1
|
Lu J, He R, Liu J, Chen H, Chi H, Yang G. Letter to the editor for the article "The impact of health care on outcomes of suspected testicular torsion: results from the GRAND study". World J Urol 2024; 42:390. [PMID: 38985192 DOI: 10.1007/s00345-024-05069-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2024] [Accepted: 05/14/2024] [Indexed: 07/11/2024] Open
Affiliation(s)
- Jiaan Lu
- Clinical Medical College, Southwest Medical University, Luzhou, 646000, China
| | - Ru He
- Clinical Medical College, Southwest Medical University, Luzhou, 646000, China
| | - Jie Liu
- Department of General Surgery, Dazhou Central Hospital, Dazhou, 635000, China
| | - Haiqing Chen
- Clinical Medical College, Southwest Medical University, Luzhou, 646000, China
| | - Hao Chi
- Clinical Medical College, Southwest Medical University, Luzhou, 646000, China.
| | - Guanhu Yang
- Department of Specialty Medicine, Ohio University, Athens, OH, 45701, USA.
| |
Collapse
|
2
|
Liu X, Nianogo RA, Janzen C, Fei Z, Seamans MJ, Wen R, Li X, Chen L. Association Between Gestational Diabetes Mellitus and Hypertension: A Systematic Review and Meta-Analysis of Cohort Studies With a Quantitative Bias Analysis of Uncontrolled Confounding. Hypertension 2024; 81:1257-1268. [PMID: 38501243 DOI: 10.1161/hypertensionaha.123.22418] [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: 11/15/2023] [Accepted: 02/19/2024] [Indexed: 03/20/2024]
Abstract
BACKGROUND Whether individuals with gestational diabetes mellitus (GDM) had an increased risk of hypertension remains unclear. We conducted a systematic literature review and meta-analysis to examine the association between GDM and hypertension and performed a quantitative bias analysis to quantify the impact of uncontrolled confounding due to antenatal psychological stress. METHODS We searched databases (PUBMED, EMBASE, and Web of Science) through 2022/11. Eligible studies were cohort studies that reported the association of GDM with hypertension. We assessed the risk of bias using the Newcastle-Ottawa Scale for cohort studies. We pooled adjusted risk ratios with 95% CIs using a random effects model. We performed the quantitative bias analysis using the bias formula. RESULTS We included 15 cohort studies, with a total of 3 959 520 (GDM, 175 378; non-GDM, 3 784 142) individuals. During the follow-up of 2 to 20 years, 106 560 cases of hypertension were reported. We found that GDM was associated with a higher risk of hypertension (pooled risk ratio, 1.78 [95% CI, 1.47, 2.17]). The risk ratio was lower among cohorts assessing incident (1.58 [95% CI, 1.29, 1.95]) than prevalent hypertension (2.60 [95% CI, 2.40, 2.83]). However, other subgroup analyses showed no differences. The quantitative bias analysis revealed that if the uncontrolled confounder of antenatal psychological stress was additionally adjusted, the positive association between GDM and hypertension would attenuate slightly (≤18%) but remains positive. CONCLUSIONS Limitations of this study included residual confounding and discrepancies in GDM and hypertension ascertainments. Our findings indicate that GDM is positively associated with hypertension after the index pregnancy.
Collapse
Affiliation(s)
- Xinyue Liu
- Department of Epidemiology, Fielding School of Public Health (X. Liu, R.A.N., M.J.S., X. Li, L.C.), University of California, Los Angeles
| | - Roch A Nianogo
- Department of Epidemiology, Fielding School of Public Health (X. Liu, R.A.N., M.J.S., X. Li, L.C.), University of California, Los Angeles
- California Center for Population Research (R.N.), University of California, Los Angeles
| | - Carla Janzen
- Department Obstetrics and Gynecology, David Geffen School of Medicine (C.J.), University of California, Los Angeles
| | - Zhe Fei
- Department of Statistics, University of California, Riverside (Z.F.)
| | - Marissa J Seamans
- Department of Epidemiology, Fielding School of Public Health (X. Liu, R.A.N., M.J.S., X. Li, L.C.), University of California, Los Angeles
| | - Renee Wen
- Department of Biology (R.W.), University of California, Los Angeles
| | - Xiang Li
- Department of Epidemiology, Fielding School of Public Health (X. Liu, R.A.N., M.J.S., X. Li, L.C.), University of California, Los Angeles
| | - Liwei Chen
- Department of Epidemiology, Fielding School of Public Health (X. Liu, R.A.N., M.J.S., X. Li, L.C.), University of California, Los Angeles
| |
Collapse
|
3
|
Szinger D, Berki T, Drenjančević I, Samardzic S, Zelić M, Sikora M, Požgain A, Markovics Á, Farkas N, Németh P, Böröcz K. Raising Epidemiological Awareness: Assessment of Measles/MMR Susceptibility in Highly Vaccinated Clusters within the Hungarian and Croatian Population-A Sero-Surveillance Analysis. Vaccines (Basel) 2024; 12:486. [PMID: 38793737 PMCID: PMC11125914 DOI: 10.3390/vaccines12050486] [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: 04/09/2024] [Revised: 04/26/2024] [Accepted: 04/29/2024] [Indexed: 05/26/2024] Open
Abstract
Perceptions of the complete eradication of vaccine-preventable diseases such as measles, mumps, and rubella (MMR) may foster complacency and compromise vaccination efforts. Decreased measles vaccination rates during the COVID-19 pandemic have heightened the risk of outbreaks, even in adequately vaccinated populations. To address this, we have aligned with ECDC recommendations, leveraging previous cross-border sero-epidemiological assessments between Pécs, Hungary, and Osijek, Croatia, to identify latent risk groups and uncover potential parallels between our nations. Testing 2680 Hungarian and 1764 Croatian serum samples for anti-MMR IgG via ELISAs revealed anti-measles seropositivity ratios below expectations in Croatian cohorts aged ~20-30 (75.7%), ~30-40 (77.5%) and ~40-50 years (73.3%). Similarly, Hungarian samples also showed suboptimal seropositivity ratios in the ~30-40 (80.9%) and ~40-50 (87.3%) age groups. Considering mumps- and rubella-associated seropositivity trends, in both examined populations, individuals aged ~30-50 years exhibited the highest vulnerability. Additionally, we noted congruent seropositivity trends across both countries, despite distinct immunization and epidemiological contexts. Therefore, we propose expanding research to encompass the intricate dynamics of vaccination, including waning long-term immunity. This understanding could facilitate targeted interventions and bolster public awareness. Our findings underscore persistent challenges in attaining robust immunity against measles despite vaccination endeavors.
Collapse
Affiliation(s)
- Dávid Szinger
- Department of Immunology and Biotechnology, Clinical Center, Medical School, University of Pécs, 7624 Pécs, Hungary; (D.S.); (T.B.); (P.N.)
| | - Timea Berki
- Department of Immunology and Biotechnology, Clinical Center, Medical School, University of Pécs, 7624 Pécs, Hungary; (D.S.); (T.B.); (P.N.)
| | - Ines Drenjančević
- Department of Physiology and Immunology, Faculty of Medicine Osijek, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia;
- Scientific Centre for Excellence for Personalized Health Care, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia
| | - Senka Samardzic
- Department of Public Health, Teaching Institute of Public Health for The Osijek-Baranja County, 31000 Osijek, Croatia; (S.S.); (M.Z.); (M.S.); (A.P.)
| | - Marija Zelić
- Department of Public Health, Teaching Institute of Public Health for The Osijek-Baranja County, 31000 Osijek, Croatia; (S.S.); (M.Z.); (M.S.); (A.P.)
| | - Magdalena Sikora
- Department of Public Health, Teaching Institute of Public Health for The Osijek-Baranja County, 31000 Osijek, Croatia; (S.S.); (M.Z.); (M.S.); (A.P.)
| | - Arlen Požgain
- Department of Public Health, Teaching Institute of Public Health for The Osijek-Baranja County, 31000 Osijek, Croatia; (S.S.); (M.Z.); (M.S.); (A.P.)
- Department of Microbiology, Parasitology and Clinical Laboratory Diagnostics, Medical Faculty of Osijek, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia
| | - Ákos Markovics
- Department of General and Physical Chemistry, Faculty of Natural Sciences, University of Pécs, 7622 Pécs, Hungary;
| | - Nelli Farkas
- Department of Bioanalysis, Medical School, University of Pécs, Szigeti u. 12, 7643 Pécs, Hungary;
| | - Péter Németh
- Department of Immunology and Biotechnology, Clinical Center, Medical School, University of Pécs, 7624 Pécs, Hungary; (D.S.); (T.B.); (P.N.)
| | - Katalin Böröcz
- Department of Immunology and Biotechnology, Clinical Center, Medical School, University of Pécs, 7624 Pécs, Hungary; (D.S.); (T.B.); (P.N.)
| |
Collapse
|
4
|
Guo P, Jin Z, Bellia G, Luo J, Inoue K, Pollitt KJG, Deziel NC, Liew Z. Per- and polyfluoroalkyl substances and sleep health in U.S. adults, NHANES 2005-2014. ENVIRONMENTAL RESEARCH 2023; 237:117092. [PMID: 37683785 DOI: 10.1016/j.envres.2023.117092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Revised: 09/03/2023] [Accepted: 09/05/2023] [Indexed: 09/10/2023]
Abstract
BACKGROUND Per- and polyfluoroalkyl substances (PFAS) are synthetic chemicals that induce oxidative inflammatory responses and disrupt the endocrine and central nervous systems, all of which can influence sleep. OBJECTIVE To investigate the association between PFAS exposure and sleep health measures in U.S. adults. METHODS We analyzed serum concentration data of four PFAS [perfluorooctane sulfonic acid (PFOS), perfluorooctanoic acid (PFOA), perfluorohexane sulfonic acid (PFHxS), and perfluorononanoic acid (PFNA)] reported for 8913 adults in NHANES 2005-2014. Sleep outcomes, including trouble sleeping, having a diagnosis of sleep disorder, and recent daily sleep duration classified as insufficient or excessive sleep (<6 or >9 h/day) were examined. Weighted logistic regression was used to estimate the association between the sleep outcomes and each PFAS modeled continuously (log2) or in exposure tertiles. We applied quantile g-computation to estimate the effect of the four PFAS as a mixture on the sleep outcomes. We conducted a quantitative bias analysis to assess the potential influence of self-selection and uncontrolled confounding. RESULTS We observed some inverse associations between serum PFAS and trouble sleeping or sleep disorder, which were more consistent for PFOS (e.g., per log2-PFOS (ng/ml) and trouble sleeping OR = 0.93, 95%CI: 0.89, 0.98; sleep disorder OR = 0.89, 95%CI: 0.83, 0.95). Per quartile increase of the PFAS mixture was inversely associated with trouble sleeping and sleep disorder. No consistent associations were found for sleep duration across analyses. Our bias analysis suggests that the finding on sleep disorder could be explained by a moderate level of self-selection and negative confounding effects. CONCLUSIONS We found no evidence to suggest exposure to four legacy PFAS worsened self-reported sleep health among U.S. adults. While some inverse associations between specific PFAS and sleep disorder were observed, self-selection and uncontrolled confounding biases may play a role in these findings.
