Outcomes of patients who participate in randomised controlled trials compared to similar patients receiving similar interventions who do not participate
Bibliographic record
Abstract
BACKGROUND: Some people believe that patients who take part in randomised controlled trials (RCTs) face risks that they would not face if they opted for non-trial treatment. Others think that trial participation is beneficial and the best way to ensure access to the most up to date physicians and treatments. OBJECTIVES: To assess the effects of patient participation in RCTs ('trial effects') independent both of the effects of the clinical treatments being compared ('treatment effects') and any differences between patients who participated in RCTs and those who did not. SEARCH STRATEGY: In May 2001, we searched The Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, EMBASE, The Cochrane Methodology Register, SciSearch and PsycINFO for potentially relevant studies. Our search yielded over 10,000 references. In addition, we reviewed the reference lists of relevant articles and wrote to over 250 investigators to try to obtain further information. SELECTION CRITERIA: Randomised studies and cohort studies with data on clinical outcomes of RCT participants and similar patients who received similar treatment outside of RCTs. DATA COLLECTION AND ANALYSIS: At least two reviewers independently assessed studies for inclusion, assessed study quality and extracted data. Study authors were contacted for additional information. MAIN RESULTS: We included five randomised studies (yielding 6 comparisons) and 50 non-randomised cohort studies (85 comparisons), with 31,140 patients treated in RCTs and 20,380 patients treated outside RCTs. In the randomised studies, patients were invited to participate in an RCT or not; these comparisons provided limited information because of small sample sizes (a total of 412 patients) and the nature of the questions they addressed. There was statistically significant heterogeneity (P < 0.002, I(2) = 36.2%) among the 73 dichotomous outcome comparisons; none of the potential explanatory factors we investigated helped to explain this heterogeneity. No statistically significant differences were found for 63 of the 73 comparisons. Eight comparisons reported statistically significant better outcomes for patients treated within RCTs, and two comparisons reported statistically significant worse outcomes for patients treated within RCTs. There were no statistically significant differences in heterogeneity (P = 0.53, I(2) = 0%) or in outcomes (SMD 0.01, 95% CI -0.10 to 0.12) of patients treated within and outside RCTs in the 18 comparisons which had used continuous outcomes. AUTHORS' CONCLUSIONS: This review indicates that participation in RCTs is not associated with greater risks than receiving the same treatment outside RCTs. These results challenge the assertion that the results of RCTs are not applicable to usual practice.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.202 | 0.525 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.016 |
| Bibliometrics | 0.010 | 0.014 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".