No differential attrition was found in randomized controlled trials published in general medical journals: a meta-analysis
Open accessAbstract
Objective Differential attrition is regarded as a major threat to the internal validity of a randomized controlled trial (RCT). This study identifies the degree of differential attrition in RCTs covering a broad spectrum of clinical areas and factors that are related to this. Study design and setting A PubMed search was conducted to obtain a random sample of 100 RCTs published between 2008 and 2010 in journals from the ISI Web of Knowledge(SM) category of medicine, general and internal. Eligibility criteria for selecting studies were primary publications of two-arm parallel randomized clinical trials, containing human participants and one or multiple follow-up measurements whose availability depended on the patients' willingness to participate. Results A significant amount of differential attrition was observed in 8% of the trials. The average differential attrition rate was 0.99 (95% confidence interval: 0.97-1.01), indicating no general difference in attrition rates between intervention and control groups. Moreover, no indication of heterogeneity was found, suggesting that the occurrence of differential attrition in the published literature is mostly a chance finding, unrelated to any particular design factors. Conclusion Differential attrition did not generally occur in RCTs covering a broad spectrum of clinical areas within general and internal medicine.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In peer-reviewed health research, loss to follow-up was normally similar across trial arms.
“because in peer-reviewed health research LTFU was normally similar across trial arms [32].”
From Patient Engagement with Conversational Agents in Health Applications 2016–2022: A Systematic Review and Meta-Analysis (2024) · cites this paper as [32]
Meta-analysis of all 14 studies produced an overall effect size of 0.99 (95% CI 0.95-1.03; p < 0.01), indicating no statistically significant difference between chatbot loss to follow-up and three other types of intervention.
“Meta-analysis of all 14 studies produced an overall effect size of 0.99 (95% CI 0.95–1.03; p < 0.01), which indicated no statistically significant difference between chatbot loss to follow-up and three other types of intervention.”
From Patient Engagement with Conversational Agents in Health Applications 2016–2022: A Systematic Review and Meta-Analysis (2024) · cites this paper as [32]
Cites
R: A Language and Environment for Statistical Computing
R Core Team (2000) · doi:10.32614/r.manuals · Cited by 355,706 · see citing works
Cochrane Handbook for Systematic Reviews of Interventions: Cochrane Book Series
(2008) · doi:10.1002/9780470712184 · Cited by 25,048 · see citing works
Conducting Meta-Analyses in <i>R</i> with the <b>metafor</b> Package
Viechtbauer, W. (2010) · Journal of Statistical Software · doi:10.18637/jss.v036.i03 · Cited by 20,464 · see citing works
Self-citation(2002) · Cited by 13,211 · see citing works
Outlier and influence diagnostics for meta-analysis
Viechtbauer, W., & Cheung, M. W.-L. (2010) · Research Synthesis Methods · doi:10.1002/jrsm.11 · Cited by 2,949 · see citing works
Self-citationPublication Bias in Meta‐Analysis: Prevention, Assessment and Adjustments
(2005) · doi:10.1002/0470870168 · Cited by 2,368 · see citing works
Missing Data in Clinical Studies
Molenberghs, G., & Kenward, M. G. (2007) · Wiley eBooks · doi:10.1002/9780470510445 · Cited by 969 · see citing works
Regression Methods to Detect Publication and Other Bias in Meta‐Analysis
Sterne, J. A. C., & Egger, M. (2005) · Publication Bias in Meta‐Analysis · doi:10.1002/0470870168.ch6 · Cited by 826 · cited 1× · see citing works
“The rank correlation and regression test were used to examine whether asymmetry was present in the funnel plot [14].”
MethodSample size slippages in randomised trials: exclusions and the lost and wayward.
