Prognostic analysis of three forms of Ki-67 in patients with breast cancer with non-pathological complete response before and after neoadjuvant systemic treatment

Abstract

Background: Patients who do not achieve a pathological complete response (pCR) after neoadjuvant systemic treatment (NST) have a significantly worse prognosis. A reliable predictor of prognosis is required to further subdivide non-pCR patients. To date, the prognostic role in terms of disease-free survival (DFS) between the terminal index of Ki-67 after surgery (Ki-67_T ) and the combination of the baseline Ki-67 at biopsy before NST (Ki-67_B ) and the percentage change in Ki-67 before and after NST (Ki-67_C ) has not been compared.

Aim: This study aimed to explore the most useful form or combination of Ki-67 that can provide prognostic information to non-pCR patients.

Patients and methods: We retrospectively reviewed 499 patients who were diagnosed with inoperable breast cancer between August 2013 and December 2020 and received NST with anthracycline plus taxane.

Results: Among all the patients, 335 did not achieve pCR (with a follow-up period of ≥1 year). The median follow-up duration was 36 months. The optimal cutoff value of Ki-67_C to predict a DFS was 30%. A significantly worse DFS was observed in patients with a low Ki-67_C (p < 0.001). In addition, the exploratory subgroup analysis showed relatively good internal consistency. Ki-67_C and Ki-67_T were considered as independent risk factors for DFS (both p < 0.001). The forecasting model combining Ki-67_B and Ki-67_C showed a significantly higher area under the curve at years 3 and 5 than Ki-67_T (p = 0.029 and p = 0.022, respectively).

Conclusions: Ki-67_C and Ki-67_T were good independent predictors of DFS, whereas Ki-67_B was a slightly inferior predictor. The combination of Ki-67_B and Ki-67_C is superior to Ki-67_T for predicting DFS, especially at longer follow-ups. Regarding clinical application, this combination could be used as a novel indicator for predicting DFS to more clearly identify high-risk patients.

Keywords: breast cancer; cell cycle; neoadjuvant chemotherapy; prognosis.

FIGURE 1

Study design and patient flow. _B, baseline; _C, percentage change; DFS, disease‐free survival; NST, neoadjuvant systemic treatment; pCR, pathological complete response; _T, terminal.

FIGURE 2

Subgroup analysis of disease‐free survival related to Ki‐67_C among non‐pCR patients. _B, baseline; _C, percentage change; CI, confidence interval; HR, hormone receptor; Non‐pCR, not achieved pathological complete response; TN, triple‐negative (HR−/HER2−).

FIGURE 3

Kaplan–Meier survival curve for disease‐free survival by Ki67_B (A), Ki67_C (B), and combination of Ki‐67_B and K‐67_C (C, D). _B, baseline; _C, percentage change; CI, confidence interval; low Ki‐67_B = Ki‐67_B ≤ 30%; high Ki‐67_B = Ki‐67_B > 30%; low Ki‐67_C = Ki‐67_C increased or ≤ 30% reduction; high Ki‐67_C = Ki‐67_C > 30% reduction.

FIGURE 4

Time‐dependent ROC curve analysis for the Cox regression models at year 1 (A), 3 (B), and 5 (B). AUC, area under the curve; _B, baseline; _C, percentage change; ROC, receiver operating characteristic; _T, terminal.