Collapse
Affiliation(s)
- Pengfei Guo
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, USA; Yale Center for Perinatal, Pediatric and Environmental Epidemiology, Yale School of Public Health, New Haven, USA.
| | - Zhihao Jin
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, USA.
| | - Giselle Bellia
- Yale Center for Perinatal, Pediatric and Environmental Epidemiology, Yale School of Public Health, New Haven, USA.
| | - Jiajun Luo
- Institute for Population and Precision Health, University of Chicago, USA.
| | - Kosuke Inoue
- Department of Social Epidemiology, Graduate School of Medicine, Kyoto University, Japan.
| | - Krystal J Godri Pollitt
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, USA; Yale Center for Perinatal, Pediatric and Environmental Epidemiology, Yale School of Public Health, New Haven, USA.
| | - Nicole C Deziel
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, USA; Yale Center for Perinatal, Pediatric and Environmental Epidemiology, Yale School of Public Health, New Haven, USA.
| | - Zeyan Liew
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, USA; Yale Center for Perinatal, Pediatric and Environmental Epidemiology, Yale School of Public Health, New Haven, USA.
| |
Collapse
|
5
|
Ren S, Xue C, Xu M, Li X. Mendelian Randomization Analysis Reveals Causal Effects of Polyunsaturated Fatty Acids on Subtypes of Diabetic Retinopathy Risk. Nutrients 2023; 15:4208. [PMID: 37836492 PMCID: PMC10574403 DOI: 10.3390/nu15194208] [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: 08/27/2023] [Revised: 09/18/2023] [Accepted: 09/27/2023] [Indexed: 10/15/2023] Open
Abstract
Polyunsaturated fatty acids (PUFAs) affect several physiological processes, including visual acuity, but their relationship with diabetic retinopathy (DR) remains elusive. The aim of this study was to determine whether PUFAs have a causal effect on DR. PUFAs- (total and omega-3 [FAw3] and omega-6 [FAw6] fatty acids and their ratio) and DR-associated single nucleotide polymorphisms derived from genome-wide association studies; sample sizes were 114,999 for fatty acids and 216,666 for any DR (ADR), background DR (BDR), severe non-proliferative DR (SNPDR), and proliferative DR (PDR). We hypothesized that the intra-body levels of PUFAs have an impact on DR and conducted a two-sample Mendelian randomization (MR) study to assess the causality. Pleiotropy, heterogeneity, and sensitivity analyses were performed to verify result reliability. High levels of PUFAs were found to be associated with reduced risk of both ADR and PDR. Moreover, FAw3 was associated with a decreased risk of PDR, whereas FAw6 demonstrated an association with lowered risks of both BDR and PDR. Our findings provide genetic evidence, for the first time, for a causal relationship between PUFAs and reduced DR risk. Consequently, our comprehensive MR analysis strongly urges further investigation into the precise functions and long-term effects of PUFAs, FAw3, and FAw6 on DR.
Collapse
Affiliation(s)
| | | | | | - Xiaorong Li
- Tianjin Key Laboratory of Retinal Functions and Diseases, Tianjin Branch of National Clinical Research Center for Ocular Disease, Eye Institute and School of Optometry, Tianjin Medical University Eye Hospital, Tianjin 300384, China; (S.R.); (C.X.); (M.X.)
| |
Collapse
|
6
|
Chaguendo-Quintero MA, Quintero-Monjes D, Cuervo MT, Sanabria-Mazo JP. Alterations in executive functions in inmates convicted for violent behavior: a systematic review. Front Psychol 2023; 14:1066474. [PMID: 37663323 PMCID: PMC10468974 DOI: 10.3389/fpsyg.2023.1066474] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Accepted: 03/31/2023] [Indexed: 09/05/2023] Open
Abstract
Background The growth of the prison population and the high recidivism rates of inmates represent a major public safety problem. Objective This systematic review explored executive functions in inmates convicted of violent behavior compared with inmates convicted of non-violent behavior and healthy controls (HCs). Methods Systematic searches were carried out using five databases (PubMed, Scopus, Web of Science, EBSCO, and Embase) until March 6th, 2023. Following Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines, two reviewers independently performed the screening, data extraction, and risk of bias assessment of the 8 studies included. The protocol of this study was registered in Prospective Register of Systematic Reviews (PROSPERO), under registration number CRD42021252043. Results Consistently, inmates convicted of violent behavior exhibited a greater alteration in inhibition than inmates convicted of non-violent behavior (four out of four studies) and HCs (two out of two studies). In addition, inmates convicted of violent behavior showed greater impairments in cognitive flexibility (two out of three studies) and working memory (two out of three studies) than HCs. Although with limited evidence (only one study), they also showed worse performance in set shifting and planning than HCs. Conclusion This study provides evidence of alterations in inhibition in inmates convicted of violent behavior compared to inmates convicted of non-violent behavior and HCs. Even though inmates convicted of violent behavior showed greater impairments in planning and set shifting than HCs, these findings were supported in only one study. In general, more robust evidence is needed to confirm alterations in inmates convicted due to violent behavior. These findings highlight the importance of designing and promoting specific cognitive interventions that contribute to the reintegration of inmates into society. Systematic review registration https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021252043, identifier CRD42021252043.
Collapse
Affiliation(s)
| | | | - Maria Teresa Cuervo
- Department of Social Sciences, Pontificia Universidad Javeriana, Cali, Colombia
| | - Juan P. Sanabria-Mazo
- Teaching, Research, and Innovation Unit, Parc Sanitari Sant Joan de Dèu, Barcelona, Spain
- Centre for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
- Department of Basic, Developmental, and Educational Psychology, Universidad Autónoma de Barcelona, Barcelona, Spain
| |
Collapse
|
7
|
Brendel P, Torres A, Arah OA. Simultaneous adjustment of uncontrolled confounding, selection bias and misclassification in multiple-bias modelling. Int J Epidemiol 2023; 52:1220-1230. [PMID: 36718093 PMCID: PMC10893963 DOI: 10.1093/ije/dyad001] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Accepted: 01/23/2023] [Indexed: 02/01/2023] Open
Abstract
BACKGROUND Adjusting for multiple biases usually involves adjusting for one bias at a time, with careful attention to the order in which these biases are adjusted. A novel, alternative approach to multiple-bias adjustment involves the simultaneous adjustment of all biases via imputation and/or regression weighting. The imputed value or weight corresponds to the probability of the missing data and serves to 'reconstruct' the unbiased data that would be observed based on the provided assumptions of the degree of bias. METHODS We motivate and describe the steps necessary to implement this method. We also demonstrate the validity of this method through a simulation study with an exposure-outcome relationship that is biased by uncontrolled confounding, exposure misclassification, and selection bias. RESULTS The study revealed that a non-biased effect estimate can be obtained when correct bias parameters are applied. It also found that incorrect specification of every bias parameter by +/-25% still produced an effect estimate with less bias than the observed, biased effect. CONCLUSIONS Simultaneous multi-bias analysis is a useful way of investigating and understanding how multiple sources of bias may affect naive effect estimates. This new method can be used to enhance the validity and transparency of real-world evidence obtained from observational, longitudinal studies.
Collapse
Affiliation(s)
- Paul Brendel
- Department of Epidemiology, Fielding School of Public Health, UCLA, Los Angeles, CA, USA
- Valo Health, Boston, MA, USA
| | | | - Onyebuchi A Arah
- Department of Epidemiology, Fielding School of Public Health, UCLA, Los Angeles, CA, USA
- Department of Statistics, College of Letters and Science, UCLA, Los Angeles, CA, USA
- Department of Public Health, Section for Epidemiology, Aarhus University, Aarhus, Denmark
| |
Collapse
|
8
|
Thiesmeier R, Skyving M, Möller J, Orsini N. A probabilistic bias analysis on the magnitude of unmeasured confounding: The impact of driving mileage on road traffic crashes. ACCIDENT; ANALYSIS AND PREVENTION 2023; 191:107144. [PMID: 37473524 DOI: 10.1016/j.aap.2023.107144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 05/15/2023] [Accepted: 05/26/2023] [Indexed: 07/22/2023]
Abstract
INTRODUCTION Unmeasured confounding can lead to biased interpretations of empirical findings. This paper aimed to assess the magnitude of suspected unmeasured confounding due to driving mileage and simulate the statistical power required to detect a discrepancy in the effect of polypharmacy on road traffic crashes (RTCs) among older adults. METHODS Based on Monte Carlo Simulation (MCS) approach, we estimated 1) the magnitude of confounding of driving mileage on the association of polypharmacy and RTCs and 2) the statistical power of to detect a discrepancy from no adjusted effect. A total of 1000 studies, each of 500000 observations, were simulated. RESULTS Under the assumption of a modest adjusted exposure-outcome odds ratio of 1.35, the magnitude of confounding bias by driving mileage was estimated to be 16% higher with a statistical power of 50%. Only an adjusted odds ratio of at least 1.60 would be associated with a statistical power of about 80% CONCLUSION: This applied probabilistic bias analysis showed that not adjusting for driving mileage as a confounder can lead to an overestimation of the effect of polypharmacy on RTCs in older adults. Even considering a large sample, small to moderate adjusted exposure effects were difficult to be detected.
Collapse
Affiliation(s)
- Robert Thiesmeier
- Karolinska Institutet, Department of Global Public Health, Solnavägen 1E, SE-11365 Stockholm, Sweden.
| | - Marie Skyving
- Karolinska Institutet, Department of Global Public Health, Solnavägen 1E, SE-11365 Stockholm, Sweden; Swedish Transport Agency, Department of Road and Rail, Isafjordsgatan 1, SE-16440 Kista, Sweden
| | - Jette Möller
- Karolinska Institutet, Department of Global Public Health, Solnavägen 1E, SE-11365 Stockholm, Sweden
| | - Nicola Orsini
- Karolinska Institutet, Department of Global Public Health, Solnavägen 1E, SE-11365 Stockholm, Sweden
| |
Collapse
|
9
|
Kawabata E, Tilling K, Groenwold RHH, Hughes RA. Quantitative bias analysis in practice: review of software for regression with unmeasured confounding. BMC Med Res Methodol 2023; 23:111. [PMID: 37142961 PMCID: PMC10158211 DOI: 10.1186/s12874-023-01906-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Accepted: 03/30/2023] [Indexed: 05/06/2023] Open
Abstract
BACKGROUND Failure to appropriately account for unmeasured confounding may lead to erroneous conclusions. Quantitative bias analysis (QBA) can be used to quantify the potential impact of unmeasured confounding or how much unmeasured confounding would be needed to change a study's conclusions. Currently, QBA methods are not routinely implemented, partly due to a lack of knowledge about accessible software. Also, comparisons of QBA methods have focused on analyses with a binary outcome. METHODS We conducted a systematic review of the latest developments in QBA software published between 2011 and 2021. Our inclusion criteria were software that did not require adaption (i.e., code changes) before application, was still available in 2022, and accompanied by documentation. Key properties of each software tool were identified. We provide a detailed description of programs applicable for a linear regression analysis, illustrate their application using two data examples and provide code to assist researchers in future use of these programs. RESULTS Our review identified 21 programs with [Formula: see text] created post 2016. All are implementations of a deterministic QBA with [Formula: see text] available in the free software R. There are programs applicable when the analysis of interest is a regression of binary, continuous or survival outcomes, and for matched and mediation analyses. We identified five programs implementing differing QBAs for a continuous outcome: treatSens, causalsens, sensemakr, EValue, and konfound. When applied to one of our illustrative examples, causalsens incorrectly indicated sensitivity to unmeasured confounding whereas the other four programs indicated robustness. sensemakr performs the most detailed QBA and includes a benchmarking feature for multiple unmeasured confounders. CONCLUSIONS Software is now available to implement a QBA for a range of different analyses. However, the diversity of methods, even for the same analysis of interest, presents challenges to their widespread uptake. Provision of detailed QBA guidelines would be highly beneficial.
Collapse
Affiliation(s)
- Emily Kawabata
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
| | - Kate Tilling
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Rolf H H Groenwold
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - Rachael A Hughes
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| |
Collapse
|
10
|
Lippi G, Mattiuzzi C, Henry BM. Uncontrolled confounding in COVID-19 epidemiology. Diagnosis (Berl) 2023; 10:200-202. [PMID: 36474317 DOI: 10.1515/dx-2022-0128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 11/25/2022] [Indexed: 12/12/2022]
Affiliation(s)
- Giuseppe Lippi
- Section of Clinical Biochemistry and School of Medicine, University of Verona, Verona, Italy
| | - Camilla Mattiuzzi
- Service of Clinical Governance, Provincial Agency for Social and Sanitary Services (APSS), Trento, Italy
| | - Brandon M Henry
- Clinical Laboratory, Division of Nephrology and Hypertension, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| |
Collapse
|
11
|
Lin TT, Park C, Kapella MC, Martyn-Nemeth P, Tussing-Humphreys L, Rospenda KM, Zenk SN. Shift Work Domains and their Interactions with Empty Calorie Food/Beverage Consumption: A 14-day Intensive Longitudinal Study. Int J Nurs Stud 2023; 141:104490. [PMID: 37004340 DOI: 10.1016/j.ijnurstu.2023.104490] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2022] [Revised: 03/05/2023] [Accepted: 03/08/2023] [Indexed: 03/17/2023]
Abstract
BACKGROUND/OBJECTIVES Shift work has been linked to unhealthy eating behaviors such as imbalanced diet, or increased empty calorie food/beverage consumption. However, most research has focused on the impact of shift timing. The concept of shift work is complex, and it contains several domains such as shift timing, intensity, and speed. Previous studies have suggested that greater shift intensity and quicker shift speed may contribute to adverse health effects. However, evidence regarding associations between other domains of shift work and empty calorie food/beverage consumption has been relatively lacking. Therefore, the purpose of this study was to evaluate how other shift work domains related to empty calorie food/beverage consumption and whether different shift work domains interacted to influence the intake of foods or beverages. DESIGN A 14-day intensive longitudinal study employing ecological momentary assessment. SETTINGS AND PARTICIPANTS Eighty registered nurses working in 24 accredited Taiwanese hospitals (i.e., 9 medical centers, 12 regional hospitals, and 3 district hospitals) were recruited. METHODS During the study period, a convenience sample of 77 participants completed 2444 momentary surveys about empty calorie food/beverage consumption on a smartphone. Three shift work domains (shift timing, intensity, and speed) were evaluated based on registry-based work schedules. To study how these shift work domains influenced empty calorie food/beverage consumption, we employed three-level mixed-effects regression models for data analyses. RESULTS Findings suggested that greater night shift intensity increased the likelihood of sugar-sweetened beverage intake (odds ratio = 1.64, 95% confidence interval [1.01, 2.68]). The impacts of work shift intensity and shift timing on sugar-sweetened beverage consumption varied by shift speed. Among participants assigned a schedule with either medium or rapid shift speed, higher work shift intensity was associated with a higher probability of sugar-sweetened beverage consumption. Compared to day shifts, those who were assigned a quicker shift speed on evening shifts were more likely to consume sugar-sweetened beverages. However, associations between night shift intensity and sugar-sweetened beverage intake did not change by shift speed. Furthermore, shift intensity and shift timing did not interact to affect empty calorie food/beverage consumption. CONCLUSIONS This study demonstrated assignments of shift schedules (i.e., high night shift intensity, more changes in shift timings) might influence workers' consumption of empty calorie foods/beverages. Therefore, identifying and mitigating hazardous shift schedules may help to improve shift workers' eating behaviors and benefit their overall health.
