Outcomes for patients with the same disease treated inside and outside of randomized trials: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: It is unclear whether participation in a randomized controlled trial (RCT), irrespective of assigned treatment, is harmful or beneficial to participants. We compared outcomes for patients with the same diagnoses who did ("insiders") and did not ("outsiders") enter RCTs, without regard to the specific therapies received for their respective diagnoses. METHODS: By searching the MEDLINE (1966-2010), Embase (1980-2010), CENTRAL (1960-2010) and PsycINFO (1880-2010) databases, we identified 147 studies that reported the health outcomes of "insiders" and a group of parallel or consecutive "outsiders" within the same time period. We prepared a narrative review and, as appropriate, meta-analyses of patients' outcomes. RESULTS: We found no clinically or statistically significant differences in outcomes between "insiders" and "outsiders" in the 23 studies in which the experimental intervention was ineffective (standard mean difference in continuous outcomes -0.03, 95% confidence interval [CI] -0.1 to 0.04) or in the 7 studies in which the experimental intervention was effective and was received by both "insiders" and "outsiders" (mean difference 0.04, 95% CI -0.04 to 0.13). However, in 9 studies in which an effective intervention was received only by "insiders," the "outsiders" experienced significantly worse health outcomes (mean difference -0.36, 95% CI -0.61 to -0.12). INTERPRETATION: We found no evidence to support clinically important overall harm or benefit arising from participation in RCTs. This conclusion refutes earlier claims that trial participants are at increased risk of harm.
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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 | 0.040 | 0.105 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.027 | 0.045 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".