Abstract 197: Identification and Evaluation of Five Meta-Analytic Statistical Procedures to Validate Surrogate End Points for Use in Randomized Controlled Trials
Notice bibliographique
Résumé
Introduction: Although randomized trials for atherosclerosis widely measure treatment effects on biomarkers or surrogate end points in order to reduce follow-up duration and study costs, treatment effects on surrogate end points do not always predict treatment effects on patient outcomes. It is difficult to validate whether beneficial treatment effects on surrogate end points translate to beneficial effects on patient outcomes since gold-standard statistical procedures for surrogate end point validation require large amounts of individual patient data which is not easily available to investigators designing clinical trials. Objectives: We sought to identify and evaluate meta-analytic statistical procedures for surrogate end point validation that can be applied to summary data from published randomized trials. Methods: We performed a systematic review to identify studies describing meta-analytic statistical procedures to validate surrogate end points. Studies were eligible if the statistical procedure being described could be applied to summary estimates (such as risk ratios and mean differences) from published randomized controlled trials. We identified studies from comprehensive texts in the field of surrogate end point validation and an electronic search of MEDLINE (1930 - 2010). We evaluated the performance and reliability of the meta-analytic statistical procedures that we identified, by applying them to summary data from a previously published review of 11 randomized stent trials. We extracted summary data on the surrogate end point, in-segment diameter stenosis (% differences) at 6-9 months of follow-up, and the patient outcome target lesion revascularization (odds ratios) at 1 year of follow-up. Nine trials compared drug eluting stents with bare metal stents and 2 trials compared drug eluting stents. Results: In total, we identified 31 eligible articles that described 5 meta-analytic statistical procedures and indices to quantify the degree to which treatment effects on surrogate end points are predictive of their effects on patient outcomes. These include Spearman’s rank correlation coefficient (ρ), % concordance, R2, surrogate threshold effect (STE), and delta (Δ). The results of applying these procedures to summary data on in-segment diameter stenosis and target lesion revascularization were consistent with results from procedures requiring individual patient data and showed in-segment diameter stenosis is a good surrogate end point for target lesion revascularization. In 72.7% of studies (8 of 11), the effect of stenting on in-segment diameter stenosis agreed with its effect on target lesion revascularization (% concordance = 72.7%) and 85.2% of the variation in risk of target lesion revascularization was explained by in-segment diameter stenosis (R2=0.852, p <0.0001). A 17.7% difference in diameter stenosis is needed to predict a difference in risk of target lesion revascularization (STE=17.7%). These results agree with those from the ρ and Δ index. Conclusion: In conclusion, we have identified five meta-analytic statistical procedures which may be used to validate surrogate end points when individual patient data is unavailable.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,318 | 0,156 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,008 | 0,002 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».