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Clinicopathological factors predict residual lymph node metastasis in locally advanced rectal cancer with ypT0-2

Yujun Cui1, Maxiaowei Song1, Jian Tie1

  • 1Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital and Institute, Beijing, 100142, China.

Journal of Cancer Research and Clinical Oncology
|April 4, 2024
PubMed
Summary

A new nomogram predicts residual lymph node metastases (RLNM) in locally advanced rectal cancer (LARC) patients after neoadjuvant chemoradiotherapy (NCRT). This tool aids in selecting patients for organ-preserving strategies, improving treatment outcomes.

Keywords:
Locally advanced rectal cancerNeoadjuvant chemoradiotherapyOrgan preservationResidual lymph node metastasesypT0-2

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Area of Science:

  • Oncology
  • Surgical Oncology
  • Radiotherapy

Background:

  • Residual lymph node metastases (RLNM) are a significant concern in locally advanced rectal cancer (LARC), impacting organ-preserving strategies and patient prognosis.
  • Accurate prediction of RLNM is crucial for tailoring treatment and improving outcomes in LARC patients.

Purpose of the Study:

  • To identify clinicopathological factors associated with RLNM in LARC patients with ypT0-2 stage after neoadjuvant chemoradiotherapy (NCRT).
  • To develop and validate a predictive nomogram for RLNM in this patient cohort.

Main Methods:

  • Retrospective analysis of 417 LARC patients (ypT0-2) treated with NCRT and total mesorectal excision (TME).
  • Development of a nomogram using binary logistic regression based on clinicopathological factors identified through multivariable analysis.
  • Performance evaluation of the nomogram using receiver operating characteristic (ROC) curves, calibration curves, decision curve analysis (DCA), and clinical impact curve (CIC).

Main Results:

  • The study identified MRI-defined mesorectal fascia (MRF)-positive status, high-grade biopsy histopathology, advanced ypT-category, and perineural invasion (PNI) as significant predictors of RLNM.
  • The developed nomogram demonstrated good discrimination and calibration, with an area under the ROC curve of 0.690.
  • DCA and CIC confirmed the clinical utility of the nomogram for predicting RLNM.

Conclusions:

  • A validated nomogram effectively predicts RLNM in LARC patients with ypT0-2 disease post-NCRT.
  • This predictive tool can assist clinicians in selecting appropriate candidates for organ-preserving treatment strategies, potentially improving patient selection and outcomes.