Paris, France
- Sorbonne Université, CNRS, INSERM Laboratoire d'Imagerie Biomédicale, Paris, France
| | - Dominique Valla
- Université Paris Cité, Inserm, Centre de recherche sur l'inflammation, Paris, France
- Service d'hépatologie, Hôpital Beaujon, Clichy, France
| | - Valérie Vilgrain
- Department of Radiology, Hôpital Beaujon, AP-HP.Nord, Clichy, France
- Université Paris Cité, Inserm, Centre de recherche sur l'inflammation, Paris, France
| | - Marco Dioguardi Burgio
- Department of Radiology, Hôpital Beaujon, AP-HP.Nord, Clichy, France
- Université Paris Cité, Inserm, Centre de recherche sur l'inflammation, Paris, France
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13
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Kim S, Can MH, Agizew TB, Auld AF, Balcells ME, Bjerrum S, Dheda K, Dorman SE, Esmail A, Fielding K, Garcia-Basteiro AL, Hanrahan CF, Kebede W, Kohli M, Luetkemeyer AF, Mita C, Reeve BWP, Silva DR, Sweeney S, Theron G, Trajman A, Vassall A, Warren JL, Yotebieng M, Cohen T, Menzies NA. Factors associated with tuberculosis treatment initiation among bacteriologically negative individuals evaluated for tuberculosis: an individual patient data meta-analysis. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.07.24305445. [PMID: 38645191 PMCID: PMC11030305 DOI: 10.1101/2024.04.07.24305445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Background Globally, over one-third of pulmonary tuberculosis (TB) disease diagnoses are made based on clinical criteria after a negative diagnostic test result. Understanding factors associated with clinicians' decisions to initiate treatment for individuals with negative test results is critical for predicting the potential impact of new diagnostics. Methods We performed a systematic review and individual patient data meta-analysis using studies conducted between January/2010 and December/2022 (PROSPERO: CRD42022287613). We included trials or cohort studies that enrolled individuals evaluated for TB in routine settings. In these studies participants were evaluated based on clinical examination and routinely-used diagnostics, and were followed for ≥1 week after the initial test result. We used hierarchical Bayesian logistic regression to identify factors associated with treatment initiation following a negative result on an initial bacteriological test (e.g., sputum smear microscopy, Xpert MTB/RIF). Findings Multiple factors were positively associated with treatment initiation: male sex [adjusted Odds Ratio (aOR) 1.61 (1.31-1.95)], history of prior TB [aOR 1.36 (1.06-1.73)], reported cough [aOR 4.62 (3.42-6.27)], reported night sweats [aOR 1.50 (1.21-1.90)], and having HIV infection but not on ART [aOR 1.68 (1.23-2.32)]. Treatment initiation was substantially less likely for individuals testing negative with Xpert [aOR 0.77 (0.62-0.96)] compared to smear microscopy and declined in more recent years. Interpretation Multiple factors influenced decisions to initiate TB treatment despite negative test results. Clinicians were substantially less likely to treat in the absence of a positive test result when using more sensitive, PCR-based diagnostics.
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Affiliation(s)
- Sun Kim
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Melike Hazal Can
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | | | - Andrew F. Auld
- U.S. Centers for Disease Control and Prevention, Lusaka, Zambia
| | - Maria Elvira Balcells
- Infectious Disease Department, School of Medicine, Pontificia Universidad Católica de Chile
| | - Stephanie Bjerrum
- Department of Clinical Research, University of Southern Denmark, Odense Denmark
- Department of Infectious Diseases, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Keertan Dheda
- Centre for Lung Infection and Immunity, Division of Pulmonology, Department of Medicine and UCT Lung Institute, Cape Town, South Africa
- South African MRC Centre for the Study of Antimicrobial Resistance, University of Cape Town, Cape Town, South Africa
- Faculty of Infectious and Tropical Diseases, Department of Infection Biology, London School of Hygiene and Tropical Medicine, London, UK
| | | | - Aliasgar Esmail
- Centre for Lung Infection and Immunity, Division of Pulmonology, Department of Medicine and UCT Lung Institute, Cape Town, South Africa
- South African MRC Centre for the Study of Antimicrobial Resistance, University of Cape Town, Cape Town, South Africa
| | - Katherine Fielding
- TB Centre, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | - Alberto L. Garcia-Basteiro
- ISGlobal, Hospital Clínic – Universitat de Barcelona, Barcelona, Spain
- Centro de Investigação em Saúde de Manhiça (CISM), Maputo, Mozambique
- Centro de Investigación Biomédica en Red de Enfermedades Infecciosas (CIBERINFEC), Barcelona, Spain
| | - Colleen F. Hanrahan
- Epidemiology Department, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Wakjira Kebede
- School of Medical Laboratory Sciences, Jimma University, Jimma Ethiopia
- Mycobacteriology Research Center of Jimma University, Ethiopia
| | | | | | - Carol Mita
- Countway Library of Medicine, Harvard University, Boston, MA, USA
| | - Byron W. P. Reeve
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research and SAMRC Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, South Africa
| | - Denise Rossato Silva
- Faculdade de Medicina, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Sedona Sweeney
- Faculty of Public Health and Policy, London School of Hygiene & Tropical Medicine, London, UK
| | - Grant Theron
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research and SAMRC Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, South Africa
| | - Anete Trajman
- Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
- McGill University, Montreal, QC, Canada
| | - Anna Vassall
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK
| | - Joshua L. Warren
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
| | - Marcel Yotebieng
- Division of General Internal Medicine, Department of Medicine, Albert Einstein College of Medicine, New York City, NY, USA
| | - Ted Cohen
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | - Nicolas A. Menzies
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Center for Health Decision Science, Harvard T.H. Chan School of Public Health, Boston, MA, USA
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14
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Brantner CL, Nguyen TQ, Tang T, Zhao C, Hong H, Stuart EA. Comparison of methods that combine multiple randomized trials to estimate heterogeneous treatment effects. Stat Med 2024; 43:1291-1314. [PMID: 38273647 PMCID: PMC11086055 DOI: 10.1002/sim.9955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 10/06/2023] [Accepted: 10/23/2023] [Indexed: 01/27/2024]
Abstract
Individualized treatment decisions can improve health outcomes, but using data to make these decisions in a reliable, precise, and generalizable way is challenging with a single dataset. Leveraging multiple randomized controlled trials allows for the combination of datasets with unconfounded treatment assignment to better estimate heterogeneous treatment effects. This article discusses several nonparametric approaches for estimating heterogeneous treatment effects using data from multiple trials. We extend single-study methods to a scenario with multiple trials and explore their performance through a simulation study, with data generation scenarios that have differing levels of cross-trial heterogeneity. The simulations demonstrate that methods that directly allow for heterogeneity of the treatment effect across trials perform better than methods that do not, and that the choice of single-study method matters based on the functional form of the treatment effect. Finally, we discuss which methods perform well in each setting and then apply them to four randomized controlled trials to examine effect heterogeneity of treatments for major depressive disorder.
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Affiliation(s)
- Carly Lupton Brantner
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Trang Quynh Nguyen
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Tengjie Tang
- Department of Statistical Science, Duke University, Durham, North Carolina, USA
| | - Congwen Zhao
- Department of Biostatistics and Bioinformatics, Duke University, Durham, North Carolina, USA
| | - Hwanhee Hong
- Department of Biostatistics and Bioinformatics, Duke University, Durham, North Carolina, USA
| | - Elizabeth A. Stuart
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
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15
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Zhu AH, Nir TM, Javid S, Villalon-Reina JE, Rodrigue AL, Strike LT, de Zubicaray GI, McMahon KL, Wright MJ, Medland SE, Blangero J, Glahn DC, Kochunov P, Håberg AK, Thompson PM, Jahanshad N. Lifespan reference curves for harmonizing multi-site regional brain white matter metrics from diffusion MRI. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.22.581646. [PMID: 38463962 PMCID: PMC10925090 DOI: 10.1101/2024.02.22.581646] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Age-related white matter (WM) microstructure maturation and decline occur throughout the human lifespan, complementing the process of gray matter development and degeneration. Here, we create normative lifespan reference curves for global and regional WM microstructure by harmonizing diffusion MRI (dMRI)-derived data from ten public datasets (N = 40,898 subjects; age: 3-95 years; 47.6% male). We tested three harmonization methods on regional diffusion tensor imaging (DTI) based fractional anisotropy (FA), a metric of WM microstructure, extracted using the ENIGMA-DTI pipeline. ComBat-GAM harmonization provided multi-study trajectories most consistent with known WM maturation peaks. Lifespan FA reference curves were validated with test-retest data and used to assess the effect of the ApoE4 risk factor for dementia in WM across the lifespan. We found significant associations between ApoE4 and FA in WM regions associated with neurodegenerative disease even in healthy individuals across the lifespan, with regional age-by-genotype interactions. Our lifespan reference curves and tools to harmonize new dMRI data to the curves are publicly available as eHarmonize (https://github.com/ahzhu/eharmonize).
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Affiliation(s)
- Alyssa H Zhu
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
- Department of Biomedical Engineering, USC Viterbi School of Engineering, Los Angeles, CA, USA
| | - Talia M Nir
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - Shayan Javid
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
- Department of Biomedical Engineering, USC Viterbi School of Engineering, Los Angeles, CA, USA
| | - Julio E Villalon-Reina
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - Amanda L Rodrigue
- Department of Psychiatry and Behavioral Science, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Lachlan T Strike
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- Queensland University of Technology, Brisbane, QLD, Australia
| | | | - Katie L McMahon
- Queensland University of Technology, Brisbane, QLD, Australia
| | - Margaret J Wright
- Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia
- Centre for Advanced Imaging, University of Queensland, Brisbane, QLD, Australia
| | - Sarah E Medland
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- Queensland University of Technology, Brisbane, QLD, Australia
- School of Psychology, `, Brisbane, QLD, Australia
| | - John Blangero
- Department of Human Genetics, University of Texas Rio Grande Valley, Brownsville, TX, USA
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, TX, USA
| | - David C Glahn
- Department of Psychiatry and Behavioral Science, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford, CT, USA
| | - Peter Kochunov
- Faillace Department of Psychiatry and Behavioral Sciences at McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Asta K Håberg
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- Department of MiDtT National Research Center, St. Olav's Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Paul M Thompson
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
- Department of Biomedical Engineering, USC Viterbi School of Engineering, Los Angeles, CA, USA
| | - Neda Jahanshad
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
- Department of Biomedical Engineering, USC Viterbi School of Engineering, Los Angeles, CA, USA
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16
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Nicoară-Farcău O, Han G, Rudler M, Angrisani D, Monescillo A, Torres F, Casanovas G, Bosch J, Lv Y, Dunne PDJ, Hayes PC, Thabut D, Fan D, Hernández-Gea V, García-Pagán JC. Pre-emptive TIPS in high-risk acute variceal bleeding. An updated and revised individual patient data meta-analysis. Hepatology 2024; 79:624-635. [PMID: 37782566 DOI: 10.1097/hep.0000000000000613] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/21/2023] [Accepted: 08/23/2023] [Indexed: 10/04/2023]
Abstract
BACKGROUND AND AIMS A previous individual patient data meta-analysis (IPD-MA) showed that compared with drugs+endoscopy, the placement of transjugular portosystemic shunt within 72 hours of admission (pre-emptive transjugular intrahepatic portosystemic shunt: p-TIPS) increases the survival of high-risk patients (Child-Pugh B+ active bleeding and Child-Pugh C<14 points) with cirrhosis and acute variceal bleeding. However, the previous IPD-MA was not a two-stage meta-analysis, did not consider the potential risk of selection bias of observational studies, and did not include the most recent randomized clinical trial. We performed an updated and revised IPD-MA to reassess the efficacy of p-TIPS, addressing all previous issues. APPROACH AND RESULTS We included all studies from the previous IPD-MA and searched for other possible eligible publications until September 2022. We performed a two-stage IPD-MA of data from 8 studies (4 randomized clinical trials and 4 observational). In addition, we performed a sensitivity analysis excluding those patients dying up to the first 72 hours after admission in the Drugs+Endoscopy arms of the 4 observational studies. The primary end point was the effects of p-TIPS versus Drugs+Endoscopy on 1-year survival.We identified 1389 patients (342 p-TIPS and 1047 Drugs+Endoscopy). The two-stage IPD-MA showed that p-TIPS significantly reduced the mortality in the overall population (HR=0·43, 95% CI: 0.32-0.60, p <0.001. This effect was observed in both subgroups of patients with Child-Pugh. The sensitivity analysis confirmed the survival benefit of p-TIPS. CONCLUSIONS The updated two-stage IPD-MA confirms the significant survival advantage of p-TIPS in high-risk patients with cirrhosis and acute variceal bleeding. As a result, we recommend p-TIPS as the preferred first-choice treatment for these patients.
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Affiliation(s)
- Oana Nicoară-Farcău
- Hepatology Department, Regional Institute of Gastroenterology and Hepatology "Octavian Fodor", "Iuliu Hatieganu" University of Medicine and Pharmacy, 3rd Medical Clinic, Cluj-Napoca, Romania
- Barcelona Hepatic Hemodynamic Laboratory, Liver Unit, Hospital Clinic, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain
- Health Care Provider of the European Reference Network on Rare Liver Disorders (ERN-Liver)
| | - Guohong Han
- Department of Liver Diseases and Digestive Interventional Radiology, Xi'an International Medical Center Hospital, Digestive Diseases Hospital, Northwest University, Xi'an, China
- Department of Liver Disease and Digestive Interventional Radiology, Xijing Hospital of Digestive Diseases, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Marika Rudler
- Groupement Hospitalier Pitié-Salpêtrière- Charles Foix, Sorbonne University, Paris, France
| | - Debora Angrisani
- Barcelona Hepatic Hemodynamic Laboratory, Liver Unit, Hospital Clinic, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain
- Health Care Provider of the European Reference Network on Rare Liver Disorders (ERN-Liver)
| | - Alberto Monescillo
- Digestive Disease Department, Hospital Universitario Insular de Gran Canaria, Canary Islands, Spain
| | - Ferran Torres
- Medical Statistics Core Facility, Institut D'Investigacions Biomédiques August Pi i Sunyer (IDIBAPS), Hospital Clinic Barcelona, Barcelona, Spain
- Biostatistics Unit, Faculty of Medicine, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Georgina Casanovas
- Medical Statistics Core Facility, Institut D'Investigacions Biomédiques August Pi i Sunyer (IDIBAPS), Hospital Clinic Barcelona, Barcelona, Spain
| | - Jaime Bosch
- Barcelona Hepatic Hemodynamic Laboratory, Liver Unit, Hospital Clinic, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain
- Health Care Provider of the European Reference Network on Rare Liver Disorders (ERN-Liver)
- Centro de Investigación Biomédica Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), Madrid, Spain
- Hepatology, University Clinic for Visceral Surgery and Medicine, Inselspital, Bern University, Bern, Switzerland
| | - Yong Lv
- Department of Liver Disease and Digestive Interventional Radiology, Xijing Hospital of Digestive Diseases, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Philip D J Dunne
- Liver Unit, Royal Infirmary of Edinburgh and University of Edinburgh, Edinburgh, UK
| | - Peter C Hayes
- Liver Unit, Royal Infirmary of Edinburgh and University of Edinburgh, Edinburgh, UK
| | - Dominique Thabut
- Groupement Hospitalier Pitié-Salpêtrière- Charles Foix, Sorbonne University, Paris, France
| | - Daiming Fan
- State Key Laboratory of Cancer Biology, National Clinical Research Center for Digestive Diseases and Xijing Hospital of Digestive Diseases, Fourth Military Medical University, Xi'an, China
| | - Virginia Hernández-Gea
- Barcelona Hepatic Hemodynamic Laboratory, Liver Unit, Hospital Clinic, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain
- Health Care Provider of the European Reference Network on Rare Liver Disorders (ERN-Liver)
- Centro de Investigación Biomédica Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), Madrid, Spain
| | - Juan C García-Pagán
- Barcelona Hepatic Hemodynamic Laboratory, Liver Unit, Hospital Clinic, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain
- Health Care Provider of the European Reference Network on Rare Liver Disorders (ERN-Liver)
- Centro de Investigación Biomédica Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), Madrid, Spain
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Yang JJ, Wen W, Zahed H, Zheng W, Lan Q, Abe SK, Rahman MS, Islam MR, Saito E, Gupta PC, Tamakoshi A, Koh WP, Gao YT, Sakata R, Tsuji I, Malekzadeh R, Sugawara Y, Kim J, Ito H, Nagata C, You SL, Park SK, Yuan JM, Shin MH, Kweon SS, Yi SW, Pednekar MS, Kimura T, Cai H, Lu Y, Etemadi A, Kanemura S, Wada K, Chen CJ, Shin A, Wang R, Ahn YO, Shin MH, Ohrr H, Sheikh M, Blechter B, Ahsan H, Boffetta P, Chia KS, Matsuo K, Qiao YL, Rothman N, Inoue M, Kang D, Robbins HA, Shu XO. Lung Cancer Risk Prediction Models for Asian Ever-Smokers. J Thorac Oncol 2024; 19:451-464. [PMID: 37944700 PMCID: PMC11126207 DOI: 10.1016/j.jtho.2023.11.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 10/19/2023] [Accepted: 11/04/2023] [Indexed: 11/12/2023]
Abstract
INTRODUCTION Although lung cancer prediction models are widely used to support risk-based screening, their performance outside Western populations remains uncertain. This study aims to evaluate the performance of 11 existing risk prediction models in multiple Asian populations and to refit prediction models for Asians. METHODS In a pooled analysis of 186,458 Asian ever-smokers from 19 prospective cohorts, we assessed calibration (expected-to-observed ratio) and discrimination (area under the receiver operating characteristic curve [AUC]) for each model. In addition, we developed the "Shanghai models" to better refine risk models for Asians on the basis of two well-characterized population-based prospective cohorts and externally validated them in other Asian cohorts. RESULTS Among the 11 models, the Lung Cancer Death Risk Assessment Tool yielded the highest AUC (AUC [95% confidence interval (CI)] = 0.71 [0.67-0.74] for lung cancer death and 0.69 [0.67-0.72] for lung cancer incidence) and the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial Model had good calibration overall (expected-to-observed ratio [95% CI] = 1.06 [0.90-1.25]). Nevertheless, these models substantially underestimated lung cancer risk among Asians who reported less than 10 smoking pack-years or stopped smoking more than or equal to 20 years ago. The Shanghai models were found to have marginal improvement overall in discrimination (AUC [95% CI] = 0.72 [0.69-0.74] for lung cancer death and 0.70 [0.67-0.72] for lung cancer incidence) but consistently outperformed the selected Western models among low-intensity smokers and long-term quitters. CONCLUSIONS The Shanghai models had comparable performance overall to the best existing models, but they improved much in predicting the lung cancer risk of low-intensity smokers and long-term quitters in Asia.
