Literature DB >> 28858561

Differential losses to follow-up that are outcome-dependent can vitiate a clinical trial: Simulation results.

Richard F Potthoff1.   

Abstract

Loss to follow-up (LTFU) in clinical trials represents a potential threat to their soundness that may not be adequately recognized. We consider a log-rank test in a trial with two arms, experimental and control, and with a single unfavorable binary endpoint such as death. Commonly, one applies censoring to patients with LTFU. That approach is valid if LTFU is independent of outcome, but can lead to bias otherwise. Unfortunately, there is no statistical test for independence, so the legitimacy of the approach rests on unverifiable assumptions. For two cases, we evaluate the impact of the approach based on simulations that use reasonable models for outcome-dependent LTFU. In each case, LTFU in one arm disproportionately suppresses recognition of relatively early deaths or other outcomes, thus producing bias favoring that arm. The first case has extra LTFU in the experimental arm and the treatment has no benefit. The second case has extra LTFU in the control arm and the treatment is effective. The simulation results show severe inflation of Type I error in the first case and major loss of power in the second case. Remedies for LTFU are scarce but include avoiding it in the first place where possible.

Entities:  

Keywords:  Bias; clinical trials; log-rank test; loss to follow-up; simulations

Mesh:

Year:  2017        PMID: 28858561      PMCID: PMC6145451          DOI: 10.1080/10543406.2017.1372773

Source DB:  PubMed          Journal:  J Biopharm Stat        ISSN: 1054-3406            Impact factor:   1.051


  21 in total

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8.  Using the National Death Index to validate the noninformative censoring assumption of survival estimation.

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9.  Non-ignorable loss to follow-up: correcting mortality estimates based on additional outcome ascertainment.

Authors:  M Schomaker; T Gsponer; J Estill; M Fox; A Boulle
Journal:  Stat Med       Date:  2013-07-22       Impact factor: 2.373

10.  Problems in dealing with missing data and informative censoring in clinical trials.

Authors:  Weichung Shih
Journal:  Curr Control Trials Cardiovasc Med       Date:  2002-01-08
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  1 in total

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