Collapse
|
12
|
Soohoo M, Streja E, Hsiung JT, Kovesdy CP, Kalantar-Zadeh K, Arah OA. Cohort Study and Bias Analysis of the Obesity Paradox Across Stages of Chronic Kidney Disease. J Ren Nutr 2022; 32:529-536. [PMID: 34861399 PMCID: PMC10032545 DOI: 10.1053/j.jrn.2021.10.007] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Revised: 10/06/2021] [Accepted: 10/17/2021] [Indexed: 02/03/2023] Open
Abstract
OBJECTIVE In advanced chronic kidney disease (CKD), patients with obesity often have better outcomes than patients without obesity, often called the 'obesity paradox'. Yet, in CKD, the prevalence of inflammation increases as CKD progresses. Although a potential confounder, inflammation may be left unaccounted in obesity-mortality studies. We examined the associations of body mass index (BMI) with all-cause and cause-specific mortality across CKD stages, with consideration for uncontrolled confounding due to unmeasured inflammation. METHODS We investigated 2,703,512 patients with BMI data between 2004 and 2006. We used Cox models to examine the associations of BMI with all-cause, cardiovascular, and cancer mortality, (ref: BMI 25-<30 kg/m2), adjusted for clinical characteristics and stratified by CKD stages. To address uncontrolled confounding, we performed bias analysis using a weighted probabilistic model of inflammation given the observed data applied to weighted Cox models. RESULTS The cohort included 5% females and 14% African Americans. In adjusted analyses, the associations of the BMI with all-cause and cardiovascular mortality showed a reverse J-shape, where a higher BMI (>40 kg/m2) was associated with a higher risk. Conversely, a lower mortality risk was observed with a BMI 30-<35 kg/m2 across all CKD stages and for BMI >40 kg/m2 in CKD stage 4/5. Cancer mortality analyses showed an inverse relationship. Bias analysis for uncontrolled confounding suggested that independent of inflammation, the obesity paradox was present. CONCLUSION We observed the presence of the obesity paradox in this study. This association was consistent in advanced CKD and in our bias analysis, suggesting that inflammation may not fully explain the observed BMI-mortality associations including in patients with CKD.
Collapse
Affiliation(s)
- Melissa Soohoo
- Harold Simmons Center for Kidney Disease Research and Epidemiology, Division of Nephrology and Hypertension, University of California Irvine Medical Center, Orange, California; Nephrology Section, Tibor Rubin Veterans Affairs Medical Center, Long Beach, California; Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles (UCLA), Los Angeles, California
| | - Elani Streja
- Harold Simmons Center for Kidney Disease Research and Epidemiology, Division of Nephrology and Hypertension, University of California Irvine Medical Center, Orange, California; Nephrology Section, Tibor Rubin Veterans Affairs Medical Center, Long Beach, California; Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles (UCLA), Los Angeles, California.
| | - Jui-Ting Hsiung
- Harold Simmons Center for Kidney Disease Research and Epidemiology, Division of Nephrology and Hypertension, University of California Irvine Medical Center, Orange, California; Nephrology Section, Tibor Rubin Veterans Affairs Medical Center, Long Beach, California
| | - Csaba P Kovesdy
- Division of Nephrology, Department of Medicine, University of Tennessee Health Science Center, Memphis, Tennessee; Nephrology Section, Memphis Veterans Affairs Medical Center, Memphis, Tennessee
| | - Kamyar Kalantar-Zadeh
- Harold Simmons Center for Kidney Disease Research and Epidemiology, Division of Nephrology and Hypertension, University of California Irvine Medical Center, Orange, California; Nephrology Section, Tibor Rubin Veterans Affairs Medical Center, Long Beach, California; Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles (UCLA), Los Angeles, California
| | - Onyebuchi A Arah
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles (UCLA), Los Angeles, California; Department of Statistics, College of Letters and Science, University of California, Los Angeles (UCLA), Los Angeles, California; Section for Epidemiology, Department of Public Health, Aarhus University, Aarhus, Denmark.
| |
Collapse
|
13
|
Abstract
Randomized controlled trials (RCTs) are the gold standard design to establish the efficacy of new drugs and to support regulatory decision making. However, a marked increase in the submission of single-arm trials (SATs) has been observed in recent years, especially in the field of oncology due to the trend towards precision medicine contributing to the rise of new therapeutic interventions for rare diseases. SATs lack results for control patients, and information from external sources can be compiled to provide context for better interpretability of study results. External comparator arm (ECA) studies are defined as a clinical trial (most commonly a SAT) and an ECA of a comparable cohort of patients-commonly derived from real-world settings including registries, natural history studies, or medical records of routine care. This publication aims to provide a methodological overview, to sketch emergent best practice recommendations and to identify future methodological research topics. Specifically, existing scientific and regulatory guidance for ECA studies is reviewed and appropriate causal inference methods are discussed. Further topics include sample size considerations, use of estimands, handling of different data sources regarding differential baseline covariate definitions, differential endpoint measurements and timings. In addition, unique features of ECA studies are highlighted, specifically the opportunity to address bias caused by unmeasured ECA covariates, which are available in the SAT.
Collapse
|
14
|
Abravan A, Price G, Banfill K, Marchant T, Craddock M, Wood J, Aznar MC, McWilliam A, van Herk M, Faivre-Finn C. Role of Real-World Data in Assessing Cardiac Toxicity After Lung Cancer Radiotherapy. Front Oncol 2022; 12:934369. [PMID: 35928875 PMCID: PMC9344971 DOI: 10.3389/fonc.2022.934369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Accepted: 06/13/2022] [Indexed: 11/13/2022] Open
Abstract
Radiation-induced heart disease (RIHD) is a recent concern in patients with lung cancer after being treated with radiotherapy. Most of information we have in the field of cardiac toxicity comes from studies utilizing real-world data (RWD) as randomized controlled trials (RCTs) are generally not practical in this field. This article is a narrative review of the literature using RWD to study RIHD in patients with lung cancer following radiotherapy, summarizing heart dosimetric factors associated with outcome, strength, and limitations of the RWD studies, and how RWD can be used to assess a change to cardiac dose constraints.
Collapse
Affiliation(s)
- Azadeh Abravan
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom
- Department of Radiotherapy Related Research, The Christie National Health Service (NHS) Foundation Trust, Manchester, United Kingdom
| | - Gareth Price
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom
- Department of Radiotherapy Related Research, The Christie National Health Service (NHS) Foundation Trust, Manchester, United Kingdom
| | - Kathryn Banfill
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom
| | - Tom Marchant
- Department of Radiotherapy Related Research, The Christie National Health Service (NHS) Foundation Trust, Manchester, United Kingdom
| | - Matthew Craddock
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom
- Department of Radiotherapy Related Research, The Christie National Health Service (NHS) Foundation Trust, Manchester, United Kingdom
| | - Joe Wood
- Christie Medical Physics and Engineering, The Christie National Health Service (NHS) Foundation Trust, Manchester, United Kingdom
| | - Marianne C. Aznar
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom
- Department of Radiotherapy Related Research, The Christie National Health Service (NHS) Foundation Trust, Manchester, United Kingdom
| | - Alan McWilliam
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom
- Department of Radiotherapy Related Research, The Christie National Health Service (NHS) Foundation Trust, Manchester, United Kingdom
| | - Marcel van Herk
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom
- Department of Radiotherapy Related Research, The Christie National Health Service (NHS) Foundation Trust, Manchester, United Kingdom
| | - Corinne Faivre-Finn
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom
- Department of Radiotherapy Related Research, The Christie National Health Service (NHS) Foundation Trust, Manchester, United Kingdom
| |
Collapse
|
15
|
Inoue K, Ritz B, Arah OA. Causal Effect of Chronic Pain on Mortality Through Opioid Prescriptions: Application of the Front-Door Formula. Epidemiology 2022; 33:572-580. [PMID: 35384895 PMCID: PMC9148671 DOI: 10.1097/ede.0000000000001490] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2019] [Accepted: 03/24/2022] [Indexed: 11/26/2022]
Abstract
BACKGROUND Chronic pain is the leading cause of disability worldwide and is strongly associated with the epidemic of opioid overdosing events. However, the causal links between chronic pain, opioid prescriptions, and mortality remain unclear. METHODS This study included 13,884 US adults aged ≥20 years who provided data on chronic pain in the National Health and Nutrition Examination Survey 1999-2004 with linkage to mortality databases through 2015. We employed the generalized form of the front-door formula within the structural causal model framework to investigate the causal effect of chronic pain on all-cause mortality mediated by opioid prescriptions. RESULTS We identified a total of 718 participants at 3 years of follow-up and 1260 participants at 5 years as having died from all causes. Opioid prescriptions increased the risk of all-cause mortality with an estimated odds ratio (OR) (95% confidence interval) = 1.5 (1.1, 1.9) at 3 years and 1.3 (1.1, 1.6) at 5 years. The front-door formula revealed that chronic pain increased the risk of all-cause mortality through opioid prescriptions; OR = 1.06 (1.01, 1.11) at 3 years and 1.03 (1.01, 1.06) at 5 years. Our bias analysis showed that our findings based on the front-door formula were likely robust to plausible sources of bias from uncontrolled exposure-mediator or mediator-outcome confounding. CONCLUSIONS Chronic pain increased the risk of all-cause mortality through opioid prescriptions. Our findings highlight the importance of careful guideline-based chronic pain management to prevent death from possibly inappropriate opioid prescriptions driven by chronic pain.
