Outcomes of patients who participate in randomized controlled trials compared to similar patients receiving similar interventions who do not participate
Notice bibliographique
Résumé
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. This is an updated version of the original Cochrane review published in Issue 1, 2005. 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. We aimed to compare similar patients receiving similar treatment inside and outside of RCTs. SEARCH STRATEGY: In March 2007, 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 7586 new references. In addition, we reviewed the reference lists of relevant articles. SELECTION CRITERIA: Randomized 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 review authors independently assessed studies for inclusion, assessed study quality and extracted data. MAIN RESULTS: We identified 30 new non-randomized cohort studies (45 comparisons): no new RCTs were found. This update now includes five RCTs (yielding 6 comparisons) and 80 non-randomized cohort studies (130 comparisons), with 86,640 patients treated in RCTs and 57,205 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. When the results of RCTs and non-randomized cohorts that reported dichotomous outcomes were combined, there were 98 comparisons; there was also heterogeneity (P < 0.00001, I(2) = 42.2%) between studies. No statistical significant differences were found for 85 of the 98 comparisons. Eight comparisons reported statistically significant better outcomes for patients treated within RCTs, and five comparisons reported statistically significant worse outcomes for patients treated within RCTs. There was significant heterogeneity (P < 0.00001, I(2) = 58.2%) among the 38 continuous outcome comparisons. No statistically significant differences were found for 30 of the 38 comparisons. Three comparisons reported statistically significant better outcomes for patients treated within RCTs, and five comparisons reported statistically significant worse outcomes for patients treated within RCTs. AUTHORS' CONCLUSIONS: This review indicates that participation in RCTs is associated with similar outcomes to receiving the same treatment outside RCTs. These results challenge the assertion that the results of RCTs are not applicable to usual practice.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,150 | 0,521 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,002 |
| Méta-épidémiologie (sens large) | 0,014 | 0,017 |
| Bibliométrie | 0,011 | 0,015 |
| Études des sciences et des technologies | 0,001 | 0,003 |
| Communication savante | 0,007 | 0,007 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,006 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,009 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».