# Nomogram Development for Assessing Oncotype DX Recurrence Scores in Breast Cancer: A Chinese Population Study

## TL;DR

This study creates a cost-effective tool to predict breast cancer recurrence risk in Chinese patients using clinicopathological factors, reducing the need for expensive genetic tests.

## Contribution

The paper introduces the first nomogram tailored for Chinese breast cancer patients to predict Oncotype DX recurrence scores using accessible clinical data.

## Key findings

- The nomogram achieved an AUC of 0.811 in the development group and 0.794 in the validation group.
- Older age, lower histologic grade, and higher ER expression were linked to lower recurrence risk.
- The nomogram outperformed the TAILORx-nomogram in predictive accuracy for Chinese patients.

## Abstract

Breast cancer (BC) is the most prevalent cancer among women worldwide, with increasing incidence rates, particularly in China. Given the high costs of Oncotype DX (ODX) testing, which predicts recurrence scores (RSs) on the basis of gene expression, developing a nomogram utilizing clinicopathological variables may provide an accessible alternative for risk stratification.

We conducted a retrospective analysis of 703 estrogen receptor (ER)‐positive, HER2‐negative T1‐3N0M0 BC patients who underwent ODX testing at Qilu Hospital. A nomogram was developed using multivariate logistic regression to predict low and high RSs in the group. Model performance was validated by receiver operating characteristic curve, calibration curve, and decision curve analysis.

Multivariate analysis revealed that older age, lower histologic grade, a higher ER expression level, a higher proportion of cells expressing progesterone receptor, and a lower proportion of cells expressing Ki‐67 were significantly associated with a patient being in the low‐risk subgroup. A nomogram was then developed using these variables to predict the RS, with an area under the curve (AUC) of 0.811 (95% confidence interval [CI] = 0.772–0.850) in the development group and 0.794 (95% CI = 0.737–0.851) in the validation group. Calibration and decision curve analyses further confirmed the nomogram's clinical utility. Moreover, a comparison between the TAILORx‐nomogram and our nomogram was conducted, which proved that our nomogram has better predictive accuracy and reliability in Chinese BC patients.

We present the first nomogram for predicting the RS in Chinese patients with BC on the basis of clinicopathological factors. This model could aid in identifying patients who may not need ODX testing and serve as a cost‐effective alternative for those unable to access ODX, thereby optimizing treatment decisions and enhancing patient management in resource‐limited settings.