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Critical Appraisal of Leibovich 2018 and GRANT Models for Prediction of Cancer-Specific Survival in Non-Metastatic Chromophobe Renal Cell Carcinoma

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Critical Appraisal of Leibovich 2018 and GRANT Models for Prediction of Cancer-Specific Survival in Non-Metastatic Chromophobe Renal Cell Carcinoma. / Piccinelli, Mattia Luca; Morra, Simone; Tappero, Stefano; Cano Garcia, Cristina; Barletta, Francesco; Incesu, Reha-Baris; Scheipner, Lukas; Baudo, Andrea; Tian, Zhe; Luzzago, Stefano; Mistretta, Francesco Alessandro; Ferro, Matteo; Saad, Fred; Shariat, Shahrokh F; Carmignani, Luca; Ahyai, Sascha; Tilki, Derya; Briganti, Alberto; Chun, Felix K H; Terrone, Carlo; Longo, Nicola; de Cobelli, Ottavio; Musi, Gennaro; Karakiewicz, Pierre I.

In: CANCERS, Vol. 15, No. 7, 2155, 05.04.2023.

Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review

Harvard

Piccinelli, ML, Morra, S, Tappero, S, Cano Garcia, C, Barletta, F, Incesu, R-B, Scheipner, L, Baudo, A, Tian, Z, Luzzago, S, Mistretta, FA, Ferro, M, Saad, F, Shariat, SF, Carmignani, L, Ahyai, S, Tilki, D, Briganti, A, Chun, FKH, Terrone, C, Longo, N, de Cobelli, O, Musi, G & Karakiewicz, PI 2023, 'Critical Appraisal of Leibovich 2018 and GRANT Models for Prediction of Cancer-Specific Survival in Non-Metastatic Chromophobe Renal Cell Carcinoma', CANCERS, vol. 15, no. 7, 2155. https://doi.org/10.3390/cancers15072155

APA

Piccinelli, M. L., Morra, S., Tappero, S., Cano Garcia, C., Barletta, F., Incesu, R-B., Scheipner, L., Baudo, A., Tian, Z., Luzzago, S., Mistretta, F. A., Ferro, M., Saad, F., Shariat, S. F., Carmignani, L., Ahyai, S., Tilki, D., Briganti, A., Chun, F. K. H., ... Karakiewicz, P. I. (2023). Critical Appraisal of Leibovich 2018 and GRANT Models for Prediction of Cancer-Specific Survival in Non-Metastatic Chromophobe Renal Cell Carcinoma. CANCERS, 15(7), [2155]. https://doi.org/10.3390/cancers15072155

Vancouver

Piccinelli ML, Morra S, Tappero S, Cano Garcia C, Barletta F, Incesu R-B et al. Critical Appraisal of Leibovich 2018 and GRANT Models for Prediction of Cancer-Specific Survival in Non-Metastatic Chromophobe Renal Cell Carcinoma. CANCERS. 2023 Apr 5;15(7). 2155. https://doi.org/10.3390/cancers15072155

Bibtex

@article{d7fe88207d6743658c70aed142fc1843,
title = "Critical Appraisal of Leibovich 2018 and GRANT Models for Prediction of Cancer-Specific Survival in Non-Metastatic Chromophobe Renal Cell Carcinoma",
abstract = "Within the Surveillance, Epidemiology, and End Results database (2000-2019), we identified 5522 unilateral surgically treated non-metastatic chromophobe kidney cancer (chRCC) patients. This population was randomly divided into development vs. external validation cohorts. In the development cohort, the original Leibovich 2018 and GRANT categories were applied to predict 5- and 10-year cancer-specific survival (CSS). Subsequently, a novel multivariable nomogram was developed. Accuracy, calibration and decision curve analyses (DCA) tested the Cox regression-based nomogram as well as the Leibovich 2018 and GRANT risk categories in the external validation cohort. The accuracy of the Leibovich 2018 and GRANT models was 0.65 and 0.64 at ten years, respectively. The novel prognostic nomogram had an accuracy of 0.78 at ten years. All models exhibited good calibration. In DCA, Leibovich 2018 outperformed the novel nomogram within selected ranges of threshold probabilities at ten years. Conversely, the novel nomogram outperformed Leibovich 2018 for other values of threshold probabilities. In summary, Leibovich 2018 and GRANT risk categories exhibited borderline low accuracy in predicting CSS in North American non-metastatic chRCC patients. Conversely, the novel nomogram exhibited higher accuracy. However, in DCA, all examined models exhibited limitations within specific threshold probability intervals. In consequence, all three examined models provide individual predictions that might be suboptimal and be affected by limitations determined by the natural history of chRCC, where few deaths occur within ten years from surgery. Further investigations regarding established and novel predictors of CSS and relying on large sample sizes with longer follow-up are needed to better stratify CSS in chRCC.",
author = "Piccinelli, {Mattia Luca} and Simone Morra and Stefano Tappero and {Cano Garcia}, Cristina and Francesco Barletta and Reha-Baris Incesu and Lukas Scheipner and Andrea Baudo and Zhe Tian and Stefano Luzzago and Mistretta, {Francesco Alessandro} and Matteo Ferro and Fred Saad and Shariat, {Shahrokh F} and Luca Carmignani and Sascha Ahyai and Derya Tilki and Alberto Briganti and Chun, {Felix K H} and Carlo Terrone and Nicola Longo and {de Cobelli}, Ottavio and Gennaro Musi and Karakiewicz, {Pierre I}",
year = "2023",
month = apr,
day = "5",
doi = "10.3390/cancers15072155",
language = "English",
volume = "15",
journal = "CANCERS",
issn = "2072-6694",
publisher = "Multidisciplinary Digital Publishing Institute (MDPI)",
number = "7",

