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Kelly T, Salter A, Pratt NL. The weighted cumulative exposure method and its application to pharmacoepidemiology: A narrative review. Pharmacoepidemiol Drug Saf 2024; 33:e5701. [PMID: 37749615 PMCID: PMC10952599 DOI: 10.1002/pds.5701] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 08/15/2023] [Accepted: 09/12/2023] [Indexed: 09/27/2023]
Abstract
PURPOSE The weighted cumulative exposure (WCE) method has been used in a number of fields including pharmacoepidemiology where it can account for intensity, duration and timing of exposures on the risk of an outcome. The method uses a data driven approach with flexible cubic B-splines to assign weights to past doses and select an aetiologically appropriate time window. Predictions of risk are possible for common exposure patterns encountered in real-world studies. The purpose of this study was to describe applications of the WCE method to pharmacoepidemiology and assess the strengths and limitations of the method. METHOD A literature search was undertaken to find studies applying the WCE method to the study of medicines. Articles published in PubMed using the search term 'weighted cumulative exposure' and articles citing Sylvestre et al. (2009) in Google Scholar or Scopus up to March 2023 were subsequently reviewed. Articles were selected based on title and review of abstracts. RESULTS Seventeen clinical applications using the data-driven WCE method with flexible cubic splines were identified in the review. These included 3 case-control studies and 14 cohort studies, of which 12 were analysed with Cox proportional hazards models and 2 with logistic regression. Thirteen studies used time windows of 1 year or longer. Of 11 studies which compared conventional models with the WCE method, 10 (91%) studies found a better fit with WCE models while one had an equivalent fit. The freely available 'WCE' software package has facilitated the applications of the WCE method with flexible cubic splines. CONCLUSIONS The WCE method allows additional insights into the effect of cumulative exposure on outcomes, including the timing and intensity (dose) of the exposure on the risk. The flexibility of the method is particularly well suited to studies with long-term exposures that vary over time or where the current risk of an event is affected by how far the exposure is in the past, which is difficult to model with conventional definitions of exposure. Interpretation of the results can be more complex than for conventional models and would be facilitated by a standardised reporting framework.
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Affiliation(s)
- Thu‐Lan Kelly
- Quality Use of Medicines and Pharmacy Research Centre, Clinical and Health SciencesUniversity of South AustraliaAdelaideAustralia
| | - Amy Salter
- School of Public HealthThe University of AdelaideAdelaideAustralia
| | - Nicole L. Pratt
- Quality Use of Medicines and Pharmacy Research Centre, Clinical and Health SciencesUniversity of South AustraliaAdelaideAustralia
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Danieli C, Moura CS, Pilote L, Bernatsky S, Abrahamowicz M. Importance of accounting for timing of time-varying exposures in association studies: Hydrochlorothiazide and non-melanoma skin cancer. Pharmacoepidemiol Drug Saf 2023; 32:1411-1420. [PMID: 37528702 DOI: 10.1002/pds.5674] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 07/14/2023] [Accepted: 07/19/2023] [Indexed: 08/03/2023]
Abstract
PURPOSE Hydrochlorothiazide (HCTZ), a widely prescribed antihypertensive drug with photosensitising properties, has been linked with non-melanoma skin cancer (NMSC) risk. However, previous analyses did not fully explore if and how the impact of past HCTZ exposures accumulates with prolonged use and/or depends on time elapsed since exposures. Therefore, we used different models to more comprehensively assess how NMSC risk vary with HCTZ exposure, and explore how the results may depend on modeling strategies. METHODS We used different parametric models with alternative time-varying exposure metrics, and the flexible weighted cumulative exposure model (WCE) to estimate associations between HCTZ exposures and NMSC risk in a population-based cohort of HCTZ users over 65 years old, in the province of Ontario, Canada. RESULTS Among 3844 HCTZ users, 273 developed NMSC during up to 8 years of follow-up. In parametric models, based on all exposures, increased duration of past HCTZ use was associated with an increase of NMSC risk but cumulative dose showed no systematic association. Yet, WCE results suggested that only exposures taken 2.5-4 years in the past were associated with the current NMSC hazard. This finding led us to re-define the parametric models, which also confirmed that any HCTZ dose taken outside this time-window were not systematically associated with NMSC incidence. CONCLUSIONS Our analyses illustrate how flexible modeling may yield new insights into complex temporal relationships between a time-varying drug exposure and risks of adverse events. Duration and recency of antihypertensive agents exposures must be taken into account in evaluating risk and benefits.
