Evidence map›Paper›PMID 25407057›Full record

ReviewBMC medical research methodology2014

Handling missing data in RCTs; a review of the top medical journals.

Melanie L Bell, Mallorie Fiero, Nicholas J Horton, Chiu-Hsieh Hsu

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in BMC medical research methodology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 202 papers, 11 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
202citing papers in PubMed, 11 pooled it
–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

202 citing papers in PubMed, 11 syntheses or guidelines pooled it.

  1. Pooled it
  2. Guideline
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Pooled it
  7. Pooled it
  8. Pooled it
  9. Pooled it
  10. Pooled it
  11. Pooled it
  12. Kinematic effects of two therapeutic interventions for glenohumeral joint instability: A preliminary feasibility trial.Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology · 2026
    Trial
  13. Trial
  14. Trial
  15. Trial
  16. Trial
  17. Trial
  18. Trial
  19. Trial
  20. Trial

142 more citing papers are in PubMed but not listed here.

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

4 authors.

Melanie L BellDivision of Epidemiology and Biostatistics, Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ 85724, USA. melaniebell@email.arizona.edu.
Mallorie Fiero
Nicholas J Horton
Chiu-Hsieh Hsu

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMissing outcome data is a threat to the validity of treatment effect estimates in randomized controlled trials. We aimed to evaluate the extent, handling, and sensitivity analysis of missing data and intention-to-treat (ITT) analysis of randomized controlled trials (RCTs) in top tier medical journals, and compare our findings with previous reviews related to missing data and ITT in RCTs.

methodsReview of RCTs published between July and December 2013 in the BMJ, JAMA, Lancet, and New England Journal of Medicine, excluding cluster randomized trials and trials whose primary outcome was survival.

resultsOf the 77 identified eligible articles, 73 (95%) reported some missing outcome data. The median percentage of participants with a missing outcome was 9% (range 0 - 70%). The most commonly used method to handle missing data in the primary analysis was complete case analysis (33, 45%), while 20 (27%) performed simple imputation, 15 (19%) used model based methods, and 6 (8%) used multiple imputation. 27 (35%) trials with missing data reported a sensitivity analysis. However, most did not alter the assumptions of missing data from the primary analysis. Reports of ITT or modified ITT were found in 52 (85%) trials, with 21 (40%) of them including all randomized participants. A comparison to a review of trials reported in 2001 showed that missing data rates and approaches are similar, but the use of the term ITT has increased, as has the report of sensitivity analysis.

conclusionsMissing outcome data continues to be a common problem in RCTs. Definitions of the ITT approach remain inconsistent across trials. A large gap is apparent between statistical methods research related to missing data and use of these methods in application settings, including RCTs in top medical journals.

Indexed as

Intention to Treat AnalysisPublishingRandomized Controlled Trials as TopicResearch DesignHumansTreatment Outcome

Identifiers

PMID25407057
PMCPMC4247714

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.