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A Simplified Novel Algorithm to Predict the 21-Gene Recurrence Score.

Maher A Sughayer1, Bayan Maraqa1, Batool Qura'an2

  • 1Department of Pathology and Laboratory Medicine, King Hussein Cancer Center, Amman, Jordan.

World Journal of Oncology
|November 10, 2025
PubMed
Summary

A new algorithm using histologic grade and progesterone receptor (PR) expression accurately predicts Oncotype DX recurrence score (RS) categories. This tool aids breast cancer treatment decisions, especially where molecular testing is limited.

Keywords:
21-gene recurrence scoreBreast cancerHistologic gradeOncotype DXPredictive algorithmProgesterone receptor

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Area of Science:

  • Oncology
  • Pathology
  • Genomics

Background:

  • The 21-gene recurrence score (Oncotype DX) is crucial for adjuvant chemotherapy decisions in early-stage ER+/HER2- breast cancer.
  • High cost and limited availability of Oncotype DX necessitate simpler predictive models using routine pathology parameters.

Purpose of the Study:

  • To develop and validate a practical, rule-based algorithm for predicting Oncotype DX recurrence score (RS) categories.
  • To utilize histologic grade and progesterone receptor (PR) expression percentage for risk stratification.

Main Methods:

  • Retrospective study of 528 ER+/HER2- early breast cancer patients who underwent Oncotype DX testing.
  • Random assignment to learning (n=377) and validation (n=151) sets.
  • Univariate analysis and ROC curves to determine PR% cut-offs within histologic grades for risk stratification.

Main Results:

  • Histologic grade and PR% were significantly associated with RS.
  • Grade 1 tumors were low-risk; Grade 2 required PR ≥ 60% for low RS; Grade 3 required PR < 40% for high risk.
  • The algorithm achieved 87.5% sensitivity, 100% specificity, and 99% overall accuracy in the validation set, stratifying ~65% of cases.

Conclusions:

  • A simplified algorithm accurately predicts Oncotype DX RS category using histologic grade and PR%.
  • This tool enables confident risk stratification without molecular testing, offering a low-cost, practical solution.
  • Particularly beneficial in resource-limited settings for clinical decision-making.