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Exclusion rates in randomized controlled trials of treatments for physical conditions: a systematic review
Open accessAbstract
Background: The generalisability of randomized controlled trials (RCTs) can be uncertain because the impact of exclusion criteria is rarely quantified. The aim of this study was to systematically review studies examining the percentage of clinical populations with a physical health condition who would be excluded by RCTs of treatments for that condition. Methods: Medline and Embase were searched from inception to Feb 11th 2018. Two reviewers independently completed screening, full-text review, data extraction and risk-of-bias assessment. The primary outcome was the percentage of patients in the clinical population who would have been excluded from each examined trial. Subgroup analyses examined exclusion by population setting, publication date and funding source. Results: Titles/abstracts (20,754) were screened, and 50 studies were included which reported exclusion rates from 305 trials of treatments in 31 physical conditions. Estimated rates of exclusion from trials varied from 0% to 100%, and the median exclusion rate was 77.1% of patients (interquartile range 55.5% to 89.0% exclusion). Median exclusion rates for trials in common chronic conditions were high, including hypertension 83.0%, type 2 diabetes 81.7%, chronic obstructive pulmonary disease 84.3%, and asthma 96.0%. The most commonly applied exclusion criteria related to age, co-morbidity and co-prescribing, whereas more implicit criteria relating to life expectancy or functional status were not typically examined. There was no evidence that exclusion varied by the nature of the clinical population in which exclusion was evaluated or trial funding source. There was no statistically significant change in exclusion rates in more recent compared with older trials. Conclusions: The majority of trials of treatments for physical conditions examined excluded the majority of patients with the condition being treated. Almost a quarter of the trials studied excluded over 90% of patients, more than half of trials excluded at least three quarters of patients, and four out of five trials excluded at least half of patients. A limitation is that most studies applied only a subset of eligibility criteria, so exclusion rates are likely under-estimated. Exclusion from trials of older people and people with co-morbidity and co-prescribing is increasingly untenable given population aging and increasing multimorbidity. Trial registration: PROSPERO registration CRD42016042282 .
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Barnett, K., Mercer, S. W., Norbury, M., Watt, G., Wyke, S., & Guthrie, B. (2012) · The Lancet · doi:10.1016/s0140-6736(12)60240-2 · Cited by 6,972
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Marengoni, A., Angleman, S., Melis, R., Mangialasche, F., Karp, A., Garmen, A., Meinow, B., & Fratiglioni, L. (2011) · Ageing Research Reviews · doi:10.1016/j.arr.2011.03.003 · Cited by 3,092
Boyd, C. M., Darer, J., Boult, C., Fried, L. P., Boult, L., & Wu, A. W. (2005) · JAMA · doi:10.1001/jama.294.6.716 · Cited by 2,581
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Spall, H. G. C. V., Toren, A., Kiss, A., & Fowler, R. (2007) · JAMA · doi:10.1001/jama.297.11.1233 · Cited by 1,054
Lee, P. Y. (2001) · JAMA · doi:10.1001/jama.286.6.708 · Cited by 841
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Hughes, L. D., McMurdo, M. E. T., & Guthrie, B. (2013) · Age and Ageing · doi:10.1093/ageing/afs100 · Cited by 506
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Nagarajan, K., Muniyandi, M., Jeyachithra, A. V., Muniappan, S., Rajamani, N., D’Souza, P. M., Santhoshkumar, Y., Balasubramanian, A. K., Kothoju, B. C., Rebecca, P., et al. (2026) · Trials · doi:10.1186/s13063-026-09590-x
Legg, A., Lambova, A., Ralphs, E., Keapoletswe, K., Wester, G., & Skácel, T. (2026) · Leukemia & lymphoma/Leukemia and lymphoma · doi:10.1080/10428194.2026.2656725
Sweeney, K., Maxwell, S. S., & Guthrie, B. (2026) · The Lancet · doi:10.1016/s0140-6736(26)01078-0
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Tao, Y., Fang, H., Pei, L., Gao, Y., Liu, K., Wang, X., Zhang, R., Cao, Z., Zhou, Y., Zhang, D., et al. (2026) · Neurology and Therapy · doi:10.1007/s40120-026-01006-x
Ekstrom, V. S. M. (2026) · npj Digital Public Health · doi:10.1038/s44482-026-00033-7
Huish, S., Barnes, R., Bhandari, S., Davenport, A., Ferro, C. J., Lambie, M., McMillan, S., Morlidge, C., Smith, R., Wheeler, D. C., et al. (2026) · BMC Nephrology · doi:10.1186/s12882-026-05384-0
Asiri, A., DANIELS, R., Najim, A., Razak, H. R. A., & Mokbel, K. (2026) · Diabetology · doi:10.3390/diabetology7100200
Metadata
- Authors
- He, J., Morales, D. R., & Guthrie, B.
- Affiliations
- University of Dundee (GB)
- University of Edinburgh (GB)
- Corresponding author
- Guthrie, Bruce
- Venue
- Trials
- Published
- 2020-02-26
- Volume
- 21
- Issue
- 1
- Pages
- 228-228
- ISSN
- 1745-6215 (ISSN-L)
- PMC
- PMC7045589
- OpenAlex
- W3009768886
- Cited by
- 147
- References
- 37
- Citations by year
- 2026: 20 · 2025: 25 · 2024: 34 · 2023: 31 · 2022: 20 · 2021: 13 · 2020: 4
- FWCI
- 2.73
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Trials (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Discovery Research Portal (University of Dundee) (submittedVersion, cc-by)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Medical Research Scotland (Vac-965-2016)
- Health Services and Delivery Research Programme (NIHR HS&DR 11/2003/27)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Ethics in Clinical Research
- Keywords
- exclusion rates, exclusion criteria, eligibility criteria, generalizability of trial results, physical health conditions, multimorbidity, older adults, co-prescribing, chronic disease, hypertension, type 2 diabetes, chronic obstructive pulmonary disease, asthma, trial funding, population aging
- MeSH terms
- Humans, Morbidity, Bias, Randomized Controlled Trials as Topic, Patient Selection
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