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Affiliation(s)
- Jae Jeong Yang
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee; Department of Surgery, University of Florida College of Medicine, Gainesville, Florida; University of Florida Health Cancer Center, Gainesville, Florida
| | - Wanqing Wen
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Hana Zahed
- International Agency for Research on Cancer, Lyon, France
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Qing Lan
- Division of Cancer Epidemiology and Genetics, Occupational and Environmental Epidemiology Branch, National Cancer Institute, National Institutes of Health, Rockville, Maryland
| | - Sarah K Abe
- Division of Prevention, National Cancer Center Institute for Cancer Control, Tokyo, Japan
| | - Md Shafiur Rahman
- Division of Prevention, National Cancer Center Institute for Cancer Control, Tokyo, Japan; Research Center for Child Mental Development, Hamamatsu University School of Medicine, Hamamatsu, Japan
| | - Md Rashedul Islam
- Division of Prevention, National Cancer Center Institute for Cancer Control, Tokyo, Japan; Hitotsubashi Institute for Advanced Study, Hitotsubashi University, Tokyo, Japan
| | - Eiko Saito
- Institute for Global Health Policy Research, National Center for Global Health and Medicine, Tokyo, Japan
| | - Prakash C Gupta
- Healis - Sekhsaria Institute for Public Health Mahaleb, Navi Mumbai, India
| | - Akiko Tamakoshi
- Department of Public Health, Hokkaido University Faculty of Medicine, Sapporo, Japan
| | - Woon-Puay Koh
- Healthy Longevity Translational Research Program, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore; Singapore Institute for Clinical Sciences, Agency for Science Technology and Research (A∗STAR), Singapore, Singapore
| | - Yu-Tang Gao
- Department of Epidemiology, Shanghai Cancer Institute Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, People's Republic of China
| | - Ritsu Sakata
- Radiation Effects Research Foundation, Hiroshima, Japan
| | - Ichiro Tsuji
- Tohoku University Graduate School of Medicine, Miyagi Prefecture, Japan
| | - Reza Malekzadeh
- Digestive Oncology Research Center, Digestive Diseases Research Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Yumi Sugawara
- Tohoku University Graduate School of Medicine, Miyagi Prefecture, Japan
| | - Jeongseon Kim
- Graduate School of Cancer Science and Policy, National Cancer Center, Goyang, Republic of Korea
| | - Hidemi Ito
- Division of Cancer Information and Control, Department of Preventive Medicine, Aichi Cancer Center Research Institute, Nagoya, Japan; Division of Descriptive Cancer Epidemiology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Chisato Nagata
- Department of Epidemiology and Preventive Medicine, Gifu University Graduate School of Medicine, Gifu, Japan
| | - San-Lin You
- School of Medicine & Big Data Research Center, Fu Jen Catholic University, New Taipei City, Taiwan
| | - Sue K Park
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Jian-Min Yuan
- Division of Cancer Control and Population Sciences, UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, Pennsylvania; Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Myung-Hee Shin
- Department of Social and Preventive Medicine, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Sun-Seog Kweon
- Department of Preventive Medicine, Chonnam National University Medical School, Gwangju, Republic of Korea
| | - Sang-Wook Yi
- Department of Preventive Medicine and Public Health, Catholic Kwandong University College of Medicine, Gangneung, Republic of Korea
| | - Mangesh S Pednekar
- Healis - Sekhsaria Institute for Public Health Mahaleb, Navi Mumbai, India
| | - Takashi Kimura
- Department of Public Health, Hokkaido University Faculty of Medicine, Sapporo, Japan
| | - Hui Cai
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Yukai Lu
- Tohoku University Graduate School of Medicine, Miyagi Prefecture, Japan
| | - Arash Etemadi
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Seiki Kanemura
- Tohoku University Graduate School of Medicine, Miyagi Prefecture, Japan
| | - Keiko Wada
- Department of Epidemiology and Preventive Medicine, Gifu University Graduate School of Medicine, Gifu, Japan
| | - Chien-Jen Chen
- Genomics Research Center, Academia Sinica, Taipei City, Taiwan
| | - Aesun Shin
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea; Cancer Research Institute, Seoul National University, Seoul, Republic of Korea
| | - Renwei Wang
- Division of Cancer Control and Population Sciences, UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Yoon-Ok Ahn
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Min-Ho Shin
- Department of Preventive Medicine, Chonnam National University Medical School, Gwangju, Republic of Korea
| | - Heechoul Ohrr
- Department of Preventive Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Mahdi Sheikh
- International Agency for Research on Cancer, Lyon, France
| | - Batel Blechter
- Division of Cancer Epidemiology and Genetics, Occupational and Environmental Epidemiology Branch, National Cancer Institute, National Institutes of Health, Rockville, Maryland
| | - Habibul Ahsan
- Department of Public Health Sciences, University of Chicago, Illinois
| | - Paolo Boffetta
- Stony Brook Cancer Center, Stony Brook University, Stony Brook, New York; Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy
| | - Kee Seng Chia
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Keitaro Matsuo
- Division Cancer Epidemiology and Prevention, Aichi Cancer Center Research Institute, Nagoya, Japan; Department of Cancer Epidemiology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - You-Lin Qiao
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China
| | - Nathaniel Rothman
- Division of Cancer Epidemiology and Genetics, Occupational and Environmental Epidemiology Branch, National Cancer Institute, National Institutes of Health, Rockville, Maryland
| | - Manami Inoue
- Division of Prevention, National Cancer Center Institute for Cancer Control, Tokyo, Japan
| | - Daehee Kang
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea; Cancer Research Institute, Seoul National University, Seoul, Republic of Korea
| | | | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee.
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Kurath J, Akhtar A, Karyotaki E, Sijbrandij M, Cuijpers P, Bryant R, Morina N. What works for whom and why? Treatment effects and their moderators among forcibly displaced people receiving psychological and psychosocial interventions: study protocol for an individual patient data meta-analysis. BMJ Open 2024; 14:e078473. [PMID: 38309750 PMCID: PMC10840047 DOI: 10.1136/bmjopen-2023-078473] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Accepted: 01/03/2024] [Indexed: 02/05/2024] Open
Abstract
INTRODUCTION Forcibly displaced people (FDP) have a high risk of developing mental disorders such as post-traumatic stress (PTS) disorder. Providing adequate mental healthcare for FDP is crucial but despite overall efficacy of many existing interventions, a large proportion of FDP does not benefit from treatment, highlighting the necessity of further investigating factors contributing to individual differences in treatment outcome. Yet, the few studies that have explored moderators of treatment effects are often insufficiently powered. Therefore, the present Individual Patient Data meta-analysis (IPD-MA) will investigate treatment effects and their moderators-variables related to beneficiaries, providers, intervention and study characteristics in relation to PTS outcomes. METHODS AND ANALYSIS A systematic literature search will be conducted from database inception in the databases PsycINFO, Cochrane, Embase, PTSDpubs and Web of Science. Only studies published in English, German, French, Spanish, Portuguese, and Dutch will be considered. Retrieved records will be screened for eligibility. Randomised controlled trials on adult FDP receiving psychological and psychosocial interventions aimed at alleviating symptoms such as PTS compared with a control condition without intervention will be included in this IPD-MA. Subsequently, authors of eligible studies will be contacted to request individual patient data (IPD). All datasets obtained will be synthesised into one large dataset which will be analysed using a one-stage approach by conducting mixed-effects linear regression models (ie, primary analysis). Additionally, aggregate data meta-analyes will be run using a two-stage approach by conducting multivariate regression models including all IPD (transformed) and available meta-data from study reports (ie, secondary analysis). PTS will serve as primary outcome measure, while mental health outcomes other than PTS, attendance, attrition, treatment non-response and adverse outcomes will be examined as secondary outcomes. ETHICS AND DISSEMINATION This IPD-MA does not require ethical approval. The results will be published in international peer-reviewed journals. PROSPERO REGISTRATION NUMBER CRD42022299510.
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Affiliation(s)
- Jennifer Kurath
- Department of Consultation-Liaison Psychiatry and Psychosomatic Medicine, University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Faculty of Medicine, University of Zurich, Zurich, Switzerland
| | - Aemal Akhtar
- Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden
- School of Psychology, University of New South Wales, Sydney, New South Wales, Australia
| | - Eirini Karyotaki
- Department of Clinical, Neuro- and Developmental Psychology, WHO Collaborating Center for Research and Dissemination of Psychological Interventions, Amsterdam Public Health Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Marit Sijbrandij
- Department of Clinical, Neuro- and Developmental Psychology, WHO Collaborating Center for Research and Dissemination of Psychological Interventions, Amsterdam Public Health Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Pim Cuijpers
- Department of Clinical, Neuro- and Developmental Psychology, WHO Collaborating Center for Research and Dissemination of Psychological Interventions, Amsterdam Public Health Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Richard Bryant
- School of Psychology, University of New South Wales, Sydney, New South Wales, Australia
| | - Naser Morina
- Department of Consultation-Liaison Psychiatry and Psychosomatic Medicine, University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Faculty of Medicine, University of Zurich, Zurich, Switzerland
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19
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Zou Y, Grender J, Adam R, Levin L. A Meta-analysis Comparing Toothbrush Technologies on Gingivitis and Plaque. Int Dent J 2024; 74:146-156. [PMID: 37481415 PMCID: PMC10829363 DOI: 10.1016/j.identj.2023.06.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 06/19/2023] [Accepted: 06/22/2023] [Indexed: 07/24/2023] Open
Abstract
BACKGROUND Research continues to show an association between oral health and systemic health, further stressing the importance of effective daily plaque removal via toothbrushing to maintain periodontal health and overall well-being. This investigation was undertaken to compare the efficacy of oscillating-rotating, sonic, and manual toothbrushes in reducing gingivitis and plaque in randomised controlled trials (RCTs) with up to 6 months' follow-up. METHODS This meta-analysis was conducted from a single database (Procter & Gamble Oral Care Clinical Archive) including RCTs from 2007 to 2022. Three authors independently assessed study eligibility. Disagreements concerning selected studies were resolved by discussion with an expert colleague. Direct and indirect treatment comparisons along with transition rates to gingival health were calculated using participant-level data. Transition-to-health time was calculated using data from all time points. Subregion analyses evaluated number of bleeding sites and plaque reduction. RESULTS This meta-analysis included 21 gingivitis RCTs and 25 plaque RCTs. Relative to manual and sonic brushes, oscillating-rotating brushes had a higher percentage of participants who transitioned to gingival health (72% vs 21% and 54%; P < .001). Compared with manual and sonic brushes, respectively, oscillating-rotating brushes demonstrated greater bleeding site reductions (by 52% and 29%; P < .001) and superior plaque reductions (by 19% and 5%; P < .001). Oscillating-rotating brushes provided faster transitions to health than sonic brushes and showed greater efficacy across subregions. The most advanced oscillating-rotating brush demonstrated statistically significantly greater efficacy compared with traditional oscillating-rotating, manual, and sonic brushes when analysed separately. Risk of bias was deemed low for all studies. CONCLUSIONS Oscillating-rotating toothbrushes offer superior results for transition to health, gingivitis, and plaque reduction compared with manual and sonic brushes. The most advanced oscillating-rotating model offers enhanced efficacy vs traditional models.
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Affiliation(s)
- Yuanshu Zou
- Oral Care Research & Development, The Procter & Gamble Company, Mason, Ohio, USA.
| | - Julie Grender
- Oral Care Research & Development, The Procter & Gamble Company, Mason, Ohio, USA
| | - Ralf Adam
- Oral Care Research & Development, Procter & Gamble Service GmbH, Kronberg, Germany
| | - Liran Levin
- Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada
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20
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Cheng C, Messerschmidt L, Bravo I, Waldbauer M, Bhavikatti R, Schenk C, Grujic V, Model T, Kubinec R, Barceló J. A General Primer for Data Harmonization. Sci Data 2024; 11:152. [PMID: 38297013 PMCID: PMC10831085 DOI: 10.1038/s41597-024-02956-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Accepted: 01/11/2024] [Indexed: 02/02/2024] Open
Affiliation(s)
- Cindy Cheng
- Hochschule für Politik, Technical University of Munich, Richard-Wagner Str. 1, Munich, 80333, Bavaria, Germany.
| | - Luca Messerschmidt
- Hochschule für Politik, Technical University of Munich, Richard-Wagner Str. 1, Munich, 80333, Bavaria, Germany
| | - Isaac Bravo
- Hochschule für Politik, Technical University of Munich, Richard-Wagner Str. 1, Munich, 80333, Bavaria, Germany
| | - Marco Waldbauer
- Hochschule für Politik, Technical University of Munich, Richard-Wagner Str. 1, Munich, 80333, Bavaria, Germany
| | | | - Caress Schenk
- School of Humanities and Social Sciences, Nazarbayev University, Kabanbay Batry Ave., 53, Astana, 010000, Kazakhstan
| | - Vanja Grujic
- Faculty of Law, University of Brasilia, Campus Universitário Darcy Ribeiro Asa Norte, Brasília, 10587, Brazil
| | - Tim Model
- Delve, 2225 3rd St, San Francisco, 94107, California, USA
| | - Robert Kubinec
- Division of Social Science, New York University Abu Dhabi, Social Science Building (A5), Abu Dhabi, 129188, United Arab Emirates
| | - Joan Barceló
- Division of Social Science, New York University Abu Dhabi, Social Science Building (A5), Abu Dhabi, 129188, United Arab Emirates
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Alshehri MA, Alzahrani H, van den Hoorn W, Klyne DM, Vette AH, Hendershot BD, Roberts BWR, Larivière C, Barbado D, Vera-Garcia FJ, van Dieen JH, Cholewicki J, Nussbaum MA, Madigan ML, Reeves NP, Silfies SP, Brown SHM, Hodges PW. Trunk postural control during unstable sitting among individuals with and without low back pain: A systematic review with an individual participant data meta-analysis. PLoS One 2024; 19:e0296968. [PMID: 38265999 PMCID: PMC10807788 DOI: 10.1371/journal.pone.0296968] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Accepted: 12/26/2023] [Indexed: 01/26/2024] Open
Abstract
INTRODUCTION Sitting on an unstable surface is a common paradigm to investigate trunk postural control among individuals with low back pain (LBP), by minimizing the influence lower extremities on balance control. Outcomes of many small studies are inconsistent (e.g., some find differences between groups while others do not), potentially due to confounding factors such as age, sex, body mass index [BMI], or clinical presentations. We conducted a systematic review with an individual participant data (IPD) meta-analysis to investigate whether trunk postural control differs between those with and without LBP, and whether the difference between groups is impacted by vision and potential confounding factors. METHODS We completed this review according to PRISMA-IPD guidelines. The literature was screened (up to 7th September 2023) from five electronic databases: MEDLINE, CINAHL, Embase, Scopus, and Web of Science Core Collection. Outcome measures were extracted that describe unstable seat movements, specifically centre of pressure or seat angle. Our main analyses included: 1) a two-stage IPD meta-analysis to assess the difference between groups and their interaction with age, sex, BMI, and vision on trunk postural control; 2) and a two-stage IPD meta-regression to determine the effects of LBP clinical features (pain intensity, disability, pain catastrophizing, and fear-avoidance beliefs) on trunk postural control. RESULTS Forty studies (1,821 participants) were included for the descriptive analysis and 24 studies (1,050 participants) were included for the IPD analysis. IPD meta-analyses revealed three main findings: (a) trunk postural control was worse (higher root mean square displacement [RMSdispl], range, and long-term diffusion; lower mean power frequency) among individuals with than without LBP; (b) trunk postural control deteriorated more (higher RMSdispl, short- and long-term diffusion) among individuals with than without LBP when vision was removed; and (c) older age and higher BMI had greater adverse impacts on trunk postural control (higher short-term diffusion; longer time and distance coordinates of the critical point) among individuals with than without LBP. IPD meta-regressions indicated no associations between the limited LBP clinical features that could be considered and trunk postural control. CONCLUSION Trunk postural control appears to be inferior among individuals with LBP, which was indicated by increased seat movements and some evidence of trunk stiffening. These findings are likely explained by delayed or less accurate corrective responses. SYSTEMATIC REVIEW REGISTRATION This review has been registered in PROSPERO (registration number: CRD42021124658).
