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A Predictive Model to Evaluate Pathologic Complete Response in Rectal Adenocarcinoma.

Shuiwang Qing1, Lei Gu1, Tingting Du2

  • 1Department of Radiation Oncology, Changhai Hospital of Naval Military Medical University, Shanghai, China.

Technology in Cancer Research & Treatment
|September 26, 2023
PubMed
Summary

Circumferential tumor extent rate, CEA levels, and interval time predict pathological complete response in rectal cancer patients receiving neoadjuvant chemoradiotherapy. MMR status is also a key factor in ultra-low rectal cancer.

Keywords:
pCRpredictive modelpreoperative chemo-radiotherapyrectal cancerultra-low rectal cancer

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Area of Science:

  • Oncology
  • Gastroenterology
  • Radiotherapy

Background:

  • Neoadjuvant chemoradiotherapy (nCRT) is standard for locally advanced rectal cancer (LARC).
  • Predicting pathological complete response (pCR) is crucial for treatment individualization.
  • Ultra-low rectal cancer presents unique challenges in treatment response assessment.

Purpose of the Study:

  • To identify predictive factors for pCR in LARC patients undergoing nCRT.
  • To specifically analyze predictive factors for pCR in ultra-low rectal cancer.
  • To develop and evaluate predictive models for pCR in LARC.

Main Methods:

  • Retrospective analysis of 402 LARC patients treated with nCRT.
  • Univariate and multivariate logistic regression analyses to identify predictive factors.
  • Area Under the Curve (AUC) analysis to assess predictive model performance.

Main Results:

  • Circumferential tumor extent rate (CER), CEA levels, and interval to surgery predicted pCR in all LARC patients.
  • The predictive model for all LARC patients achieved an AUC of 0.709.
  • In ultra-low rectal cancer, CER and mismatch repair (MMR) status predicted pCR, with an AUC of 0.653 for the model.

Conclusions:

  • Predictive models for pCR in LARC vary based on histologic types and MMR status.
  • These models can aid in stratifying LARC patients for individualized treatment.
  • CER, CEA, interval time, and MMR status are important factors for predicting nCRT response.