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Talebi AH, Darweesh SKL, Bloem BR, Bucur IG, Heskes T. Effect of Early Levodopa Treatment on Mortality in People with Parkinson's Disease. Mov Disord Clin Pract 2024. [PMID: 39091192 DOI: 10.1002/mdc3.14174] [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: 12/11/2023] [Revised: 06/24/2024] [Accepted: 07/09/2024] [Indexed: 08/04/2024] Open
Abstract
BACKGROUND The ideal timing for initiating levodopa in newly diagnosed people with Parkinson's disease (PD) is uncertain due to limited data on the long-term effects of levodopa. OBJECTIVE The aim was to investigate whether early levodopa initiation postpones mortality (primary outcome), the requirement of device-aided therapies, and the incidence of PD-related complications, such as fall-induced injuries. METHODS Using nationwide claims data from Dutch hospitals (2012-2020), we grouped newly diagnosed PD individuals as "early initiators" (initiating levodopa within 2 years of diagnosis) or "nonearly initiators." We used the national death registry to assess mortality and health-care claims to assess PD-related complications and device-aided therapies. We used marginal structural models to compare mortality and device-aided therapy rates between groups, and a Poisson regression model to compare PD-related complication rates. RESULTS Among 29,943 newly diagnosed PD individuals (mean age at diagnosis: 71.6, 38.5% female), there were 24,847 early and 5096 nonearly levodopa initiators. Over a median 4.25 years, 8109 (27.1%) died. The causal risk ratio for mortality was 1.04 (95% confidence interval [CI] 0.92-1.19) for early versus nonearly initiators. The risk ratio of receiving any device-aided therapy was 3.19 (95% CI 2.56-5.80). No association was observed with incidence of PD-related complications (incidence rate ratio: 1.00, 95% CI 0.96-1.05). CONCLUSIONS Early levodopa initiation in PD does neither postpone nor accelerate mortality or PD-related complications, nor does it precipitate earlier occurrence of PD-related complications or mortality. However, we cannot exclude that the results were influenced by residual confounding due to unmeasured risk factors of mortality.
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Affiliation(s)
- Amir H Talebi
- Radboud University Medical Centre, Donders Institute for Brain, Cognition and Behaviour, Department of Neurology, Center of Expertise for Parkinson & Movement Disorders, Nijmegen, The Netherlands
| | - Sirwan K L Darweesh
- Radboud University Medical Centre, Donders Institute for Brain, Cognition and Behaviour, Department of Neurology, Center of Expertise for Parkinson & Movement Disorders, Nijmegen, The Netherlands
| | - Bas R Bloem
- Radboud University Medical Centre, Donders Institute for Brain, Cognition and Behaviour, Department of Neurology, Center of Expertise for Parkinson & Movement Disorders, Nijmegen, The Netherlands
| | - Ioan G Bucur
- Data Science Research Department, Institute for Computing and Information Sciences, Radboud University, Nijmegen, The Netherlands
| | - Tom Heskes
- Data Science Research Department, Institute for Computing and Information Sciences, Radboud University, Nijmegen, The Netherlands
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Couchoud C, Raffray M, Lassalle M, Duisenbekov Z, Moranne O, Erbault M, Lazareth H, Parmentier C, Guebre-Egziabher F, Hamroun A, Metzger M, Mansouri I, Goldberg M, Zins M, Bayat-Makoei S, Kab S. Prevalence of chronic kidney disease in France: methodological considerations and pitfalls with the use of Health claims databases. Clin Kidney J 2024; 17:sfae117. [PMID: 38774439 PMCID: PMC11106789 DOI: 10.1093/ckj/sfae117] [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: 12/19/2023] [Indexed: 05/24/2024] Open
Abstract
Background Health policy-making require careful assessment of chronic kidney disease (CKD) epidemiology to develop efficient and cost-effective care strategies. The aim of the present study was to use the RENALGO-EXPERT algorithm to estimate the global prevalence of CKD in France. Methods An expert group developed the RENALGO-EXPERT algorithm based on healthcare consumption. This algorithm has been applied to the French National Health claims database (SNDS), where no biological test findings are available to estimate a national CKD prevalence for the years 2018-2021. The CONSTANCES cohort (+219 000 adults aged 18-69 with one CKD-EPI eGFR) was used to discuss the limit of using health claims data. Results Between 2018 and 2021, the estimated prevalence in the SNDS increased from 8.1% to 10.5%. The RENALGO-EXPERT algorithm identified 4.5% of the volunteers in the CONSTANCES as CKD. The RENALGO-EXPERT algorithm had a positive predictive value of 6.2% and negative predictive value of 99.1% to detect an eGFR<60 ml/min/1.73 m². Half of 252 false positive cases (ALGO+, eGFR > 90) had been diagnosed with kidney disease