نبذة مختصرة : The purpose of this study was to develop an algorithm to assist oncologists validate chemotherapy for early-stage breast cancer in elderly patients.Patients over 70 with early-stage breast cancer and a standardised Comprehensive Geriatric Assessment (CGA) made at baseline were screened. We assessed the benefit/risk balance of a therapeutic strategy escalation with simulated efficacy (PREDICT tool) and tolerability data (CRASH test). We defined 3 new study cohorts based on simulated survival benefit. In conclusion, we presented a decision algorithm with therapeutic escalation or de-escalation strategy (EEBC algorithm). Even though 74% of the patients had been initially assigned to chemotherapy, only 34% had finally received this treatment. Significant geriatric differences were found between patients given an initial decision to receive chemotherapy, or not, but these differences were almost absent in patients with completed surgery. Treatment without chemotherapy was expected to result in a 5-year OS loss of 3.2%-4.0%. No additional chemo-induced toxicities were expected. In simulated cohorts, considering the potential gain in overall survival, patients with the highest expected gain after 5 years (16.7%) and the highest expected benefit from chemotherapy (9.5%) had the lowest proposed chemotherapy rate (73.1%) despite the absence of the expected additional simulated chemo-induced toxicities. Finally, the EEBC algorithm proposed 62% de-escalation and 38% escalation approaches. Results should be confirmed in a validation cohort and the algorithm should be tested in a randomised study comparing usual practice versus EEBC-guided practice. ; Le but de cette étude était de développer un algorithme décisionnel de chimiothérapie dans le cancer du sein localisé chez le sujet âgé.Les patients de plus de 70 ans atteints d'un cancer du sein localisé et ayant bénéficié d'une évaluation gériatrique complète standardisée ont été sélectionnées. Nous avons évalué le rapport bénéfice/risque d'une stratégie d'escalade ...
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