Evidence map›Paper›PMID 28858561›Full record

ArticleJournal of biopharmaceutical statistics2018

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

Richard F Potthoff

Abstract read
In one paragraph

Article in Journal of biopharmaceutical statistics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Observational
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Richard F Potthoffa Cancer Statistical Center, Duke University Medical Center , Durham , NC , U.S.A.

Funding

Statistical Methods for Cancer Clinical TrialsP01CA142538 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI DAVIDIAN, MARIE, KOSOROK, MICHAEL R · 2010 to 2019
$21.3M
NCI NIH HHS P01 CA142538
6 · The paper itself

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.

Indexed as

Lost to Follow-UpComputer SimulationFollow-Up StudiesHumansRandomized Controlled Trials as TopicTreatment OutcomeBiasclinical trialslog-rank testloss to follow-upsimulations

Identifiers

PMID28858561
PMCPMC6145451

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.