during hospitalization, and the other half based on healthcare consumption suggestive of a 'high-risk' profile; 95% of the 1661 false negatives (ALGO-, eGFR < 60) had an eGFR between 45 and 60 ml/min, half had medication and two-thirds had biological exams possibly linked to CKD. Half of them had a hospital stay during the period but none had a diagnosis of kidney disease. Conclusions Our result is in accordance with other estimations of CKD prevalence in the general population. Analysis of diverging cases (FP and FN) suggests using health claims data have inherent limitations. Such an algorithm can identify patients whose care pathway is close to the usual and specific CKD pathways. It does not identify patients who have not been diagnosed or whose care is inappropriate or at early stage with stable GFR.
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Affiliation(s)
- Cécile Couchoud
- Réseau Epidémiologie et Information en Néphrologie, Agence de la Biomédecine, Saint-Denis-La-Plaine, France
| | - Maxime Raffray
- Univ. Rennes, EHESP, CNRS, Inserm, Arènes - UMR 6051, RSMS (Recherche sur les Services et Management en Santé)- U 1309 – Rennes, France
| | - Mathilde Lassalle
- Réseau Epidémiologie et Information en Néphrologie, Agence de la Biomédecine, Saint-Denis-La-Plaine, France
| | - Zhanibek Duisenbekov
- Réseau Epidémiologie et Information en Néphrologie, Agence de la Biomédecine, Saint-Denis-La-Plaine, France
| | - Olivier Moranne
- Service Néphrologie-Dialyse-Apherese, Hôpital Universitaire Caremau, Nîmes, IDESP Université de Montpellier, France
| | - Marie Erbault
- Haute Autorité de Santé, Saint-Denis-La-Plaine, France
| | | | | | - Fitsum Guebre-Egziabher
- Service Néphrologie-Dialyse-Aphérèse-Hypertension, Hôpital Edouard Herriot, Hospices Civils de Lyon, Université Lyon-1 INSERM U 1060, Lyon, France
| | - Aghiles Hamroun
- Department of Public Health – Epidemiology, Department of Nephrology, Lille University Hospital Center, RIDAGE, Pasteur Institute of Lille, Inserm, Lille University, Lille, France
| | - Marie Metzger
- Center for Research in Epidemiology and Population Health, Paris-Saclay University, Paris-Sud University, Versailles Saint Quentin University, Inserm, Villejuif, France
| | - Imene Mansouri
- Direction Procréation, Embryologie et Génétique Humaine, Agence de la Biomédecine, Saint-Denis-La-Plaine, France
| | | | - Maris Zins
- Cohorte CONSTANCES, Inserm UMS11, Villejuif, France
| | - Sahar Bayat-Makoei
- Univ. Rennes, EHESP, CNRS, Inserm, Arènes - UMR 6051, RSMS (Recherche sur les Services et Management en Santé)- U 1309 – Rennes, France
| | - Sofiane Kab
- Cohorte CONSTANCES, Inserm UMS11, Villejuif, France
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Stolwijk ML, van Nispen RMA, van der Pas SL, van Rens GHMB. A retrospective big data study using healthcare insurance claims to investigate the role of comorbidities in receiving low vision services. FRONTIERS IN HEALTH SERVICES 2024; 4:1264838. [PMID: 38500632 PMCID: PMC10944930 DOI: 10.3389/frhs.2024.1264838] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Accepted: 02/19/2024] [Indexed: 03/20/2024]
Abstract
Introduction The aim was to examine the association between physical and mental comorbidity with receiving low vision services (LVS). Methods A retrospective study based on Dutch claims data of health insurers was performed. We retrieved data (2015-2018) of patients (≥18 years) with eye diseases causing severe vision loss who received LVS at Dutch rehabilitation organizations in 2018 (target group) and patients who did not receive LVS, but who received ophthalmic medical specialist care for glaucoma, macular, diabetic retinal and/or retinal diseases in 2018 (reference group). For examining the association between the patients' comorbidities and receiving LVS, multivariable logistic regression was used. The relative quality of five different models was assessed with the Akaike Information Criterion (AIC). Results The study population consisted of 574,262 patients, of which 8,766 in the target group and 565,496 in the reference group. Physical comorbidity was found in 83% and 14% had mental comorbidity. After adjustment for all assumed confounders, both physical and mental comorbidity remained significantly associated with receiving LVS. In the adjusted model, which also included both comorbidity variables, the best relative quality was found to describe the association between mental and physical comorbidity and receiving LVS. Conclusions Mental comorbidity seemed to be independently associated with receiving LVS, implying that the odds for receiving a LVS referral are higher in patients who are vulnerable to mental comorbidity. Physical comorbidity was independently associated, however, the association with receiving LVS might not be that meaningful in terms of policy implications. Providing mental healthcare interventions for people with VI seems warranted.