Collapse
Affiliation(s)
- Kosuke Inoue
- From the Department of Social Epidemiology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles (UCLA), Los Angeles, California, USA
| | - Beate Ritz
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles (UCLA), Los Angeles, California, USA
- Department of Environmental Health Sciences, UCLA Fielding School of Public Health, Los Angeles, California, USA
- Department of Neurology, UCLA David Geffen School of Medicine, Los Angeles, California, USA
| | - Onyebuchi A. Arah
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles (UCLA), Los Angeles, California, USA
- Department of Statistics, UCLA College, Los Angeles, California, USA
- Center for Social Statistics, UCLA, Los Angeles, California, USA
- California Center for Population Research, UCLA Los Angeles, California, USA
- Department of Public Health, Research Unit for Epidemiology, Aarhus University, Aarhus, Denmark
| |
Collapse
|
16
|
Arah OA, Sullivan SG, Fell DB, Regan AK. Analyzing Uncontrolled Confounding of the Perinatal Health Effects of Severe Acute Respiratory Syndrome Coronavirus 2 Infection During Pregnancy. J Infect Dis 2022; 226:1678-1680. [PMID: 35543276 PMCID: PMC9384079 DOI: 10.1093/infdis/jiac194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Revised: 05/05/2022] [Accepted: 05/06/2022] [Indexed: 02/03/2023] Open
Affiliation(s)
- Onyebuchi A. Arah
- Fielding School of Public Health, University of California, Los Angeles, Los Angeles, California, USA,Department of Statistics, College of Letters and Science, University of California, Los Angeles, Los Angeles, California, USA,Department of Public Health, Aarhus University, Aarhus, Denmark
| | - Sheena G. Sullivan
- Fielding School of Public Health, University of California, Los Angeles, Los Angeles, California, USA,WHO Collaborating Center for Reference and Research on Influenza, Melbourne, Victoria, Australia,Department of Infectious Diseases, Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, Victoria, Australia
| | - Deshayne B. Fell
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada,Children’s Hospital of Eastern Ontario Research Institute, Ottawa, Ontario, Canada
| | - Annette K. Regan
- Correspondence: Annette Regan, PhD, MPH, MInfDis, School of Nursing and Public Health, University of San Francisco, 480 S Batavia St, Orange, CA 98484, USA ()
| |
Collapse
|
17
|
Burton I, McCormack A. The Effectiveness of Combined Extracorporeal Shockwave Therapy and Exercise for Plantar Heel Pain: A Systematic Review. EXPLORATORY RESEARCH AND HYPOTHESIS IN MEDICINE 2022; 7:39-52. [DOI: 10.14218/erhm.2021.00059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
|
18
|
Maier-Hein L, Eisenmann M, Sarikaya D, März K, Collins T, Malpani A, Fallert J, Feussner H, Giannarou S, Mascagni P, Nakawala H, Park A, Pugh C, Stoyanov D, Vedula SS, Cleary K, Fichtinger G, Forestier G, Gibaud B, Grantcharov T, Hashizume M, Heckmann-Nötzel D, Kenngott HG, Kikinis R, Mündermann L, Navab N, Onogur S, Roß T, Sznitman R, Taylor RH, Tizabi MD, Wagner M, Hager GD, Neumuth T, Padoy N, Collins J, Gockel I, Goedeke J, Hashimoto DA, Joyeux L, Lam K, Leff DR, Madani A, Marcus HJ, Meireles O, Seitel A, Teber D, Ückert F, Müller-Stich BP, Jannin P, Speidel S. Surgical data science - from concepts toward clinical translation. Med Image Anal 2022; 76:102306. [PMID: 34879287 PMCID: PMC9135051 DOI: 10.1016/j.media.2021.102306] [Citation(s) in RCA: 85] [Impact Index Per Article: 42.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 11/03/2021] [Accepted: 11/08/2021] [Indexed: 02/06/2023]
Abstract
Recent developments in data science in general and machine learning in particular have transformed the way experts envision the future of surgery. Surgical Data Science (SDS) is a new research field that aims to improve the quality of interventional healthcare through the capture, organization, analysis and modeling of data. While an increasing number of data-driven approaches and clinical applications have been studied in the fields of radiological and clinical data science, translational success stories are still lacking in surgery. In this publication, we shed light on the underlying reasons and provide a roadmap for future advances in the field. Based on an international workshop involving leading researchers in the field of SDS, we review current practice, key achievements and initiatives as well as available standards and tools for a number of topics relevant to the field, namely (1) infrastructure for data acquisition, storage and access in the presence of regulatory constraints, (2) data annotation and sharing and (3) data analytics. We further complement this technical perspective with (4) a review of currently available SDS products and the translational progress from academia and (5) a roadmap for faster clinical translation and exploitation of the full potential of SDS, based on an international multi-round Delphi process.
Collapse
Affiliation(s)
- Lena Maier-Hein
- Division of Computer Assisted Medical Interventions (CAMI), German Cancer Research Center (DKFZ), Heidelberg, Germany; Faculty of Mathematics and Computer Science, Heidelberg University, Heidelberg, Germany; Medical Faculty, Heidelberg University, Heidelberg, Germany.
| | - Matthias Eisenmann
- Division of Computer Assisted Medical Interventions (CAMI), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Duygu Sarikaya
- Department of Computer Engineering, Faculty of Engineering, Gazi University, Ankara, Turkey; LTSI, Inserm UMR 1099, University of Rennes 1, Rennes, France
| | - Keno März
- Division of Computer Assisted Medical Interventions (CAMI), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | | | - Anand Malpani
- The Malone Center for Engineering in Healthcare, The Johns Hopkins University, Baltimore, Maryland, USA
| | | | - Hubertus Feussner
- Department of Surgery, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Stamatia Giannarou
- The Hamlyn Centre for Robotic Surgery, Imperial College London, London, United Kingdom
| | - Pietro Mascagni
- ICube, University of Strasbourg, CNRS, France; IHU Strasbourg, Strasbourg, France
| | | | - Adrian Park
- Department of Surgery, Anne Arundel Health System, Annapolis, Maryland, USA; Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Carla Pugh
- Department of Surgery, Stanford University School of Medicine, Stanford, California, USA
| | - Danail Stoyanov
- Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, London, United Kingdom
| | - Swaroop S Vedula
- The Malone Center for Engineering in Healthcare, The Johns Hopkins University, Baltimore, Maryland, USA
| | - Kevin Cleary
- The Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, D.C., USA
| | | | - Germain Forestier
- L'Institut de Recherche en Informatique, Mathématiques, Automatique et Signal (IRIMAS), University of Haute-Alsace, Mulhouse, France; Faculty of Information Technology, Monash University, Clayton, Victoria, Australia
| | - Bernard Gibaud
- LTSI, Inserm UMR 1099, University of Rennes 1, Rennes, France
| | - Teodor Grantcharov
- University of Toronto, Toronto, Ontario, Canada; The Li Ka Shing Knowledge Institute of St. Michael's Hospital, Toronto, Ontario, Canada
| | - Makoto Hashizume
- Kyushu University, Fukuoka, Japan; Kitakyushu Koga Hospital, Fukuoka, Japan
| | - Doreen Heckmann-Nötzel
- Division of Computer Assisted Medical Interventions (CAMI), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Hannes G Kenngott
- Department for General, Visceral and Transplantation Surgery, Heidelberg University Hospital, Heidelberg, Germany
| | - Ron Kikinis
- Department of Radiology, Brigham and Women's Hospital, and Harvard Medical School, Boston, Massachusetts, USA
| | | | - Nassir Navab
- Computer Aided Medical Procedures, Technical University of Munich, Munich, Germany; Department of Computer Science, The Johns Hopkins University, Baltimore, Maryland, USA
| | - Sinan Onogur
- Division of Computer Assisted Medical Interventions (CAMI), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Tobias Roß
- Division of Computer Assisted Medical Interventions (CAMI), German Cancer Research Center (DKFZ), Heidelberg, Germany; Medical Faculty, Heidelberg University, Heidelberg, Germany
| | - Raphael Sznitman
- ARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland
| | - Russell H Taylor
- Department of Computer Science, The Johns Hopkins University, Baltimore, Maryland, USA
| | - Minu D Tizabi
- Division of Computer Assisted Medical Interventions (CAMI), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Martin Wagner
- Department for General, Visceral and Transplantation Surgery, Heidelberg University Hospital, Heidelberg, Germany
| | - Gregory D Hager
- The Malone Center for Engineering in Healthcare, The Johns Hopkins University, Baltimore, Maryland, USA; Department of Computer Science, The Johns Hopkins University, Baltimore, Maryland, USA
| | - Thomas Neumuth
- Innovation Center Computer Assisted Surgery (ICCAS), University of Leipzig, Leipzig, Germany
| | - Nicolas Padoy
- ICube, University of Strasbourg, CNRS, France; IHU Strasbourg, Strasbourg, France
| | - Justin Collins
- Division of Surgery and Interventional Science, University College London, London, United Kingdom
| | - Ines Gockel
- Department of Visceral, Transplant, Thoracic and Vascular Surgery, Leipzig University Hospital, Leipzig, Germany
| | - Jan Goedeke
- Pediatric Surgery, Dr. von Hauner Children's Hospital, Ludwig-Maximilians-University, Munich, Germany
| | - Daniel A Hashimoto
- University Hospitals Cleveland Medical Center, Case Western Reserve University, Cleveland, Ohio, USA; Surgical AI and Innovation Laboratory, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Luc Joyeux
- My FetUZ Fetal Research Center, Department of Development and Regeneration, Biomedical Sciences, KU Leuven, Leuven, Belgium; Center for Surgical Technologies, Faculty of Medicine, KU Leuven, Leuven, Belgium; Department of Obstetrics and Gynecology, Division Woman and Child, Fetal Medicine Unit, University Hospitals Leuven, Leuven, Belgium; Michael E. DeBakey Department of Surgery, Texas Children's Hospital and Baylor College of Medicine, Houston, Texas, USA
| | - Kyle Lam
- Department of Surgery and Cancer, Imperial College London, London, United Kingdom
| | - Daniel R Leff
- Department of BioSurgery and Surgical Technology, Imperial College London, London, United Kingdom; Hamlyn Centre for Robotic Surgery, Imperial College London, London, United Kingdom; Breast Unit, Imperial Healthcare NHS Trust, London, United Kingdom
| | - Amin Madani
- Department of Surgery, University Health Network, Toronto, Ontario, Canada
| | - Hani J Marcus
- National Hospital for Neurology and Neurosurgery, and UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Ozanan Meireles
- Massachusetts General Hospital, and Harvard Medical School, Boston, Massachusetts, USA
| | - Alexander Seitel
- Division of Computer Assisted Medical Interventions (CAMI), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Dogu Teber
- Department of Urology, City Hospital Karlsruhe, Karlsruhe, Germany
| | - Frank Ückert
- Institute for Applied Medical Informatics, Hamburg University Hospital, Hamburg, Germany
| | - Beat P Müller-Stich
- Department for General, Visceral and Transplantation Surgery, Heidelberg University Hospital, Heidelberg, Germany
| | - Pierre Jannin
- LTSI, Inserm UMR 1099, University of Rennes 1, Rennes, France
| | - Stefanie Speidel
- Division of Translational Surgical Oncology, National Center for Tumor Diseases (NCT/UCC) Dresden, Dresden, Germany; Centre for Tactile Internet with Human-in-the-Loop (CeTI), TU Dresden, Dresden, Germany
| |
Collapse
|
19
|
Innes GK, Bhondoekhan F, Lau B, Gross AL, Ng DK, Abraham AG. The Measurement Error Elephant in the Room: Challenges and Solutions to Measurement Error in Epidemiology. Epidemiol Rev 2022; 43:94-105. [PMID: 34664648 PMCID: PMC9005058 DOI: 10.1093/epirev/mxab011] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Revised: 09/30/2021] [Accepted: 10/06/2021] [Indexed: 11/12/2022] Open
Abstract
Measurement error, although ubiquitous, is uncommonly acknowledged and rarely assessed or corrected in epidemiologic studies. This review offers a straightforward guide to common problems caused by measurement error in research studies and a review of several accessible bias-correction methods for epidemiologists and data analysts. Although most correction methods require criterion validation including a gold standard, there are also ways to evaluate the impact of measurement error and potentially correct for it without such data. Technical difficulty ranges from simple algebra to more complex algorithms that require expertise, fine tuning, and computational power. However, at all skill levels, software packages and methods are available and can be used to understand the threat to inferences that arises from imperfect measurements.
Collapse
Affiliation(s)
| | | | | | | | | | - Alison G Abraham
- Correspondence to Dr. Alison G. Abraham, Department of Epidemiology, University of Colorado, Anschutz Medical Campus, 1635 Aurora Ct, Aurora, CO 80045 (e-mail: )
| |
Collapse
|
20
|
Banack HR, Hayes-Larson E, Mayeda ER. Monte Carlo Simulation Approaches for Quantitative Bias Analysis: A Tutorial. Epidemiol Rev 2021; 43:106-117. [PMID: 34664653 DOI: 10.1093/epirev/mxab012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2020] [Revised: 09/17/2021] [Accepted: 10/14/2021] [Indexed: 11/14/2022] Open
Abstract
Quantitative bias analysis can be used to empirically assess how far study estimates are from the truth (i.e., an estimate that is free of bias). These methods can be used to explore the potential impact of confounding bias, selection bias (collider stratification bias), and information bias. Quantitative bias analysis includes methods that can be used to check the robustness of study findings to multiple types of bias and methods that use simulation studies to generate data and understand the hypothetical impact of specific types of bias in a simulated dataset. In this article, we review two strategies for quantitative bias analysis: 1) traditional probabilistic quantitative bias analysis and 2) quantitative bias analysis with generated data. An important difference between the two strategies relates to the type of data (real vs. generated data) used in the analysis. As we describe, Monte Carlo simulations are used in both approaches, but the simulation process is used for different purposes in each. For both approaches, we outline and describe the steps required to carry out the quantitative bias analysis and also present a bias analysis tutorial demonstrating how both approaches can be applied in the context of an analysis for selection bias. Our goal is to highlight the utility of quantitative bias analysis for practicing epidemiologists and increase the use of these methods in the epidemiologic literature.
