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A nomogram for predicting lymph node metastases in nonmetastatic muscle-invasive bladder cancer: a SEER-based investigation

  • 0Department of Urology, Zhejiang Cancer Hospital, Hangzhou, China.
International Journal of Surgery (london, England) +

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January 8, 2025

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January 8, 2025

View abstract on PubMed

Summary

This summary is machine-generated.

This study developed a predictive model to identify lymph node metastasis risk in muscle-invasive bladder cancer (MIBC). Key risk factors include larger tumor size, poor grade, and advanced stage, aiding clinical decision-making.

Area Of Science

  • Urology
  • Oncology
  • Medical Informatics

Background

  • Muscle-invasive bladder cancer (MIBC) poses significant treatment challenges.
  • Accurate prediction of lymph node metastasis (pN+) is crucial for staging and treatment planning in MIBC.
  • Existing models may not fully capture the complexity of pN+ risk stratification.

Purpose Of The Study

  • To develop and validate a predictive nomogram model for lymph node metastasis in non-metastatic MIBC patients.
  • To establish a risk classification system to stratify MIBC patients based on pN+ probability.
  • To enhance clinical decision-making and patient outcome estimation for MIBC.

Main Methods

  • Utilized a large population-based cancer database for retrospective analysis.
  • Developed a nomogram incorporating key clinicopathological variables.
  • Validated the predictive accuracy and discriminatory performance of the nomogram.

Main Results

  • Identified independent risk factors for pN+ in MIBC: larger tumor size, overlapping lesions, younger age, female sex, poorly differentiated histological grade, and advanced T stage.
  • The developed nomogram demonstrated precise prediction of pN+ probability.
  • The risk classification system effectively stratified patients into different risk categories.

Conclusions

  • The predictive nomogram offers a valuable tool for precise risk stratification of MIBC patients regarding lymph node metastasis.
  • This model can aid clinicians in tailoring treatment strategies and improving prognostic accuracy for MIBC.
  • Further validation in diverse cohorts is warranted to solidify its clinical utility.