Title: Evaluation of the best cut-off point for Ki-67 and progesterone receptor as a prognostic factor in hormone receptor-positive (HR+) breast cancer.
Abstract: e12549 Background: Because in much of the world the analysis of intrinsic subtype of breast cancer are not available, surrogate approaches have been developed using Immunohistochemistry (IHC) measurement of estrogen receptor, progesterone receptor (PR), HER2 and Ki-67. Different cut-off points for Ki-67 and RP have been established mainly to differentiate the Luminal A and Luminal B subtypes by IHC, but without total international agreement. The aim of this study was to identify the best cut-off point for Ki-67 and PR expression to stratify the prognosis of patients with HR+ breast cancer. Methods: We retrospectively examined a mono-institutional cohort of 506 stage I-III breast cancer patients with ER+ and/or PR+ and HER2+/-, diagnosed between 1998 and 2016. Univariate Cox-regression analysis for disease-free survival (DFS) was performed using different Ki-67 and PR cut-off points and comparing the hazard ratios (HR). ROC curves were used to determine the accurate value with the best sensitivity and specificity to predict relapse. In order to estimate the association between Ki-67 and PR values with the other standard clinico-pathological variables, multivariable Cox proportional hazards regression model was used. Results: The univariate analysis of Ki-67, revealed that the cut-off point of 20% had the highest HR for DFS (HR 7.14; 95% CI, 3.87 to 13.16; p < 0.001). For PR this value was 30% (HR 5.30; 95% IC, 3,02 to 9.31; p < 0.001). ROC curve analysis showed that Ki-67 of 23.4% (AUC 0.72; p < 0.001) and PR of 32.5% (AUC 0.77; p < 0.001) had the best sensitivity and specificity to predict relapse. The multivariate analysis confirmed that these values were independently associated with DFS (Table). Conclusions: In our study, Ki-67 of 23.4% and PR of 32.5% were the most effective cut-off points to be used as independent prognostic factors in HR+ breast cancer patients. Multivariate analysis for DFS. Variables DFS HR (95% CI) p-value Grade (3 vs 2/1) 1.37 (0.73-2.57) 0.322 Tumor size ( > 2 cm vs ≤2 cm) 1.64 (0.71-3.81) 0.247 HER2 (+ vs -) 2.15 (1.02-4.54) 0.044 Node Status (+ vs -) 3.34 (1.59-6.99) 0.001 PR (≤32.5% vs > 32.5%) 2.89 (1.44-5.79) 0.003 Ki-67 ( > 23.4% vs ≤23.4%) 3.52 (1.66-7.49) 0.001
Publication Year: 2018
Publication Date: 2018-05-20
Language: en
Type: article
Indexed In: ['crossref']
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Cited By Count: 3
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