# A prediction model for predicting relapsed-free survival of early-stage invasive breast cancer patients with hormone receptor positive based on Ki67, HER2 and TOP2A

## TL;DR

This study developed a prediction model to estimate relapse-free survival in hormone receptor-positive breast cancer patients using biomarkers like Ki67, HER2, and TOP2A.

## Contribution

A novel nomogram model was developed to predict relapse-free survival in HR+ breast cancer patients using specific biomarkers and chemotherapy status.

## Key findings

- Chemotherapy, TOP2A, HER2, and Ki67 were identified as independent predictors of relapse-free survival.
- The developed nomogram showed good predictive ability for relapse-free survival in HR+ breast cancer patients.
- 23 out of 126 patients experienced relapse, with a median relapse-free survival of 29 months.

## Abstract

The purpose of the current study was to determine the relationship between ribonucleotide reductase M1 (RRM1), topoisomerase II alpha (TOP2A), Thymidylate synthase (TYMS), class III beta-tubulin (TUBB3) and phosphatase and tensin homolog (PTEN) expressions and relapse-free survival (RFS) in early-stage invasive breast cancer (IBC) patients with hormone receptor positive (HR+), as well as to develop a nomogram model for forecasting RFS.

Early-stage IBC patients with HR+ who were diagnosed and treated at the First Affiliated Hospital of Xi’an Jiaotong University from June 2017 to December 2020 were enrolled in this study. The survival analysis was performed by utilizing the Kaplan-Meier method, and the risk factors linked to patient RFS were determined by performing Cox regression analysis. The nomogram for predicting RFS in early-stage IBC patients with HR+ was stablished and validated based on the results of the Cox regression analysis.

In total, 126 early-stage IBC patients with HR+ were included in the current study. Among these patients, 23 cases experienced relapse after surgery, with a median RFS of 29 months. Significant relationships were observed between TYMS, RRM1, TUBB3, TOP2 and PTEN, Ki67 and human epidermal growth factor receptor 2 (HER2) and patient RFS. Cox regression analysis revealed that chemotherapy and higher expression levels of TOP2A, HER2 and Ki67 were independent predictors of RFS in early-stage IBC patients with HR+. The nomogram we constructed using the above independent risk factors exhibited good ability for predicting RFS in early-stage IBC patients with HR+.

Chemotherapy, TOP2A, HER2, and Ki67 expression were independent predictors of RFS in early-stage IBC patients with HR+. The nomogram we developed using these predictors is a reliable tool for predicting RFS in this patient population.