R X Wong1, F Y Wong2, John Lim3, W X Lian2, Y S Yap4. 1. National Cancer Centre Singapore, Department of Radiation Oncology, Singapore. Electronic address: Wong.Ru.Xin@singhealth.com.sg. 2. National Cancer Centre Singapore, Department of Radiation Oncology, Singapore. 3. National Cancer Centre Singapore, Division of Clinical Trials and Epidemiological Sciences, Singapore. 4. National Cancer Centre Singapore, Department of Medical Oncology, Singapore.
Abstract
AIMS: We aim to validate the AJCC 8th edition prognostic staging system for breast cancer in an Asian setting. METHODS: Clinico-pathologic information and cancer-specific survival (CSS) outcomes of 6287 stage I to III patients with invasive breast cancer who underwent upfront surgery at SingHealth institutions in Singapore from 2006 to 2014 were analyzed. Survival distributions for the different staging systems were estimated by the Kaplan-Meier method and compared using the log-rank tests. Multivariable Cox proportional hazards models were used, with Akaike Information Criterion (AIC) and Harrell's Concordance Index (C-index) to compare both staging systems. Among patients with positive hormone-receptor status, 84.8% received endocrine therapy. Among the cohort, 60.3% of received chemotherapy; 82.1% of node positive patients received chemotherapy and 86.0% of HER2-enriched patients in whom chemotherapy was also indicated received adjuvant HER2-targeted therapy. Ninety-seven percent of patients received anthracyclines and/or taxanes containing chemotherapy regime. RESULTS: The median follow up was 64 months. 2921 patients (46.5%) were discordant between the anatomic and prognostic systems of which 363 (5.8%) were upstaged and 2558 (40.7%) were down-staged. For all patients, stages in both the prognostic and anatomic systems were discriminating for 5-year CSS. Controlling for age, ethnicity and receipt of chemotherapy, the prognostic staging system model (AIC = 7538.87, C = 0.79) presented slightly better explanation and concordance of survival times than the anatomic staging system model (AIC = 7607.31, C = 0.77). CONCLUSION: The prognostic staging system was better than the anatomic staging system in predicting outcomes but the anatomic system remains relevant due to its ease of use.
AIMS: We aim to validate the AJCC 8th edition prognostic staging system for breast cancer in an Asian setting. METHODS: Clinico-pathologic information and cancer-specific survival (CSS) outcomes of 6287 stage I to III patients with invasive breast cancer who underwent upfront surgery at SingHealth institutions in Singapore from 2006 to 2014 were analyzed. Survival distributions for the different staging systems were estimated by the Kaplan-Meier method and compared using the log-rank tests. Multivariable Cox proportional hazards models were used, with Akaike Information Criterion (AIC) and Harrell's Concordance Index (C-index) to compare both staging systems. Among patients with positive hormone-receptor status, 84.8% received endocrine therapy. Among the cohort, 60.3% of received chemotherapy; 82.1% of node positive patients received chemotherapy and 86.0% of HER2-enriched patients in whom chemotherapy was also indicated received adjuvant HER2-targeted therapy. Ninety-seven percent of patients received anthracyclines and/or taxanes containing chemotherapy regime. RESULTS: The median follow up was 64 months. 2921 patients (46.5%) were discordant between the anatomic and prognostic systems of which 363 (5.8%) were upstaged and 2558 (40.7%) were down-staged. For all patients, stages in both the prognostic and anatomic systems were discriminating for 5-year CSS. Controlling for age, ethnicity and receipt of chemotherapy, the prognostic staging system model (AIC = 7538.87, C = 0.79) presented slightly better explanation and concordance of survival times than the anatomic staging system model (AIC = 7607.31, C = 0.77). CONCLUSION: The prognostic staging system was better than the anatomic staging system in predicting outcomes but the anatomic system remains relevant due to its ease of use.
Authors: Olga Kantor; Harold J Burstein; Tari A King; Steven Shak; Christy A Russell; Armando E Giuliano; Gabriel N Hortobagyi; Eric P Winer; Larissa A Korde; Joseph A Sparano; Elizabeth A Mittendorf Journal: Ann Surg Oncol Date: 2022-07-27 Impact factor: 4.339
Authors: Yi Heng Seow; Ru Xin Wong; John Heng Chi Lim; Weixiang Lian; Yoon Sim Yap; Fuh Yong Wong Journal: J Breast Cancer Date: 2019-03-27 Impact factor: 3.588
Authors: Eun Jin Kim; Hyung Seok Park; Jee Ye Kim; Seung Il Kim; Young-Up Cho; Byeong-Woo Park Journal: J Breast Cancer Date: 2020-01-09 Impact factor: 3.588