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Affiliation(s)
- Mansour Abdullah Alshehri
- NHMRC Centre of Clinical Research Excellence in Spinal Pain, Injury & Health, School of Health and Rehabilitation Sciences, The University of Queensland, Brisbane, Australia
- Physiotherapy Department, Faculty of Applied Medical Sciences, Umm Al-Qura University, Mecca, Saudi Arabia
| | - Hosam Alzahrani
- Department of Physical Therapy, College of Applied Medical Sciences, Taif University, Taif, Saudi Arabia
| | - Wolbert van den Hoorn
- NHMRC Centre of Clinical Research Excellence in Spinal Pain, Injury & Health, School of Health and Rehabilitation Sciences, The University of Queensland, Brisbane, Australia
| | - David M. Klyne
- NHMRC Centre of Clinical Research Excellence in Spinal Pain, Injury & Health, School of Health and Rehabilitation Sciences, The University of Queensland, Brisbane, Australia
| | - Albert H. Vette
- Department of Mechanical Engineering, Donadeo Innovation Centre for Engineering, University of Alberta, Edmonton, Canada
- Glenrose Rehabilitation Hospital, Alberta Health Services, Edmonton, Canada
| | - Brad D. Hendershot
- Extremity Trauma and Amputation Center of Excellence, Defense Health Agency, Falls Church, Virginia, United States of America
| | - Brad W. R. Roberts
- Department of Mechanical Engineering, Donadeo Innovation Centre for Engineering, University of Alberta, Edmonton, Canada
| | - Christian Larivière
- Institut de recherche Robert-Sauvé en santé et en sécurité du travail (IRSST), Montreal, Quebec, Canada
- Center for Interdisciplinary Research in Rehabilitation of Greater Montreal (CRIR), Montreal Rehabilitation Institute, Montreal, Quebec, Canada
| | - David Barbado
- Sport Research Centre, Department of Sport Sciences, Miguel Hernández University of Elche, Alicante, Spain
- Institute for Health and Biomedical Research (ISABIAL Foundation), Miguel Hernández University of Elche, Alicante, Spain
| | - Francisco J. Vera-Garcia
- Sport Research Centre, Department of Sport Sciences, Miguel Hernández University of Elche, Alicante, Spain
- Institute for Health and Biomedical Research (ISABIAL Foundation), Miguel Hernández University of Elche, Alicante, Spain
| | - Jaap H. van Dieen
- Department of Human Movement Sciences, Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam Movement Sciences, Amsterdam, Netherlands
| | - Jacek Cholewicki
- Center for Neuromusculoskeletal Clinical Research, Michigan State University, Lansing, Michigan, United States of America
- Department of Osteopathic Manipulative Medicine, Michigan State University, East Lansing, Michigan, United States of America
| | - Maury A. Nussbaum
- Virginia Tech-Wake Forest School of Biomedical Engineering and Sciences, Virginia Tech, Blacksburg, Virginia, United States of America
- Department of Industrial and Systems Engineering, Virginia Tech, Blacksburg, Virginia, United States of America
| | - Michael L. Madigan
- Virginia Tech-Wake Forest School of Biomedical Engineering and Sciences, Virginia Tech, Blacksburg, Virginia, United States of America
- Department of Industrial and Systems Engineering, Virginia Tech, Blacksburg, Virginia, United States of America
| | | | - Sheri P. Silfies
- Department of Exercise Science, University of South Carolina, Columbia, South Carolina, United States of America
| | - Stephen H. M. Brown
- Department of Human Health and Nutritional Sciences, University of Guelph, Guelph, Ontario, Canada
| | - Paul W. Hodges
- NHMRC Centre of Clinical Research Excellence in Spinal Pain, Injury & Health, School of Health and Rehabilitation Sciences, The University of Queensland, Brisbane, Australia
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d'Entremont MA, Alrashidi S, Seto AH, Nguyen P, Marquis-Gravel G, Abu-Fadel MS, Juergens C, Tessier P, Lemaire-Paquette S, Heenan L, Skuriat E, Tyrwhitt J, Couture ÉL, Bérubé S, Jolly SS. Ultrasound guidance for transfemoral access in coronary procedures: an individual participant-level data metaanalysis from the femoral ultrasound trialist collaboration. EUROINTERVENTION 2024; 20:66-74. [PMID: 37800723 PMCID: PMC10758987 DOI: 10.4244/eij-d-22-00809] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Accepted: 09/01/2023] [Indexed: 10/07/2023]
Abstract
BACKGROUND Randomised controlled trials of ultrasound (US)-guided transfemoral access (TFA) for coronary procedures have shown mixed results. AIMS We aimed to compare US-guided versus non-US-guided TFA from randomised data in an individual participant-level data (IPD) meta-analysis. METHODS We completed a systematic review and an IPD meta-analysis of all randomised controlled trials comparing US-guided versus non-US-guided TFA for coronary procedures. We performed a one-stage mixed-model meta-analysis using the intention-to-treat population from included trials. The primary outcome was a composite of major vascular complications or major bleeding within 30 days. RESULTS A total of 2,441 participants (1,208 US-guided, 1,233 non-US-guided) from 4 randomised clinical trials were included. The mean age was 65.5 years, 27.0% were female, and 34.5% underwent a percutaneous coronary intervention. The incidence of major vascular complications or major bleeding (34/1,208 [2.8%] vs 55/1,233 [4.5%]; odds ratio [OR] 0.61, 95% confidence interval [CI]: 0.39-0.94; p=0.026) was lower in the US-guided TFA group. In the prespecified subgroup of participants who received a vascular closure device, those randomised to US-guided TFA experienced a reduction in the primary outcome (2.1% vs 5.6%; OR 0.36, 95% CI: 0.19-0.69), while no benefit for US guidance was observed in the subgroup without vascular closure devices (4.1% vs 3.3%; OR 1.21, 95% CI: 0.65-2.26; interaction p=0.009). CONCLUSIONS In participants undergoing coronary procedures by TFA, US guidance decreased the composite outcome of major vascular complications or bleeding and may be especially helpful when using vascular closure devices.
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Affiliation(s)
- Marc-André d'Entremont
- Population Health Research Institute, Hamilton, ON, Canada
- Centre Hospitalier Universitaire de Sherbrooke (CHUS), Sherbrooke, QC, Canada
- McMaster University, Hamilton, ON, Canada
| | | | | | - Phong Nguyen
- Western Sydney University, Campbelltown, NSW, Australia
- University of New South Wales, Sydney, NSW, Australia
| | | | - Mazen S Abu-Fadel
- Oklahoma Heart Hospital, Oklahoma City, OK, USA and University of Oklahoma, Norman, OK, USA
| | - Craig Juergens
- University of New South Wales, Sydney, NSW, Australia
- Liverpool Hospital, Liverpool, NSW, Australia
| | - Pierre Tessier
- Hôpital du Sacré-Coeur-de-Montréal, Montreal, QC, Canada
| | | | - Laura Heenan
- Population Health Research Institute, Hamilton, ON, Canada
| | | | | | - Étienne L Couture
- Centre Hospitalier Universitaire de Sherbrooke (CHUS), Sherbrooke, QC, Canada
| | - Simon Bérubé
- Centre Hospitalier Universitaire de Sherbrooke (CHUS), Sherbrooke, QC, Canada
| | - Sanjit S Jolly
- Population Health Research Institute, Hamilton, ON, Canada
- McMaster University, Hamilton, ON, Canada
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23
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Godolphin PJ, Marlin N, Cornett C, Fisher DJ, Tierney JF, White IR, Rogozińska E. Use of multiple covariates in assessing treatment-effect modifiers: A methodological review of individual participant data meta-analyses. Res Synth Methods 2024; 15:107-116. [PMID: 37771175 DOI: 10.1002/jrsm.1674] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Revised: 08/22/2023] [Accepted: 09/18/2023] [Indexed: 09/30/2023]
Abstract
Individual participant data (IPD) meta-analyses of randomised trials are considered a reliable way to assess participant-level treatment effect modifiers but may not make the best use of the available data. Traditionally, effect modifiers are explored one covariate at a time, which gives rise to the possibility that evidence of treatment-covariate interaction may be due to confounding from a different, related covariate. We aimed to evaluate current practice when estimating treatment-covariate interactions in IPD meta-analysis, specifically focusing on involvement of additional covariates in the models. We reviewed 100 IPD meta-analyses of randomised trials, published between 2015 and 2020, that assessed at least one treatment-covariate interaction. We identified four approaches to handling additional covariates: (1) Single interaction model (unadjusted): No additional covariates included (57/100 IPD meta-analyses); (2) Single interaction model (adjusted): Adjustment for the main effect of at least one additional covariate (35/100); (3) Multiple interactions model: Adjustment for at least one two-way interaction between treatment and an additional covariate (3/100); and (4) Three-way interaction model: Three-way interaction formed between treatment, the additional covariate and the potential effect modifier (5/100). IPD is not being utilised to its fullest extent. In an exemplar dataset, we demonstrate how these approaches lead to different conclusions. Researchers should adjust for additional covariates when estimating interactions in IPD meta-analysis providing they adjust their main effects, which is already widely recommended. Further, they should consider whether more complex approaches could provide better information on who might benefit most from treatments, improving patient choice and treatment policy and practice.
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Affiliation(s)
- Peter J Godolphin
- MRC Clinical Trials Unit at University College London, Institute of Clinical Trials and Methodology, London, UK
| | - Nadine Marlin
- Pragmatic Clinical Trials Unit, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Chantelle Cornett
- MRC Clinical Trials Unit at University College London, Institute of Clinical Trials and Methodology, London, UK
| | - David J Fisher
- MRC Clinical Trials Unit at University College London, Institute of Clinical Trials and Methodology, London, UK
| | - Jayne F Tierney
- MRC Clinical Trials Unit at University College London, Institute of Clinical Trials and Methodology, London, UK
| | - Ian R White
- MRC Clinical Trials Unit at University College London, Institute of Clinical Trials and Methodology, London, UK
| | - Ewelina Rogozińska
- MRC Clinical Trials Unit at University College London, Institute of Clinical Trials and Methodology, London, UK
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Verma R, Commons RJ, Gupta A, Rahi M, Nitika, Bharti PK, Thriemer K, Rajasekhar M, Singh-Phulgenda S, Adhikari B, Alam MS, Ghimire P, Khan WA, Kumar R, Leslie T, Ley B, Llanos-Cuentas A, Pukrittayakamee S, Rijal KR, Rowland M, Saravu K, Simpson JA, Guerin PJ, Price RN, Sharma A. Safety and efficacy of primaquine in patients with Plasmodium vivax malaria from South Asia: a systematic review and individual patient data meta-analysis. BMJ Glob Health 2023; 8:e012675. [PMID: 38123228 DOI: 10.1136/bmjgh-2023-012675] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 11/25/2023] [Indexed: 12/23/2023] Open
Abstract
BACKGROUND The optimal dosing of primaquine to prevent relapsing Plasmodium vivax malaria in South Asia remains unclear. We investigated the efficacy and safety of different primaquine regimens to prevent P. vivax relapse. METHODS A systematic review identified P. vivax efficacy studies from South Asia published between 1 January 2000 and 23 August 2021. In a one-stage meta-analysis of available individual patient data, the cumulative risks of P. vivax recurrence at day 42 and 180 were assessed by primaquine total mg/kg dose and duration. The risk of recurrence by day 180 was also determined in a two-stage meta-analysis. Patients with a >25% drop in haemoglobin to <70 g/L, or an absolute drop of >50 g/L between days 1 and 14 were categorised by daily mg/kg primaquine dose. RESULTS In 791 patients from 7 studies in the one-stage meta-analysis, the day 180 cumulative risk of recurrence was 61.1% (95% CI 42.2% to 80.4%; 201 patients; 25 recurrences) after treatment without primaquine, 28.8% (95% CI 8.2% to 74.1%; 398 patients; 4 recurrences) following low total (2 to <5 mg/kg) and 0% (96 patients; 0 recurrences) following high total dose primaquine (≥5 mg/kg). In the subsequent two-stage meta-analysis of nine studies (3529 patients), the pooled proportions of P. vivax recurrences by day 180 were 12.1% (95% CI 7.7% to 17.2%), 2.3% (95% CI 0.3% to 5.4%) and 0.7% (95% CI 0% to 6.1%), respectively. No patients had a >25% drop in haemoglobin to <70 g/L. CONCLUSIONS Primaquine treatment led to a marked decrease in P. vivax recurrences following low (~3.5 mg/kg) and high (~7 mg/kg) total doses, with no reported severe haemolytic events. PROSPERO REGISTRATION NUMBER CRD42022313730.
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Affiliation(s)
- Reena Verma
- ICMR-National Institute of Malaria Research, New Delhi, India
| | - Robert J Commons
- Global Health Division, Menzies School of Health Research, Charles Darwin University, Tiwi, Northern Territory, Australia
- WorldWide Antimalarial Resistance Network, Asia Pacific Regional Hub - Australia, Melbourne, Victoria, Australia
- General and Subspecialty Medicine, Grampians Health Ballarat, Ballarat, Victoria, Australia
| | - Apoorv Gupta
- ICMR-National Institute of Malaria Research, New Delhi, India
| | - Manju Rahi
- ICMR-National Institute of Malaria Research, New Delhi, India
- Indian Council of Medical Research, New Delhi, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, India
| | - Nitika
- ICMR-National Institute of Malaria Research, New Delhi, India
| | | | - Kamala Thriemer
- Global Health Division, Menzies School of Health Research, Charles Darwin University, Tiwi, Northern Territory, Australia
| | - Megha Rajasekhar
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Sauman Singh-Phulgenda
- WorldWide Antimalarial Resistance Network (WWARN), Oxford, UK
- Infectious Diseases Data Observatory (IDDO), Oxford, UK
- Centre for Tropical Medicine and Global Health, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK
| | - Bipin Adhikari
- Centre for Tropical Medicine and Global Health, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK
- Mahidol Oxford Tropical Medicine Research Unit (MORU), Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
| | - Mohammad Shafiul Alam
- International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh
| | - Prakash Ghimire
- Central Department of Microbiology, Tribhuvan University, Kirtipur, Nepal
| | - Wasif A Khan
- International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh
| | - Rishikesh Kumar
- ICMR-National Institute of Malaria Research, New Delhi, India
- ICMR-Rajendra Memorial Research Institute of Medical Sciences, Patna, Bihar, India
| | - Toby Leslie
- Department of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK
- HealthNet TPO, Kabul, Afghanistan
| | - Benedikt Ley
- Global Health Division, Menzies School of Health Research, Charles Darwin University, Tiwi, Northern Territory, Australia
| | - Alejandro Llanos-Cuentas
- Unit of Leishmaniasis and Malaria, Instituto de Medicina Tropical "Alexander von Humboldt", Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Sasithon Pukrittayakamee
- Mahidol Oxford Tropical Medicine Research Unit (MORU), Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
| | - Komal Raj Rijal
- Central Department of Microbiology, Tribhuvan University, Kirtipur, Nepal
- Department of Clinical Tropical Medicine, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
| | - Mark Rowland
- Department of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK
| | - Kavitha Saravu
- Department of Infectious Diseases, Kasturba Medical College, Manipal Academy of Higher Education, Manipal, Karnataka, India
- Manipal Centre for Infectious Diseases, Prasanna School of Public Health, Manipal Academy of Higher Education, Manipal, Karnataka, India
| | - Julie A Simpson
- WorldWide Antimalarial Resistance Network, Asia Pacific Regional Hub - Australia, Melbourne, Victoria, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Philippe J Guerin
- WorldWide Antimalarial Resistance Network (WWARN), Oxford, UK
- Infectious Diseases Data Observatory (IDDO), Oxford, UK
- Centre for Tropical Medicine and Global Health, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK
| | - Ric N Price
- Global Health Division, Menzies School of Health Research, Charles Darwin University, Tiwi, Northern Territory, Australia
- WorldWide Antimalarial Resistance Network, Asia Pacific Regional Hub - Australia, Melbourne, Victoria, Australia
| | - Amit Sharma
- International Centre For Genetic Engineering and Biotechnology, New Delhi, India
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Westerhausen R. Interhemispheric Integration after Callosotomy: A Meta-Analysis of Poffenberger and Redundant-Target Paradigms. Neuropsychol Rev 2023; 33:872-890. [PMID: 36484870 PMCID: PMC10769931 DOI: 10.1007/s11065-022-09569-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Accepted: 11/16/2022] [Indexed: 12/13/2022]
Abstract
The central role of the corpus callosum in integrating perception and cognition across the cerebral hemispheres makes it highly desirable for clinical and basic research to have a repertoire of experimental paradigms assessing callosal functioning. Here, the objective was to assess the validity of two such paradigms (Poffenberger, redundant-target paradigms) by conducting single-step meta-analyses on individual case data of callosotomy patients. Studies were identified by systematic literature search (source: Pubmed and WebOfKnowledge, date: 07.03.2022) and all studies were included that reported callosotomy case data for either paradigm. Twenty-two studies (38 unique cases) provided 116 observations of the crossed-uncrossed difference (CUD) for the Poffenberger paradigm, while ten studies (22 cases, 103 observations) provided bilateral redundancy gain (bRG) measures. Using linear-mixed models with "individual" and "experiment" as random-effects variable, the mean CUD was estimated at 60.6 ms (CI95%: 45.3; 75.9) for commissurotomy, 43.5 ms (26.7; 60.2) for complete callosotomy, and 8.8 ms (1.1; 16.6) for partial anterior-medial callosotomy patients. The estimates of commissurotomy/callosotomy patients differed significantly from patients with partial callosotomy and healthy controls. The mean bRGmin (minimum unilateral reference) was estimated at 42.8 ms (27.1;58.4) for patients with complete and 30.8 ms (16.8; 44.7) for patients with partial callosotomy, both differing significantly from controls. One limitation was that different formulas for bRG were used, making it necessary to split the sample and reducing test power of some analyses. Nevertheless, the present findings suggest that both paradigms assess interhemispheric callosal integration, confirming their construct validity, but likely test distinct callosal functions.
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Affiliation(s)
- René Westerhausen
- Section for Cognitive and Clinical Neuroscience, Department of Psychology, University of Oslo, POB 1094 Blindern, Oslo, 0317, Norway.
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26
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Umemneku-Chikere CM, Wheaton L, Poad H, Ray D, Andrade IC, Khan S, Tappenden P, Abrams KR, Owen RK, Bujkiewicz S. Individual participant data from digital sources informed and improved precision in the evaluation of predictive biomarkers in Bayesian network meta-analysis. J Clin Epidemiol 2023; 164:96-103. [PMID: 37918640 DOI: 10.1016/j.jclinepi.2023.10.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Revised: 10/16/2023] [Accepted: 10/24/2023] [Indexed: 11/04/2023]
Abstract
OBJECTIVES We aimed to develop a network meta-analytic model for the evaluation of treatment effectiveness within predictive biomarker subgroups, by combining evidence from individual participant data (IPD) from digital sources (in the absence of randomized controlled trials) and aggregate data (AD). STUDY DESIGN AND SETTING A Bayesian framework was developed for modeling time-to-event data to evaluate predictive biomarkers. IPD were sourced from electronic health records, using a target trial emulation approach, or digitized Kaplan-Meier curves. The model is illustrated using two examples: breast cancer with a hormone receptor biomarker, and metastatic colorectal cancer with the Kirsten Rat Sarcoma (KRAS) biomarker. RESULTS The model allowed for the estimation of treatment effects in two subgroups of patients defined by their biomarker status. Effectiveness of taxanes did not differ in hormone receptor positive and negative breast cancer patients. Epidermal growth factor receptor inhibitors were more effective than chemotherapy in KRAS wild type colorectal cancer patients but not in patients with KRAS mutant status. Use of IPD reduced uncertainty of the subgroup-specific treatment effect estimates by up to 49%. CONCLUSION Utilization of IPD allowed for more detailed evaluation of predictive biomarkers and cancer therapies and improved precision of the estimates compared to use of AD alone.
