Greedy caliper propensity score matching can yield variable estimates of the treatment-outcome association-A simulation study

被引:12
作者
Komen, Joris J. [1 ,2 ]
Belitser, Svetlana V. [1 ]
Wyss, Richard [3 ,4 ]
Schneeweiss, Sebastian [3 ,4 ]
Taams, Anne C. [1 ]
Pajouheshnia, Romin [1 ]
Forslund, Tomas [2 ,5 ]
Klungel, Olaf H. [1 ]
机构
[1] Univ Utrecht, Utrecht Inst Pharmaceut Sci, Div Pharmacoepidemiol & Clin Pharmacol, Univ Weg 99, NL-3584 CG Utrecht, Netherlands
[2] Stockholm Cty Council, Publ Healthcare Serv Comm, Dept Healthcare Dev, Stockholm, Sweden
[3] Brigham & Womens Hosp, Dept Med, Div Pharmacoepidemiol & Pharmacoecon, 75 Francis St, Boston, MA 02115 USA
[4] Harvard Med Sch, Boston, MA 02115 USA
[5] Karolinska Inst, Dept Med Solna, Clin Epidmiol, Clin Pharmacol, Stockholm, Sweden
关键词
greedy; matching; caliper matching; nearest neighbor matching; pharmacoepidemiology; propensity score; simulation; ATRIAL-FIBRILLATION;
D O I
10.1002/pds.5232
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Purpose Greedy caliper propensity score (PS) matching is dependent on randomness, which can ultimately affect causal estimates. We sought to investigate the variation introduced by this randomness. Methods Based on a literature search to define the simulation parameters, we simulated 36 cohorts of different sizes, treatment prevalence, outcome prevalence, treatment-outcome-association. We performed 1:1 caliper and nearest neighbor (NN) caliper PS-matching and repeated this 1000 times in the same cohort, before calculating the treatment-outcome association. Results Repeating caliper and NN caliper matching in the same cohort yielded large variations in effect estimates, in all 36 scenarios, with both types of matching. The largest variation was found in smaller cohorts, where the odds ratio (OR) ranged from 0.53 to 10.00 (IQR of ORs: 1.11-1.67). The 95% confidence interval was not consistently overlapping a neutral association after repeating the matching with both algorithms. We confirmed these findings in a noninterventional example study. Conclusion Caliper PS-matching can yield highly variable estimates of the treatment-outcome association if the analysis is repeated.
引用
收藏
页码:934 / 951
页数:18
相关论文
共 4 条
  • [1] Matching on propensity and prognostic scores can lead to different estimates of heterogeneous treatment effects: a case study and simulation
    Daijiro Kabata
    Yasufumi Gon
    Ayumi Shintani
    Health Services and Outcomes Research Methodology, 2024, 24 : 227 - 238
  • [2] Matching on propensity and prognostic scores can lead to different estimates of heterogeneous treatment effects: a case study and simulation
    Kabata, Daijiro
    Gon, Yasufumi
    Shintani, Ayumi
    HEALTH SERVICES AND OUTCOMES RESEARCH METHODOLOGY, 2024, 24 (02) : 227 - 238
  • [3] Variable selection for propensity score models when estimating treatment effects on multiple outcomes: a simulation study
    Wyss, Richard
    Girman, Cynthia J.
    LoCasale, Robert J.
    Brookhart, M. Alan
    Stuermer, Til
    PHARMACOEPIDEMIOLOGY AND DRUG SAFETY, 2013, 22 (01) : 77 - 85
  • [4] Propensity Score Weighting and Trimming Strategies for Reducing Variance and Bias of Treatment Effect Estimates: A Simulation Study
    Sturmer, Til
    Webster-Clark, Michael
    Lund, Jennifer L.
    Wyss, Richard
    Ellis, Alan R.
    Lunt, Mark
    Rothman, Kenneth J.
    Glynn, Robert J.
    AMERICAN JOURNAL OF EPIDEMIOLOGY, 2021, 190 (08) : 1659 - 1670