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Impact of patient and public involvement on enrolment and retention in clinical trials: systematic review and meta-analysis
Open accessAbstract
Objective: To investigate the impact of patient and public involvement (PPI) on rates of enrolment and retention in clinical trials and explore how this varies with the context and nature of PPI. Design: Systematic review and meta-analysis. Data sources: Ten electronic databases, including Medline, INVOLVE Evidence Library, and clinical trial registries. Eligibility criteria: Experimental and observational studies quantitatively evaluating the impact of a PPI intervention, compared with no intervention or non-PPI intervention(s), on participant enrolment and/or retention rates in a clinical trial or trials. PPI interventions could include additional non-PPI components inseparable from the PPI (for example, other stakeholder involvement). Data extraction and analysis: Two independent reviewers extracted data on enrolment and retention rates, as well as on the context and characteristics of PPI intervention, and assessed risk of bias. Random effects meta-analyses were used to determine the average effect of PPI interventions on enrolment and retention in clinical trials: main analysis including randomised studies only, secondary analysis adding non-randomised studies, and several exploratory subgroup and sensitivity analyses. Results: 26 studies were included in the review; 19 were eligible for enrolment meta-analysis and five for retention meta-analysis. Various PPI interventions were identified with different degrees of involvement, different numbers and types of people involved, and input at different stages of the trial process. On average, PPI interventions modestly but significantly increased the odds of participant enrolment in the main analysis (odds ratio 1.16, 95% confidence interval and prediction interval 1.01 to 1.34). Non-PPI components of interventions may have contributed to this effect. In exploratory subgroup analyses, the involvement of people with lived experience of the condition under study was significantly associated with improved enrolment (odds ratio 3.14 v 1.07; P=0.02). The findings for retention were inconclusive owing to the paucity of eligible studies (odds ratio 1.16, 95% confidence interval 0.33 to 4.14), for main analysis). Conclusions: These findings add weight to the case for PPI in clinical trials by indicating that it is likely to improve enrolment of participants, especially if it includes people with lived experience of the health condition under study. Further research is needed to assess which types of PPI work best in particular contexts, the cost effectiveness of PPI, the impact of PPI at earlier stages of trial design, and the impact of PPI interventions specifically targeting retention. Systematic review registration: PROSPERO CRD42016043808.
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The Cochrane Collaboration's tool for assessing risk of bias in randomised trials
Higgins, J. P. T., Altman, D. G., Gotzsche, P. C., Juni, P., Moher, D., Oxman, A. D., Savovic, J., Schulz, K. F., Weeks, L., Sterne, J. A. C., et al. (2011) · BMJ · doi:10.1136/bmj.d5928 · Cited by 33,817
Liberati, A., Altman, D. G., Tetzlaff, J., Mulrow, C., Gøtzsche, P. C., Ioannidis, J. P. A., Clarke, M., Devereaux, P. J., Kleijnen, J., & Moher, D. (2009) · PLoS Medicine · doi:10.1371/journal.pmed.1000100 · Cited by 28,164
Dermyshi, E., Wang, Y., Yan, C., Hong, W., Qiu, G., Gong, X., & Zhang, T. (2017) · Neonatology · doi:10.1159/000454668 · Cited by 24,451
ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions
Sterne, J. A., Hernán, M. A., Reeves, B. C., Savović, J., Berkman, N. D., Viswanathan, M., Henry, D., Altman, D. G., Ansari, M. T., Boutron, I., et al. (2016) · BMJ · doi:10.1136/bmj.i4919 · Cited by 20,329
Liberati, A., Altman, D. G., Tetzlaff, J., Mulrow, C., Gotzsche, P. C., Ioannidis, J. P. A., Clarke, M., Devereaux, P. J., Kleijnen, J., & Moher, D. (2009) · BMJ · doi:10.1136/bmj.b2700 · Cited by 17,648
Reduced Lung-Cancer Mortality with Low-Dose Computed Tomographic Screening
The National Lung Screening Trial Research Team (2011) · New England Journal of Medicine · doi:10.1056/nejmoa1102873 · Cited by 11,064
Sterne, J. A. C., Sutton, A. J., Ioannidis, J. P. A., Terrin, N., Jones, D. R., Lau, J., Carpenter, J., Rucker, G., Harbord, R. M., Schmid, C. H., et al. (2011) · BMJ · doi:10.1136/bmj.d4002 · Cited by 7,709
Interpretation of random effects meta-analyses
Riley, R. D., Higgins, J. P. T., & Deeks, J. J. (2011) · BMJ · doi:10.1136/bmj.d549 · Cited by 2,884
A Re-Evaluation of Random-Effects Meta-Analysis
Higgins, J. P. T., Thompson, S. G., & Spiegelhalter, D. J. (2009) · Journal of the Royal Statistical Society Series A: Statistics in Society · doi:10.1111/j.1467-985x.2008.00552.x · Cited by 2,569
Comparison of two methods to detect publication bias in meta-analysis.
Peters, J. L. (2006) · JAMA · doi:10.1001/jama.295.6.676 · Cited by 2,278
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Smits, D.-W., van Meeteren, K., Klem, M., Alsem, M., & Ketelaar, M. (2020) · Research Involvement and Engagement · doi:10.1186/s40900-020-00188-4 · Cited by 295
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Boivin, A., Richards, T., Forsythe, L., Grégoire, A., L’Espérance, A., Abelson, J., & Carman, K. L. (2018) · BMJ · doi:10.1136/bmj.k5147 · Cited by 208
Tembo, D., Hickey, G., Montenegro, C., Chandler, D., Nelson, E., Porter, K., Dikomitis, L., Chambers, M., Chimbari, M., Mumba, N., et al. (2021) · BMJ · doi:10.1136/bmj.n178 · Cited by 163
Metadata
- Authors
- Crocker, J. C., Ricci-Cabello, I., Parker, A., Hirst, J. A., Chant, A., Petit-Zeman, S., Evans, D., & Rees, S.
- Venue
- BMJ
- Publisher
- BMJ
- Published
- 2018-11-28
- Volume
- 363
- Pages
- k4738
- ISSN
- 1756-1833 (ISSN-L)
- 0959-8138
- OpenAlex
- W2902219846
- Cited by
- 624
- References
- 80
- FWCI
- 12.04
- Type
- journal article
- Language
- en
- Open access
- hybrid
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