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Affiliation(s)
- Chinyereugo M Umemneku-Chikere
- Department of Population Health Sciences, Biostatistics Research Group, University of Leicester, Leicester, UK; Centre for Review and Dissemination, University of York, York, UK.
| | - Lorna Wheaton
- Department of Population Health Sciences, Biostatistics Research Group, University of Leicester, Leicester, UK
| | - Heather Poad
- Department of Population Health Sciences, Biostatistics Research Group, University of Leicester, Leicester, UK
| | - Devleena Ray
- Department of Population Health Sciences, Biostatistics Research Group, University of Leicester, Leicester, UK
| | - Ilse Cuevas Andrade
- Department of Population Health Sciences, Biostatistics Research Group, University of Leicester, Leicester, UK
| | - Sam Khan
- Leicester Cancer Research Centre, Robert Kilpatrick Clinical Sciences Building, University of Leicester, Leicester, UK
| | - Paul Tappenden
- Sheffield Centre for Health and Related Research, University of Sheffield, Sheffield, UK
| | - Keith R Abrams
- Department of Statistics, University of Warwick, Coventry, UK; Centre for Health Economics, University of York, York, UK
| | - Rhiannon K Owen
- Swansea University Medical School, Swansea University, Swansea, UK
| | - Sylwia Bujkiewicz
- Department of Population Health Sciences, Biostatistics Research Group, University of Leicester, Leicester, UK
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27
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Mishra NK, Kwan P, Tanaka T, Sunnerhagen KS, Dawson J, Zhao Y, Misra S, Wang S, Sharma VK, Mazumder R, Funaro MC, Ihara M, Nicolo JP, Liebeskind DS, Yasuda CL, Cendes F, Quinn TJ, Ge Z, Scalzo F, Zelano J, Kasner SE. Clinical characteristics and outcomes of patients with post-stroke epilepsy: protocol for an individual patient data meta-analysis from the International Post-stroke Epilepsy Research Repository (IPSERR). BMJ Open 2023; 13:e078684. [PMID: 37968000 PMCID: PMC10660442 DOI: 10.1136/bmjopen-2023-078684] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Accepted: 10/12/2023] [Indexed: 11/17/2023] Open
Abstract
INTRODUCTION Despite significant advances in managing acute stroke and reducing stroke mortality, preventing complications like post-stroke epilepsy (PSE) has seen limited progress. PSE research has been scattered worldwide with varying methodologies and data reporting. To address this, we established the International Post-stroke Epilepsy Research Consortium (IPSERC) to integrate global PSE research efforts. This protocol outlines an individual patient data meta-analysis (IPD-MA) to determine outcomes in patients with post-stroke seizures (PSS) and develop/validate PSE prediction models, comparing them with existing models. This protocol informs about creating the International Post-stroke Epilepsy Research Repository (IPSERR) to support future collaborative research. METHODS AND ANALYSIS We utilised a comprehensive search strategy and searched MEDLINE, Embase, PsycInfo, Cochrane, and Web of Science databases until 30 January 2023. We extracted observational studies of stroke patients aged ≥18 years, presenting early or late PSS with data on patient outcome measures, and conducted the risk of bias assessment. We did not apply any restriction based on the date or language of publication. We will invite these study authors and the IPSERC collaborators to contribute IPD to IPSERR. We will review the IPD lodged within IPSERR to identify patients who developed epileptic seizures and those who did not. We will merge the IPD files of individual data and standardise the variables where possible for consistency. We will conduct an IPD-MA to estimate the prognostic value of clinical characteristics in predicting PSE. ETHICS AND DISSEMINATION Ethics approval is not required for this study. The results will be published in peer-reviewed journals. This study will contribute to IPSERR, which will be available to researchers for future PSE research projects. It will also serve as a platform to anchor future clinical trials. TRIAL REGISTRATION NUMBER NCT06108102.
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Affiliation(s)
- Nishant K Mishra
- Department of Neurology, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Patrick Kwan
- Department of Neuroscience, Monash University, Clayton, Victoria, Australia
| | - Tomotaka Tanaka
- Department of Neurology, National Cerebral and Cardiovascular Center, Suita, Japan
| | - Katharina S Sunnerhagen
- Department of Clinical Neuroscience, University of Gothenburg, Goteborg, Västra Götaland, Sweden
| | - Jesse Dawson
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Yize Zhao
- Department of Biostatistics, Yale University School of Public Health, New Haven, Connecticut, USA
| | - Shubham Misra
- Department of Neurology, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Selena Wang
- Department of Biostatistics, Yale University School of Public Health, New Haven, Connecticut, USA
| | - Vijay K Sharma
- Division of Neurology, Yong Loo Lin School of Medicine, National University of Singapore, National University Health System, Singapore
| | - Rajarshi Mazumder
- Department of Neurology, University of California Los Angeles, Los Angeles, California, USA
| | - Melissa C Funaro
- Harvey Cushing/John Hay Whitney Medical Library, Yale University, New Haven, Connecticut, USA
| | - Masafumi Ihara
- Department of Neurology, National Cerebral and Cardiovascular Center, Suita, Japan
| | - John-Paul Nicolo
- Department of Neuroscience, Monash University, Clayton, Victoria, Australia
- Department of Neurology and Medicine, The University of Melbourne, Royal Melbourne Hospital, Melbourne, Victoria, Australia
| | - David S Liebeskind
- Department of Neurology, University of California Los Angeles, Los Angeles, California, USA
| | - Clarissa L Yasuda
- Department of Neurology, School of Medical Sciences, University of Campinas - UNICAMP, Campinas, SP, Brazil
| | - Fernando Cendes
- Department of Neurology, School of Medical Sciences, University of Campinas - UNICAMP, Campinas, SP, Brazil
| | - Terence J Quinn
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Zongyuan Ge
- Department of Neuroscience, Monash University, Clayton, Victoria, Australia
| | - Fabien Scalzo
- Department of Neurology, University of California Los Angeles, Los Angeles, California, USA
- Department of Computer Science, Pepperdine University, Seaver College, Malibu, California, USA
| | - Johan Zelano
- Department of Clinical Neuroscience, University of Gothenburg, Goteborg, Västra Götaland, Sweden
- Department of Neurology, Sahlgrenska University Hospital, Goteborg, Sweden
| | - Scott E Kasner
- Department of Neurology, The University of Pennsylvania, Philadelphia, Pennsylvania, USA
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28
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Barrera-Gómez J, Puig X, Ginebra J, Basagaña X. Conditional Poisson Regression with Random Effects for the Analysis of Multi-site Time Series Studies. Epidemiology 2023; 34:873-878. [PMID: 37708493 PMCID: PMC10538616 DOI: 10.1097/ede.0000000000001664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Accepted: 08/02/2023] [Indexed: 09/16/2023]
Abstract
The analysis of time series studies linking daily counts of a health indicator with environmental variables (e.g., mortality or hospital admissions with air pollution concentrations or temperature; or motor vehicle crashes with temperature) is usually conducted with Poisson regression models controlling for long-term and seasonal trends using temporal strata. When the study includes multiple zones, analysts usually apply a two-stage approach: first, each zone is analyzed separately, and the resulting zone-specific estimates are then combined using meta-analysis. This approach allows zone-specific control for trends. A one-stage approach uses spatio-temporal strata and could be seen as a particular case of the case-time series framework recently proposed. However, the number of strata can escalate very rapidly in a long time series with many zones. A computationally efficient alternative is to fit a conditional Poisson regression model, avoiding the estimation of the nuisance strata. To allow for zone-specific effects, we propose a conditional Poisson regression model with a random slope, although available frequentist software does not implement this model. Here, we implement our approach in the Bayesian paradigm, which also facilitates the inclusion of spatial patterns in the effect of interest. We also provide a possible extension to deal with overdispersed data. We first introduce the equations of the framework and then illustrate their application to data from a previously published study on the effects of temperature on the risk of motor vehicle crashes. We provide R code and a semi-synthetic dataset to reproduce all analyses presented.
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Affiliation(s)
- Jose Barrera-Gómez
- From the ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Xavier Puig
- Department of Statistics and Operations Research, Universitat Politècnica de Catalunya, Barcelona, Spain
| | - Josep Ginebra
- Department of Statistics and Operations Research, Universitat Politècnica de Catalunya, Barcelona, Spain
| | - Xavier Basagaña
- From the ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
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Mun EY, Zhou Z, Huh D, Tan L, Li D, Tanner-Smith EE, Walters ST, Larimer ME. Brief Alcohol Interventions are Effective through 6 Months: Findings from Marginalized Zero-inflated Poisson and Negative Binomial Models in a Two-step IPD Meta-analysis. PREVENTION SCIENCE : THE OFFICIAL JOURNAL OF THE SOCIETY FOR PREVENTION RESEARCH 2023; 24:1608-1621. [PMID: 35976524 PMCID: PMC10678823 DOI: 10.1007/s11121-022-01420-1] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/02/2022] [Indexed: 12/14/2022]
Abstract
To evaluate and optimize brief alcohol interventions (BAIs), it is critical to have a credible overall effect size estimate as a benchmark. Estimating such an effect size has been challenging because alcohol outcomes often represent responses from a mixture of individuals: those at high risk for alcohol misuse, occasional nondrinkers, and abstainers. Moreover, some BAIs exclusively focus on heavy drinkers, whereas others take a universal prevention approach. Depending on sample characteristics, the outcome distribution might have many zeros or very few zeros and overdispersion; consequently, the most appropriate statistical model may differ across studies. We synthesized individual participant data (IPD) from 19 studies in Project INTEGRATE (Mun et al., 2015b) that randomly allocated participants to intervention and control groups (N = 7,704 participants, 38.4% men, 74.7% White, 58.5% first-year students). We sequentially estimated marginalized zero-inflated Poisson (Long et al., 2014) or negative binomial regression models to obtain covariate-adjusted, study-specific intervention effect estimates in the first step, which were subsequently combined in a random-effects meta-analysis model in the second step. BAIs produced a statistically significant 8% advantage in the mean number of drinks at both 1-3 months (RR = 0.92, 95% CI = [0.85, 0.98]) and 6 months (RR = 0.92, 95% CI = [0.85, 0.99]) compared to controls. At 9-12 months, there was no statistically significant difference in the mean number of drinks between BAIs and controls. In conclusion, BAIs are effective at reducing the mean number of drinks through at least 6 months post intervention. IPD can play a critical role in deriving findings that could not be obtained in original individual studies or standard aggregate data meta-analyses.
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Affiliation(s)
- Eun-Young Mun
- Department of Health Behavior and Health Systems, School of Public Health, University of North Texas Health Science Center, 3500 Camp Bowie Blvd., Fort Worth, TX, 76107, USA.
| | - Zhengyang Zhou
- Department of Biostatistics and Epidemiology, University of North Texas Health Science Center, Fort Worth, TX, 76107, USA
| | - David Huh
- School of Social Work, University of Washington, Seattle, WA, 98195, USA
| | - Lin Tan
- Department of Health Behavior and Health Systems, School of Public Health, University of North Texas Health Science Center, 3500 Camp Bowie Blvd., Fort Worth, TX, 76107, USA
| | - Dateng Li
- , 121 Westmoreland Ave, White Plains, NY, 10606, USA
| | - Emily E Tanner-Smith
- Department of Counseling Psychology and Human Services, University of Oregon, Eugene, OR, 97403, USA
| | - Scott T Walters
- Department of Health Behavior and Health Systems, School of Public Health, University of North Texas Health Science Center, 3500 Camp Bowie Blvd., Fort Worth, TX, 76107, USA
| | - Mary E Larimer
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, 98195, USA
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30
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Brantner CL, Chang TH, Nguyen TQ, Hong H, Stefano LD, Stuart EA. Methods for Integrating Trials and Non-experimental Data to Examine Treatment Effect Heterogeneity. Stat Sci 2023; 38:640-654. [PMID: 38638306 PMCID: PMC11025720 DOI: 10.1214/23-sts890] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/20/2024]
Abstract
Estimating treatment effects conditional on observed covariates can improve the ability to tailor treatments to particular individuals. Doing so effectively requires dealing with potential confounding, and also enough data to adequately estimate effect moderation. A recent influx of work has looked into estimating treatment effect heterogeneity using data from multiple randomized controlled trials and/or observational datasets. With many new methods available for assessing treatment effect heterogeneity using multiple studies, it is important to understand which methods are best used in which setting, how the methods compare to one another, and what needs to be done to continue progress in this field. This paper reviews these methods broken down by data setting: aggregate-level data, federated learning, and individual participant-level data. We define the conditional average treatment effect and discuss differences between parametric and nonparametric estimators, and we list key assumptions, both those that are required within a single study and those that are necessary for data combination. After describing existing approaches, we compare and contrast them and reveal open areas for future research. This review demonstrates that there are many possible approaches for estimating treatment effect heterogeneity through the combination of datasets, but that there is substantial work to be done to compare these methods through case studies and simulations, extend them to different settings, and refine them to account for various challenges present in real data.
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Affiliation(s)
- Carly Lupton Brantner
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland 21205, USA
| | - Ting-Hsuan Chang
- Department of Biostatistics, Columbia Mailman School of Public Health, New York, New York 10032, USA
| | - Trang Quynh Nguyen
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland 21205, USA
| | - Hwanhee Hong
- Department of Biostatistics and Bioinformatics, Duke University, Durham, North Carolina 27710, USA
| | - Leon Di Stefano
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland 21205, USA
| | - Elizabeth A Stuart
- Departments of Biostatistics, Mental Health, and Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland 21205, USA
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31
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Russell MA, Coatsworth JD, Brown A, Zaharakis N, Mennis J, Rodriguez GC, Mason MJ. Peer Network Counseling Effects on Substance Use: an Individual Participant Data Meta-Analysis Integrating Three Randomized Controlled Trials. PREVENTION SCIENCE : THE OFFICIAL JOURNAL OF THE SOCIETY FOR PREVENTION RESEARCH 2023; 24:1510-1522. [PMID: 36478336 DOI: 10.1007/s11121-022-01468-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/16/2022] [Indexed: 12/12/2022]
Abstract
The current study describes an individual participant data meta-analysis (IPDMA) testing the efficacy of a peer-network counseling (PNC) intervention for preventing substance use escalation in adolescents and young adults. PNC has shown efficacy in reducing substance use among adolescents and young adults across small-scale randomized controlled trials (RCTs). Identifying expected large-scale effects and moderators is an important next step in guiding use of PNC in practice. To this end, we combine three small-scale RCTs to test PNC intervention effects on substance use change in a combined sample of 421 adolescents and young adults (50% intervention, 55% female, 69% Black/African-American, M age [SD] = 17.3 [2.2] years). Our approach combines latent change score modeling in a structural equation modeling (SEM) framework with study-level fixed effects to obtain (a) a more generalizable PNC effect than we could obtain with each constituent sample and (b) greater power and precision for individual-level moderation of treatment effects. We found that although PNC main effects on substance use outcomes (past 30-day cannabis, alcohol, tobacco, and drug use) were not significant, PNC effects were moderated by individual-level pre-intervention substance use frequency. PNC more strongly reduced drug use at the 1-month follow-up and cannabis use at the 3-month follow-up among participants who showed higher baseline use of these substances. Implications of our approach and findings for prevention researchers are discussed.
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Affiliation(s)
- Michael A Russell
- The Pennsylvania State University, 219 Biobehavioral Health Building, The Pennsylvania State University, University Park, PA, 16803, USA.
| | | | | | | | | | - Gabriel C Rodriguez
- The Pennsylvania State University, 219 Biobehavioral Health Building, The Pennsylvania State University, University Park, PA, 16803, USA
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Zaslavsky K, Park T, Lang Mcinnis R, Mandell M, Lee J, Lee C, Gilbert R, Derzko-Dzulynsky L. Outcomes in PIC-Related CNV: Pooled Analysis of Individual Participant Data. Ocul Immunol Inflamm 2023; 31:1825-1836. [PMID: 36179037 DOI: 10.1080/09273948.2022.2124176] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 09/06/2022] [Indexed: 10/14/2022]
Abstract
Choroidal neovascularization (CNV) affects 64-75% of eyes with punctate inner choroidopathy (PIC). Although anti-VEGF agents are considered first-line therapy, there is controversy regarding other modalities, such as immunosuppression. We performed a systematic review of individual participant data (IPD) and generated a dataset of 278 eyes with PIC-related CNV from 45 studies. Forty-two percent presented with moderate visual loss (MVL) or worse. Four different treatment modalities (anti-VEGF, photodynamic therapy, local immunosuppression, and systemic immunosuppression) and most combinations among them were represented. Anti-VEGF injections decreased the likelihood of MVL (Odds Ratio 0.3, p = .027), an effect moderated by presenting visual acuity and patient age. Eyes receiving more than 3 injections were more likely to receive additional therapeutic modalities. Increasing number of modalities was associated with longer follow-up time and did not improve vision. The beneficial effect of anti-VEGF injections persisted when controlling for presenting visual acuity and follow-up time.
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Affiliation(s)
- Kirill Zaslavsky
- Department of Ophthalmology and Vision Sciences, University of Toronto, Toronto, Ontario, Canada
| | - Teresa Park
- Department of Ophthalmology, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Rachel Lang Mcinnis
- Department of Ophthalmology, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
| | - Mark Mandell
- Department of Ophthalmology and Vision Sciences, University of Toronto, Toronto, Ontario, Canada
- Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Jihwan Lee
- Department of Ophthalmology, The Institute of Vision Research, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Christopher Lee
- Department of Ophthalmology, The Institute of Vision Research, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Rose Gilbert
- Moorfields Eye Hospital NHS Foundation Trust, London, UK
- National Institute for Health Research Moorfields Biomedical Research Centre, London, UK
- Addenbrooke's Hospital, Cambridge University Hospitals NHS Trust, Cambridge, UK
| | - Larissa Derzko-Dzulynsky
- Department of Ophthalmology and Vision Sciences, University of Toronto, Toronto, Ontario, Canada
- Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
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Riley RD, Ensor J, Hattle M, Papadimitropoulou K, Morris TP. Two-stage or not two-stage? That is the question for IPD meta-analysis projects. Res Synth Methods 2023; 14:903-910. [PMID: 37606180 PMCID: PMC7615283 DOI: 10.1002/jrsm.1661] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 06/27/2023] [Accepted: 07/22/2023] [Indexed: 08/23/2023]
Abstract
Individual participant data meta-analysis (IPDMA) projects obtain, check, harmonise and synthesise raw data from multiple studies. When undertaking the meta-analysis, researchers must decide between a two-stage or a one-stage approach. In a two-stage approach, the IPD are first analysed separately within each study to obtain aggregate data (e.g., treatment effect estimates and standard errors); then, in the second stage, these aggregate data are combined in a standard meta-analysis model (e.g., common-effect or random-effects). In a one-stage approach, the IPD from all studies are analysed in a single step using an appropriate model that accounts for clustering of participants within studies and, potentially, between-study heterogeneity (e.g., a general or generalised linear mixed model). The best approach to take is debated in the literature, and so here we provide clearer guidance for a broad audience. Both approaches are important tools for IPDMA researchers and neither are a panacea. If most studies in the IPDMA are small (few participants or events), a one-stage approach is recommended due to using a more exact likelihood. However, in other situations, researchers can choose either approach, carefully following best practice. Some previous claims recommending to always use a one-stage approach are misleading, and the two-stage approach will often suffice for most researchers. When differences do arise between the two approaches, often it is caused by researchers using different modelling assumptions or estimation methods, rather than using one or two stages per se.