Collapse
Affiliation(s)
- Hailey R Banack
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, Buffalo, New York
| | - Eleanor Hayes-Larson
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, California
| | - Elizabeth Rose Mayeda
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, California
| |
Collapse
|
21
|
Brand JE, Xu J, Koch B, Geraldo P. Uncovering Sociological Effect Heterogeneity Using Tree-Based Machine Learning. SOCIOLOGICAL METHODOLOGY 2021; 51:189-223. [PMID: 36741684 PMCID: PMC9897445 DOI: 10.1177/0081175021993503] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Individuals do not respond uniformly to treatments, such as events or interventions. Sociologists routinely partition samples into subgroups to explore how the effects of treatments vary by selected covariates, such as race and gender, on the basis of theoretical priors. Data-driven discoveries are also routine, yet the analyses by which sociologists typically go about them are often problematic and seldom move us beyond our biases to explore new meaningful subgroups. Emerging machine learning methods based on decision trees allow researchers to explore sources of variation that they may not have previously considered or envisaged. In this article, the authors use tree-based machine learning, that is, causal trees, to recursively partition the sample to uncover sources of effect heterogeneity. Assessing a central topic in social inequality, college effects on wages, the authors compare what is learned from covariate and propensity score-based partitioning approaches with recursive partitioning based on causal trees. Decision trees, although superseded by forests for estimation, can be used to uncover subpopulations responsive to treatments. Using observational data, the authors expand on the existing causal tree literature by applying leaf-specific effect estimation strategies to adjust for observed confounding, including inverse propensity weighting, nearest neighbor matching, and doubly robust causal forests. We also assess localized balance metrics and sensitivity analyses to address the possibility of differential imbalance and unobserved confounding. The authors encourage researchers to follow similar data exploration practices in their work on variation in sociological effects and offer a straightforward framework by which to do so.
Collapse
Affiliation(s)
- Jennie E. Brand
- University of California, Los Angeles, Los Angeles, CA, USA
- California Center for Population Research, Los Angeles, CA, USA
- Center for Social Statistics, Los Angeles, CA, USA
| | - Jiahui Xu
- Pennsylvania State University, University Park, PA, USA
| | - Bernard Koch
- University of California, Los Angeles, Los Angeles, CA, USA
| | - Pablo Geraldo
- University of California, Los Angeles, Los Angeles, CA, USA
| |
Collapse
|
22
|
Pace NP, Vassallo J. Association Between Neutrophil-Lymphocyte Ratio and Gestational Diabetes-A Systematic Review and Meta-Analysis. J Endocr Soc 2021; 5:bvab051. [PMID: 34095691 PMCID: PMC8169042 DOI: 10.1210/jendso/bvab051] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Indexed: 12/21/2022] Open
Abstract
A growing body of evidence shows that the neutrophil-lymphocyte ratio (NLR) is a surrogate index of systemic inflammation in several chronic diseases. Conflicting associations between NLR and gestational diabetes mellitus (GDM) have been reported in individual studies. This meta-analysis sought to investigate the association between NLR and GDM. The PubMed, EMBASE, and Google Scholar databases were searched to identify relevant articles. The pooled standardized mean difference with 95% CI was calculated using a random-effects model. Subgroup and meta-regression analysis were carried out to control for the effects of GDM diagnostic criteria, ethnicity, body mass index (BMI), and age. Eleven eligible articles were included, containing 1271 participants with GDM and 1504 controls. Pooled outcomes indicated a higher NLR in GDM pregnancies than in normoglycemic controls (SMD = 0.584; 95% CI, 0.339-0.830; P < .001), although extensive heterogeneity between studies was noted. Subgroup analysis revealed that the higher pooled estimate in GDM was not affected by diagnostic criteria, ethnicity, or BMI, although matching for BMI reduced heterogeneity between studies. This meta-analysis supports the higher NLR in GDM described by some individual studies.
Collapse
Affiliation(s)
- Nikolai Paul Pace
- Centre for Molecular Medicine and Biobanking, Faculty of Medicine and Surgery, University of Malta, MSD2080 Msida, Malta
| | - Josanne Vassallo
- Centre for Molecular Medicine and Biobanking, Faculty of Medicine and Surgery, University of Malta, MSD2080 Msida, Malta
- Department of Medicine, Faculty of Medicine and Surgery, University of Malta, MSD2080, Msida, Malta
| |
Collapse
|
23
|
Burton I, McCormack A. Autoregulated and individualised resistance training versus predetermined and standardised resistance training in tendinopathy: A systematic review protocol. Musculoskeletal Care 2021; 19:533-539. [PMID: 33687141 DOI: 10.1002/msc.1551] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Revised: 02/19/2021] [Accepted: 02/20/2021] [Indexed: 01/06/2023]
Abstract
REVIEW OBJECTIVE To synthesise the best available evidence on the effectiveness of interventions that have used autoregulated and individualised resistance training versus predetermined and standardised resistance training in treating any tendinopathy. INTRODUCTION Recent evidence suggests that individualised exercise may be more effective than standardised exercise for musculoskeletal disorders such as tendinopathy. However, no systematic reviews have been conducted on the topic and optimal treatment protocols and clinical recommendations are lacking. INCLUSION CRITERIA Randomised controlled trials assessing the effectiveness of autoregulated and individualised resistance training versus predetermined and standardised resistance training for tendinopathy in adults will be included. METHODS The authors will search for a wide range of sources to find both published and unpublished studies via EBSCOhost, including, but not limited to, MEDLINE, SPORTDiscus, CINAHL, Cochrane Central Register of Controlled Trials and Allied and Complementary Medicine Database. Studies published in a language other than English will only be considered if a translation is available. The Joanna Briggs Institute systematic review methodology will be followed when conducting the review. Data synthesis will be conducted using meta-analysis or narrative synthesis, where appropriate.
Collapse
Affiliation(s)
- Ian Burton
- Angus Physiotherapy Department, Arbroath Infirmary, NHS Tayside, Arbroath, UK
| | | |
Collapse
|
24
|
Lam B, Jamieson LM, Mittinty M. Black Lives Matter: A Decomposition of Racial Inequalities in Oral Cancer Screening. Cancers (Basel) 2021; 13:cancers13040848. [PMID: 33671439 PMCID: PMC7922532 DOI: 10.3390/cancers13040848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Revised: 02/10/2021] [Accepted: 02/13/2021] [Indexed: 11/30/2022] Open
Abstract
Simple Summary Black Lives Matter has highlighted the increased social discrepancies that exist not only in the context of social justice but also in public health. Oral cancer screening is not exempt from disparity, with Black Americans less likely to seek screening leading to higher incidence and worse outcomes of oropharyngeal cancers. We investigate interaction analysis and Blinder–Oaxaca decomposition as tools to guide policy to address this disparity. Using National Health and Nutrition Examination Survey (NHANES) data from 2011–2018 we find that being both in poverty and Black results in sub-additive interaction, which is further deconstructed into differences in higher education levels and poverty status. Abstract (1) Background: The Black Lives Matter movement has highlighted the discrepancies in public health in regard to race. This study aims to investigate tools that can be used to analyze and investigate this discrepancy, which can be applied to policymaking. (2) Methods: National Health and Nutrition Examination Survey (NHANES) data from 2011–2018 was combined (N = 22,617) to investigate discrepancies of oral cancer screening in Black Americans. We give examples of counterfactual techniques that can be used to guide policy. Inverse probability treatment weighting (IPTW) was used to remove all measured confounding in an interaction analysis to assess the combined effect of socioeconomic status and race. Blinder–Oaxaca decomposition was then used to investigate the intervenable factors associated with differences in race. (3) Results: Sub-additive interaction was found on additive and multiplicative scales when all measured confounding was removed via IPTW (relative excess risk due to interaction (RERI)(OR) = −0.55 (−0.67–−0.42)). Decomposition analysis found that 32% of the discrepancy could be explained by characteristics of higher education and poverty status. (4) Conclusions: Black Americans in poverty are less likely to seek oral cancer screening than the additive likelihood would suggest. Blinder–Oaxaca decomposition is a strong tool to use for guiding policy as it quantifies clear breakdowns of what intervenable factors there are that would improve the discrepancy the most.
Collapse
Affiliation(s)
- Benjamin Lam
- School of Public Health, The University of Adelaide, Adelaide 5005, Australia; (L.M.J.); (M.M.)
- Correspondence:
| | - Lisa M. Jamieson
- School of Public Health, The University of Adelaide, Adelaide 5005, Australia; (L.M.J.); (M.M.)
- Australian Research Centre for Population Oral Health, The University of Adelaide, Adelaide 5005, Australia
| | - Murthy Mittinty
- School of Public Health, The University of Adelaide, Adelaide 5005, Australia; (L.M.J.); (M.M.)
| |
Collapse
|
25
|
Inoue K, Kitamoto T, Tsurutani Y, Saito J, Omura M, Nishikawa T. Cortisol Co-Secretion and Clinical Usefulness of ACTH Stimulation Test in Primary Aldosteronism: A Systematic Review and Biases in Epidemiological Studies. Front Endocrinol (Lausanne) 2021; 12:645488. [PMID: 33796078 PMCID: PMC8008473 DOI: 10.3389/fendo.2021.645488] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Accepted: 02/15/2021] [Indexed: 02/03/2023] Open
Abstract
The hypothalamus-pituitary-adrenal (HPA) axis plays an important role in primary aldosteronism. Aldosterone biosynthesis is regulated not only by angiotensin II in the renin-angiotensin-aldosterone system, but also by adrenocorticotropic hormone (ACTH), one of the key components of the HPA axis. Although previous studies have reported cortisol cosecretion in primary aldosteronism, particularly aldosterone-producing adenoma (APA), the clinical relevance of such aldosterone and cortisol cosecretion from APA and hypertension or other metabolic disorders has not been fully established. Several somatic mutations including KCNJ5 and CACNA1D are known to induce autonomous production of aldosterone in APA, and the aldosterone responsiveness to ACTH may vary according to each mutation. The ACTH stimulation test has been reported to be a useful tool to distinguish the subtypes of primary aldosteronism (e.g., unilateral vs bilateral) in some studies, but it has not been commonly applied in clinical practice due to limited evidence. Given the recent advancement of imaging, omics research, and computational approach, it is important to summarize the most updated evidence to disentangle the potential impact of cortisol excess in primary aldosteronism and whether the ACTH stimulation test needs to be considered during the diagnostic process of primary aldosteronism. In this article, we conducted a systematic review of epidemiological studies about (i) cortisol cosecretion in primary aldosteronism and (ii) the ACTH stimulation test for the diagnosis of primary aldosteronism (including subtype diagnosis). Then, we discussed potential biases (e.g., confounding bias, overadjustment, information bias, selection bias, and sampling bias) in the previous studies and introduced some advanced epidemiological/statistical methods to minimize these limitations. A better understanding of biases and epidemiological perspective on this topic would allow us to produce further robust evidence and balanced discussion about the causal mechanisms involving the HPA axis and clinical usefulness of the ACTH stimulation test among patients with primary aldosteronism.