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Affiliation(s)
- M. L. Stolwijk
- Department of Ophthalmology, Amsterdam UMC, Vrije Universiteit, Amsterdam, Netherlands
- Quality of Care, Amsterdam Public Health, Amsterdam, Netherlands
| | - R. M. A. van Nispen
- Department of Ophthalmology, Amsterdam UMC, Vrije Universiteit, Amsterdam, Netherlands
- Quality of Care, Amsterdam Public Health, Amsterdam, Netherlands
| | - S. L. van der Pas
- Department of Epidemiology and Data Science, Amsterdam UMC, Vrije Universiteit, Amsterdam, Netherlands
- Methodology, Amsterdam Public Health, Amsterdam, Netherlands
| | - G. H. M. B. van Rens
- Department of Ophthalmology, Amsterdam UMC, Vrije Universiteit, Amsterdam, Netherlands
- Quality of Care, Amsterdam Public Health, Amsterdam, Netherlands
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Bothe T, Fietz AK, Schaeffner E, Douros A, Pöhlmann A, Mielke N, Villain C, Barghouth MH, Wenning V, Ebert N. Diagnostic Validity of Chronic Kidney Disease in Health Claims Data Over Time: Results from a Cohort of Community-Dwelling Older Adults in Germany. Clin Epidemiol 2024; 16:143-154. [PMID: 38410416 PMCID: PMC10895982 DOI: 10.2147/clep.s438096] [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: 09/14/2023] [Accepted: 12/15/2023] [Indexed: 02/28/2024] Open
Abstract
Purpose The validity of ICD-10 diagnostic codes for chronic kidney disease (CKD) in health claims data has not been sufficiently studied in the general population and over time. Patients and Methods We used data from the Berlin Initiative Study (BIS), a prospective longitudinal cohort of community-dwelling individuals aged ≥70 years in Berlin, Germany. With estimated glomerular filtration rate (eGFR) as reference, we assessed the diagnostic validity (sensitivity, specificity, positive [PPV], and negative predictive values [NPV]) of different claims-based ICD-10 codes for CKD stages G3-5 (eGFR <60mL/min/1.73m²: ICD-10 N18.x-N19), G3 (eGFR 30-<60mL/min/1.73m²: N18.3), and G4-5 (eGFR <30mL/min/1.73m²: N18.4-5). We analysed trends over five study visits (2009-2019). Results We included data of 2068 participants at baseline (2009-2011) and 870 at follow-up 4 (2018-2019), of whom 784 (38.9%) and 440 (50.6%) had CKD G3-5, respectively. At baseline, sensitivity for CKD in claims data ranged from 0.25 (95%-confidence interval [CI] 0.22-0.28) to 0.51 (95%-CI 0.48-0.55) for G3-5, depending on the included ICD-10 codes, 0.20 (95%-CI 0.18-0.24) for G3, and 0.36 (95%-CI 0.25-0.49) for G4-5. Over the course of 10 years, sensitivity increased by 0.17 to 0.29 in all groups. Specificity, PPVs, and NPVs remained mostly stable over time and ranged from 0.82-0.99, 0.47-0.89, and 0.66-0.98 across all study visits, respectively. Conclusion German claims data showed overall agreeable performance in identifying older adults with CKD, while differentiation between stages was limited. Our results suggest increasing sensitivity over time possibly attributable to improved CKD diagnosis and awareness.