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Affiliation(s)
- Richard D. Riley
- Institute of Applied Health Research, College of Medical and Dental SciencesUniversity of BirminghamBirminghamUK
| | - Joie Ensor
- Institute of Applied Health Research, College of Medical and Dental SciencesUniversity of BirminghamBirminghamUK
| | - Miriam Hattle
- Institute of Applied Health Research, College of Medical and Dental SciencesUniversity of BirminghamBirminghamUK
- School of MedicineKeele UniversityKeeleStaffordshireUK
| | | | - Tim P. Morris
- MRC Clinical Trials Unit at UCLInstitute of Clinical Trials and Methodology, UCLLondonUK
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Schweer-Collins ML, Parr NJ, Saitz R, Tanner-Smith EE. Investigating for Whom Brief Substance Use Interventions Are Most Effective: An Individual Participant Data Meta-analysis. PREVENTION SCIENCE : THE OFFICIAL JOURNAL OF THE SOCIETY FOR PREVENTION RESEARCH 2023; 24:1459-1482. [PMID: 37133684 PMCID: PMC10678844 DOI: 10.1007/s11121-023-01525-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/07/2023] [Indexed: 05/04/2023]
Abstract
Prior research suggests that brief interventions (BIs) for alcohol and other drug use may vary in effectiveness across patient sociodemographic factors. The objective of this individual participant data (IPD) meta-analysis was to explore for whom BIs delivered in general healthcare settings are more or less effective. We examined variability in BI effects by patient age, sex, employment, education, relationship status, and baseline severity of substance use using a two-stage IPD meta-analysis approach. All trials included in a parent aggregate data meta-analysis (k = 116) were invited to contribute IPD, and 29 trials provided patient-level data (12,074 participants). Among females, BIs led to significant reductions in binge alcohol consumption ([Formula: see text] = 0.09, 95% CI [0.03, 0.14]), frequency of alcohol consumption ([Formula: see text] = 0.10, 95% CI [0.03, 0.17]), and alcohol-related consequences ([Formula: see text] = 0.16, 95% CI [0.08, 0.25]), as well as greater substance use treatment utilization ([Formula: see text] = 0.25, 95% CI [0.21, 0.30]). BIs yielded larger reductions in frequency of alcohol consumption at 3-month follow-up for individuals with less than a high school level education ([Formula: see text] = 0.16, 95% CI [0.09, 0.22]). Given evidence demonstrating modest BI effects on alcohol use and mixed or null findings for BI effects on other drug use, BI research should continue to investigate potential drivers of effect magnitude and variation. PROTOCOL REGISTRATION DETAILS: The protocol for this review was pre-registered in PROSPERO #CRD42018086832 and the analysis plan was pre-registered in OSF: osf.io/m48g6.
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Affiliation(s)
- Maria L Schweer-Collins
- Prevention Science Institute, University of Oregon, University of Oregon, 97403-6217, Eugene, OR, USA.
- HEDCO Institute for Evidence-Based Educational Practice, University of Oregon, University of Oregon, 1215, 97403-1215, Eugene, OR, USA.
| | - Nicholas J Parr
- U.S. Department of Veterans Affairs Evidence Synthesis Program Coordinating Center, VA Portland Health Care System, 3710 SW U.S. Veterans Hospital Rd, 97239, Portland, OR, USA
| | - Richard Saitz
- Department of Community Health Sciences, School of Public Health, Boston University, 801 Massachusetts Ave, 4th Floor, 02118, Boston, MA, USA
- Clinical Addiction Research and Education Unit, Section of General Internal Medicine, Boston University School of Medicine, Boston, USA
- Grayken Center for Addiction, Boston Medical Center, Boston, USA
| | - Emily E Tanner-Smith
- Prevention Science Institute, University of Oregon, University of Oregon, 97403-6217, Eugene, OR, USA
- HEDCO Institute for Evidence-Based Educational Practice, University of Oregon, University of Oregon, 1215, 97403-1215, Eugene, OR, USA
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Huh D, Baldwin SA, Zhou Z, Park J, Mun EY. Which is Better for Individual Participant Data Meta-Analysis of Zero-Inflated Count Outcomes, One-Step or Two-Step Analysis? A Simulation Study. MULTIVARIATE BEHAVIORAL RESEARCH 2023; 58:1090-1105. [PMID: 36952487 PMCID: PMC10517064 DOI: 10.1080/00273171.2023.2173135] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Meta-analysis using individual participant data (IPD) is an important methodology in intervention research because it (a) increases accuracy and precision of estimates, (b) allows researchers to investigate mediators and moderators of treatment effects, and (c) makes use of extant data. IPD meta-analysis can be conducted either via a one-step approach that uses data from all studies simultaneously, or a two-step approach, which aggregates data for each study and then combines them in a traditional meta-analysis model. Unfortunately, there are no evidence-based guidelines for how best to approach IPD meta-analysis for count outcomes with many zeroes, such as alcohol use. We used simulation to compare the performance of four hurdle models (3 one-step and 1 two-step models) for zero-inflated count IPD, under realistic data conditions. Overall, all models yielded adequate coverage and bias for the treatment effect in the count portion of the model, across all data conditions. However, in the zero portion, the treatment effect was underestimated in most models and data conditions, especially when there were fewer studies. The performance of both one- and two-step approaches depended on the formulation of the treatment effects, suggesting a need to carefully consider model assumptions and specifications when using IPD.
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Affiliation(s)
- David Huh
- University of Washington, School of Social Work, Seattle, WA, USA
| | - Scott A. Baldwin
- Department of Psychology, Brigham Young University, Provo, UT, USA
| | - Zhengyang Zhou
- Department of Biostatistics and Epidemiology, University of North Texas Health Science Center, Fort Worth, TX, USA
| | - Joonsuk Park
- Department of Psychology, The Ohio State University, Columbus, OH, USA
| | - Eun-Young Mun
- Department of Health Behavior and Health Systems, University of North Texas Health Science Center, Fort Worth, TX, USA
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Kumar R, Dahal P, Singh-Phulgenda S, Siddiqui NA, Munir A, Naylor C, Wilson J, Buck G, Rahi M, Malaviya P, Alves F, Sundar S, Ritmeijer K, Stepniewska K, Guérin PJ, Pandey K. Host, parasite and drug determinants of clinical outcomes following treatment of visceral leishmaniasis: a protocol for individual participant data meta-analysis. BMJ Open 2023; 13:e074679. [PMID: 37898487 PMCID: PMC10618999 DOI: 10.1136/bmjopen-2023-074679] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Accepted: 09/04/2023] [Indexed: 10/30/2023] Open
Abstract
INTRODUCTION Visceral leishmaniasis (VL) is a parasitic disease with an estimated 30 000 new cases occurring annually. There is an observed variation in the efficacy of the current first-line therapies across different regions. Such heterogeneity could be a function of host, parasite and drug factors. An individual participant data meta-analysis (IPD-MA) is planned to explore the determinants of treatment outcomes. METHODS AND ANALYSIS The Infectious Diseases Data Observatory (IDDO) VL living systematic review (IDDO VL LSR) library is an open-access resource of all published therapeutic studies in VL since 1980. For this current review, the search includes all clinical trials published between 1 January 1980 and 2 May 2021. Studies indexed in the IDDO VL LSR library were screened for eligibility for inclusion in this IPD-MA. Corresponding authors and principal investigators of the studies meeting the eligibility criteria for inclusion were invited to be part of the collaborative IPD-MA. Authors agreeing to participate in this collaborative research were requested to share the IPD using the IDDO VL data platform. The IDDO VL data platform currently holds data sets from clinical trials standardised to a common data format and provides a unique opportunity to identify host, parasite and drug determinants of treatment outcomes. Multivariable regression models will be constructed to identify determinants of therapeutic outcomes using generalised linear mixed-effects models accounting for within-study site clustering. ETHICS AND DISSEMINATION This IPD-MA meets the criteria for waiver of ethical review as defined by the Oxford Tropical Research Ethics Committee (OxTREC) granted to IDDO, as the research consists of secondary analysis of existing anonymised data (Exempt granted on 29 March 2023, OxTREC REF: IDDO) Ethics approval was granted by the ICMR-Rajendra Memorial Research Institute of Medical Sciences ethics committee (Letter no: RMRI/EC/30/2022) on 04-07-2022. The results of this IPD-MA will be disseminated at conferences, IDDO website and any peer-reviewed publications. All publications will be open source. Findings of this research will be critically important for the control programmes at regional/global levels, policy makers and groups developing new VL treatments. PROSPERO REGISTRATION CRD42021284622.
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Affiliation(s)
- Rishikesh Kumar
- Indian Council of Medical Research (ICMR)-Rajendra Memorial Research Institute of Medical Sciences (RMRIMS), Patna, India
| | - Prabin Dahal
- Infectious Diseases Data Observatory (IDDO), University of Oxford, Oxford, UK
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Sauman Singh-Phulgenda
- Infectious Diseases Data Observatory (IDDO), University of Oxford, Oxford, UK
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Niyamat Ali Siddiqui
- Indian Council of Medical Research (ICMR)-Rajendra Memorial Research Institute of Medical Sciences (RMRIMS), Patna, India
| | - Abdalla Munir
- Infectious Diseases Data Observatory (IDDO), University of Oxford, Oxford, UK
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Caitlin Naylor
- Infectious Diseases Data Observatory (IDDO), University of Oxford, Oxford, UK
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - James Wilson
- Infectious Diseases Data Observatory (IDDO), University of Oxford, Oxford, UK
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Gemma Buck
- Infectious Diseases Data Observatory (IDDO), University of Oxford, Oxford, UK
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Manju Rahi
- Epidemiology and Communicable Diseases, Indian Council of Medical Research (ICMR), New Delhi, Delhi, India
| | - Paritosh Malaviya
- Infectious Disease Research Laboratory, Department of Medicine, Institute of Medical Sciences, Banaras Hindu University, Varanasi, India
| | - Fabiana Alves
- Drugs for Neglected Disease Initiative, Geneva, Switzerland
| | - Shyam Sundar
- Infectious Disease Research Laboratory, Department of Medicine, Institute of Medical Sciences, Banaras Hindu University, Varanasi, India
| | | | - Kasia Stepniewska
- Infectious Diseases Data Observatory (IDDO), University of Oxford, Oxford, UK
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Philippe J Guérin
- Infectious Diseases Data Observatory (IDDO), University of Oxford, Oxford, UK
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Krishna Pandey
- Indian Council of Medical Research (ICMR)-Rajendra Memorial Research Institute of Medical Sciences (RMRIMS), Patna, India
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Sánchez-de-la-Torre M, Gracia-Lavedan E, Benitez ID, Sánchez-de-la-Torre A, Moncusí-Moix A, Torres G, Loffler K, Woodman R, Adams R, Labarca G, Dreyse J, Eulenburg C, Thunström E, Glantz H, Peker Y, Anderson C, McEvoy D, Barbé F. Adherence to CPAP Treatment and the Risk of Recurrent Cardiovascular Events: A Meta-Analysis. JAMA 2023; 330:1255-1265. [PMID: 37787793 PMCID: PMC10548300 DOI: 10.1001/jama.2023.17465] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Accepted: 08/20/2023] [Indexed: 10/04/2023]
Abstract
Importance The effect of continuous positive airway pressure (CPAP) on secondary cardiovascular disease prevention is highly debated. Objective To assess the effect of CPAP treatment for obstructive sleep apnea (OSA) on the risk of adverse cardiovascular events in randomized clinical trials. Data Sources PubMed (MEDLINE), EMBASE, Current Controlled Trials: metaRegister of Controlled Trials, ISRCTN Registry, European Union clinical trials database, CENTRAL (Cochrane Central Register of Controlled Trials), and ClinicalTrials.gov databases were systematically searched through June 22, 2023. Study Selection For qualitative and individual participant data (IPD) meta-analysis, randomized clinical trials addressing the therapeutic effect of CPAP on cardiovascular outcomes and mortality in adults with cardiovascular disease and OSA were included. Data Extraction and Synthesis Two reviewers independently screened records, evaluated potentially eligible primary studies in full text, extracted data, and cross-checked errors. IPD were requested from authors of the selected studies (SAVE [NCT00738179], ISAACC [NCT01335087], and RICCADSA [NCT00519597]). Main Outcomes and Measures One-stage and 2-stage IPD meta-analyses were completed to estimate the effect of CPAP treatment on risk of recurrent major adverse cardiac and cerebrovascular events (MACCEs) using mixed-effect Cox regression models. Additionally, an on-treatment analysis with marginal structural Cox models using inverse probability of treatment weighting was fitted to assess the effect of good adherence to CPAP (≥4 hours per day). Results A total of 4186 individual participants were evaluated (82.1% men; mean [SD] body mass index, 28.9 [4.5]; mean [SD] age, 61.2 [8.7] years; mean [SD] apnea-hypopnea index, 31.2 [17] events per hour; 71% with hypertension; 50.1% receiving CPAP [mean {SD} adherence, 3.1 {2.4} hours per day]; 49.9% not receiving CPAP [usual care], mean [SD] follow-up, 3.25 [1.8] years). The main outcome was defined as the first MACCE, which was similar for the CPAP and no CPAP groups (hazard ratio, 1.01 [95% CI, 0.87-1.17]). However, an on-treatment analysis by marginal structural model revealed a reduced risk of MACCEs associated with good adherence to CPAP (hazard ratio, 0.69 [95% CI, 0.52-0.92]). Conclusions and Relevance Adherence to CPAP was associated with a reduced MACCE recurrence risk, suggesting that treatment adherence is a key factor in secondary cardiovascular prevention in patients with OSA.
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Affiliation(s)
- Manuel Sánchez-de-la-Torre
- Precision Medicine in Chronic Diseases, Hospital Universitari Arnau de Vilanova-Santa Maria, IRB Lleida, Department of Nursing and Physiotherapy, Faculty of Nursing and Physiotherapy, University of Lleida, Lleida, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain
| | - Esther Gracia-Lavedan
- Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain
- Translation Research in Respiratory Medicine, Hospital Universitari Arnau de Vilanova-Santa Maria, IRBLleida, Lleida, Spain
| | - Ivan D. Benitez
- Precision Medicine in Chronic Diseases, Hospital Universitari Arnau de Vilanova-Santa Maria, IRB Lleida, Department of Nursing and Physiotherapy, Faculty of Nursing and Physiotherapy, University of Lleida, Lleida, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain
| | - Alicia Sánchez-de-la-Torre
- Precision Medicine in Chronic Diseases, Hospital Universitari Arnau de Vilanova-Santa Maria, IRB Lleida, Department of Nursing and Physiotherapy, Faculty of Nursing and Physiotherapy, University of Lleida, Lleida, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain
| | - Anna Moncusí-Moix
- Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain
- Translation Research in Respiratory Medicine, Hospital Universitari Arnau de Vilanova-Santa Maria, IRBLleida, Lleida, Spain
| | - Gerard Torres
- Precision Medicine in Chronic Diseases, Hospital Universitari Arnau de Vilanova-Santa Maria, IRB Lleida, Department of Nursing and Physiotherapy, Faculty of Nursing and Physiotherapy, University of Lleida, Lleida, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain
| | - Kelly Loffler
- Flinders Health and Medical Research Institute, College of Medicine and Public Health, Flinders University, Adelaide, South Australia, Australia
| | - Richard Woodman
- Flinders Health and Medical Research Institute, College of Medicine and Public Health, Flinders University, Adelaide, South Australia, Australia
| | - Robert Adams
- Flinders Health and Medical Research Institute, College of Medicine and Public Health, Flinders University, Adelaide, South Australia, Australia
| | - Gonzalo Labarca
- Laboratorio de Inmunología Traslacional, Departamento de Bioquímica Clínica e Inmunología, Facultad de Farmacia, Universidad de Concepción, Concepción, Chile
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts
| | | | - Christine Eulenburg
- Department for Medical Biometry and Epidemiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Erik Thunström
- Department of Molecular and Clinical Medicine/Cardiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Helena Glantz
- Department of Internal Medicine, Skarabrg Hospital, Lidköping, Sweden
| | - Yüksel Peker
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts
- Department of Molecular and Clinical Medicine/Cardiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Pulmonary Medicine, Koç University School of Medicine, Istanbul, Turkey
- Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
- Department of Clinical Sciences, Respiratory Medicine, and Allergology, Faculty of Medicine, Lund University, Lund, Sweden
| | - Craig Anderson
- The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, New South Wales, Australia
| | - Doug McEvoy
- Flinders Health and Medical Research Institute, College of Medicine and Public Health, Flinders University, Adelaide, South Australia, Australia
| | - Ferran Barbé
- Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain
- Translation Research in Respiratory Medicine, Hospital Universitari Arnau de Vilanova-Santa Maria, IRBLleida, Lleida, Spain
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Sadeghirad B, Dodsworth BT, Schmutz Gelsomino N, Goettel N, Spence J, Buchan TA, Crandon HN, Baneshi MR, Pol RA, Brattinga B, Park UJ, Terashima M, Banning LBD, Van Leeuwen BL, Neerland BE, Chuan A, Martinez FT, Van Vugt JLA, Rampersaud YR, Hatakeyama S, Di Stasio E, Milisen K, Van Grootven B, van der Laan L, Thomson Mangnall L, Goodlin SJ, Lungeanu D, Denhaerynck K, Dhakharia V, Sampson EL, Zywiel MG, Falco L, Nguyen ALV, Moss SJ, Krewulak KD, Jaworska N, Plotnikoff K, Kotteduwa-Jayawarden S, Sandarage R, Busse JW, Mbuagbaw L. Perioperative Factors Associated With Postoperative Delirium in Patients Undergoing Noncardiac Surgery: An Individual Patient Data Meta-Analysis. JAMA Netw Open 2023; 6:e2337239. [PMID: 37819663 PMCID: PMC10568362 DOI: 10.1001/jamanetworkopen.2023.37239] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Accepted: 08/21/2023] [Indexed: 10/13/2023] Open
Abstract
Importance Postoperative delirium (POD) is a common and serious complication after surgery. Various predisposing factors are associated with POD, but their magnitude and importance using an individual patient data (IPD) meta-analysis have not been assessed. Objective To identify perioperative factors associated with POD and assess their relative prognostic value among adults undergoing noncardiac surgery. Data Sources MEDLINE, EMBASE, and CINAHL from inception to May 2020. Study Selection Studies were included that (1) enrolled adult patients undergoing noncardiac surgery, (2) assessed perioperative risk factors for POD, and (3) measured the incidence of delirium (measured using a validated approach). Data were analyzed in 2020. Data Extraction and Synthesis Individual patient data were pooled from 21 studies and 1-stage meta-analysis was performed using multilevel mixed-effects logistic regression after a multivariable imputation via chained equations model to impute missing data. Main Outcomes and Measures The end point of interest was POD diagnosed up to 10 days after a procedure. A wide range of perioperative risk factors was considered as potentially associated with POD. Results A total of 192 studies met the eligibility criteria, and IPD were acquired from 21 studies that enrolled 8382 patients. Almost 1 in 5 patients developed POD (18%), and an increased risk of POD was associated with American Society of Anesthesiologists (ASA) status 4 (odds ratio [OR], 2.43; 95% CI, 1.42-4.14), older age (OR for 65-85 years, 2.67; 95% CI, 2.16-3.29; OR for >85 years, 6.24; 95% CI, 4.65-8.37), low body mass index (OR for body mass index <18.5, 2.25; 95% CI, 1.64-3.09), history of delirium (OR, 3.9; 95% CI, 2.69-5.66), preoperative cognitive impairment (OR, 3.99; 95% CI, 2.94-5.43), and preoperative C-reactive protein levels (OR for 5-10 mg/dL, 2.35; 95% CI, 1.59-3.50; OR for >10 mg/dL, 3.56; 95% CI, 2.46-5.17). Completing a college degree or higher was associated with a decreased likelihood of developing POD (OR 0.45; 95% CI, 0.28-0.72). Conclusions and Relevance In this systematic review and meta-analysis of individual patient data, several important factors associated with POD were found that may help identify patients at high risk and may have utility in clinical practice to inform patients and caregivers about the expected risk of developing delirium after surgery. Future studies should explore strategies to reduce delirium after surgery.