Schulz, K. F., & Grimes, D. A. (2002) · The Lancet · doi:10.1016/s0140-6736(02)07882-0 · Cited by 642 · see citing works
Pharmacotherapy for post traumatic stress disorder (PTSD)
Stein, D. J., Ipser, J. C., Seedat, S., Sager, C., & Amos, T. (2006) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd002795.pub2 · Cited by 519 · see citing works
Chatfield, M. D., Brayne, C., & Matthews, F. E. (2005) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2004.05.006 · Cited by 456 · see citing works
Reporting attrition in randomised controlled trials
Dumville, J. C., Torgerson, D. J., & Hewitt, C. E. (2006) · BMJ · doi:10.1136/bmj.332.7547.969 · Cited by 443 · see citing works
Puffer, S., Torgerson, D., & Watson, J. (2003) · BMJ · doi:10.1136/bmj.327.7418.785 · Cited by 351 · see citing works
Impact of Participant and Physician Intervention Preferences on Randomized Trials
King, M., Nazareth, I., Lampe, F. C., Bower, P., Chandler, M., Morou, M., Sibbald, B., & Lai, R. (2005) · JAMA · doi:10.1001/jama.293.9.1089 · Cited by 276 · see citing works
Lower, E. E., Fleishman, S. B., Cooper, A., Zeldis, J. B., Faleck, H. J., Yu, Z., & Manning, D. C. (2009) · Journal of Pain and Symptom Management · doi:10.1016/j.jpainsymman.2009.03.011 · Cited by 197 · see citing works
Missing Data in Clinical Studies
Shalabh (2008) · Journal of the Royal Statistical Society Series A (Statistics in Society) · doi:10.1111/j.1467-985x.2008.00561_12.x · Cited by 178 · see citing works
Gary‐Webb, T. L., Batts-Turner, M. L., Yeh, H., Hill‐Briggs, F., Bone, L., Wang, N., Levine, D. M., Powe, N. R., Saudek, C. D., Hill, M. N., et al. (2009) · Archives of Internal Medicine · doi:10.1001/archinternmed.2009.338 · Cited by 173 · see citing works
Assessing the impact of attrition in randomized controlled trials
Hewitt, C. E., Kumaravel, B., Dumville, J. C., & Torgerson, D. J. (2010) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2010.01.010 · Cited by 139 · see citing works
painACTION-Back Pain: A Self-Management Website for People with Chronic Back Pain
Chiauzzi, E., Pujol, L. A., Wood, M., Bond, K., Black, R., Yiu, E., & Zacharoff, K. (2010) · Pain Medicine · doi:10.1111/j.1526-4637.2010.00879.x · Cited by 130 · see citing works
Martins, N., Morris, P. S., & Kelly, P. M. (2009) · BMJ · doi:10.1136/bmj.b4248 · Cited by 99 · see citing works
Rabinowitz, J., Levine, S. Z., Barkai, O., & Davidov, O. (2008) · Schizophrenia Bulletin · doi:10.1093/schbul/sbn005 · Cited by 64 · see citing works
Li, H., Ma, C., Wang, G., Zhu, X., Peng, M., & Gu, N. (2007) · Current Medical Research and Opinion · doi:10.1185/030079908x253933 · Cited by 54 · see citing works
Heneghan, C. J., Perera, R., Ward, A., Fitzmaurice, D. A., Meats, E., & Glasziou, P. (2007) · BMC Medical Research Methodology · doi:10.1186/1471-2288-7-18 · Cited by 31 · see citing works
Meta-Analysis of Dropout Rates in SSRIs Versus Placebo in Randomized Clinical Trials of PTSD
Lurie, I., & Levine, S. Z. (2010) · The Journal of Nervous and Mental Disease · doi:10.1097/nmd.0b013e3181cc41b6 · Cited by 31 · see citing works
Differential attrition: Another hazard of follow-up research.
Wortman, P. M. (1978) · American Psychologist · doi:10.1037//0003-066x.33.12.1145 · Cited by 24 · see citing works
Flagged first, then by citations
1 of the 26 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
Differential attrition in health behaviour change trials: a systematic review and meta-analysis
Crutzen, R., Viechtbauer, W., Spigt, M., & Kotz, D. (2015) · Psychology & Health · doi:10.1080/08870446.2014.953526 · Cited by 132 · see citing works
Self-citationHussain, J. A., White, I. R., Langan, D., Johnson, M. J., Currow, D. C., Torgerson, D. J., & Bland, M. (2015) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2015.12.003 · Cited by 52 · see citing works
Joseph, R., Sim, J., Ogollah, R., & Lewis, M. (2015) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2014.09.002 · Cited by 50 · see citing works
Zuidema, R., van Dulmen, S., der Sanden, M. W. G. N., Meek, I., van den Ende, C. H. M., Fransen, J., & van Gaal, B. G. I. (2018) · Journal of Medical Internet Research · doi:10.2196/12463 · Cited by 46 · see citing works
van der Wurff, I. S. M., Meyer, B. J., & de Groot, R. H. M. (2017) · Nutrients · doi:10.3390/nu9050474 · Cited by 37 · see citing works
Cevasco, K. E., Morrison Brown, R. E., Woldeselassie, R., & Kaplan, S. (2024) · Journal of Medical Systems · doi:10.1007/s10916-024-02059-x · Cited by 35 · see citing works
“We expected chatbot intervention arms to show similar LTFU rates as non-chatbot control arms; because in peer-reviewed health research LTFU was normally similar across trial arms [32].”
