Abstract P5-14-11: An estimation of the population survival benefit of first-line chemotherapy and immunotherapy for breast cancer
Notice bibliographique
Résumé
Abstract Purpose:Randomized clinical trials describe the benefit of chemo-and immunotherapy for specific breast cancer patients with selected patient and disease characteristics. However, variability in practice occurs despite evidence-based guidelines [1]. The overall survival benefit for the whole population of breast cancer patients in Australia, if evidence-based guidelines for chemo-and immunotherapy were implemented, is unknown. Our study's purpose was to estimate the overall population survival benefit of routinely using evidence-based practice. Methods and Materials:Decision trees with evidence-based indications for chemotherapy have been previously defined [2]. Each branch corresponds to a specific cohort who have, or do not have, defined indications for chemotherapy and/or immunotherapy. Chemo -and immunotherapy benefit was defined as the absolute incremental benefit of either chemotherapy and/or immunotherapy over no chemo- and/or immunotherapy for radical and palliative indications. Multiple electronic citation databases were systematically queried, including Medline and the Cochrane Library. In cases where there were multiple sources of the same level of evidence, hierarchical meta-analysis was performed. The benefits of chemo- and immunotherapy were estimated for 1, 5, 10-year survival. To assess the robustness of our estimates, sensitivity analyses were performed. Results: The estimated 1-year, 5-year and 10-year absolute population-based overall survival benefits of optimally utilized chemo- and immunotherapy for breast cancer in Australia are 1.0% (95% CI, 0.9%-1.2%), 4.4% (95% CI, 4.3%-4.6%) and 5.2% (%-%), respectively. They are summarized in the Table 1. Estimation of Population Survival Benefit for First Line Chemo- and Immuno TherapyBreast CancerProportion of all cancer in Australia1 year survival benefit (Sensitivity range)5 year survival benefit (Sensitivity range)10 year survival benefit (Sensitivity range)Stage I-II10.0%0.6% (0.6%-0.7%)4.8% (4.6%-5.0%)6.9% (6.7%- 7.2%)Stage III1.6%3.0% (3.0%-3.1%)6.1% (5.8%-6.3%)0%Stage IV0.5%5.3% (5.1%-5.5%)4.9% (4.7%-5.1%)0%Whole Breast Cancer population12.1%1.0% (0.9%-1.2)4.4% (4.3%-4.6%)5.2% (5.0%-5.4%) Conclusion: Chemo- and immunotherapy agents improves overall survival in breast cancer at 1-, 5- and 10-years. Chemo-and immunotherapy provides a modest survival benefit to this patient population in Australia when it is used in accordance with guideline recommendations. These outcomes may allow comparison of treatment outcomes in a jurisdiction against what would be considered optimal based on evidence. 1. Fong, A., et al., A comparison of systemic breast cancer therapy utilization in Canada (British Columbia), Scotland (Dundee), and Australia (Western Australia) with models of "optimal" therapy. Breast, 2012. 21(4): p. 562-9. 2. Ng, W., Estimating the optimal chemotherapy utilisation rate as an evidence-based benchmark in cancers of the breast, upper gastrointestinal tract, gynaecological tract, head and neck, kidney, bladder, thyroid and unknown primary., in University of NSW, Faculty of Medicine. 2010, UNSW: Sydney. Citation Format: Delaney GP, Do V, Ng W, Barton MB. An estimation of the population survival benefit of first-line chemotherapy and immunotherapy for breast cancer [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P5-14-11.
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 | 0,049 | 0,136 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,006 | 0,015 |
| Bibliométrie | 0,006 | 0,004 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 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 ».