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Affiliation(s)
- Behnam Sadeghirad
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada
- Department of Anesthesia, McMaster University, Hamilton, Canada
- Michael G. DeGroote Institute for Pain Research and Care, McMaster University, Hamilton, Canada
| | | | | | - Nicolai Goettel
- Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Jessica Spence
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada
- Department of Anesthesia, McMaster University, Hamilton, Canada
| | - Tayler A. Buchan
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada
| | - Holly N. Crandon
- Michael G. DeGroote Institute for Pain Research and Care, McMaster University, Hamilton, Canada
| | - Mohammad R. Baneshi
- The University of Queensland, Australian Women and Girls’ Health Research Centre, School of Public Health, Herston Road, Herston, Queensland, Australia
| | - Robert A. Pol
- Department of Surgery, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Baukje Brattinga
- Department of Surgery, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Ui Jun Park
- Transplant & Vascular Surgery, School of Medicine, Keimyung University, Dongsan Hospital, Daegu, South Korea
| | - Masanori Terashima
- Division of Gastric Surgery, Shizuoka Cancer Center, Nagaizumi-Cho, Shizuoka, Japan
| | - Louise B. D. Banning
- Department of Surgery, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Barbara L. Van Leeuwen
- Department of Surgery, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Bjørn E. Neerland
- Oslo Delirium Research Group, Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway
| | - Alwin Chuan
- South West Sydney Clinical School, University of New South Wales Australia, Sydney, New South Wales, Australia
- Department of Anaesthesia, Liverpool Hospital, Liverpool, New South Wales, Australia
| | | | - Jeroen L. A. Van Vugt
- Department of Surgery, Erasmus MC University Medical Center, Rotterdam, the Netherlands
| | - Y. Raja Rampersaud
- Division of Orthopaedic Surgery, Department of Surgery, Toronto Western Hospital, University of Toronto, Ontario, Canada
| | - Shingo Hatakeyama
- Department of Advanced Blood Purification Therapy, Hirosaki Graduate School of Medicine, Hirosaki, Japan
| | - Enrico Di Stasio
- Dipartimento di Scienze biotecnologiche di base, cliniche intensivologiche e perioperatorie, Università Cattolica del Sacro Cuore, Rome, Italy
- Dipartimento di scienze laboratoristiche ed infettivologiche, UOC Chimica, Biochimica e Biologia Molecolare Clinica, Fondazione Policlinico Universitario A. Gemelli IRCCS, Roma, Italy
| | - Koen Milisen
- Department of Public Health and Primary Care, Academic Centre for Nursing and Midwifery, KU Leuven, Leuven, Belgium
- Department of Geriatric Medicine, University Hospitals Leuven, Leuven, Belgium
| | - Bastiaan Van Grootven
- Department of Public Health and Primary Care, Academic Centre for Nursing and Midwifery, KU Leuven, Leuven, Belgium
- Institute of Nursing Science, Department Public Health (DPH), Faculty of Medicine, University of Basel, Basel, Switzerland
| | | | | | - Sarah J. Goodlin
- Geriatrics Section, Veterans Affairs Portland Health Services Center and Oregon Health & Science University, Portland, Oregon
| | - Diana Lungeanu
- Department of Functional Sciences, Centre for Modelling Biological Systems and Data Analysis, Victor Babes University of Medicine and Pharmacy, Timisoara, Romania
| | - Kris Denhaerynck
- Institute of Nursing Science, Department Public Health (DPH), Faculty of Medicine, University of Basel, Basel, Switzerland
| | - Vibhawari Dhakharia
- Department of Gynaecological Oncology, Health Care Global Enterprises Ltd, Bangalore, India
| | - Elizabeth L. Sampson
- Division of Psychiatry, University College London, London, UK
- Department of Psychological Medicine, East London NHS Foundation Trust, Royal London Hospital, London, UK
| | - Michael G. Zywiel
- Division of Orthopaedic Surgery, Department of Surgery, Toronto Western Hospital, University of Toronto, Ontario, Canada
| | - Lisa Falco
- Zühlke Engineering AG, Schlieren, Switzerland
| | - Anna-Lisa V. Nguyen
- Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
| | - Stephana J. Moss
- Department of Critical Care, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Karla D. Krewulak
- Department of Critical Care, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Natalia Jaworska
- Department of Critical Care, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Kara Plotnikoff
- Department of Critical Care, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | | | - Ryan Sandarage
- Department of Surgery, Division of Neurosurgery, University of Ottawa, Ottawa, Ontario, Canada
| | - Jason W. Busse
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada
- Department of Anesthesia, McMaster University, Hamilton, Canada
- Michael G. DeGroote National Pain Centre, McMaster University, Hamilton, Ontario, Canada
| | - Lawrence Mbuagbaw
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada
- Department of Anesthesia, McMaster University, Hamilton, Canada
- Centre for Development of Best Practices in Health, Yaoundé Central Hospital, Yaoundé, Cameroon
- Division of Epidemiology and Biostatistics, Department of Global Health, Stellenbosch University, Cape Town, South Africa
- Department of Pediatrics, McMaster University, Hamilton, Ontario, Canada
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Banaj N, Vecchio D, Piras F, De Rossi P, Bustillo J, Ciufolini S, Dazzan P, Di Forti M, Dickie EW, Ford JM, Fuentes-Claramonte P, Gruber O, Guerrero-Pedraza A, Hamilton HK, Howells FM, Kraemer B, Lawrie SM, Mathalon DH, Murray R, Pomarol-Clotet E, Potkin SG, Preda A, Radua J, Richter A, Salvador R, Sawa A, Scheffler F, Sim K, Spaniel F, Stein DJ, Temmingh HS, Thomopoulos SI, Tomecek D, Uhlmann A, Voineskos A, Yang K, Jahanshad N, Thompson PM, Van Erp TGM, Turner JA, Spalletta G, Piras F. Cortical morphology in patients with the deficit and non-deficit syndrome of schizophrenia: a worldwide meta- and mega-analyses. Mol Psychiatry 2023; 28:4363-4373. [PMID: 37644174 PMCID: PMC10827665 DOI: 10.1038/s41380-023-02221-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 08/02/2023] [Accepted: 08/07/2023] [Indexed: 08/31/2023]
Abstract
Converging evidence suggests that schizophrenia (SZ) with primary, enduring negative symptoms (i.e., Deficit SZ (DSZ)) represents a distinct entity within the SZ spectrum while the neurobiological underpinnings remain undetermined. In the largest dataset of DSZ and Non-Deficit (NDSZ), we conducted a meta-analysis of data from 1560 individuals (168 DSZ, 373 NDSZ, 1019 Healthy Controls (HC)) and a mega-analysis of a subsampled data from 944 individuals (115 DSZ, 254 NDSZ, 575 HC) collected across 9 worldwide research centers of the ENIGMA SZ Working Group (8 in the mega-analysis), to clarify whether they differ in terms of cortical morphology. In the meta-analysis, sites computed effect sizes for differences in cortical thickness and surface area between SZ and control groups using a harmonized pipeline. In the mega-analysis, cortical values of individuals with schizophrenia and control participants were analyzed across sites using mixed-model ANCOVAs. The meta-analysis of cortical thickness showed a converging pattern of widespread thinner cortex in fronto-parietal regions of the left hemisphere in both DSZ and NDSZ, when compared to HC. However, DSZ have more pronounced thickness abnormalities than NDSZ, mostly involving the right fronto-parietal cortices. As for surface area, NDSZ showed differences in fronto-parietal-temporo-occipital cortices as compared to HC, and in temporo-occipital cortices as compared to DSZ. Although DSZ and NDSZ show widespread overlapping regions of thinner cortex as compared to HC, cortical thinning seems to better typify DSZ, being more extensive and bilateral, while surface area alterations are more evident in NDSZ. Our findings demonstrate for the first time that DSZ and NDSZ are characterized by different neuroimaging phenotypes, supporting a nosological distinction between DSZ and NDSZ and point toward the separate disease hypothesis.
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Affiliation(s)
- Nerisa Banaj
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy.
| | - Daniela Vecchio
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Fabrizio Piras
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Pietro De Rossi
- Child and Adolescence Neuropsychiatry Unit, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy
| | - Juan Bustillo
- Psichiatry and Neuroscience, University of New Mexico, Albuquerque, NM, USA
| | - Simone Ciufolini
- Psychosis Studies, Institute of Psychiatry, Psychology and Neurology, King's College London, London, UK
| | - Paola Dazzan
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neurology, King's College London, London, UK
| | - Marta Di Forti
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neurology, King's College London, London, UK
| | - Erin W Dickie
- Center for Addiction and Mental Health, Campbell Family Mental Health Research Institute, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Kimel Family Lab, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Judith M Ford
- San Francisco VA Health Care System, San Francisco, CA, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Paola Fuentes-Claramonte
- FIMDAG Sisters Hospitallers Research Foundation, Barcelona, Spain
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - Oliver Gruber
- Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, Heidelberg University, Heidelberg, Baden-Wuerttemberg, Germany
| | | | - Holly K Hamilton
- San Francisco VA Health Care System, San Francisco, CA, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Fleur M Howells
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, Western Cape, South Africa
| | - Bernd Kraemer
- Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, Heidelberg University, Heidelberg, Baden-Wuerttemberg, Germany
| | - Stephen M Lawrie
- Division of Psychiatry, University of Edinburgh, Edinburg, EH10 5HF, UK
| | - Daniel H Mathalon
- San Francisco VA Health Care System, San Francisco, CA, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Robin Murray
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neurology, King's College London, London, UK
| | - Edith Pomarol-Clotet
- FIMDAG Sisters Hospitallers Research Foundation, Barcelona, Spain
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - Steven G Potkin
- Department of Psychiatry, University of California Irvine, Newfoundland, NJ, NJ 07435, USA
| | - Adrian Preda
- Psychiatry and Human Behavior, University of California Irvine, Orange, CA, 92868, USA
| | - Joaquim Radua
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
- Imaging of mood- and anxiety-related disorders (IMARD), Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, 08036, Spain
- Medicina, University of Barcelona, Barcelona, 08036, Spain
| | - Anja Richter
- Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, Heidelberg University, Heidelberg, Baden-Wuerttemberg, Germany
| | - Raymond Salvador
- FIMDAG Sisters Hospitallers Research Foundation, Barcelona, Spain
| | - Akira Sawa
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Genetic Medicine, Johns Hopkins University School of Medicine Baltimore, Baltimore, MD, USA
- Department of Pharmacology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Freda Scheffler
- Department of Psychiatry and Mental Health, Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Brain Behavior Unit, Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Kang Sim
- West Region, Institute of Mental Health, National Healthcare Group, Singapore, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Filip Spaniel
- CARE, National Institute of Mental Health, Klecany, Czech Republic
| | - Dan J Stein
- SAMRC Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry & Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Henk S Temmingh
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, Western Cape, South Africa
- Department of Psychiatry and Mental Health, Valkenberg Psychiatric Hospital, Cape Town, Western Cape, South Africa
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - David Tomecek
- CARE, National Institute of Mental Health, Klecany, Czech Republic
| | - Anne Uhlmann
- Department of child and adolescent psychiatry, TU Dresden, Dresden, Saxony, Germany
| | - Aristotle Voineskos
- Center for Addiction and Mental Health, Campbell Family Mental Health Research Institute, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Temerty Faculty of Medicine, Toronto, ON, Canada
| | - Kun Yang
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Theo G M Van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, Irvine, CA, USA
| | - Jessica A Turner
- Department of Psychiatry and Behavioral Health, Wexner Medical Center, The Ohio State University, Columbus, OH, USA
| | - Gianfranco Spalletta
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Federica Piras
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy
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40
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Dold M, Bartova L, Volz HP, Seifritz E, Möller HJ, Schläfke S, Kasper S. Efficacy of Silexan in patients with anxiety disorders: a meta-analysis of randomized, placebo-controlled trials. Eur Arch Psychiatry Clin Neurosci 2023; 273:1615-1628. [PMID: 36717399 PMCID: PMC10465640 DOI: 10.1007/s00406-022-01547-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Accepted: 12/19/2022] [Indexed: 01/31/2023]
Abstract
INTRODUCTION We report on a meta-analysis of Silexan, a proprietary active substance produced from Lavandula angustifolia, in subthreshold anxiety, mixed anxiety and depressive disorder (MADD), and generalized anxiety disorder (GAD). METHODS The present analyses are based on all currently completed 5 double-blind, randomized, placebo-controlled trials investigating Silexan in adult out-patients who received Silexan 1 × 80 mg/day or placebo for ten weeks according to random assignment (n = 1213). Efficacy was assessed based on the Hamilton Anxiety Rating Scale (HAMA), several anxiety self-rating scales, the Clinical Global Impression (CGI) scale, and the Short Form-36 (SF-36) health status questionnaire. RESULTS After ten weeks' treatment, Silexan was significantly superior to placebo in reducing the HAMA total score (including the psychic and somatic anxiety sub-scores) and self-rated anxiety. Based on a ≥ 50% HAMA total score reduction, the responder rate ratio was 1.34 favoring Silexan, and the rate ratio of subjects much or very much improved according to the CGI was 1.51. Silexan was also significantly superior in improving the physical and mental health summary scores of the SF-36. There were no significant between-group differences concerning the occurrence of adverse events (AEs), serious AEs, and premature withdrawal due to AEs. CONCLUSIONS This meta-analysis demonstrates that Silexan exerts significant anxiolytic effects in subthreshold anxiety, GAD and MADD that were consistently reflected in investigator ratings and patient-reported outcomes, including improvement of health-related life-quality, while showing favorable tolerability and safety.
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Affiliation(s)
- Markus Dold
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria
| | - Lucie Bartova
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria
| | - Hans-Peter Volz
- Hospital for Psychiatry, Psychotherapy and Psychosomatic Medicine Schloss Werneck, Balthasar-Neumann-Platz 1, 97440, Werneck, Germany
| | - Erich Seifritz
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital of the University of Zurich, Zurich, Switzerland
| | - Hans-Jürgen Möller
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilians-University Munich, Nußbaumstraße 7, 80336, Munich, Germany
| | - Sandra Schläfke
- Dr. Willmar Schwabe GmbH & Co. KG, Willmar-Schwabe-Straße 4, 76227, Karlsruhe, Germany
| | - Siegfried Kasper
- Center of Brain Research, Medical University of Vienna, Spitalgasse 4, 1090, Vienna, Austria.
