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<p>The 21-gene Oncotype DX (ODX) recurrence score (RS) is the standard for HR + /HER2- early breast cancer risk stratification, but prohibitive costs limit global accessibility. This meta-analysis of 13 studies (<i>N</i> = 5396) validates the Magee Equations (ME)—utilizing routine pathology (grade, ER/PR/HER2/Ki-67)—as a safe triage tool. For the TAILORx threshold (RS 26 or higher), a ME &lt;18 yielded a pooled negative predictive value (NPV) of 0.96 (95% CI: 0.94–0.97) and a 62% test-sparing rate. At the RS 31 or higher threshold, NPV increased to 0.99. Qualitative synthesis identified inter-observer variability in mitotic counting and Ki-67 scoring as primary discordance drivers. While manual subjectivity remains a constraint, Magee-based triage provides a robust histopathological signal. Integrating AI-driven digital pathomics offers a transformative pathway to standardize interpretations and democratize precision oncology in resource-limited settings.</p>

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Validation of pathology-based triage for the 21-gene recurrence score: a meta-analysis and qualitative synthesis of the Magee equations

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月23日

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  • Thiti Susiriwatananont,
  • Panuch Eiamprapaporn,
  • Yaohua Ma,
  • Phuwanat Sakornsakolpat,
  • Jirawat Thanestada,
  • Yi Liu,
  • E. Aubrey Thompson,
  • Saranya Chumsri

摘要

The 21-gene Oncotype DX (ODX) recurrence score (RS) is the standard for HR + /HER2- early breast cancer risk stratification, but prohibitive costs limit global accessibility. This meta-analysis of 13 studies (N = 5396) validates the Magee Equations (ME)—utilizing routine pathology (grade, ER/PR/HER2/Ki-67)—as a safe triage tool. For the TAILORx threshold (RS 26 or higher), a ME <18 yielded a pooled negative predictive value (NPV) of 0.96 (95% CI: 0.94–0.97) and a 62% test-sparing rate. At the RS 31 or higher threshold, NPV increased to 0.99. Qualitative synthesis identified inter-observer variability in mitotic counting and Ki-67 scoring as primary discordance drivers. While manual subjectivity remains a constraint, Magee-based triage provides a robust histopathological signal. Integrating AI-driven digital pathomics offers a transformative pathway to standardize interpretations and democratize precision oncology in resource-limited settings.