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Affiliation(s)
- Tim Bothe
- Institute of Public Health, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Anne-Katrin Fietz
- Institute of Biometry and Clinical Epidemiology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Elke Schaeffner
- Institute of Public Health, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Antonios Douros
- Departments of Medicine and of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, QC, Canada
- Institute of Clinical Pharmacology and Toxicology, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Center for Clinical Epidemiology, Lady Davis Institute, Jewish General Hospital, Montreal, QC, Canada
| | - Anna Pöhlmann
- Institute of Biometry and Clinical Epidemiology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Nina Mielke
- Institute of Public Health, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Cédric Villain
- Institute of Public Health, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Normandie Univ UNICAEN, INSERM U1075 COMETE, service de Gériatrie, CHU de Caen, Caen, France
| | | | | | - Natalie Ebert
- Institute of Public Health, Charité - Universitätsmedizin Berlin, Berlin, Germany
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Carrero JJ, Fu EL, Vestergaard SV, Jensen SK, Gasparini A, Mahalingasivam V, Bell S, Birn H, Heide-Jørgensen U, Clase CM, Cleary F, Coresh J, Dekker FW, Gansevoort RT, Hemmelgarn BR, Jager KJ, Jafar TH, Kovesdy CP, Sood MM, Stengel B, Christiansen CF, Iwagami M, Nitsch D. Defining measures of kidney function in observational studies using routine health care data: methodological and reporting considerations. Kidney Int 2023; 103:53-69. [PMID: 36280224 DOI: 10.1016/j.kint.2022.09.020] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Revised: 08/31/2022] [Accepted: 09/09/2022] [Indexed: 11/06/2022]
Abstract
The availability of electronic health records and access to a large number of routine measurements of serum creatinine and urinary albumin enhance the possibilities for epidemiologic research in kidney disease. However, the frequency of health care use and laboratory testing is determined by health status and indication, imposing certain challenges when identifying patients with kidney injury or disease, when using markers of kidney function as covariates, or when evaluating kidney outcomes. Depending on the specific research question, this may influence the interpretation, generalizability, and/or validity of study results. This review illustrates the heterogeneity of working definitions of kidney disease in the scientific literature and discusses advantages and limitations of the most commonly used approaches using 3 examples. We summarize ways to identify and overcome possible biases and conclude by proposing a framework for reporting definitions of exposures and outcomes in studies of kidney disease using routinely collected health care data.
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Affiliation(s)
- Juan Jesus Carrero
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden.
| | - Edouard L Fu
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden; Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA; Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Søren V Vestergaard
- Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark; Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Simon Kok Jensen
- Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark; Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Alessandro Gasparini
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden
| | - Viyaasan Mahalingasivam
- Department of Non-communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | - Samira Bell
- Division of Population Health and Genomics, University of Dundee, Dundee, UK
| | - Henrik Birn
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark; Department of Biomedicine, Aarhus University, Aarhus, Denmark; Department of Renal Medicine, Aarhus University Hospital, Aarhus, Denmark
| | - Uffe Heide-Jørgensen
- Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark; Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Catherine M Clase
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada; Department of Health Research and Methodology, McMaster University, Hamilton, Ontario, Canada
| | - Faye Cleary
- Department of Non-communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | - Josef Coresh
- Department of Epidemiology, Johns Hopkins University, Baltimore, Maryland, USA
| | - Friedo W Dekker
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Ron T Gansevoort
- Department of Nephrology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | | | - Kitty J Jager
- ERA Registry, Amsterdam UMC location University of Amsterdam, Medical Informatics, Meibergdreef, Amsterdam, Netherlands; Amsterdam Public Health Research Institute, Quality of Care, Amsterdam, the Netherlands
| | - Tazeen H Jafar
- Program in Health Services and Systems Research, Duke-NUS Medical School, Singapore
| | - Csaba P Kovesdy
- Division of Nephrology, Department of Medicine, University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Manish M Sood
- Department of Medicine, the Ottawa Hospital Research Institute, University of Ottawa, Ottawa, Ontario, Canada
| | - Bénédicte Stengel
- CESP (Center for Research in Epidemiology and Population Health), Clinical Epidemiology Team, University Paris-Saclay, University Versailles-Saint Quentin, Inserm U1018, Villejuif, France
| | - Christian F Christiansen
- Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark; Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Masao Iwagami
- Department of Non-communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK; Department of Health Services Research, University of Tsukuba, Ibaraki, Japan
| | - Dorothea Nitsch
- Department of Non-communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK; Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand; UK Renal Registry, UK Kidney Association, Bristol, UK.