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41
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Lennon MJ, Lam BCP, Lipnicki DM, Crawford JD, Peters R, Schutte AE, Brodaty H, Thalamuthu A, Rydberg-Sterner T, Najar J, Skoog I, Riedel-Heller SG, Röhr S, Pabst A, Lobo A, De-la-Cámara C, Lobo E, Bello T, Gureje O, Ojagbemi A, Lipton RB, Katz MJ, Derby CA, Kim KW, Han JW, Oh DJ, Rolandi E, Davin A, Rossi M, Scarmeas N, Yannakoulia M, Dardiotis T, Hendrie HC, Gao S, Carrière I, Ritchie K, Anstey KJ, Cherbuin N, Xiao S, Yue L, Li W, Guerchet MM, Preux PM, Aboyans V, Haan MN, Aiello AE, Ng TP, Nyunt MSZ, Gao Q, Scazufca M, Sachdev PSS. Use of Antihypertensives, Blood Pressure, and Estimated Risk of Dementia in Late Life: An Individual Participant Data Meta-Analysis. JAMA Netw Open 2023; 6:e2333353. [PMID: 37698858 PMCID: PMC10498335 DOI: 10.1001/jamanetworkopen.2023.33353] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Accepted: 07/28/2023] [Indexed: 09/13/2023] Open
Abstract
Importance The utility of antihypertensives and ideal blood pressure (BP) for dementia prevention in late life remains unclear and highly contested. Objectives To assess the associations of hypertension history, antihypertensive use, and baseline measured BP in late life (age >60 years) with dementia and the moderating factors of age, sex, and racial group. Data Source and Study Selection Longitudinal, population-based studies of aging participating in the Cohort Studies of Memory in an International Consortium (COSMIC) group were included. Participants were individuals without dementia at baseline aged 60 to 110 years and were based in 15 different countries (US, Brazil, Australia, China, Korea, Singapore, Central African Republic, Republic of Congo, Nigeria, Germany, Spain, Italy, France, Sweden, and Greece). Data Extraction and Synthesis Participants were grouped in 3 categories based on previous diagnosis of hypertension and baseline antihypertensive use: healthy controls, treated hypertension, and untreated hypertension. Baseline systolic BP (SBP) and diastolic BP (DBP) were treated as continuous variables. Reporting followed the Preferred Reporting Items for Systematic Review and Meta-Analyses of Individual Participant Data reporting guidelines. Main Outcomes and Measures The key outcome was all-cause dementia. Mixed-effects Cox proportional hazards models were used to assess the associations between the exposures and the key outcome variable. The association between dementia and baseline BP was modeled using nonlinear natural splines. The main analysis was a partially adjusted Cox proportional hazards model controlling for age, age squared, sex, education, racial group, and a random effect for study. Sensitivity analyses included a fully adjusted analysis, a restricted analysis of those individuals with more than 5 years of follow-up data, and models examining the moderating factors of age, sex, and racial group. Results The analysis included 17 studies with 34 519 community dwelling older adults (20 160 [58.4%] female) with a mean (SD) age of 72.5 (7.5) years and a mean (SD) follow-up of 4.3 (4.3) years. In the main, partially adjusted analysis including 14 studies, individuals with untreated hypertension had a 42% increased risk of dementia compared with healthy controls (hazard ratio [HR], 1.42; 95% CI 1.15-1.76; P = .001) and 26% increased risk compared with individuals with treated hypertension (HR, 1.26; 95% CI, 1.03-1.53; P = .02). Individuals with treated hypertension had no significant increased dementia risk compared with healthy controls (HR, 1.13; 95% CI, 0.99-1.28; P = .07). The association of antihypertensive use or hypertension status with dementia did not vary with baseline BP. There was no significant association of baseline SBP or DBP with dementia risk in any of the analyses. There were no significant interactions with age, sex, or racial group for any of the analyses. Conclusions and Relevance This individual patient data meta-analysis of longitudinal cohort studies found that antihypertensive use was associated with decreased dementia risk compared with individuals with untreated hypertension through all ages in late life. Individuals with treated hypertension had no increased risk of dementia compared with healthy controls.
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Affiliation(s)
- Matthew J. Lennon
- Faculty of Medicine, University of New South Wales, Sydney, Australia
- Centre for Healthy Brain Aging, Discipline of Psychiatry & Mental Health, School of Clinical Medicine, University of New South Wales, Sydney, Australia
| | - Ben Chun Pan Lam
- Faculty of Medicine, University of New South Wales, Sydney, Australia
- Centre for Healthy Brain Aging, Discipline of Psychiatry & Mental Health, School of Clinical Medicine, University of New South Wales, Sydney, Australia
- School of Psychology and Public Health, La Trobe University, Melbourne, Australia
| | - Darren M. Lipnicki
- Faculty of Medicine, University of New South Wales, Sydney, Australia
- Centre for Healthy Brain Aging, Discipline of Psychiatry & Mental Health, School of Clinical Medicine, University of New South Wales, Sydney, Australia
| | - John D. Crawford
- Faculty of Medicine, University of New South Wales, Sydney, Australia
- Centre for Healthy Brain Aging, Discipline of Psychiatry & Mental Health, School of Clinical Medicine, University of New South Wales, Sydney, Australia
| | - Ruth Peters
- The George Institute for Global Health, Sydney, Australia
- School of Biomedical Sciences, University of New South Wales, Sydney, Australia
- School of Public Health, Imperial College London, London, United Kingdom
| | - Aletta E. Schutte
- The George Institute for Global Health, Sydney, Australia
- School of Population Health, University of New South Wales, Sydney, Australia
| | - Henry Brodaty
- Faculty of Medicine, University of New South Wales, Sydney, Australia
- Centre for Healthy Brain Aging, Discipline of Psychiatry & Mental Health, School of Clinical Medicine, University of New South Wales, Sydney, Australia
- Eastern Suburbs Older Persons’ Mental Health Service, Sydney, Australia
| | - Anbupalam Thalamuthu
- Faculty of Medicine, University of New South Wales, Sydney, Australia
- Centre for Healthy Brain Aging, Discipline of Psychiatry & Mental Health, School of Clinical Medicine, University of New South Wales, Sydney, Australia
| | - Therese Rydberg-Sterner
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, Centre for Ageing and Health at the University of Gothenburg, Gothenburg, Sweden
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden
| | - Jenna Najar
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, Centre for Ageing and Health at the University of Gothenburg, Gothenburg, Sweden
- Psychiatry, Cognition and Old Age Psychiatry Clinic, Region Västra Götaland, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Ingmar Skoog
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, Centre for Ageing and Health at the University of Gothenburg, Gothenburg, Sweden
- Psychiatry, Cognition and Old Age Psychiatry Clinic, Region Västra Götaland, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Steffi G. Riedel-Heller
- Institute of Social Medicine, Occupational Health and Public Health, Medical Faculty, University of Leipzig, Leipzig, Germany
| | - Susanne Röhr
- Institute of Social Medicine, Occupational Health and Public Health, Medical Faculty, University of Leipzig, Leipzig, Germany
- School of Psychology, Manawatu Campus, Massey University, Palmerston North, New Zealand
- Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
| | - Alexander Pabst
- Institute of Social Medicine, Occupational Health and Public Health, Medical Faculty, University of Leipzig, Leipzig, Germany
| | - Antonio Lobo
- Department of Medicine and Psychiatry, Universidad de Zaragoza, Zaragoza, Spain
- Instituto de Investigación Sanitaria Aragón, Zaragoza, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Madrid, Spain
| | - Concepción De-la-Cámara
- Department of Medicine and Psychiatry, Universidad de Zaragoza, Zaragoza, Spain
- Instituto de Investigación Sanitaria Aragón, Zaragoza, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Madrid, Spain
| | - Elena Lobo
- Department of Medicine and Psychiatry, Universidad de Zaragoza, Zaragoza, Spain
- Instituto de Investigación Sanitaria Aragón, Zaragoza, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Madrid, Spain
| | - Toyin Bello
- World Health Organization Collaborating Centre for Research and Training in Mental Health, Neuroscience, and Substance Abuse, Department of Psychiatry, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Oye Gureje
- World Health Organization Collaborating Centre for Research and Training in Mental Health, Neuroscience, and Substance Abuse, Department of Psychiatry, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Akin Ojagbemi
- World Health Organization Collaborating Centre for Research and Training in Mental Health, Neuroscience, and Substance Abuse, Department of Psychiatry, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Richard B. Lipton
- Department of Neurology, Albert Einstein College of Medicine, Bronx, New York
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York
| | - Mindy J. Katz
- Department of Neurology, Albert Einstein College of Medicine, Bronx, New York
| | - Carol A. Derby
- Department of Neurology, Albert Einstein College of Medicine, Bronx, New York
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York
| | - Ki Woong Kim
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Korea
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Korea
| | - Ji Won Han
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Korea
| | - Dae Jong Oh
- Workplace Mental Health Institute, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Elena Rolandi
- Golgi Cenci Foundation, Abbiategrasso, Italy
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
| | | | | | - Nikolaos Scarmeas
- First Department of Neurology, Aiginition Hospital, National and Kapodistrian University of Athens, Athens, Greece
- Department of Neurology, Columbia University, New York, New York
| | - Mary Yannakoulia
- Department of Nutrition and Dietetics, School of Health Sciences and Education, Harokopio University, Athens, Greece
| | - Themis Dardiotis
- Department of Neurology, University Hospital of Larissa, Larissa, Greece
- Faculty of Medicine, School of Health Sciences, University of Thessaly, Larissa, Greece
| | - Hugh C. Hendrie
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis
- Indiana Alzheimer Disease Research Center, Indiana Alzheimer Disease Research Center, Indianapolis
| | - Sujuan Gao
- Indiana Alzheimer Disease Research Center, Indiana Alzheimer Disease Research Center, Indianapolis
- Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis
| | - Isabelle Carrière
- Institut for Neurosciences of Montpellier, University Montpellier, National Institute for Health and Medical Research, Montpellier, France
| | - Karen Ritchie
- Institut for Neurosciences of Montpellier, University Montpellier, National Institute for Health and Medical Research, Montpellier, France
- Institut du Cerveau Trocadéro, Paris, France
| | - Kaarin J. Anstey
- University of New South Wales, School of Psychology, Sydney, Australia
- Ageing Futures Institute, University of New South Wales, Sydney, Australia
- Neuroscience Research Australia, Sydney, Australia
| | - Nicolas Cherbuin
- National Centre for Epidemiology and Population Health, Australian National University, Canberra, Australia
| | - Shifu Xiao
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Alzheimer’s Disease and Related Disorders Center, Shanghai Jiao Tong University, Shanghai, China
| | - Ling Yue
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Alzheimer’s Disease and Related Disorders Center, Shanghai Jiao Tong University, Shanghai, China
| | - Wei Li
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Alzheimer’s Disease and Related Disorders Center, Shanghai Jiao Tong University, Shanghai, China
| | - Maëlenn M. Guerchet
- National Institute for Health and Medical Research U1094, Institut de Recherche pour le Developpement UMR270, Epidemiology of Chronic Diseases in Tropical Zone, Institute of Epidemiology and Tropical Neurology, OmegaHealth, University Limoges, Centre Hospitalier et Universitaire Limoges, Limoges, France
| | - Pierre-Marie Preux
- National Institute for Health and Medical Research U1094, Institut de Recherche pour le Developpement UMR270, Epidemiology of Chronic Diseases in Tropical Zone, Institute of Epidemiology and Tropical Neurology, OmegaHealth, University Limoges, Centre Hospitalier et Universitaire Limoges, Limoges, France
| | - Victor Aboyans
- National Institute for Health and Medical Research U1094, Institut de Recherche pour le Developpement UMR270, Epidemiology of Chronic Diseases in Tropical Zone, Institute of Epidemiology and Tropical Neurology, OmegaHealth, University Limoges, Centre Hospitalier et Universitaire Limoges, Limoges, France
- Department of Cardiology, Dupuytren 2 University Hospital, Limoges, France
| | - Mary N. Haan
- School of Medicine, University of California, San Francisco
| | - Allison E. Aiello
- Robert N. Butler Columbia Aging Center, Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York
| | - Tze Pin Ng
- Department of Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Geriatric Education and Research Institute, Ministry of Health, Singapore, Singapore
| | - Ma Shwe Zin Nyunt
- Department of Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Qi Gao
- Department of Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Marcia Scazufca
- Departamento de Psiquiatria, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil
| | - Perminder S. S. Sachdev
- Faculty of Medicine, University of New South Wales, Sydney, Australia
- Centre for Healthy Brain Aging, Discipline of Psychiatry & Mental Health, School of Clinical Medicine, University of New South Wales, Sydney, Australia
- Neuropsychiatric Institute, Prince of Wales Hospital, Sydney, Australia
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van der Worp H, Holtman GA, Blanker MH. Challenges In Performing An Individual Participant-level Data Meta-analysis. Eur Urol Focus 2023; 9:705-707. [PMID: 37872078 DOI: 10.1016/j.euf.2023.10.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Accepted: 10/12/2023] [Indexed: 10/25/2023]
Abstract
Individual participant-data meta-analysis (IPDMA) uses data at the participant level to synthesize evidence on clinical decision-making. We discuss the differences from aggregate-data meta-analysis and the advantages and challenges of IPDMA. IPDMA provides an opportunity to study effect modifiers at the participant level and can reduce bias in comparison to aggregate-data meta-analysis. A challenge with IPDMA is that it often requires considerable effort to obtain all the data, and an inability to obtain data for all the studies can lead to availability bias. PATIENT SUMMARY: Systematic reviews of the literature are performed to summarize available evidence regarding clinical decisions. Here we explain the differences between reviews that use aggregated data from published studies and reviews that use the participant-level data from those studies.
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Affiliation(s)
- Henk van der Worp
- Department of Primary and Long-term Care, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
| | - Gea A Holtman
- Department of Primary and Long-term Care, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Marco H Blanker
- Department of Primary and Long-term Care, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
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Haselimashhadi H, Babalola K, Wilson R, Groza T, Muñoz-Fuentes V. A consensus score to combine inferences from multiple centres. Mamm Genome 2023; 34:379-388. [PMID: 37154937 PMCID: PMC10382396 DOI: 10.1007/s00335-023-09993-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Accepted: 03/02/2023] [Indexed: 05/10/2023]
Abstract
Experiments in which data are collected by multiple independent resources, including multicentre data, different laboratories within the same centre or with different operators, are challenging in design, data collection and interpretation. Indeed, inconsistent results across the resources are possible. In this paper, we propose a statistical solution for the problem of multi-resource consensus inferences when statistical results from different resources show variation in magnitude, directionality, and significance. Our proposed method allows combining the corrected p-values, effect sizes and the total number of centres into a global consensus score. We apply this method to obtain a consensus score for data collected by the International Mouse Phenotyping Consortium (IMPC) across 11 centres. We show the application of this method to detect sexual dimorphism in haematological data and discuss the suitability of the methodology.
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Affiliation(s)
- Hamed Haselimashhadi
- European Bioinformatics Institute, European Molecular Biology Laboratory, Hinxton, UK.
| | - Kolawole Babalola
- European Bioinformatics Institute, European Molecular Biology Laboratory, Hinxton, UK
| | - Robert Wilson
- European Bioinformatics Institute, European Molecular Biology Laboratory, Hinxton, UK
| | - Tudor Groza
- European Bioinformatics Institute, European Molecular Biology Laboratory, Hinxton, UK
| | - Violeta Muñoz-Fuentes
- European Bioinformatics Institute, European Molecular Biology Laboratory, Hinxton, UK
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44
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Riley RD, Collins GS, Hattle M, Whittle R, Ensor J. Calculating the power of a planned individual participant data meta-analysis of randomised trials to examine a treatment-covariate interaction with a time-to-event outcome. Res Synth Methods 2023; 14:718-730. [PMID: 37386750 PMCID: PMC10947306 DOI: 10.1002/jrsm.1650] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 04/24/2023] [Accepted: 06/07/2023] [Indexed: 07/01/2023]
Abstract
Before embarking on an individual participant data meta-analysis (IPDMA) project, researchers should consider the power of their planned IPDMA conditional on the studies promising their IPD and their characteristics. Such power estimates help inform whether the IPDMA project is worth the time and funding investment, before IPD are collected. Here, we suggest how to estimate the power of a planned IPDMA of randomised trials aiming to examine treatment-covariate interactions at the participant-level (i.e., treatment effect modifiers). We focus on a time-to-event (survival) outcome with a binary or continuous covariate, and propose an approximate analytic power calculation that conditions on the actual characteristics of trials, for example, in terms of sample sizes and covariate distributions. The proposed method has five steps: (i) extracting the following aggregate data for each group in each trial-the number of participants and events, the mean and SD for each continuous covariate, and the proportion of participants in each category for each binary covariate; (ii) specifying a minimally important interaction size; (iii) deriving an approximate estimate of Fisher's information matrix for each trial and the corresponding variance of the interaction estimate per trial, based on assuming an exponential survival distribution; (iv) deriving the estimated variance of the summary interaction estimate from the planned IPDMA, under a common-effect assumption, and (v) calculating the power of the IPDMA based on a two-sided Wald test. Stata and R code are provided and a real example provided for illustration. Further evaluation in real examples and simulations is needed.
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Affiliation(s)
- Richard D. Riley
- Institute of Applied Health Research, College of Medical and Dental SciencesUniversity of BirminghamBirminghamUK
| | - Gary S. Collins
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal SciencesUniversity of OxfordOxfordUK
| | | | - Rebecca Whittle
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal SciencesUniversity of OxfordOxfordUK
| | - Joie Ensor
- Institute of Applied Health Research, College of Medical and Dental SciencesUniversity of BirminghamBirminghamUK
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Simonsson O, Carlbring P, Carhart-Harris R, Davis AK, Nutt DJ, Griffiths RR, Erritzoe D, Goldberg SB. Assessing the risk of symptom worsening in psilocybin-assisted therapy for depression: A systematic review and individual participant data meta-analysis. Psychiatry Res 2023; 327:115349. [PMID: 37523886 PMCID: PMC10528683 DOI: 10.1016/j.psychres.2023.115349] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 07/09/2023] [Accepted: 07/16/2023] [Indexed: 08/02/2023]
Abstract
We conducted a meta-analysis using individual participant data from three, two-dose psilocybin trials for depression (N = 102) with the aim of assessing the risk of symptom worsening. Clinically significant symptom worsening occurred for a minority of participants in the psilocybin and escitalopram conditions (∼10%) and for a majority of participants in the waitlist condition (63.6%). Using data from the two trials with control arms, the psilocybin arm showed a lower likelihood of symptom worsening versus waitlist, and no difference in the likelihood of symptom worsening versus escitalopram. The limitation of a relatively small sample size should be addressed in future studies.