}

RIS

TY - JOUR

T1 - Critical Appraisal of Leibovich 2018 and GRANT Models for Prediction of Cancer-Specific Survival in Non-Metastatic Chromophobe Renal Cell Carcinoma

AU - Piccinelli, Mattia Luca

AU - Morra, Simone

AU - Tappero, Stefano

AU - Cano Garcia, Cristina

AU - Barletta, Francesco

AU - Incesu, Reha-Baris

AU - Scheipner, Lukas

AU - Baudo, Andrea

AU - Tian, Zhe

AU - Luzzago, Stefano

AU - Mistretta, Francesco Alessandro

AU - Ferro, Matteo

AU - Saad, Fred

AU - Shariat, Shahrokh F

AU - Carmignani, Luca

AU - Ahyai, Sascha

AU - Tilki, Derya

AU - Briganti, Alberto

AU - Chun, Felix K H

AU - Terrone, Carlo

AU - Longo, Nicola

AU - de Cobelli, Ottavio

AU - Musi, Gennaro

AU - Karakiewicz, Pierre I

PY - 2023/4/5

Y1 - 2023/4/5

N2 - Within the Surveillance, Epidemiology, and End Results database (2000-2019), we identified 5522 unilateral surgically treated non-metastatic chromophobe kidney cancer (chRCC) patients. This population was randomly divided into development vs. external validation cohorts. In the development cohort, the original Leibovich 2018 and GRANT categories were applied to predict 5- and 10-year cancer-specific survival (CSS). Subsequently, a novel multivariable nomogram was developed. Accuracy, calibration and decision curve analyses (DCA) tested the Cox regression-based nomogram as well as the Leibovich 2018 and GRANT risk categories in the external validation cohort. The accuracy of the Leibovich 2018 and GRANT models was 0.65 and 0.64 at ten years, respectively. The novel prognostic nomogram had an accuracy of 0.78 at ten years. All models exhibited good calibration. In DCA, Leibovich 2018 outperformed the novel nomogram within selected ranges of threshold probabilities at ten years. Conversely, the novel nomogram outperformed Leibovich 2018 for other values of threshold probabilities. In summary, Leibovich 2018 and GRANT risk categories exhibited borderline low accuracy in predicting CSS in North American non-metastatic chRCC patients. Conversely, the novel nomogram exhibited higher accuracy. However, in DCA, all examined models exhibited limitations within specific threshold probability intervals. In consequence, all three examined models provide individual predictions that might be suboptimal and be affected by limitations determined by the natural history of chRCC, where few deaths occur within ten years from surgery. Further investigations regarding established and novel predictors of CSS and relying on large sample sizes with longer follow-up are needed to better stratify CSS in chRCC.

AB - Within the Surveillance, Epidemiology, and End Results database (2000-2019), we identified 5522 unilateral surgically treated non-metastatic chromophobe kidney cancer (chRCC) patients. This population was randomly divided into development vs. external validation cohorts. In the development cohort, the original Leibovich 2018 and GRANT categories were applied to predict 5- and 10-year cancer-specific survival (CSS). Subsequently, a novel multivariable nomogram was developed. Accuracy, calibration and decision curve analyses (DCA) tested the Cox regression-based nomogram as well as the Leibovich 2018 and GRANT risk categories in the external validation cohort. The accuracy of the Leibovich 2018 and GRANT models was 0.65 and 0.64 at ten years, respectively. The novel prognostic nomogram had an accuracy of 0.78 at ten years. All models exhibited good calibration. In DCA, Leibovich 2018 outperformed the novel nomogram within selected ranges of threshold probabilities at ten years. Conversely, the novel nomogram outperformed Leibovich 2018 for other values of threshold probabilities. In summary, Leibovich 2018 and GRANT risk categories exhibited borderline low accuracy in predicting CSS in North American non-metastatic chRCC patients. Conversely, the novel nomogram exhibited higher accuracy. However, in DCA, all examined models exhibited limitations within specific threshold probability intervals. In consequence, all three examined models provide individual predictions that might be suboptimal and be affected by limitations determined by the natural history of chRCC, where few deaths occur within ten years from surgery. Further investigations regarding established and novel predictors of CSS and relying on large sample sizes with longer follow-up are needed to better stratify CSS in chRCC.

U2 - 10.3390/cancers15072155

DO - 10.3390/cancers15072155

M3 - SCORING: Journal article

C2 - 37046815

VL - 15

JO - CANCERS

JF - CANCERS

SN - 2072-6694

IS - 7

M1 - 2155

ER -