Handling trial participants with missing outcome data when conducting a meta-analysis: a systematic survey of proposed approaches
Por:
Akl, EA, Kahale, LA, Agoritsas, T, Brignardello-Petersen, R, Busse, JW, Carrasco-Labra, A, Ebrahim, S, Johnston, BC, Neumann, I, Sola, I, Sun, X, Vandvik, P, Zhang, YQ, Alonso-Coello, P, Guyatt, G
Publicada:
1 ene 2015
Resumen:
Background: When potentially associated with the likelihood of outcome, missing participant data represents a serious potential source of bias in randomized trials. Authors of systematic reviews frequently face this problem when conducting meta-analyses. The objective of this study is to conduct a systematic survey of the relevant literature to identify proposed approaches for how systematic review authors should handle missing participant data when conducting a meta-analysis.
Methods: We searched MEDLINE and the Cochrane Methodology register from inception to August 2014. We included papers that devoted at least two paragraphs to discuss a relevant approach for missing data. Five pairs of reviewers, working independently and in duplicate, selected relevant papers. One reviewer abstracted data from included papers and a second reviewer verified them. We summarized the results narratively.
Results: Of 9,138 identified citations, we included 11 eligible papers. Four proposed general approaches for handling dichotomous outcomes, and all recommended a complete case analysis as the primary analysis and additional sensitivity analyses using the following imputation methods: based on reasons for missingness (n = 3), relative to risk among followed up (n = 3), best-case scenario (n = 2), and worst-case scenario (n = 3). Three of these approaches suggested taking uncertainty into account. Two papers proposed general approaches for handling continuous outcomes, and both proposed a complete case analysis as the reference analysis and the following imputation methods as sensitivity analyses: based on reasons for missingness (n = 2), based on the mean observed in the same trial or other trials (n = 1), and based on informative missingness differences in means (n = 1). The remaining eligible papers did not propose general approaches but addressed specific statistical issues.
Conclusions: All proposed approaches for handling missing participant data recommend conducting a complete case analysis for the primary analysis and some form of sensitivity analysis to evaluate robustness of results. Although these approaches require further testing, they may guide review authors in addressing missing participant data.
Filiaciones:
Akl, EA:
Amer Univ, Dept Internal Med, Clin Epidemiol Unit, Beirut Med Ctr, POB 11-0236,Riad El Solh, Beirut 1107, Lebanon
Amer Univ, Dept Internal Med, Clin Epidemiol Unit, Beirut Med Ctr, Beirut 2020, Lebanon
McMaster Univ, Dept Clin Epidemiol & Biostat, Hamilton, ON, Canada
Kahale, LA:
Amer Univ, Dept Internal Med, Clin Epidemiol Unit, Beirut Med Ctr, POB 11-0236,Riad El Solh, Beirut 1107, Lebanon
Amer Univ, Dept Internal Med, Clin Epidemiol Unit, Beirut Med Ctr, Beirut 2020, Lebanon
Agoritsas, T:
McMaster Univ, Dept Clin Epidemiol & Biostat, Hamilton, ON, Canada
Brignardello-Petersen, R:
Univ Chile, Evidence Based Dent Unit, Santiago, Chile
Univ Toronto, Inst Hlth Policy Management & Evaluat, Toronto, ON, Canada
Busse, JW:
McMaster Univ, Dept Clin Epidemiol & Biostat, Hamilton, ON, Canada
Carrasco-Labra, A:
McMaster Univ, Dept Clin Epidemiol & Biostat, Hamilton, ON, Canada
Ebrahim, S:
McMaster Univ, Dept Clin Epidemiol & Biostat, Hamilton, ON, Canada
Univ Toronto, Inst Hlth Policy Management & Evaluat, Toronto, ON, Canada
Univ Toronto, Hosp Sick Children, Dept Anesthesia & Pain Med, Toronto, ON, Canada
Stanford Univ, Dept Med, Stanford, CA 94305 USA
Johnston, BC:
McMaster Univ, Dept Clin Epidemiol & Biostat, Hamilton, ON, Canada
Univ Toronto, Hosp Sick Children, Dept Anesthesia & Pain Med, Toronto, ON, Canada
Hosp Sick Children, Res Inst, Toronto, ON, Canada
Univ Toronto, Inst Hlth Policy Management & Evaluat, Dalla Lana Sch Publ Hlth, Toronto, ON, Canada
Neumann, I:
McMaster Univ, Dept Clin Epidemiol & Biostat, Hamilton, ON, Canada
Sola, I:
Biomed Res Inst Sant Pau CIBERESP IIB Sant Pau, Iberoamer Cochrane Ctr, Barcelona, Spain
Sun, X:
McMaster Univ, Dept Clin Epidemiol & Biostat, Hamilton, ON, Canada
Vandvik, P:
Norwegian Knowledge Ctr Hlth Serv, Oslo, Norway
Zhang, YQ:
McMaster Univ, Dept Clin Epidemiol & Biostat, Hamilton, ON, Canada
Alonso-Coello, P:
Biomed Res Inst Sant Pau CIBERESP IIB Sant Pau, Iberoamer Cochrane Ctr, Barcelona, Spain
Guyatt, G:
McMaster Univ, Dept Clin Epidemiol & Biostat, Hamilton, ON, Canada
McMaster Univ, Dept Med, Hamilton, ON, Canada
Gold, Green Published
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