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Affiliation(s)
- Otto Simonsson
- Department of Neurobiology, Care Sciences and Society, Karolinska Institute, Norra Stationsgatan 69, Stockholm 113 64, Sweden; Department of Sociology, University of Oxford, Oxford, United Kingdom.
| | - Per Carlbring
- Department of Psychology, Stockholm University, Stockholm, Sweden
| | - Robin Carhart-Harris
- Neuroscape Psychedelics Division, Department of Neurology, University of California San Francisco, San Francisco, CA, United States; Centre for Psychedelic Research, Imperial College London, London, United Kingdom
| | - Alan K Davis
- Center for Psychedelic Drug Research and Education, College of Social Work, The Ohio State University, Columbus, OH, United States; Department of Psychiatry, The Ohio State University, Columbus, OH, United States; Center for Psychedelic and Consciousness Research, Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, United States
| | - David J Nutt
- Centre for Psychedelic Research, Imperial College London, London, United Kingdom
| | - Roland R Griffiths
- Center for Psychedelic and Consciousness Research, Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, United States; Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD 21205, United States; Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, United States
| | - David Erritzoe
- Centre for Psychedelic Research, Imperial College London, London, United Kingdom
| | - Simon B Goldberg
- Department of Counseling Psychology, University of Wisconsin, Madison, WI, United States
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Lee SAW, Gates KM. From the Individual to the Group: Using Idiographic Analyses and Two-Stage Random Effects Meta-Analysis to Obtain Population Level Inferences for within-Person Processes. MULTIVARIATE BEHAVIORAL RESEARCH 2023:1-20. [PMID: 37611153 DOI: 10.1080/00273171.2023.2229310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/25/2023]
Abstract
In psychology, the use of portable technology and wearable devices to ease participant burden in data collection is on the rise. This creates increased interest in collecting real-time or near real-time data from individuals within their natural environments. As a result, vast amounts of observational time series data are generated. Often, motivation for collecting this data hinges on understanding within-person processes that underlie psychological phenomena. Motivated by the body of Dr. Peter Molenaar's life work calling for analytical approaches that consider potential heterogeneity and non-ergodicity, the focus of this paper is on using idiographic analyses to generate population inferences for within-person processes. Meta-analysis techniques using one-stage and two-stage random effects meta-analysis as implemented in single-case experimental designs are presented. The case for preferring a two-stage approach for meta-analysis of single-subject observational time series data is made and demonstrated using an empirical example. This provides a novel implementation of the methodology as prior implementations focus on applications to short time series with experimental designs. Inspired by Dr. Molenaar's work, we describe how an approach, two-stage random effects meta-analysis (2SRE-MA), aligns with recent calls to consider idiographic approaches when making population-level inferences regarding within-person processes.
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47
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Zhu H, Li T, Zhao B. Statistical Learning Methods for Neuroimaging Data Analysis with Applications. Annu Rev Biomed Data Sci 2023; 6:73-104. [PMID: 37127052 DOI: 10.1146/annurev-biodatasci-020722-100353] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
The aim of this review is to provide a comprehensive survey of statistical challenges in neuroimaging data analysis, from neuroimaging techniques to large-scale neuroimaging studies and statistical learning methods. We briefly review eight popular neuroimaging techniques and their potential applications in neuroscience research and clinical translation. We delineate four themes of neuroimaging data and review major image processing analysis methods for processing neuroimaging data at the individual level. We briefly review four large-scale neuroimaging-related studies and a consortium on imaging genomics and discuss four themes of neuroimaging data analysis at the population level. We review nine major population-based statistical analysis methods and their associated statistical challenges and present recent progress in statistical methodology to address these challenges.
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Affiliation(s)
- Hongtu Zhu
- Department of Biostatistics, Department of Statistics, Department of Genetics, and Department of Computer Science, University of North Carolina, Chapel Hill, North Carolina, USA;
- Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Tengfei Li
- Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, North Carolina, USA
- Department of Radiology, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Bingxin Zhao
- Department of Statistics and Data Science, University of Pennsylvania, Philadelphia, Pennsylvania, USA
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Tan Z, Tanner-Smith EE, Walters ST, Tan L, Huh D, Zhou Z, Luningham JM, Larimer ME, Mun EY. Do brief motivational interventions increase motivation for change in drinking among college students? A two-step meta-analysis of individual participant data. ALCOHOL, CLINICAL & EXPERIMENTAL RESEARCH 2023; 47:1433-1446. [PMID: 37526588 PMCID: PMC10692312 DOI: 10.1111/acer.15126] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 05/25/2023] [Accepted: 05/27/2023] [Indexed: 08/02/2023]
Abstract
BACKGROUND Brief motivational interventions (BMIs) are one of the most effective individually focused alcohol intervention strategies for college students. Despite the central theoretical role of motivation for change in BMIs, it is unclear whether BMIs increase motivation to change drinking behavior. We conducted a two-step meta-analysis of individual participant data (IPD) to examine whether BMIs increase motivation for change. N = 5903;59% women, 72% White) from Project INTEGRATE. The BMIs included individually delivered motivational interviewing with personalized feedback (MI + PF), stand-alone personalized feedback (PF), and group-based motivational interviewing (GMI). METHODS We included 15 trials of BMI (N = 5903;59% women, 72% White) from Project INTEGRATE. The BMIs included individually-delivered motivational interviewing with personalized feedback (MI + PF), stand-alone personalized feedback (PF), and group-based motivational interviewing (GMI). Different measures and responses used in the original trials were harmonized. Effect size estimates were derived from a model that adjusted for baseline motivation and demographic variables for each trial (step 1) and subsequently combined in a random-effects meta-analysis (step 2). RESULTS The overall intervention effect of BMIs on motivation for change was not statistically significant (standard mean difference [SMD]: 0.026, 95% CI: [-0.001, 0.053], p = 0.06, k = 19 comparisons). Of the three subtypes of BMIs, GMI, which tended to provide motivation-targeted content, had a statistically significant intervention effect on motivation, compared with controls (SMD: 0.055, 95% CI: [0.007, 0.103], p = 0.025, k = 5). By contrast, there was no evidence that MI + PF (SMD = 0.04, 95% CI: [-0.02, 0.10], k = 6, p = 0.20) nor PF increased motivation (SMD = 0.005, 95% CI: [-0.028, 0.039], k = 8, p = 0.75), compared with controls. Post hoc meta-regression analysis suggested that motivation sharply decreased each month within the first 3 months postintervention (b = -0.050, z = -2.80, p = 0.005 for k = 14). CONCLUSIONS Although BMIs provide motivational content and normative feedback and are assumed to motivate behavior change, the results do not wholly support the hypothesis that BMIs improve motivation for change. Changing motivation is difficult to assess during and following interventions, but it is still a theoretically important clinical endpoint. Further, the evidence cautiously suggests that changing motivation may be achievable, especially if motivation-targeted content components are provided.
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Affiliation(s)
- Zhengqi Tan
- School of Public Health, University of North Texas Health Science Center at Fort Worth, Fort Worth, TX, USA
| | - Emily E. Tanner-Smith
- Department of Counseling Psychology and Human Services, University of Oregon, Eugene, OR, USA
| | - Scott T. Walters
- School of Public Health, University of North Texas Health Science Center at Fort Worth, Fort Worth, TX, USA
| | - Lin Tan
- School of Public Health, University of North Texas Health Science Center at Fort Worth, Fort Worth, TX, USA
| | - David Huh
- School of Social Work, University of Washington, Seattle, WA, USA
| | - Zhengyang Zhou
- School of Public Health, University of North Texas Health Science Center at Fort Worth, Fort Worth, TX, USA
| | - Justin M. Luningham
- School of Public Health, University of North Texas Health Science Center at Fort Worth, Fort Worth, TX, USA
| | - Mary E. Larimer
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, USA
| | - Eun-Young Mun
- School of Public Health, University of North Texas Health Science Center at Fort Worth, Fort Worth, TX, USA
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Mente A, Dehghan M, Rangarajan S, O'Donnell M, Hu W, Dagenais G, Wielgosz A, Lear SA, Wei L, Diaz R, Avezum A, Lopez-Jaramillo P, Lanas F, Swaminathan S, Kaur M, Vijayakumar K, Mohan V, Gupta R, Szuba A, Iqbal R, Yusuf R, Mohammadifard N, Khatib R, Nasir NM, Karsidag K, Rosengren A, Yusufali A, Wentzel-Viljoen E, Chifamba J, Dans A, Alhabib KF, Yeates K, Teo K, Gerstein HC, Yusuf S. Diet, cardiovascular disease, and mortality in 80 countries. Eur Heart J 2023:ehad269. [PMID: 37414411 PMCID: PMC10361015 DOI: 10.1093/eurheartj/ehad269] [Citation(s) in RCA: 28] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/05/2022] [Revised: 03/31/2023] [Accepted: 04/25/2023] [Indexed: 07/08/2023] Open
Abstract
AIMS To develop a healthy diet score that is associated with health outcomes and is globally applicable using data from the Prospective Urban Rural Epidemiology (PURE) study and replicate it in five independent studies on a total of 245 000 people from 80 countries. METHODS AND RESULTS A healthy diet score was developed in 147 642 people from the general population, from 21 countries in the PURE study, and the consistency of the associations of the score with events was examined in five large independent studies from 70 countries. The healthy diet score was developed based on six foods each of which has been associated with a significantly lower risk of mortality [i.e. fruit, vegetables, nuts, legumes, fish, and dairy (mainly whole-fat); range of scores, 0-6]. The main outcome measures were all-cause mortality and major cardiovascular events [cardiovascular disease (CVD)]. During a median follow-up of 9.3 years in PURE, compared with a diet score of ≤1 points, a diet score of ≥5 points was associated with a lower risk of mortality [hazard ratio (HR) 0.70; 95% confidence interval (CI) 0.63-0.77)], CVD (HR 0.82; 0.75-0.91), myocardial infarction (HR 0.86; 0.75-0.99), and stroke (HR 0.81; 0.71-0.93). In three independent studies in vascular patients, similar results were found, with a higher diet score being associated with lower mortality (HR 0.73; 0.66-0.81), CVD (HR 0.79; 0.72-0.87), myocardial infarction (HR 0.85; 0.71-0.99), and a non-statistically significant lower risk of stroke (HR 0.87; 0.73-1.03). Additionally, in two case-control studies, a higher diet score was associated with lower first myocardial infarction [odds ratio (OR) 0.72; 0.65-0.80] and stroke (OR 0.57; 0.50-0.65). A higher diet score was associated with a significantly lower risk of death or CVD in regions with lower than with higher gross national incomes (P for heterogeneity <0.0001). The PURE score showed slightly stronger associations with death or CVD than several other common diet scores (P < 0.001 for each comparison). CONCLUSION A diet comprised of higher amounts of fruit, vegetables, nuts, legumes, fish, and whole-fat dairy is associated with lower CVD and mortality in all world regions, especially in countries with lower income where consumption of these foods is low.
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Affiliation(s)
- Andrew Mente
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, 2nd Floor, Room C2-105, 237 Barton St East, Hamilton, Ontario L8L 2X2, Canada
- Department of Health Research Methods, Evidence, and Impact, McMaster University, 1280 Main St W, Hamilton, Ontario L8S 4L8, Canada
| | - Mahshid Dehghan
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, 2nd Floor, Room C2-105, 237 Barton St East, Hamilton, Ontario L8L 2X2, Canada
| | - Sumathy Rangarajan
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, 2nd Floor, Room C2-105, 237 Barton St East, Hamilton, Ontario L8L 2X2, Canada
| | - Martin O'Donnell
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada
- HRB-Clinical Research Facility, University of Galway, Galway, Connacht, Ireland
| | - Weihong Hu
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, 2nd Floor, Room C2-105, 237 Barton St East, Hamilton, Ontario L8L 2X2, Canada
| | - Gilles Dagenais
- Department of Medicine, Université Laval Institut universitaire de cardiologie et de pneumologie de Québec, Quebec City G1V 4G5, Canada
| | - Andreas Wielgosz
- Department of Medicine, University of Ottawa, Ottawa, Ontario, Canada
| | - Scott A Lear
- Faculty of Health Sciences, and Department of Biomedical Physiology & Kinesiology, Simon Fraser University Vancouver, Burnaby, British Columbia, Canada
| | - Li Wei
- State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Disease, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, Xicheng District, China
| | - Rafael Diaz
- Estudios Clinicos Latinoamerica ECLA, Universidad Nacional de Rosario, Rosario, Santa Fe, Argentina
| | - Alvaro Avezum
- International Research Center, Hospital Alemão Oswaldo Cruz & UNISA, Sao Paulo, São Paulo estado, SP Brazil
| | - Patricio Lopez-Jaramillo
- Masira Research Institute, Medical School, Universidad de Santander (UDES), Bucaramanga, Santander, Colombia
| | - Fernando Lanas
- Francisco Salazar, Universidad de La Frontera, Temuco, Araucanía, Chile
| | - Sumathi Swaminathan
- Division of Nutrition, St John's Research Institute, Koramangala, Bangalore, Karnataka, India
| | - Manmeet Kaur
- Postgraduate Institute of Medical Education and Research, School of Public Health, Chandigarh, Punjab and Haryana, India
| | - K Vijayakumar
- Health Action by People, Amrita Institute of Medical Sciences, Trivandrum, Kerala, India
| | - Viswanathan Mohan
- Director and Chief of Diabetes Research, Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, Chennai, Tamil Nadu, India
| | - Rajeev Gupta
- Eternal Heart Care Centre and Research Institute, Rajasthan University of Health Sciences, Jaipur, Rajasthan, India
| | - Andrzej Szuba
- Department of Internal Medicine, Wroclaw Medical University, 4th Military Hospital, Wroclaw, Lower Silesian Voivodeship, Poland
| | - Romaina Iqbal
- Department of Community Health Sciences and Medicine, Aga Khan University, Karachi, Sindh, Pakistan
| | - Rita Yusuf
- Department of Life Sciences, Independent University, Bangladesh, Bashundhara, Dhaka, Dhaka District, Bangladesh
| | - Noushin Mohammadifard
- Isfahan Cardiovascular Research Center, Cardiovascular Research Institute, Isfahan University of Medical Sciences, Isfahan, Isfahan Province, Iran
| | - Rasha Khatib
- Departments of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Nafiza Mat Nasir
- Department of Primary Care Medicine, Faculty of Medicine, Universiti Teknologi MARA (UiTM), Shah Alam, Selangor, Malaysia
| | - Kubilay Karsidag
- Department of Internal Medicine, Division of Endocrinology, Medical Faculty of Istanbul University, Istanbul, Istanbul Province, Turkey
| | - Annika Rosengren
- Department of Molecular and Clinical Medicine, Sahlgrenska Academy, University of Gothenburg and Sahlgrenska University Hospital/Östra Hospital, Gothenburg, Västergötland, Sweden
| | - Afzalhussein Yusufali
- Hatta Hospital, Dubai Health Authority, Dubai Medical University, Dubai, United Arab Emirates
| | - Edelweiss Wentzel-Viljoen
- Faculty of Health Sciences, Centre of Excellence for Nutrition, Potchefstroom, North West Province, South Africa
| | - Jephat Chifamba
- College of Health Sciences, Physiology Department, University of Zimbabwe, Harare, Harare Metropolitan Province, Zimbabwe
| | - Antonio Dans
- Department of Medicine, University of the Philippines, Ermita, Manila, Metro Manila, Philippines
| | - Khalid F Alhabib
- Department of Cardiac Sciences, King Fahad Cardiac Center, College of Medicine, King Saud University, Riyadh, Riyadh Province, Saudi Arabia
| | - Karen Yeates
- Department of Medicine, Queen's University, 94 Stuart Street, Etherington Hall, Kingston, Ontario, Canada
| | - Koon Teo
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, 2nd Floor, Room C2-105, 237 Barton St East, Hamilton, Ontario L8L 2X2, Canada
- Department of Health Research Methods, Evidence, and Impact, McMaster University, 1280 Main St W, Hamilton, Ontario L8S 4L8, Canada
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Hertzel C Gerstein
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, 2nd Floor, Room C2-105, 237 Barton St East, Hamilton, Ontario L8L 2X2, Canada
- Department of Health Research Methods, Evidence, and Impact, McMaster University, 1280 Main St W, Hamilton, Ontario L8S 4L8, Canada
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Salim Yusuf
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, 2nd Floor, Room C2-105, 237 Barton St East, Hamilton, Ontario L8L 2X2, Canada
- Department of Health Research Methods, Evidence, and Impact, McMaster University, 1280 Main St W, Hamilton, Ontario L8S 4L8, Canada
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada
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Marlin N, Godolphin PJ, Hooper RL, Riley RD, Rogozińska E. Nonlinear effects and effect modification at the participant-level in IPD meta-analysis part 2: methodological guidance is available. J Clin Epidemiol 2023; 159:319-329. [PMID: 37146657 DOI: 10.1016/j.jclinepi.2023.04.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Revised: 03/20/2023] [Accepted: 04/26/2023] [Indexed: 05/07/2023]
Abstract
OBJECTIVES To review methodological guidance for nonlinear covariate-outcome associations (NL), and linear effect modification and nonlinear effect modification (LEM and NLEM) at the participant level in individual participant data meta-analyses (IPDMAs) and their power requirements. STUDY DESIGN AND SETTING We searched Medline, Embase, Web of Science, Scopus, PsycINFO and the Cochrane Library to identify methodology publications on IPDMA of LEM, NL or NLEM (PROSPERO CRD42019126768). RESULTS Through screening 6,466 records we identified 54 potential articles of which 23 full texts were relevant. Nine further relevant publications were published before or after the literature search and were added. Of these 32 references, 21 articles considered LEM, 6 articles NL or NLEM and 6 articles described sample size calculations. A book described all four. Sample size may be calculated through simulation or closed form. Assessments of LEM or NLEM at the participant level need to be based on within-trial information alone. Nonlinearity (NL or NLEM) can be modeled using polynomials or splines to avoid categorization. CONCLUSION Detailed methodological guidance on IPDMA of effect modification at participant-level is available. However, methodology papers for sample size and nonlinearity are rarer and may not cover all scenarios. On these aspects, further guidance is needed.
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Affiliation(s)
- Nadine Marlin
- Methodology Research Unit, Centre for Evaluation and Methods, Wolfson Institute of Population Health, Queen Mary University of London, 58 Turner Street, London E1 2AB, UK.
| | - Peter J Godolphin
- MRC Clinical Trials Unit at University College London, Institute of Clinical Trials and Methodology, 90 High Holborn, London WC1V 6LJ, UK
| | - Richard L Hooper
- Methodology Research Unit, Centre for Evaluation and Methods, Wolfson Institute of Population Health, Queen Mary University of London, 58 Turner Street, London E1 2AB, UK
| | - Richard D Riley
- Institute of Applied Health Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham B15 2TT, UK
| | - Ewelina Rogozińska
- MRC Clinical Trials Unit at University College London, Institute of Clinical Trials and Methodology, 90 High Holborn, London WC1V 6LJ, UK
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