Abstract GS4-03: Validation of Profile for the Omission of Local Adjuvant Radiotherapy (POLAR) in a meta-analysis of three randomized controlled trials of breast conserving surgery +/- radiotherapy
Notice bibliographique
Résumé
Abstract Background: There are currently no commercially available tests to identify early stage breast cancer patients treated with breast conserving surgery (BCS) and systemic therapy at low risk of locoregional recurrence (LRR) for whom postoperative radiotherapy (RT) may be safely omitted. Profile for the Omission of Local Adjuvant Radiotherapy (POLAR) is a 16-gene molecular signature developed to identify invasive breast cancer patients who may be candidates for RT omission after BCS. In this work, we seek to validate POLAR in a meta-analysis of three RCTs of BCS +/- RT: SweBCG91RT, Scottish Conservation Trial (SCT) and Princess Margaret Hospital (PMH). Methods: A patient-level meta-analysis was performed in 623 node-negative breast cancer patients with ER+/HER2-negative tumors who were enrolled in the three RCTs and for whom primary tumor material was available for analysis. Contributions from each cohort were as follows: SweBCG91RT N=354 (57%), SCT N=137 (22%), and PMH N=132 (21%). Numbers of LRR events in each cohort were as follows: SweBCG91RT N=72 (20%), SCT N=28 (20%), and PMH N=16 (12%). There was a mix of systemic therapy used (no systemic therapy for SweBCG91RT, chemotherapy or adjuvant endocrine therapy, but not both, in SCT, and tamoxifen but no chemotherapy for PMH). Median follow-up time for the patients who did not have LRR was 13.3 years for SweBCG91RT, 21.1 years for SCT, and 8.6 years for PMH. A multivariable Cox proportional hazards model on time to LRR, including the continuous standardized POLAR score, RT, and interaction, stratified by cohort, was used to test the interaction between the continuous POLAR score and RT. Additional Cox models tested the association between treatment arms separately for patients with a low and high POLAR score using a pre-specified cut point. Cumulative incidences were computed, with distant metastasis and death without recurrence considered as competing events. Results: The test for interaction between RT treatment and POLAR was statistically significant (p = 0.022). Patients with a high POLAR score (N=429 [69%]) had a large benefit from RT (10-year cumulative incidence of LRR: 20% [15%-26%] for those not treated with RT vs 7% [4%-11%] for those treated with RT; hazard ratio for RT vs no RT: 0.37 [0.23-0.60], p < 0.001), whereas there was no evidence of benefit from RT for patients with a low POLAR score (N=194 [31%], 10-year cumulative incidence of LRR: 5% [2%-11%] for those not treated with RT vs 7% [3%-14%] for those treated with RT; hazard ratio for RT vs no RT: 0.92 [0.42-2.02], p = 0.832). Conclusions: To our knowledge, POLAR is the first genomic classifier that is not only prognostic for LRR but also predictive, showing a significant interaction between RT and the classifier. Patients with a high POLAR score should be recommended radiotherapy while patients with a low score may be candidates for omission of radiotherapy after breast conserving surgery. Citation Format: Per Karlsson, Anthony Fyles, S. Laura Chang, Bradley Arrick, Frederick Baehner, Per Malmström, Mårten Fernö, Erik Holmberg, Martin Sjöström, Fei-Fei Liu, David A. Cameron, Linda J. Williams, John MS Bartlett, Joanna Dunlop, Jacqueline Caldwell, Joseph F. Loane, Elizabeth Mallon, Tammy Piper, Wilma J. Jack, Ian Kunkler, Felix Y. Feng, Corey W. Speers, Lori Pierce, John Bennett, Karen J. Taylor. Validation of Profile for the Omission of Local Adjuvant Radiotherapy (POLAR) in a meta-analysis of three randomized controlled trials of breast conserving surgery +/- radiotherapy [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr GS4-03.
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 | 0,038 | 0,057 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,001 |
| Méta-épidémiologie (sens large) | 0,011 | 0,049 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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; 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 ».