Prognostic model for advanced breast carcinoma with luminal subtype and impact of hormonal maintenance: Implications for post-progression and conditional survival. (October 2016)

• Record Type: Journal Article
• Authors: Carbognin, Luisa; Sperduti, Isabella; Ciccarese, Mariangela; Fabi, Alessandra; Petrucelli, Luciana; Vari, Sabrina; Forcignanò, Rosa Chiara; Nortilli, Rolando; Vicentini, Cecilia; Pilotto, Sara; Merler, Sara; Zampiva, Ilaria; Brunelli, Matteo; Manfrin, Erminia; Giannarelli, Diana; Tortora, Giampaolo; Bria, Emilio
• Is Part Of: Breast. Volume 29(2016)
• Page Start: 24
• Page End: 30
• Publication Date: 2016-10
• Subjects: Breast cancer -- Luminal -- Advanced breast -- Prognosis; Breast -- Diseases -- Periodicals; Breast -- Tumors -- Periodicals; Breast -- Periodicals; Electronic journals; Periodicals; 616
• DOI: 10.1016/j.breast.2016.06.021
• Languages: English
• ISSNs: 0960-9776

Abstract

Abstract: Background: The aim of this analysis was to develop and validate a prognostic model for advanced breast cancer (ABC) with luminal subtype based on the combination of clinical, pathological and therapeutic predictors to provide a practical tool to evaluate patients' prognosis. Methods: Clinical and pathological data were retrospectively correlated to progression-free and overall survival (PFS/OS) using a Cox model. Significant treatment variables were adjusted with the propensity score analysis. A continuous score to identify risk classes was derived according to model ratios. The performance of the risk-class model was tested for post-progression survival (PPS) and conditional survival (CS) as well. Results: Data from 335 patients (3 institutions) were gathered (median follow-up 58 months). At multivariate analysis Ki67, Performance Status (PS) and number of metastatic sites were significant predictors for PFS, whereas Ki67, PS, brain metastases, PFS after 1st-line therapy, number of chemotherapy lines, hormonal therapy and maintenance were significant predictors for OS. The hormonal maintenance resulted to be prognostic after adjustment with propensity score analysis. A two-class model significantly differentiated low-risk and high-risk patients for 2-year PFS (31.5% and 11.0%, p < 0.0001 ), and 3-years OS (57.1% and 4.8%, p < 0.0001 ). A three-class model separated low risk, intermediate-risk, and high-risk patients for 2-year PFS (40.8%, 24.4%, and 11.0%, p < 0.0001 ) and 3-year OS (68.1%, 24.8%, and 4.8%, p < 0.0001 ). Both models equally discriminate the luminal ABC prognosis in terms of PPS and CS. Conclusions: A risk stratification model including ' easy-to-obtain ' clinical, pathological and therapeutic parameters accurately separates luminal ABC patients into different risk classes. Highlights: Prognosis of luminal advanced breast cancer (ABC) appears currently unpredictable. The current analysis creates and validates a prognostic nomogram for luminal ABC. The deriving model strikingly discriminates prognosis at different time-points. Among therapeutic variables, the hormonal maintenance prolongs patients' outcome.