Literature DB >> 29554199

Relative Performance of Propensity Score Matching Strategies for Subgroup Analyses.

Shirley V Wang1, Yinzhu Jin1, Bruce Fireman2, Susan Gruber3, Mengdong He1, Richard Wyss1, HoJin Shin3, Yong Ma4, Stephine Keeton4, Sara Karami5, Jacqueline M Major5, Sebastian Schneeweiss1, Joshua J Gagne1.   

Abstract

Postapproval drug safety studies often use propensity scores (PSs) to adjust for a large number of baseline confounders. These studies may involve examining whether treatment safety varies across subgroups. There are many ways a PS could be used to adjust for confounding in subgroup analyses. These methods have trade-offs that are not well understood. We conducted a plasmode simulation to compare relative performance of 5 methods involving PS matching for subgroup analysis, including methods frequently used in applied literature whose performance has not been previously directly compared. These methods varied as to whether the overall PS, subgroup-specific PS, or no rematching was used in subgroup analysis as well as whether subgroups were fully nested within the main analytical cohort. The evaluated PS subgroup matching methods performed similarly in terms of balance, bias, and precision in 12 simulated scenarios varying size of the cohort, prevalence of exposure and outcome, strength of relationships between baseline covariates and exposure, the true effect within subgroups, and the degree of confounding within subgroups. Each had strengths and limitations with respect to other performance metrics that could inform choice of method.

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Year:  2018        PMID: 29554199     DOI: 10.1093/aje/kwy049

Source DB:  PubMed          Journal:  Am J Epidemiol        ISSN: 0002-9262            Impact factor:   4.897


  13 in total

1.  Association Between Gabapentin Receipt for Any Indication and Alcohol Use Disorders Identification Test-Consumption Scores Among Clinical Subpopulations With and Without Alcohol Use Disorder.

Authors:  Christopher T Rentsch; David A Fiellin; Kendall J Bryant; Amy C Justice; Janet P Tate
Journal:  Alcohol Clin Exp Res       Date:  2019-02-03       Impact factor: 3.455

Review 2.  A Review of Causal Inference for External Comparator Arm Studies.

Authors:  Gerd Rippin; Nicolás Ballarini; Héctor Sanz; Joan Largent; Chantal Quinten; Francesco Pignatti
Journal:  Drug Saf       Date:  2022-07-27       Impact factor: 5.228

3.  SGLT2 Inhibitors and the Risk of Acute Kidney Injury in Older Adults With Type 2 Diabetes.

Authors:  Min Zhuo; Julie M Paik; Deborah J Wexler; Joseph V Bonventre; Seoyoung C Kim; Elisabetta Patorno
Journal:  Am J Kidney Dis       Date:  2021-11-08       Impact factor: 11.072

4.  Using primary care data to assess comparative effectiveness and safety of apixaban and rivaroxaban in patients with nonvalvular atrial fibrillation in the UK: an observational cohort study.

Authors:  Ashley Jaksa; Liza Gibbs; Seamus Kent; Shaun Rowark; Stephen Duffield; Manuj Sharma; Lynne Kincaid; Ayad K Ali; Amanda R Patrick; Priya Govil; Pall Jonsson; Nicolle Gatto
Journal:  BMJ Open       Date:  2022-10-17       Impact factor: 3.006

5.  Effect of empirical antifungal treatment on mortality in non-neutropenic critically ill patients: a propensity-matched retrospective cohort study.

Authors:  Yue Tang; Wenjing Hu; Shuangyan Jiang; Maoyu Xie; Wenying Zhu; Lin Zhang; Jing Sha; Tengfei Wang; Min Ding; Juan Zeng; Jinjiao Jiang
Journal:  Eur J Clin Microbiol Infect Dis       Date:  2022-10-18       Impact factor: 5.103

6.  The Magnitude of the Warfarin-Amiodarone Drug-Drug Interaction Varies With Renal Function: A Propensity-Matched Cohort Study.

Authors:  Todd A Miano; Wei Yang; Michael G S Shashaty; Athena Zuppa; Jeremiah R Brown; Sean Hennessy
Journal:  Clin Pharmacol Ther       Date:  2020-03-26       Impact factor: 6.875

7.  Recommendations for the use of propensity score methods in multiple sclerosis research.

Authors:  Gabrielle Simoneau; Fabio Pellegrini; Thomas Pa Debray; Julie Rouette; Johanna Muñoz; Robert W Platt; John Petkau; Justin Bohn; Changyu Shen; Carl de Moor; Mohammad Ehsanul Karim
Journal:  Mult Scler       Date:  2022-04-06       Impact factor: 5.855

Review 8.  Propensity Score Methods in Health Technology Assessment: Principles, Extended Applications, and Recent Advances.

Authors:  M Sanni Ali; Daniel Prieto-Alhambra; Luciane Cruz Lopes; Dandara Ramos; Nivea Bispo; Maria Y Ichihara; Julia M Pescarini; Elizabeth Williamson; Rosemeire L Fiaccone; Mauricio L Barreto; Liam Smeeth
Journal:  Front Pharmacol       Date:  2019-09-18       Impact factor: 5.810

9.  Association between aspirin use and cardiovascular outcomes in ALLHAT participants with and without chronic kidney disease: A post hoc analysis.

Authors:  Niraj Desai; Brigid Wilson; Michael Bond; Alexander Conant; Mahboob Rahman
Journal:  J Clin Hypertens (Greenwich)       Date:  2020-12-19       Impact factor: 3.738

10.  The effect of the underlying malignancy on short- and medium-term survival of critically ill patients admitted to the intensive care unit: a retrospective analysis based on propensity score matching.

Authors:  Zhen-Nan Yuan; Hai-Jun Wang; Yong Gao; Shi-Ning Qu; Chu-Lin Huang; Hao Wang; Hao Zhang; Quan-Hui Yang; Xue-Zhong Xing
Journal:  BMC Cancer       Date:  2021-04-15       Impact factor: 4.430

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