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Mansouri I, Raffray M, Lassalle M, de Vathaire F, Fresneau B, Fayech C, Lazareth H, Haddy N, Bayat S, Couchoud C. An algorithm for identifying chronic kidney disease in the French national health insurance claims database. Nephrol Ther 2022; 18:255-262. [DOI: 10.1016/j.nephro.2022.03.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Accepted: 03/11/2022] [Indexed: 10/17/2022]
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van Oosten MJM, Logtenberg SJJ, Hemmelder MH, Leegte MJH, Bilo HJG, Jager KJ, Stel VS. Polypharmacy and medication use in patients with chronic kidney disease with and without kidney replacement therapy compared to matched controls. Clin Kidney J 2021; 14:2497-2523. [PMID: 34950462 PMCID: PMC8690067 DOI: 10.1093/ckj/sfab120] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Revised: 04/16/2021] [Accepted: 04/20/2021] [Indexed: 12/12/2022] Open
Abstract
Background This study aims to examine polypharmacy (PP) prevalence in patients with chronic kidney disease (CKD) Stage G4/G5 and patients with kidney replacement therapy (KRT) compared with matched controls from the general population. Furthermore, we examine risk factors for PP and describe the most commonly dispensed medications. Methods Dutch health claims data were used to identify three patient groups: CKD Stage G4/G5, dialysis and kidney transplant patients. Each patient was matched to two controls based on age, sex and socio-economic status (SES) score. We differentiated between ‘all medication use’ and ‘chronic medication use’. PP was defined at three levels: use of ≥5 medications (PP), ≥10 medications [excessive PP (EPP)] and ≥15 medications [hyper PP (HPP)]. Results The PP prevalence for all medication use was 87, 93 and 95% in CKD Stage G4/G5, dialysis and kidney transplant patients, respectively. For chronic medication use, this was 66, 70 and 75%, respectively. PP and comorbidity prevalence were higher in patients than in controls. EPP was 42 times more common in young CKD Stage G4/G5 patients (ages 20–44 years) than in controls, while this ratio was 3.8 in patients ≥75 years. Older age (64–75 and ≥75 years) was a risk factor for PP in CKD Stage G4/G5 and kidney transplant patients. Dialysis patients ≥75 years of age had a lower risk of PP compared with their younger counterparts. Additional risk factors in all patients were low SES, diabetes mellitus, vascular disease, hospitalization and an emergency room visit. The most commonly dispensed medications were proton pump inhibitors (PPIs) and statins. Conclusions CKD Stage G4/G5 patients and patients on KRT have a high medication burden, far beyond that of individuals from the general population, as a result of their kidney disease and a large burden of comorbidities. A critical approach to medication prescription in general, and of specific medications like PPIs and statins (in the dialysis population), could be a first step towards more appropriate medication use.
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Affiliation(s)
- Manon J M van Oosten
- Department of Medical Informatics, Amsterdam UMC, University of Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | | | - Marc H Hemmelder
- Division of Nephrology, Department of Internal Medicine, Maastricht University Medical Center, The Netherlands
| | | | - Henk J G Bilo
- Diabetes Research Center and Department of Epidemiology and Statistics, Isala Hospital, Zwolle, The Netherlands
| | - Kitty J Jager
- Department of Medical Informatics, Amsterdam UMC, University of Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Vianda S Stel
- Department of Medical Informatics, Amsterdam UMC, University of Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
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