Propensity score matching in otolaryngologic literature: A systematic review and critical appraisal

被引:6
|
作者
Prasad, Aman [1 ]
Shin, Max [1 ]
Carey, Ryan M. [2 ]
Chorath, Kevin [2 ]
Parhar, Harman [2 ]
Appel, Scott [3 ]
Moreira, Alvaro [4 ]
Rajasekaran, Karthik [3 ]
机构
[1] Univ Penn, Perelman Sch Med, Philadelphia, PA 19104 USA
[2] Univ Penn, Dept Otorhinolaryngol, Philadelphia, PA 19104 USA
[3] Univ Penn, Biostat Anal Ctr, Philadelphia, PA 19104 USA
[4] Univ Texas Hlth San Antonio, Dept Pediat, San Antonio, TX USA
来源
PLOS ONE | 2020年 / 15卷 / 12期
关键词
RANDOMIZED CONTROLLED-TRIALS; SURVIVAL; BIAS; OUTCOMES; SURGERY; CANCER; HEAD;
D O I
10.1371/journal.pone.0244423
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Background Propensity score techniques can reduce confounding and bias in observational studies. Such analyses are able to measure and balance pre-determined covariates between treated and untreated groups, leading to results that can approximate those generated by randomized prospective studies when such trials are not feasible. The most commonly used propensity score -based analytic technique is propensity score matching (PSM). Although PSM popularity has continued to increase in medical literature, improper methodology or methodological reporting may lead to biased interpretation of treatment effects or limited scientific reproducibility and generalizability. In this study, we aim to characterize and assess the quality of PSM methodology reporting in high-impact otolaryngologic literature. Methods PubMed and Embase based systematic review of the top 20 journals in otolaryngology, as measured by impact factor from the Journal Citations Reports from 2012 to 2018, for articles using PSM analysis throughout their publication history. Eligible articles were reviewed and assessed for quality and reporting of PSM methodology. Results Our search yielded 101 studies, of which 92 were eligible for final analysis and review. The proportion of studies utilizing PSM increased significantly over time (p < 0.001). Nearly all studies (96.7%, n = 89) specified the covariates used to calculate propensity scores. Covariate balance was illustrated in 67.4% (n = 62) of studies, most frequently through p-values. A minority (17.4%, n = 16) of studies were found to be fully reproducible according to previously established criteria. Conclusions While PSM analysis is becoming increasingly prevalent in otolaryngologic literature, the quality of PSM methodology reporting can be improved. We provide potential recommendations for authors regarding optimal reporting for analyses using PSM.
引用
收藏
页数:16
相关论文
共 50 条
  • [41] Propensity score matching versus propensity score fine stratification and coarsened exact matching in claims data
    Ripollone, John E.
    Huybrechts, Krista F.
    Rothman, Kenneth J.
    Ferguson, Ryan E.
    Franklin, Jessica M.
    PHARMACOEPIDEMIOLOGY AND DRUG SAFETY, 2018, 27 : 24 - 24
  • [42] Critical appraisal of the literature (critical appraisal tools)
    Raslich, Marc A.
    Onady, Gary M.
    PEDIATRICS IN REVIEW, 2007, 28 (04) : 132 - 138
  • [43] Propensity score matching and complex surveys
    Austin, Peter C.
    Jembere, Nathaniel
    Chiu, Maria
    STATISTICAL METHODS IN MEDICAL RESEARCH, 2018, 27 (04) : 1240 - 1257
  • [44] Caliper considerations for propensity score matching
    Garry, Elizabeth M.
    Eddings, Wesley
    Rajan, Aditya
    Patrick, Amanda R.
    Gatto, Nicolle M.
    PHARMACOEPIDEMIOLOGY AND DRUG SAFETY, 2020, 29 : 375 - 376
  • [45] Propensity Score Matching A Statistical Method
    Kane, Liam T.
    Fang, Taolin
    Galetta, Matthew S.
    Goyal, Dhruv K. C.
    Nicholson, Kristen J.
    Kepler, Christopher K.
    Vaccaro, Alexander R.
    Schroeder, Gregory D.
    CLINICAL SPINE SURGERY, 2020, 33 (03): : 120 - 122
  • [46] Propensity Score Matching with Limited Overlap
    Baser, Onur
    ECONOMICS BULLETIN, 2007, 9
  • [47] Propensity score matching with limited overlap
    Baser, O
    VALUE IN HEALTH, 2006, 9 (03) : A115 - A115
  • [48] To use or not to use propensity score matching?
    Wang, Jixian
    PHARMACEUTICAL STATISTICS, 2021, 20 (01) : 15 - 24
  • [49] Propensity Score Matching: Retrospective Randomization?
    Jupiter, Daniel C.
    JOURNAL OF FOOT & ANKLE SURGERY, 2017, 56 (02): : 417 - 420
  • [50] Propensity Score Matching in Observational Research
    Schober, Patrick
    Vetter, Thomas R.
    ANESTHESIA AND ANALGESIA, 2020, 130 (06): : 1616 - 1617