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April 24, 2026The Oncologist0 citationsOpen Access

Prognostic Utility of Systemic Immune-Inflammation Markers in Locally Advanced Cervical Cancer Undergoing Radical Radiotherapy

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YLYue LiJHJing HanSXShuyue Xiao

Key Points

  • The aim is to evaluate the prognostic value of immune-inflammation markers in patients with locally advanced cervical cancer undergoing treatment.
  • Utilized both nomogram and machine learning models for prediction.
  • Compared predictive accuracy over a 1-5 year follow-up period.
  • Machine learning models demonstrated higher predictive accuracy than nomograms.
  • Both models provided valuable insights into patient outcomes.

Abstract

Both nomogram and ML models provide valuable prognostic insights for LACC. The logistic regression ML model showed superior predictive accuracy compared to the nomogram during 1-5 years of follow-up.

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Cite This Study

Li et al. (2026) studied this question.

synapsesocial.com/papers/69eb08ef553a5433e34b3ac6https://doi.org/10.1093/oncolo/oyag139
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Development, validation, and visualization of a novel nomogram for predicting clinical outcomes of radiotherapy combined with chemotherapy in locally advanced cervical cancer2025 · 2 citations
  2. 2Development and Validation of a Nomogram Integrating Body Composition and Inflammatory Markers to Predict Concurrent Chemoradiotherapy Response in Locally Advanced Cervical Cancer2026
  3. 3Dynamic multimodal radiomic model for survival prediction in cervical cancer: a multi-cohort study2026
  4. 4Inflammatory biomarker-based prognostic model for immunotherapy outcomes in patients with recurrent or metastatic cervical cancer.2026
  5. 5Machine learning–based prognostic modeling for locally advanced non-small cell lung cancer treated with immuno-radiotherapy2025