ResultEngelen, M. M., van Dulmen, S., Puijk‐Hekman, S., Vermeulen, H., der Sanden, M. W. G. N., Bredie, S. J. H., & van Gaal, B. G. I. (2020) · Journal of Medical Internet Research · doi:10.2196/17422 · Cited by 33 · see citing works
Brueton, V. C., Stenning, S. P., Stevenson, F. A., Tierney, J. F., & Rait, G. (2017) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2017.05.010 · Cited by 24 · see citing works
Körner, L. S., Mülder, L. M., Bruno, L., Janneck, M., Dettmers, J., & Rigotti, T. (2022) · Applied Psychology Health and Well-Being · doi:10.1111/aphw.12410 · Cited by 20 · see citing works
Xu, Z., Sun, W. J., Zhang, D., & Wong, S. Y. S. (2020) · International Journal of Geriatric Psychiatry · doi:10.1002/gps.5336 · Cited by 19 · see citing works
Thompson, T., Greaves, C. J., Ayres, R., Aveyard, P. N., Warren, F. C., Byng, R., Taylor, R. S., Campbell, J., USSHER, M. H., Michie, S., et al. (2016) · Trials · doi:10.1186/s13063-016-1641-5 · Cited by 19 · see citing works
Clinical prediction models are not being validated
Tugwell, P., & Knottnerus, J. A. (2014) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2014.11.020 · Cited by 15 · see citing works
Gnambs, T., & Schroeders, U. (2023) · Research Synthesis Methods · doi:10.1002/jrsm.1673 · Cited by 13 · see citing works
Bevens, W., Shoushtari, A. N., Jelı́nek, P., Jelinek, G., & Weiland, T. J. (2021) · BMC Medical Research Methodology · doi:10.1186/s12874-021-01313-x · Cited by 13 · see citing works
Powell, L. H., Kaufmann, P. G., & Freedland, K. E. (2021) · Springer eBooks · doi:10.1007/978-3-030-39330-4_7 · Cited by 12 · see citing works
Kotz, D., Viechtbauer, W., Spigt, M., & Crutzen, R. (2019) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2019.01.007 · Cited by 13 · see citing works
Self-citationMissing, Presumed different: Quantifying the risk of Attrition Bias in Education Evaluations
Weidmann, B., & Miratrix, L. W. (2021) · Journal of the Royal Statistical Society Series A (Statistics in Society) · doi:10.1111/rssa.12677 · Cited by 10 · see citing works
Saha, C., Shubrook, J. H., Hornsby, W. G., Yang, Z., Pillay, Y., Mather, K. J., & de Groot, M. (2023) · Journal of Diabetes and its Complications · doi:10.1016/j.jdiacomp.2023.108666 · Cited by 10 · see citing works
de Haan, E., Terblanche, N. H. D., & Nowack, K. M. (2026) · Human Resource Development International · doi:10.1080/13678868.2026.2633990 · Cited by 8 · see citing works
The consultation open and close study: A feasibility study of a complex intervention
Murphy, M., Scott, A., Wong, G., Walter, S., Hancock, J., Palmer, T., & Salisbury, C. (2022) · NIHR Open Research · doi:10.3310/nihropenres.13267.1 · Cited by 8 · see citing works
Historical Benchmarks for Quality Tolerance Limits Parameters in Clinical Trials
Makowski, M., Bhagat, R., Chevalier, S., Gilbert, S. A., Görtz, D. R., Kozińska, M., Nadolny, P., Suprin, M., & Turri, S. (2021) · Therapeutic Innovation & Regulatory Science · doi:10.1007/s43441-021-00335-3 · Cited by 8 · see citing works
Attrition and discontinuation in amyotrophic lateral sclerosis clinical trials: a meta-analysis
