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Cancer Survival Analysis01:21

Cancer Survival Analysis

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Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
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Parameters That May Predict NAC Effectiveness in Hormone-Positive Breast Cancer According to CPS Score.

Mehmet Emin Buyukbayram1, Zekeriya Hannarici2, Aykut Turhan3

  • 1Department of Medical Oncology, Atatürk University Faculty of Medicine, Erzurum, Turkey.

Cancer Management and Research
|March 20, 2026
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Summary

Predicting neoadjuvant chemotherapy response in hormone-positive breast cancer is key. The study found axillary pathological response (ypN) correlates with the clinical-pathological stage score (CPS), aiding survival prediction.

Keywords:
breast neoplasmsneoadjuvant therapyprognosis

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Optimization of a Multiplex RNA-based Expression Assay Using Breast Cancer Archival Material
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Area of Science:

  • Oncology
  • Breast Cancer Research
  • Chemotherapy Efficacy

Background:

  • Neoadjuvant chemotherapy (NAC) improves outcomes in hormone-positive breast cancer, enabling breast-conserving surgery.
  • However, pathological complete response (pCR) rates to NAC remain low, necessitating predictive markers.
  • Identifying predictors of NAC response and survival is crucial for personalized treatment.

Purpose of the Study:

  • To investigate clinical, pathological, inflammatory, and metabolic parameters for predicting NAC response and survival in hormone-positive breast cancer.
  • To evaluate the association between the clinical-pathological stage score (CPS) and patient outcomes.
  • To identify reliable biomarkers for NAC response.

Main Methods:

  • Retrospective analysis of 120 hormone-positive breast cancer patients treated with NAC.
  • Calculation of CPS score based on clinical and pathological staging.
  • Statistical analysis including Kruskal Wallis, Bonferroni, and Pearson Chi-Square tests to assess parameter associations.

Main Results:

  • Axillary pathological response (ypN) showed a significant correlation with the CPS score (p=0.003).
  • pCR was significant in univariate but not multivariate analysis (p=0.258).
  • No significant association was found between the CPS score and inflammatory or metabolic markers.

Conclusions:

  • Axillary pathological response (ypN) is associated with the CPS score in predicting survival after NAC for hormone-positive breast cancer.
  • Inflammatory and metabolic parameters did not show a significant association with the CPS score.
  • Further validation in larger cohorts is recommended to confirm these findings.