Development and External Validation of a Novel Nomogram Predicting Cancer-specific Mortality-free Survival in Surgically Treated Papillary Renal Cell Carcinoma Patients

TY - JOUR

T1 - Development and External Validation of a Novel Nomogram Predicting Cancer-specific Mortality-free Survival in Surgically Treated Papillary Renal Cell Carcinoma Patients

AU - Piccinelli, Mattia Luca

AU - Barletta, Francesco

AU - Tappero, Stefano

AU - Cano Garcia, Cristina

AU - Incesu, Reha-Baris

AU - Morra, Simone

AU - Scheipner, Lukas

AU - Tian, Zhe

AU - Luzzago, Stefano

AU - Mistretta, Francesco A

AU - Ferro, Matteo

AU - Saad, Fred

AU - Shariat, Shahrokh F

AU - Ahyai, Sascha

AU - Longo, Nicola

AU - Tilki, Derya

AU - Chun, Felix K H

AU - Terrone, Carlo

AU - Briganti, Alberto

AU - de Cobelli, Ottavio

AU - Musi, Gennaro

AU - Karakiewicz, Pierre I

N1 - Copyright © 2023 European Association of Urology. All rights reserved.

PY - 2023/9

Y1 - 2023/9

N2 - BACKGROUND: Accurate prediction of cancer control outcomes in renal cell carcinoma (RCC) patients is important for counselling, follow-up planning, and selection of appropriate adjuvant trial designs.OBJECTIVE: To develop and externally validate a novel contemporary population-based model for predicting cancer-specific mortality-free survival (CSM-FS) in surgically treated papillary RCC (papRCC) patients and to compare it with established risk categories (Leibovich 2018).DESIGN, SETTING, AND PARTICIPANTS: Within the Surveillance, Epidemiology, and End Results database (2004-2019), we identified surgically treated papRCC patients (n = 3978). The population was randomly divided into development (50%, n = 1989) and external validation (50%, n = 1989) cohorts. Of the external validation cohort, 97% (n = 1930) of patients were included in a head-to-head comparison of the Leibovich 2018 risk categories addressing nonmetastatic patients.OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Univariable Cox regression models tested the statistical significance in the prediction of CSM-FS. The most parsimonious model with the best validation metrics was selected as the multivariable nomogram. Accuracy, calibration, and decision curve analyses (DCAs) tested the Cox regression-based nomogram, as well as the Leibovich 2018 risk categories in the external validation cohort.RESULTS AND LIMITATIONS: Age at diagnosis, grade, T stage, N stage, and M stage qualified for inclusion in the novel nomogram. In external validation, the accuracy of the novel nomogram was 0.83 at 5 yr and 0.80 at 10 yr. In nonmetastatic patients, 5- and 10-yr accuracy of the novel nomogram was 0.77 and 0.76, respectively. Conversely, 5- and 10-yr accuracy of the Leibovich 2018 risk categories was 0.70 and 0.66, respectively. The novel nomogram exhibited smaller departures from ideal predictions in calibration plots and higher net benefit in DCAs, when it was compared with the Leibovich 2018 risk categories. Limitations include the retrospective nature of the study, absence of a central pathological review, and inclusion of only North American patients.CONCLUSIONS: The novel nomogram may represent a valuable clinical aid, when papRCC CSM-FS predictions are required.PATIENT SUMMARY: We developed an accurate tool to predict death due to papillary kidney cancer in a North American population.

AB - BACKGROUND: Accurate prediction of cancer control outcomes in renal cell carcinoma (RCC) patients is important for counselling, follow-up planning, and selection of appropriate adjuvant trial designs.OBJECTIVE: To develop and externally validate a novel contemporary population-based model for predicting cancer-specific mortality-free survival (CSM-FS) in surgically treated papillary RCC (papRCC) patients and to compare it with established risk categories (Leibovich 2018).DESIGN, SETTING, AND PARTICIPANTS: Within the Surveillance, Epidemiology, and End Results database (2004-2019), we identified surgically treated papRCC patients (n = 3978). The population was randomly divided into development (50%, n = 1989) and external validation (50%, n = 1989) cohorts. Of the external validation cohort, 97% (n = 1930) of patients were included in a head-to-head comparison of the Leibovich 2018 risk categories addressing nonmetastatic patients.OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Univariable Cox regression models tested the statistical significance in the prediction of CSM-FS. The most parsimonious model with the best validation metrics was selected as the multivariable nomogram. Accuracy, calibration, and decision curve analyses (DCAs) tested the Cox regression-based nomogram, as well as the Leibovich 2018 risk categories in the external validation cohort.RESULTS AND LIMITATIONS: Age at diagnosis, grade, T stage, N stage, and M stage qualified for inclusion in the novel nomogram. In external validation, the accuracy of the novel nomogram was 0.83 at 5 yr and 0.80 at 10 yr. In nonmetastatic patients, 5- and 10-yr accuracy of the novel nomogram was 0.77 and 0.76, respectively. Conversely, 5- and 10-yr accuracy of the Leibovich 2018 risk categories was 0.70 and 0.66, respectively. The novel nomogram exhibited smaller departures from ideal predictions in calibration plots and higher net benefit in DCAs, when it was compared with the Leibovich 2018 risk categories. Limitations include the retrospective nature of the study, absence of a central pathological review, and inclusion of only North American patients.CONCLUSIONS: The novel nomogram may represent a valuable clinical aid, when papRCC CSM-FS predictions are required.PATIENT SUMMARY: We developed an accurate tool to predict death due to papillary kidney cancer in a North American population.

KW - Humans

KW - Carcinoma, Renal Cell/pathology

KW - Nomograms

KW - Prognosis

KW - Retrospective Studies

KW - Nephrectomy/methods

KW - Kidney Neoplasms/pathology

U2 - 10.1016/j.euf.2023.03.014

DO - 10.1016/j.euf.2023.03.014

M3 - SCORING: Journal article

C2 - 37024421

VL - 9

SP - 799

EP - 806

JO - EUR UROL FOCUS

JF - EUR UROL FOCUS

SN - 2405-4569

IS - 5

ER -