Multivariable Models Based on Baseline Imaging Features and Clinicopathological Characteristics to Predict Breast Pathologic Response after Neoadjuvant Chemotherapy in Patients with Breast Cancer.

ABSTRACT:

Introduction

Currently, the accurate evaluation and prediction of response to neoadjuvant chemotherapy (NAC) remains a great challenge. We developed several multivariate models based on baseline imaging features and clinicopathological characteristics to predict the breast pathologic complete response (pCR).

Methods

We retrospectively collected clinicopathological and imaging data of patients who received NAC and subsequent surgery for breast cancer at our hospital from June 2014 till September 2020. We used mammography, ultrasound, and magnetic resonance imaging (MRI) to investigate the breast tumors at baseline.

Results

A total of 308 patients were included and 111 patients achieved pCR. The HER-2 status and Ki-67 index were significant factors for pCR on univariate

SUBMITTER: Chen P 

PROVIDER: S-EPMC9247529 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature