# A nomogram for predicting subsequent liver metastasis in patients with metastatic breast cancer

## TL;DR

This study developed a tool to predict liver metastasis in breast cancer patients, helping identify those at risk for better treatment planning.

## Contribution

A new competing risk nomogram was developed to predict liver metastasis in metastatic breast cancer patients.

## Key findings

- Menopausal status, HER-2 status, bone metastasis, and lung metastasis were identified as independent prognostic factors.
- The nomogram showed good discrimination with C-index values of 0.719 in the training set and 0.740 in the validation set.
- Calibration curves confirmed the nomogram's accuracy, and a risk stratification divided patients into three prognostic groups.

## Abstract

To investigate the clinical characteristics of liver metastasis from metastatic breast cancer and construct a competing risk nomogram for predicting the probability of liver metastasis.

Clinical data of patients with metastatic breast cancer from Tianjin Medical University Cancer Institute during 2008–2018 were retrospectively collected. Independent prognostic factors were assessed by the Fine-Gray competing risk model. A competing risk nomogram was constructed by integrating those independent prognostic factors and evaluated with concordance index (C-index) and calibration curves.

A total of 1406 patients were retrospectively analyzed, and randomly divided into the training set (n=986) and the validation set (n=420). Multivariate analysis showed that menopausal status, HER-2 status, bone metastasis and lung metastasis were identified as independent prognostic factors in the nomogram. The C-index in the training set was 0.719 (95% CI: 0.706–0.732), and in the validation set was 0.740 (95% CI: 0.720–0.732). The calibration curves in the training set and validation set showed that the nomogram had a sufficient level of calibration. A risk stratification was further established to divide all the patients into three prognostic groups.

We had developed a tool that can predict subsequent liver metastasis from metastatic breast cancer, which may be useful for identifying the patients at risk of liver metastasis and guiding the individualized treatment. It had been verified that the nomogram has good discrimination and calibration, and had certain potential clinical value. This nomogram can be used to screen patients with low, intermediate and high risk of liver metastasis from metastatic breast cancer, so as to develop a more complete follow-up plan.