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Affiliation(s)
- Coraline Danieli
- Centre for Outcomes Research and Evaluation and Division of Clinical Epidemiology, McGill University Health Centre, Montreal, Québec, Canada
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Québec, Canada
| | - Cristiano S Moura
- Centre for Outcomes Research and Evaluation and Division of Clinical Epidemiology, McGill University Health Centre, Montreal, Québec, Canada
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Québec, Canada
| | - Louise Pilote
- Centre for Outcomes Research and Evaluation and Division of Clinical Epidemiology, McGill University Health Centre, Montreal, Québec, Canada
- Division of General Internal Medicine, McGill University Health Center, Montreal, Québec, Canada
| | - Sasha Bernatsky
- Centre for Outcomes Research and Evaluation and Division of Clinical Epidemiology, McGill University Health Centre, Montreal, Québec, Canada
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Québec, Canada
- Division of Rheumatology, McGill University Health Center, Montreal, Québec, Canada
| | - Michal Abrahamowicz
- Centre for Outcomes Research and Evaluation and Division of Clinical Epidemiology, McGill University Health Centre, Montreal, Québec, Canada
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Québec, Canada
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Dankner R, Agay N, Olmer L, Murad H, Keinan Boker L, Balicer RD, Freedman LS. Metformin Treatment and Cancer Risk: Cox Regression Analysis, With Time-Dependent Covariates, of 320,000 Persons With Incident Diabetes Mellitus. Am J Epidemiol 2019; 188:1794-1800. [PMID: 31269196 PMCID: PMC6768811 DOI: 10.1093/aje/kwz157] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2019] [Revised: 06/14/2019] [Accepted: 06/18/2019] [Indexed: 12/15/2022] Open
Abstract
There is conflicting evidence regarding the association between metformin use and cancer risk in diabetic patients. During 2002–2012, we followed a cohort of 315,890 persons aged 21–87 years with incident diabetes who were insured by the largest health maintenance organization in Israel. We used a discrete form of weighted cumulative metformin exposure to evaluate the association of metformin with cancer incidence. This was implemented in a time-dependent covariate Cox model, adjusting for treatment with other glucose-lowering medications, as well as age, sex, ethnic background, socioeconomic status, smoking (for bladder and lung cancer), and parity (for breast cancer). We excluded from the analysis metformin exposure during the year before cancer diagnosis in order to minimize reverse causation of cancer on changes in medication use. Estimated hazard ratios associated with exposure to 1 defined daily dose of metformin over the previous 2–7 years were 0.98 (95% confidence interval (CI): 0.82, 1.18) for all-sites cancer (excluding prostate and pancreas), 1.05 (95% CI: 0.67, 1.63) for colon cancer, 0.98 (95% CI: 0.49, 1.97) for bladder cancer, 1.02 (95% CI: 0.59, 1.78) for lung cancer, and 0.88 (95% CI: 0.56, 1.39) for female breast cancer. Our results do not support an association between metformin treatment and the incidence of major cancers (excluding prostate and pancreas).
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Affiliation(s)
- Rachel Dankner
- Unit for Cardiovascular Epidemiology, Gertner Institute for Epidemiology and Health Policy Research, Sheba Medical Center, Ramat Gan, Israel
- Department of Epidemiology and Preventive Medicine, Sackler Faculty of Medicine, School of Public Health, Tel Aviv University, Tel Aviv, Israel
- Center for Patient-Oriented Research, Feinstein Institute for Medical Research, Manhasset, New York
| | - Nirit Agay
- Unit for Cardiovascular Epidemiology, Gertner Institute for Epidemiology and Health Policy Research, Sheba Medical Center, Ramat Gan, Israel
| | - Liraz Olmer
- Unit of Biostatistics and Biomathematics, Gertner Institute for Epidemiology and Health Policy Research, Sheba Medical Center, Ramat Gan, Israel
| | - Havi Murad
- Unit of Biostatistics and Biomathematics, Gertner Institute for Epidemiology and Health Policy Research, Sheba Medical Center, Ramat Gan, Israel
| | - Lital Keinan Boker
- Israel Center for Disease Control, Israel Ministry of Health, Ramat Gan, Israel
- School of Public Health, Faculty of Social Welfare and Health Sciences, Haifa University, Haifa, Israel
| | - Ran D Balicer
- Clalit Health Services, Clalit Research Institute, Tel Aviv, Israel
- Public Health Department, Ben Gurion University of the Negev, Be’er Sheva, Israel
| | - Laurence S Freedman
- Department of Epidemiology and Preventive Medicine, Sackler Faculty of Medicine, School of Public Health, Tel Aviv University, Tel Aviv, Israel
- Unit of Biostatistics and Biomathematics, Gertner Institute for Epidemiology and Health Policy Research, Sheba Medical Center, Ramat Gan, Israel
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