Collapse
Affiliation(s)
- Kosuke Inoue
- Department of Epidemiology, University of California, Los Angeles (UCLA) Fielding School of Public Health, Los Angeles, CA, United States
- Endocrinology and Diabetes Center, Yokohama Rosai Hospital, Yokohama, Japan
| | - Takumi Kitamoto
- Endocrinology and Diabetes Center, Yokohama Rosai Hospital, Yokohama, Japan
- Division of Endocrinology, Department of Medicine, Columbia University, New York, NY, United States
| | - Yuya Tsurutani
- Endocrinology and Diabetes Center, Yokohama Rosai Hospital, Yokohama, Japan
| | - Jun Saito
- Endocrinology and Diabetes Center, Yokohama Rosai Hospital, Yokohama, Japan
| | - Masao Omura
- Endocrinology and Diabetes Center, Yokohama Rosai Hospital, Yokohama, Japan
| | - Tetsuo Nishikawa
- Endocrinology and Diabetes Center, Yokohama Rosai Hospital, Yokohama, Japan
- *Correspondence: Tetsuo Nishikawa,
| |
Collapse
|
26
|
Inoue K, Beekley J, Goto A, Jeon CY, Ritz BR. Depression and cardiovascular disease events among patients with type 2 diabetes: A systematic review and meta-analysis with bias analysis. J Diabetes Complications 2020; 34:107710. [PMID: 32921574 PMCID: PMC7467011 DOI: 10.1016/j.jdiacomp.2020.107710] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Revised: 07/22/2020] [Accepted: 08/18/2020] [Indexed: 12/31/2022]
Abstract
AIMS To provide updated systematic and quantitative summary of the association between depression and the risk of CVD events among individuals with type 2 diabetes. We also aimed to examine the sensitivity of the association to uncontrolled confounding. METHODS Data sources included Medline, Embase, and PsycInfo through September 2019. Two independent reviewers selected cohort studies that evaluated the association between depression and fatal or non-fatal CVD events among individuals with type 2 diabetes. Bias analysis was performed using the bias formula approach. RESULTS Of 2527 citations screened, 17 eligible studies with a total of 1,033,131 participants were identified. Based on random-effects meta-analysis, depression was associated with higher risks of non-fatal CVD events (relative risk 1.35, 95% confidence interval [CI] 1.20 to 1.53) and fatal CVD event (relative risk 1.47, 95% CI 1.21 to 1.77). Bias analysis indicated that unmeasured confounders alone may not explain the observed association between depression and CVD events among individuals with type 2 diabetes. CONCLUSIONS Depression was associated with a higher risk of non-fatal and fatal CVD events among individuals with type 2 diabetes. Our findings provide updated and robust evidence about the association between depression and CVD events among individuals with type 2 diabetes.
Collapse
Affiliation(s)
- Kosuke Inoue
- Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, CA, United States; Division of Nephrology and Endocrinology, University of Tokyo Graduate School of Medicine, Tokyo, Japan..
| | - James Beekley
- Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, CA, United States
| | - Atsushi Goto
- Metabolic Epidemiology Section, Center for Public Health Sciences, National Cancer Center, Tokyo, Japan
| | - Christie Y Jeon
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States
| | - Beate R Ritz
- Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, CA, United States; Department of Environmental Health Sciences, UCLA Fielding School of Public Health, Los Angeles, CA, United States; Department of Neurology, UCLA David Geffen School of Medicine, Los Angeles, CA, United States
| |
Collapse
|
27
|
Burton I, Cooper K, Alexander L, Swinton PA. Effectiveness of combined shockwave therapy and plantar fascia stretching interventions in treating plantar heel pain: a systematic review and meta-analysis protocol. JBI Evid Synth 2020; 19:1186-1192. [PMID: 33074993 DOI: 10.11124/jbies-20-00186] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/31/2022]
Abstract
OBJECTIVE The objective of this review is to synthesize the best available evidence on the effectiveness of interventions that have used a combination of extracorporeal shockwave therapy and plantar fascia-specific stretching to treat plantar heel pain compared to any other non-surgical intervention. INTRODUCTION Recent evidence suggests combining shockwave therapy and plantar fascia stretching may be more effective than other treatments for plantar heel pain. However, no systematic reviews have been conducted on the topic and optimal treatment protocols and clinical recommendations are lacking. INCLUSION CRITERIA Randomized controlled trials assessing the effectiveness of combined shockwave therapy and plantar stretching for plantar heel pain in adults will be included. METHODS The authors will search a wide range of sources to identify both published and unpublished studies via EBSCOhost, including, but not limited to MEDLINE, SPORTDiscus, CINAHL, Cochrane Central Register of Controlled Trials (CENTRAL), and Allied and Complementary Medicine Database (AMED). Studies published in a language other than English will only be considered if a translation is available. The JBI systematic review methodology will be followed when conducting the review. Data synthesis will be conducted using meta-analysis or narrative synthesis, where appropriate. SYSTEMATIC REVIEW REGISTRATION NUMBER PROSPERO CRD42020171538.
Collapse
Affiliation(s)
- Ian Burton
- School of Health Sciences, Robert Gordon University, Aberdeen, UK
| | - Kay Cooper
- School of Health Sciences, Robert Gordon University, Aberdeen, UK.,The Scottish Centre for Evidence-based, Multi-professional Practice: A JBI Centre of Excellence, Aberdeen, UK.,NHS Grampian, Aberdeen, UK
| | - Lyndsay Alexander
- School of Health Sciences, Robert Gordon University, Aberdeen, UK.,The Scottish Centre for Evidence-based, Multi-professional Practice: A JBI Centre of Excellence, Aberdeen, UK
| | | |
Collapse
|
28
|
Hazlett C, Maokola W, Wulf DA. Inference without randomization or ignorability: A stability-controlled quasi-experiment on the prevention of tuberculosis. Stat Med 2020; 39:4169-4186. [PMID: 32885470 DOI: 10.1002/sim.8717] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2019] [Revised: 06/09/2020] [Accepted: 07/14/2020] [Indexed: 11/06/2022]
Abstract
The stability-controlled quasi-experiment (SCQE) is an approach to study the effects of nonrandomized, newly adopted treatments. While covariate adjustment techniques rely on a "no unobserved confounding" assumption, SCQE imposes an assumption on the change in the average nontreatment outcome between successive cohorts (the "baseline trend"). We provide inferential tools for SCQE and its first application, examining whether isoniazid preventive therapy (IPT) reduced tuberculosis (TB) incidence among 26 715 HIV patients in Tanzania. After IPT became available, 16% of untreated patients developed TB within a year, compared with only 0.5% of patients under treatment. Thus, a simple difference in means suggests a 15.5 percentage point (pp) lower risk (p ≪ .001). Adjusting for covariates using numerous techniques leaves this effectively unchanged. Yet, due to confounding biases, such estimates can be misleading regardless of their statistical strength. By contrast, SCQE reveals valid causal effect estimates for any chosen assumption on the baseline trend. For example, assuming a baseline trend near 0 (no change in TB incidence over time, absent this treatment) implies a small and insignificant effect. To argue IPT was beneficial requires arguing that the nontreatment incidence would have risen by at least 0.7 pp per year, which is plausible but far from certain. SCQE may produce narrow estimates when the plausible range of baseline trends can be sufficiently constrained, while in every case it tells us what baseline trends must be believed in order to sustain a given conclusion, protecting against inferences that rely upon infeasible assumptions.
Collapse
Affiliation(s)
- Chad Hazlett
- UCLA Statistics and Political Science, University of California, Los Angeles, Los Angeles, California, USA
| | - Werner Maokola
- National AIDS Control Program (NACP); Department of Epidemiology, Kilimanjaro Christian Medical University College, Moshi, Tanzania
| | - David Ami Wulf
- UCLA Statistics, University of California Los Angeles, Los Angeles, California, USA
| |
Collapse
|
29
|
Fox MP, Arah OA, Stuart EA. Commentary: The value of E-values and why they are not enough. Int J Epidemiol 2020; 49:1505-1506. [DOI: 10.1093/ije/dyaa093] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/04/2020] [Indexed: 11/13/2022] Open
Affiliation(s)
- Matthew P Fox
- Department of Epidemiology and Global Health, Boston University School of Public Health, Boston, MA, USA
| | - Onyebuchi A Arah
- Department of Epidemiology, Fielding School of Public Health and Department of Statistics, College of Letters and Science, UCLA, Los Angeles, CA, USA
| | - Elizabeth A Stuart
- Department of Mental Health, Biostatistics and Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins, Baltimore, MD, USA
| |
Collapse
|
30
|
The role of dwelling type when estimating the effect of magnetic fields on childhood leukemia in the California Power Line Study (CAPS). Cancer Causes Control 2020; 31:559-567. [PMID: 32277327 DOI: 10.1007/s10552-020-01299-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2019] [Accepted: 04/02/2020] [Indexed: 10/24/2022]
Abstract
PURPOSE The type of dwelling where a child lives is an important factor when considering residential exposure to environmental agents. In this paper, we explore its role when estimating the potential effects of magnetic fields (MF) on leukemia using data from the California Power Line Study (CAPS). In this context, dwelling type could be a risk factor, a proxy for other risk factors, a cause of MF exposure, a confounder, an effect-measure modifier, or some combination. METHODS We obtained information on type of dwelling at birth on over 2,000 subjects. Using multivariable-adjusted logistic regression, we assessed whether dwelling type was a risk factor for childhood leukemia, which covariates and MF exposures were associated with dwelling type, and whether dwelling type was a potential confounder or an effect-measure modifier in the MF-leukemia relationship under the assumption of no-uncontrolled confounding. RESULTS A majority of children lived in single-family homes or duplexes (70%). Dwelling type was associated with race/ethnicity and socioeconomic status but not with childhood leukemia risk, after other adjustments, and did not alter the MF-leukemia relationship upon adjustment as a potential confounder. Stratification revealed potential effect-measure modification by dwelling type on the multiplicative scale. CONCLUSION Dwelling type does not appear to play a significant role in the MF-leukemia relationship in the CAPS dataset as a leukemia risk factor or confounder. Future research should explore the role of dwelling as an effect-measure modifier of the MF-leukemia association.
Collapse
|
31
|
Jackson JW, Arah OA. Invited Commentary: Making Causal Inference More Social and (Social) Epidemiology More Causal. Am J Epidemiol 2020; 189:179-182. [PMID: 31573030 PMCID: PMC7217274 DOI: 10.1093/aje/kwz199] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Revised: 07/29/2019] [Accepted: 08/01/2019] [Indexed: 01/13/2023] Open
Abstract
A society's social structure and the interactions of its members determine when key drivers of health occur, for how long they last, and how they operate. Yet, it has been unclear whether causal inference methods can help us find meaningful interventions on these fundamental social drivers of health. Galea and Hernán propose we place hypothetical interventions on a spectrum and estimate their effects by emulating trials, either through individual-level data analysis or systems science modeling (Am J Epidemiol. 2020;189(3):167-170). In this commentary, by way of example in health disparities research, we probe this "closer engagement of social epidemiology with formal causal inference approaches." The formidable, but not insurmountable, tensions call for causal reasoning and effect estimation in social epidemiology that should always be enveloped by a thorough understanding of how systems and the social exposome shape risk factor and health distributions. We argue that one way toward progress is a true partnership of social epidemiology and causal inference with bilateral feedback aimed at integrating social epidemiologic theory, causal identification and modeling methods, systems thinking, and improved study design and data. To produce consequential work, we must make social epidemiology more causal and causal inference more social.
Collapse
Affiliation(s)
- John W Jackson
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Center for Health Equity, Johns Hopkins University
- Center for Health Disparities Solutions, Johns Hopkins Bloomberg School of Public Health
| | - Onyebuchi A Arah
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, California
- Department of Statistics, UCLA College of Letters and Science, Los Angeles, California
- Department of Public Health, Aarhus University, Aarhus, Denmark
| |
Collapse
|
32
|
Xie Y, Near C, Xu H, Song X. Heterogeneous treatment effects on Children's cognitive/non-cognitive skills: A reevaluation of an influential early childhood intervention. SOCIAL SCIENCE RESEARCH 2020; 86:102389. [PMID: 32056571 PMCID: PMC7401325 DOI: 10.1016/j.ssresearch.2019.102389] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/12/2019] [Revised: 09/04/2019] [Accepted: 11/12/2019] [Indexed: 06/10/2023]
Abstract
The 1962-67 High/Scope Perry Preschool Program, a well-known experimental early childhood intervention study that provided quality preschool education to disadvantaged children, has been shown to have had positive impacts on early child development and on a variety of adulthood outcomes. However, most previous analyses have only examined average treatment effects across all program participants without exploring possible effect heterogeneity by children's background characteristics. We investigated this question by first using the 1964-65 Current Population Survey data in combination with the Perry data to construct a scale of child socioeconomic status based on the estimated propensity for inclusion in the Perry program, then analyzing effect heterogeneity within the Perry sample by strata of our socioeconomic scale. We found that the treatment effects of enrollment in the Perry preschool on cognitive and non-cognitive skills were much larger and more persistent among the most disadvantaged children than among others in the Perry program. Furthermore, among the most disadvantaged children, the treatment (i.e., preschool enrollment) affects later outcomes through a reinforcement mechanism of skill development (i.e., early cognitive gain leads to a non-cognitive gain, which in turn leads to later cognitive gain) and a sequential improvement of cognitive skills over time. These findings have important implications for the evaluation of policy interventions in early child development using experimental data.
