Abstract P4-14-03: Influence of competing risks of death on the interpretation of adjuvant endocrine therapy trials for breast cancer
Notice bibliographique
Résumé
Abstract Background: Early stage, hormone sensitive breast cancer is associated generally with a good prognosis, with only a minority of patients expected to die of breast cancer. Death from causes other than breast cancer can dilute the patients at risk of breast cancer events and result in over-estimation of risk of recurrence and consequently the benefit from breast cancer therapy, a so-called immortal time bias. The MA.17R trial (Goss et al 2016) evaluated the role of extending adjuvant treatment with letrozole from 5 to 10 years. Here we determine the effect of analyzing the MA.17R trial using methods accounting for competing risks. Methods: We compared conventional and competing risk methods for disease-free survival (DFS) and for distant recurrence-free survival (DRFS). In Kaplan-Meier analyses death from any cause was considered an event while cumulative incidence functions (CIFs) assumed death without recurrence to be a competing risk. The complement of the survival function (one minus the survival function) was used to estimate incidence of the primary event of interest. This was compared to estimates obtained using CIFs accounting for the occurrence of competing events. Results: Non-breast cancer death was the most common event defining DFS and DRFS. Over the course of follow-up, there was increasing discrepancy between the risk of disease recurrence measured using Kaplan-Meier and CIF. Among letrozole treated patients the estimated distant recurrence at 5 years of follow-up was 5.4% using CIF and 9.6% using Kaplan-Meier. At 10 years of follow-up, the estimated distant recurrence was 8.4% using CIF and 20.0% using Kaplan-Meier. Similar results were observed for the placebo group (8.5% vs 12.1% at 5 years and 14.8% vs 27.3% at 10 years), and in patients with baseline cardiovascular disease (see Table). Benefit from letrozole on DFS and DRFS was greater when accounting for competing risk (hazard ratio [HR] for DFS 0.66, 95%CI 0.48-0.90; DFRS HR 0.75, 0.50-1.14) compared to the conventional method (DFS HR 0.79, 0.62-0.99; DRFS HR 0.91, 0.70-1.18). In women with baseline cardiovascular risk, the benefits of extended adjuvant letrozole when considering competing risk (DFS HR 0.38, 0.16-0.89; DRFS HR 0.46, 0.16-1.35) were also greater than those observed in the conventional analysis (DFS HR 0.55, 0.32-0.93; DRFS HR 0.59, 0.33-1.04). Treatment with extended letrozole did not influence non-breast cancer death in women who died with disease recurrence (HR 1.06, 0.74 -1.50) or in those with competing risk or censored from the analysis (HR 1.05, 0.73 -1.49). Conclusion: Over the course of follow-up, estimates of DFS and DRFS differ increasingly if measured using Kaplan-Meier or CIF, with CIF estimates of risk being substantially lower. Using a competing risk model, the reduction in distant recurrence at 8 years with extended letrozole is less than 1%. Additional competing risk analyses of the MA.17 (Goss 2006) and MA.27 (Goss 2013) trials are ongoing. Cumulative incidence of disease recurrence in patients with baseline cardiovascular riskTime (years)CIF (%)1-KM (%)Letrozole11.51.534.46.555.813.8Placebo13.53.538.311.8512.520.3 Citation Format: Ethier J-L, Parulekar W, Shepherd L, Summers L, Strasser-Weippl K, Tu D, Amir E. Influence of competing risks of death on the interpretation of adjuvant endocrine therapy trials for breast cancer [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P4-14-03.
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 | 0,488 | 0,692 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,004 | 0,008 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,006 | 0,003 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,003 | 0,007 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,010 | 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; l’étiquette directe de Gemma et le classifieur distillé Codex 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 ».