van Eijk, R. P. A., van Loon, F. T., van Unnik, J. W. J., Weemering, D. N., Seitidis, G., Mavridis, D., van den Berg, L. H., & Nikolakopoulos, S. (2024) · Journal of Neurology · doi:10.1007/s00415-024-12813-3 · Cited by 7 · see citing works
Overgaard, S. H., Moos, C. M., Ioannidis, J. P. A., Luta, G., Berg, J., Nielsen, S. M., Andersen, V. C., & Christensen, R. (2024) · Research Synthesis Methods · doi:10.1002/jrsm.1708 · Cited by 5 · see citing works
Biggs, K., Hind, D., Bradburn, M. J., Swaby, L., & Brown, S. R. (2019) · Trials · doi:10.1186/s13063-019-3649-0 · Cited by 3 · see citing works
Newman, C., Adriaens, E., Virgilio, N., Vleminckx, S., Pelsmaeker, S. D., Prawitt, J., & Silva, C. I. F. (2023) · JMIR Formative Research · doi:10.2196/42967 · Cited by 2 · see citing works
Prognostic value of early proms for one-year recovery trajectories after total hip arthroplasty
Klinder, A., Schrödl, F. M., MITTELMEIER, W., Rohde-Lindner, M., Paulokat, H. M., & Osmanski-Zenk, K. (2026) · Scientific Reports · doi:10.1038/s41598-026-39653-7 · Cited by 1 · see citing works
Revenue Losses: Exploring Strategies Required by Managers to Inhibit Movie Piracy
Akaeze, S., & Aishat, N. (2016) · Cited by 1 · see citing works
ten Hoor, G. A. (2017) · doi:10.26481/dis.20170707gth · Cited by 1 · see citing works
Het ontwikkelen en evalueren van het online zelfmanagementprogramma ‘Reuma zelf te lijf ’
Zuidema, R. (2021) · Verpleegkunde · doi:10.24078/vpg.2021.3.126593
Gnambs, T., & Schroeders, U. (2022) · doi:10.31234/osf.io/hte6z
Murphy, M., Scott, A., Wong, G., et al. (2023) · NIHR Open Research · doi:10.3310/nihropenres.14386.r28943
Murphy, M., Scott, A., Wong, G., et al. (2023) · NIHR Open Research · doi:10.3310/nihropenres.14386.r29118
- Authors
- Crutzen, R., Viechtbauer, W., Kotz, D., & Spigt, M.
- Affiliations
- Maastricht University (NL)
- Cancer Research UK (GB)
- Corresponding author
- Crutzen, Rik
- Venue
- Journal of Clinical Epidemiology
- Publisher
- Elsevier BV
- Published
- 2013-09
- Volume
- 66
- Issue
- 9
- Pages
- 948-954
- ISSN
- 0895-4356 (ISSN-L)
- OpenAlex
- W2060232599
- Cited by
- 32
- References
- 26
- Citations by year
- 2026: 2 · 2024: 3 · 2023: 5 · 2022: 3 · 2021: 5 · 2020: 2 · 2019: 2 · 2018: 1 · 2017: 3 · 2016: 2 · 2015: 1 · 2014: 3
- FWCI
- 0.41
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of Clinical Epidemiology (publishedVersion)
- PubMed (publishedVersion)
- Research Publications (Maastricht University) (publishedVersion, other-oa)
- Lirias (submittedVersion)
- Research Publications (Maastricht University) (submittedVersion, other-oa)
- Funders
- Cancer Research UK (14135)
- Medical Research Council (MR/K023195/1)
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Keywords
- differential attrition, loss to follow-up, randomized controlled trials, internal validity, attrition bias, general medical journals, internal medicine
- MeSH terms
- Humans, Periodicals as Topic, Publishing, Research Design, Randomized Controlled Trials as Topic, Internet, Lost to Follow-Up
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