Collapse
Affiliation(s)
- Yu Xie
- Princeton University, USA.
| | | | - Hongwei Xu
- Queens College, City University of New York, USA
| | - Xi Song
- University of Pennsylvania, USA
| |
Collapse
|
33
|
Yu Y, Arah OA, Liew Z, Cnattingius S, Olsen J, Sørensen HT, Qin G, Li J. Maternal diabetes during pregnancy and early onset of cardiovascular disease in offspring: population based cohort study with 40 years of follow-up. BMJ 2019; 367:l6398. [PMID: 31801789 PMCID: PMC6891797 DOI: 10.1136/bmj.l6398] [Citation(s) in RCA: 158] [Impact Index Per Article: 31.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
OBJECTIVE To evaluate the associations between maternal diabetes diagnosed before or during pregnancy and early onset cardiovascular disease (CVD) in offspring during their first four decades of life. DESIGN Population based cohort study. SETTING Danish national health registries. PARTICIPANTS All 2 432 000 liveborn children without congenital heart disease in Denmark during 1977-2016. Follow-up began at birth and continued until first time diagnosis of CVD, death, emigration, or 31 December 2016, whichever came first. EXPOSURES FOR OBSERVATIONAL STUDIES Pregestational diabetes, including type 1 diabetes (n=22 055) and type 2 diabetes (n=6537), and gestational diabetes (n=26 272). MAIN OUTCOME MEASURES The primary outcome was early onset CVD (excluding congenital heart diseases) defined by hospital diagnosis. Associations between maternal diabetes and risks of early onset CVD in offspring were studied. Cox regression was used to assess whether a maternal history of CVD or maternal diabetic complications affected these associations. Adjustments were made for calendar year, sex, singleton status, maternal factors (parity, age, smoking, education, cohabitation, residence at childbirth, history of CVD before childbirth), and paternal history of CVD before childbirth. The cumulative incidence was averaged across all individuals, and factors were adjusted while treating deaths from causes other than CVD as competing events. RESULTS During up to 40 years of follow-up, 1153 offspring of mothers with diabetes and 91 311 offspring of mothers who did not have diabetes were diagnosed with CVD. Offspring of mothers with diabetes had a 29% increased overall rate of early onset CVD (hazard ratio 1.29 (95% confidence interval 1.21 to 1.37); cumulative incidence among offspring unexposed to maternal diabetes at 40 years of age 13.07% (12.92% to 13.21%), difference in cumulative incidence between exposed and unexposed offspring 4.72% (2.37% to 7.06%)). The sibship design yielded results similar to those of the unpaired design based on the whole cohort. Both pregestational diabetes (1.34 (1.25 to 1.43)) and gestational diabetes (1.19 (1.07 to 1.32)) were associated with increased rates of CVD in offspring. We also observed varied increased rates of specific early onset CVDs, particularly heart failure (1.45 (0.89 to 2.35)), hypertensive disease (1.78 (1.50 to 2.11)), deep vein thrombosis (1.82 (1.38 to 2.41)), and pulmonary embolism (1.91 (1.31 to 2.80)). Increased rates of CVD were seen in different age groups from childhood to early adulthood until age 40 years. The increased rates were more pronounced among offspring of mothers with diabetic complications (1.60 (1.25 to 2.05)). A higher incidence of early onset CVD in offspring of mothers with diabetes and comorbid CVD (1.73 (1.36 to 2.20)) was associated with the added influence of comorbid CVD but not due to the interaction between diabetes and CVD on the multiplicative scale (P value for interaction 0.94). CONCLUSIONS Children of mothers with diabetes, especially those mothers with a history of CVD or diabetic complications, have increased rates of early onset CVD from childhood to early adulthood. If maternal diabetes does have a causal association with increased CVD rate in offspring, the prevention, screening, and treatment of diabetes in women of childbearing age could help to reduce the risk of CVD in the next generation.
Collapse
Affiliation(s)
- Yongfu Yu
- Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles (UCLA), CA, USA
| | - Onyebuchi A Arah
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles (UCLA), CA, USA
- Department of Statistics, College of Letters and Science, University of California, Los Angeles (UCLA), CA, USA
| | - Zeyan Liew
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, USA
- Yale Center for Perinatal, Pediatric, and Environmental Epidemiology, Yale School of Public Health, New Haven, CT, USA
| | - Sven Cnattingius
- Division of Epidemiology, Department of Medicine Solna 17176, Karolinska University Hospital, Karolinska Institute, Stockholm, Sweden
| | - Jørn Olsen
- Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles (UCLA), CA, USA
| | - Henrik Toft Sørensen
- Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark
| | - Guoyou Qin
- Department of Biostatistics, School of Public Health, and The Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai 200032, China
| | - Jiong Li
- Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark
- Ministry of Education-Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| |
Collapse
|
34
|
Affiliation(s)
- Onyebuchi A. Arah
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles (UCLA), Los Angeles, California, USA
- Department of Statistics, UCLA College of Letters and Science, Los Angeles, California, USA
- Center for Social Statistics, UCLA, Los Angeles, California, USA
- California Center for Population Research, UCLA Los Angeles, California, USA
- Department of Public Health, Aarhus University, Aarhus, Denmark
| |
Collapse
|
35
|
Amoon AT, Arah OA, Kheifets L. The sensitivity of reported effects of EMF on childhood leukemia to uncontrolled confounding by residential mobility: a hybrid simulation study and an empirical analysis using CAPS data. Cancer Causes Control 2019; 30:901-908. [PMID: 31144088 DOI: 10.1007/s10552-019-01189-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2018] [Accepted: 05/22/2019] [Indexed: 12/27/2022]
Abstract
PURPOSE Residential mobility is considered as a potential source of confounding in studies assessing environmental exposures, including in studies of electromagnetic field (EMF) exposures and childhood leukemia. METHODS We present a hybrid simulation study where we simulate a synthetic dataset based on an existing study and use it to assess the sensitivity of EMF-leukemia associations to different scenarios of uncontrolled confounding by mobility under two major hypotheses of the infectious etiology of childhood leukemia. We then used the findings to conduct sensitivity analysis and empirically offset the potential bias due to unmeasured mobility in the California Power Line Study dataset. RESULTS As expected, the stronger the assumed relationship between mobility and exposure and outcome, the greater the potential bias. However, no scenario created a bias strong enough to completely explain away previously observed associations. CONCLUSIONS We conclude that uncontrolled confounding by residential mobility had some impact on the estimated effect of EMF exposures on childhood leukemia, but that it was unlikely to be the primary explanation behind previously observed largely consistent, but unexplained associations.
Collapse
Affiliation(s)
- Aryana T Amoon
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles (UCLA), 650 Charles E. Young Drive South, Los Angeles, CA, 90095-1772, USA.
| | - Onyebuchi A Arah
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles (UCLA), 650 Charles E. Young Drive South, Los Angeles, CA, 90095-1772, USA.,Department of Statistics, UCLA College of Letters and Science, Los Angeles, CA, USA
| | - Leeka Kheifets
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles (UCLA), 650 Charles E. Young Drive South, Los Angeles, CA, 90095-1772, USA
| |
Collapse
|
36
|
Lases LSS, Arah OA, Busch ORC, Heineman MJ, Lombarts KMJMH. Learning climate positively influences residents' work-related well-being. ADVANCES IN HEALTH SCIENCES EDUCATION : THEORY AND PRACTICE 2019; 24:317-330. [PMID: 30519786 PMCID: PMC6483960 DOI: 10.1007/s10459-018-9868-4] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/06/2018] [Accepted: 11/21/2018] [Indexed: 06/09/2023]
Abstract
An optimal learning climate is crucial for the quality of residency training and may also improve residents' well-being and empathy. We investigated the associations of learning climate with residents' work-related well-being. A multicenter questionnaire study was performed among 271 surgery and gynaecology residents in 21 training programs from September 2012 to February 2013. Residents were asked to complete work-related well-being measurements: work engagement (Utrecht Work Engagement Scale), job and specialty satisfaction (measures from Physician Worklife Study), and physician empathy (Jefferson Scale of Physician Empathy). The Dutch Residency Educational Climate Test was used to evaluate learning climate. Multivariate adjusted linear regression analyses were used to estimate associations of learning climate with work-related well-being measures. Well-being measures were completed by 144 residents (53.1%). Learning climate was evaluated by 193 residents, yielding 9.2 evaluations per training program on average. Overall learning climate score was positively associated with work engagement [regression coefficient b = 0.58; 95% confidence interval (CI) 0.18-0.98; p = 0.004] and job satisfaction (b = 0.80; 95% CI 0.48-1.13; p < 0.001). No associations were found between learning climate and empathy and specialty satisfaction. Residents' work engagement and job satisfaction are positively related to the learning climate and may be further enhanced by improved learning climates of training programs.
Collapse
Affiliation(s)
- Lenny S S Lases
- Professional Performance Research Group, Department of Medical Psychology, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.
- Department of Surgery, Isala, Zwolle, The Netherlands.
| | - Onyebuchi A Arah
- Department of Epidemiology, Fielding School of Public Health, University of California Los Angeles (UCLA), Los Angeles, CA, USA
| | - Olivier R C Busch
- Department of Surgery, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Maas Jan Heineman
- Professional Performance Research Group, Department of Medical Psychology, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
- Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Kiki M J M H Lombarts
- Professional Performance Research Group, Department of Medical Psychology, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| |
Collapse
|
37
|
Smirnova A, Sebok-Syer SS, Chahine S, Kalet AL, Tamblyn R, Lombarts KMJMH, van der Vleuten CPM, Schumacher DJ. Defining and Adopting Clinical Performance Measures in Graduate Medical Education: Where Are We Now and Where Are We Going? ACADEMIC MEDICINE : JOURNAL OF THE ASSOCIATION OF AMERICAN MEDICAL COLLEGES 2019; 94:671-677. [PMID: 30720528 DOI: 10.1097/acm.0000000000002620] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Assessment and evaluation of trainees' clinical performance measures is needed to ensure safe, high-quality patient care. These measures also aid in the development of reflective, high-performing clinicians and hold graduate medical education (GME) accountable to the public. Although clinical performance measures hold great potential, challenges of defining, extracting, and measuring clinical performance in this way hinder their use for educational and quality improvement purposes. This article provides a way forward by identifying and articulating how clinical performance measures can be used to enhance GME by linking educational objectives with relevant clinical outcomes. The authors explore four key challenges: defining as well as measuring clinical performance measures, using electronic health record and clinical registry data to capture clinical performance, and bridging silos of medical education and health care quality improvement. The authors also propose solutions to showcase the value of clinical performance measures and conclude with a research and implementation agenda. Developing a common taxonomy of uniform specialty-specific clinical performance measures, linking these measures to large-scale GME databases, and applying both quantitative and qualitative methods to create a rich understanding of how GME affects quality of care and patient outcomes is important, the authors argue. The focus of this article is primarily GME, yet similar challenges and solutions will be applicable to other areas of medical and health professions education as well.
Collapse
Affiliation(s)
- Alina Smirnova
- A. Smirnova is a PhD researcher, School of Health Professions Education, Department of Educational Development and Research, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands, and Professional Performance Research Group, Department of Medical Psychology, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands. S.S. Sebok-Syer is instructor, Department of Emergency Medicine, Stanford University School of Medicine, Palo Alto, California. S. Chahine is assistant professor and scientist, Centre for Educational Research and Innovation (CERI), Western University, London, Ontario, Canada. A.L. Kalet is professor of medicine and surgery, director of research on medical education outcomes (ROMEO), Unit of the Division of General Internal Medicine and Clinical Innovation, Department of Medicine, and director of research, Program on Medical Education and Technology, NYU School of Medicine, New York, New York. R. Tamblyn is professor, Department of Medicine and Department of Epidemiology and Biostatistics, McGill University, medical scientist, McGill University Health Center Research Institute, scientific director, Clinical and Health Informatics Research Group, McGill University, and scientific director, Canadian Institutes of Health Research-Institute of Health Services and Policy Research, Montreal, Quebec, Canada. K.M.J.M.H. Lombarts is professor and lead investigator, Professional Performance Research Group, Department of Medical Psychology, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands. C.P.M. van der Vleuten is professor and scientific director, School of Health Professions Education, Department of Educational Development and Research, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands. D.J. Schumacher is associate professor, Division of Emergency Medicine, and pediatric emergency physician, Cincinnati Children's Hospital Medical Center/University of Cincinnati College of Medicine, Cincinnati, Ohio
| | | | | | | | | | | | | | | |
Collapse
|
38
|
Brand JE, Moore R, Song X, Xie Y. Why Does Parental Divorce Lower Children's Educational Attainment? A Causal Mediation Analysis. SOCIOLOGICAL SCIENCE 2019; 6:264-292. [PMID: 31187049 PMCID: PMC6559749 DOI: 10.15195/v6.a11] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
Mechanisms explaining the negative effects of parental divorce on children's attainment have long been conjectured and assessed. Yet few studies of parental divorce have carefully attended to the assumptions and methods necessary to estimate causal mediation effects. Applying a causal framework to linked U.S. panel data, we assess the degree to which parental divorce limits children's education among whites and nonwhites and whether observed lower levels of educational attainment are explained by postdivorce family conditions and children's skills. Our analyses yield three key findings. First, the negative effect of divorce on educational attainment, particularly college, is substantial for white children; by contrast, divorce does not lower the educational attainment of nonwhite children. Second, declines in family income explain as much as one- to two-thirds of the negative effect of parental divorce on white children's education. Family instability also helps explain the effect, particularly when divorce occurs in early childhood. Children's psychosocial skills explain about one-fifth of the effect, whereas children's cognitive skills play a minimal role. Third, among nonwhites, the minimal total effect on education is explained by the offsetting influence of postdivorce declines in family income and stability alongside increases in children's psychosocial and cognitive skills.
