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Cancer Survival Analysis

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Development And Validation Of A Nomogram For Predicting Postoperative Recurrence-free Survival In Patients With Nonmetastatic Pathological T3a Stage Renal Cell Carcinoma.

Home
Research Domains
Biomedical And Clinical Sciences
Oncology And Carcinogenesis
Predictive And Prognostic Markers
Development And Validation Of A Nomogram For Predicting Postoperative Recurrence-free Survival In Patients With Nonmetastatic Pathological T3a Stage Renal Cell Carcinoma.

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Development and Validation of a Nomogram for Predicting Postoperative Recurrence-Free Survival in Patients With Nonmetastatic Pathological T3a Stage Renal Cell Carcinoma.

Xintao Li¹, Qingbo Huang², Liangyou Gu²

¹Department of Urology, Air Force Medical Center, PLA, Air Force Medical University, Beijing, China; Department of Traditional Chinese Medicine, The Sixth Medical Centre, Chinese People's Liberation Army General Hospital, Beijing, China; Department of Urology, The Third Medical Centre, Chinese People's Liberation Army General Hospital, Beijing, China.

Clinical Genitourinary Cancer

|September 14, 2024

View abstract on PubMed

Summary

This summary is machine-generated.

Keywords:

Nephrectomy Prognostic nomogram Risk stratification

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This study developed a nomogram to predict recurrence-free survival (RFS) in nonmetastatic renal cell carcinoma (RCC) patients. The model accurately identifies high-risk patients, aiding in personalized treatment strategies for pathological T3a RCC.

Area of Science:

Urology
Oncology
Medical Statistics

Background:

Nonmetastatic renal cell carcinoma (RCC) patients with pathological T3a (pT3a) stage undergoing nephrectomy face risks of recurrence.
Accurate prediction of postoperative recurrence-free survival (RFS) is crucial for managing these patients.

Purpose of the Study:

To establish a predictive nomogram for RFS in patients with nonmetastatic pT3a RCC.
To identify key prognostic factors influencing RFS in this patient cohort.

Main Methods:

Retrospective review of 668 pT3a RCC patients (2008-2019), divided into training and validation sets.
Cox regression analysis to develop the RFS-predicting nomogram.
Performance evaluation using C-index, ROC curves, decision curve analysis, and Kaplan-Meier survival analysis.

Main Results:

Multivariable Cox regression identified tumor size, ISUP grade, necrosis, capsular invasion, and pT3a invasion pattern as significant RFS predictors.
The nomogram achieved a C-index of 0.753 (training) and 0.762 (validation).
AUC values for 1, 3, and 5-year RFS were 0.814, 0.769, and 0.768, respectively; decision curve analysis supported clinical utility.

Conclusions:

Tumor size, ISUP grade, necrosis, capsular invasion, and T3a invasion patterns are independent risk factors for worse RFS in nonmetastatic pT3a RCC.
The developed nomogram effectively predicts RFS in patients with nonmetastatic pT3a RCC, aiding clinical decision-making.