Collapse
Affiliation(s)
- Jennie E Brand
- Departments of Sociology and Statistics, California Center for Population Research; and Center for Social Statistics.University of California, Los Angeles
| | - Ravaris Moore
- Department of Sociology, Loyola Marymount University
| | - Xi Song
- Department of Sociology, University of Chicago
| | - Yu Xie
- Department of Sociology, Princeton University
| |
Collapse
|
39
|
Arah OA. Commentary: Tobacco smoking and asthma: multigenerational effects, epigenetics and multilevel causal mediation analysis. Int J Epidemiol 2019; 47:1117-1119. [PMID: 30184137 DOI: 10.1093/ije/dyy193] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/15/2018] [Indexed: 11/13/2022] Open
Affiliation(s)
- Onyebuchi A Arah
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles (UCLA), Los Angeles, CA, USA.,Center for Health Policy Research, UCLA Fielding School of Public Health, Los Angeles, CA, USA.,California Center for Population Research, Los Angeles, CA, USA.,Department of Statistics, UCLA College of Letters and Science, Los Angeles, CA, USA
| |
Collapse
|
40
|
Young JC, Conover MM, Jonsson Funk M. Measurement Error and Misclassification in Electronic Medical Records: Methods to Mitigate Bias. CURR EPIDEMIOL REP 2018; 5:343-356. [PMID: 35633879 PMCID: PMC9141310 DOI: 10.1007/s40471-018-0164-x] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
PURPOSE OF REVIEW We sought to: 1) examine common sources of measurement error in research using data from electronic medical records (EMR), 2) discuss methods to assess the extent and type of measurement error, and 3) describe recent developments in methods to address this source of bias. RECENT FINDINGS We identified eight sources of measurement error frequently encountered in EMR studies, the most prominent being that EMR data usually reflect only the health services and medications delivered within the specific health facility/system contributing to the EMR data. Methods for assessing measurement error in EMR data usually require gold standard or validation data, which may be possible using data linkage. Recent methodological developments to address the impact of measurement error in EMR analyses were particularly rich in the multiple imputation literature. SUMMARY Presently, sources of measurement error impacting EMR studies are still being elucidated, as are methods for assessing and addressing them. Given the magnitude of measurement error that has been reported, investigators are urged to carefully evaluate and rigorously address this potential source of bias in studies based in EMR data.
Collapse
|
41
|
Smirnova A, Ravelli ACJ, Stalmeijer RE, Arah OA, Heineman MJ, van der Vleuten CPM, van der Post JAM, Lombarts KMJMH. The Association Between Learning Climate and Adverse Obstetrical Outcomes in 16 Nontertiary Obstetrics-Gynecology Departments in the Netherlands. ACADEMIC MEDICINE : JOURNAL OF THE ASSOCIATION OF AMERICAN MEDICAL COLLEGES 2017; 92:1740-1748. [PMID: 28953570 DOI: 10.1097/acm.0000000000001964] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
PURPOSE To investigate the association between learning climate and adverse perinatal and maternal outcomes in obstetrics-gynecology departments. METHOD The authors analyzed 23,629 births and 103 learning climate evaluations from 16 nontertiary obstetrics-gynecology departments in the Netherlands in 2013. Multilevel logistic regressions were used to calculate the odds of adverse perinatal and maternal outcomes, by learning climate score tertile, adjusting for maternal and department characteristics. Adverse perinatal outcomes included fetal or early neonatal mortality, five-minute Apgar score < 7, or neonatal intensive care unit admission for ≥ 24 hours. Adverse maternal outcomes included postpartum hemorrhage and/or transfusion, death, uterine rupture, or third- or fourth-degree perineal laceration. Bias analyses were conducted to quantify the sensitivity of the results to uncontrolled confounding and selection bias. RESULTS Learning climate scores were significantly associated with increased odds of adverse perinatal outcomes (aOR 2.06, 95% CI 1.14-3.72). Compared with the lowest tertile, departments in the middle tertile had 46% greater odds of adverse perinatal outcomes (aOR 1.46, 95% CI 1.09-1.94); departments in the highest tertile had 69% greater odds (aOR 1.69, 95% CI 1.24-2.30). Learning climate was not associated with adverse maternal outcomes (middle vs. lowest tertile: OR 1.04, 95% CI 0.93-1.16; highest vs. lowest tertile: OR 0.98, 95% CI 0.88-1.10). CONCLUSIONS Learning climate was associated with significantly increased odds of adverse perinatal, but not maternal, outcomes. Research in similar clinical contexts is needed to replicate these findings and explore potential mechanisms behind these associations.
Collapse
Affiliation(s)
- Alina Smirnova
- A. Smirnova is a PhD candidate, School of Health Professions Education, Department of Educational Development and Research, Faculty of Health, Medicine, and Life Sciences, Maastricht University, Maastricht, The Netherlands, and researcher, Professional Performance Research Group, Institute for Education and Training, Academic Medical Center, Amsterdam, The Netherlands. A.C.J. Ravelli is epidemiologist and assistant professor, Departments of Medical Informatics and Obstetrics and Gynecology, Academic Medical Center, Amsterdam, The Netherlands. R.E. Stalmeijer is assistant professor, Department of Educational Development and Research, Faculty of Health, Medicine, and Life Sciences, Maastricht University, Maastricht, The Netherlands. O.A. Arah is professor, Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, California. M.J. Heineman is professor, Board of Directors, Academic Medical Center, Amsterdam, The Netherlands. C.P.M. van der Vleuten is professor and scientific director, School of Health Professions Education, Department of Educational Development and Research, Faculty of Health, Medicine, and Life Sciences, Maastricht University, Maastricht, The Netherlands. J.A.M. van der Post is professor, Department of Obstetrics and Gynecology, Academic Medical Center, Amsterdam, The Netherlands. K.M.J.M.H. Lombarts is professor, Professional Performance Research Group, Institute for Education and Training, Academic Medical Center, Amsterdam, The Netherlands
| | | | | | | | | | | | | | | |
Collapse
|
42
|
Jackson JW, Schmid I, Stuart EA. Propensity Scores in Pharmacoepidemiology: Beyond the Horizon. CURR EPIDEMIOL REP 2017; 4:271-280. [PMID: 29456922 DOI: 10.1007/s40471-017-0131-y] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
Purpose of review Propensity score methods have become commonplace in pharmacoepidemiology over the past decade. Their adoption has confronted formidable obstacles that arise from pharmacoepidemiology's reliance on large healthcare databases of considerable heterogeneity and complexity. These include identifying clinically meaningful samples, defining treatment comparisons, and measuring covariates in ways that respect sound epidemiologic study design. Additional complexities involve correctly modeling treatment decisions in the face of variation in healthcare practice, and dealing with missing information and unmeasured confounding. In this review, we examine the application of propensity score methods in pharmacoepidemiology with particular attention to these and other issues, with an eye towards standards of practice, recent methodological advances, and opportunities for future progress. Recent findings Propensity score methods have matured in ways that can advance comparative effectiveness and safety research in pharmacoepidemiology. These include natural extensions for categorical treatments, matching algorithms that can optimize sample size given design constraints, weighting estimators that asymptotically target matched and overlap samples, and the incorporation of machine learning to aid in covariate selection and model building. Summary These recent and encouraging advances should be further evaluated through simulation and empirical studies, but nonetheless represent a bright path ahead for the observational study of treatment benefits and harms.
Collapse
Affiliation(s)
- John W Jackson
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205.,Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205
| | - Ian Schmid
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205
| | - Elizabeth A Stuart
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205.,Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205.,Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205
| |
Collapse
|
43
|
Krause N, Arah OA, Kauhanen J. Physical activity and 22-year all-cause and coronary heart disease mortality. Am J Ind Med 2017; 60:976-990. [PMID: 28940659 DOI: 10.1002/ajim.22756] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/25/2017] [Indexed: 11/10/2022]
Abstract
BACKGROUND This study explores the effects of occupational (OPA) and leisure time physical activity (LTPA) on mortality relative to cardiorespiratory fitness and pre-existing coronary heart disease (CHD). METHODS Associations between OPA, measured as energy expenditure (kcal/day) and relative aerobic workload (%VO2 max), LTPA, and 22-year mortality among 1891 Finnish men were assessed by Cox regression models stratified by CHD and adjusted for 19 confounders. RESULTS In fully adjusted models, each 10% of relative aerobic workload increased all-cause mortality by 13% and CHD mortality 28% (P < 0.01). Compared to healthy subjects, men with CHD experienced lower mortality risks due to OPA and higher risks due to LTPA. While LTPA had no effect among healthy men, in men with CHD each weekly hour of conditioning LTPA increased all-cause mortality risks by 10% and CHD mortality by14%. CONCLUSION OPA was positively associated with both all-cause and CHD mortality. LTPA was not protective. Among men with CHD, LTPA increased mortality risks.
Collapse
Affiliation(s)
- Niklas Krause
- Department of Environmental Health Sciences, Fielding School of Public Health; University of California; Los Angeles (UCLA) California
- Department of Epidemiology, Fielding School of Public Health; University of California; Los Angeles (UCLA) California
| | - Onyebuchi A. Arah
- Department of Epidemiology, Fielding School of Public Health; University of California; Los Angeles (UCLA) California
| | - Jussi Kauhanen
- Institute of Public Health and Clinical Nutrition; University of Eastern Finland; Kuopio Finland
| |
Collapse
|
44
|
Gebremariam MK, Lien N, Nianogo RA, Arah OA. Mediators of socioeconomic differences in adiposity among youth: a systematic review. Obes Rev 2017; 18:880-898. [PMID: 28434193 DOI: 10.1111/obr.12547] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2016] [Revised: 03/06/2017] [Accepted: 03/07/2017] [Indexed: 01/01/2023]
Abstract
BACKGROUND Youth with a low socioeconomic position in developed countries are at a disproportionately higher risk of being overweight or obese than their counterparts. Tackling these inequalities requires that the mechanisms behind them are well understood. OBJECTIVES The aim of this review was to summarize existing evidence regarding the factors that mediate or contribute to the explanation of the relationship between socioeconomic position and adiposity among youth. METHODS AND RESULTS A systematic literature search, conducted using the databases Medline, Embase, Web of Science and PsycINFO, yielded 28 eligible studies. These studies were of low to moderate methodological quality. The most consistent mediators of the association between socioeconomic position and adiposity identified in this review were as follows: consumption of sugar-sweetened beverages, television viewing, computer use, parental body mass index, breastfeeding duration, breakfast consumption, maternal smoking during pregnancy and infant feeding practices. The mediating role of physical activity as well as fruit and vegetable consumption was found to be indeterminate. Other potential mediators were explored in too few studies to make conclusions about their mediating role. CONCLUSION The review found several modifiable factors that could be targeted as feasible in interventions aimed at reducing socioeconomic differences in overweight and obesity among youth.
Collapse
Affiliation(s)
- M K Gebremariam
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles (UCLA), Los Angeles, California, USA.,Department of Nutrition, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - N Lien
- Department of Nutrition, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - R A Nianogo
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles (UCLA), Los Angeles, California, USA
| | - O A Arah
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles (UCLA), Los Angeles, California, USA.,UCLA Center for Health Policy Research, Los Angeles, California, USA.,California Center for Population Research, UCLA, Los Angeles, California, USA
| |
Collapse
|