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Abstract

Simple Summary

Despite the continuous therapeutic efforts metastatic renal cell carcinoma (mRCC) is a dreadful disease, but the many options available provide an horizon of hope for these patients. Sequential therapy based on vascular endothelial growth factor-tyrosine kinase inhibitors (VEGFR-TKI) continues in use. We present a nomogram for a more individualized and accurate estimation of cancer-specific survival (CSS) for patients with clear-cell (CC) mRCC treated with nephrectomy and VEGFR-TK, based on four independent clinical predictors: Eastern Cooperative Oncology Group (ECOG) status; International Metastatic RCC Database Consortium (IMDC) score; Morphology, Attenuation, Size and Structure (MASS) and Response Evaluation Criteria in Solid Tumors (RECIST) response criteria. This tool may be useful to clinicians assessing risk and prognosis of patients with mRCC.

Abstract

(1) Objective: To develop a clinically useful nomogram that may provide a more individualized and accurate estimation of cancer-specific survival (CSS) for patients with clear-cell (CC) metastatic renal cell carcinoma (mRCC) treated with nephrectomy and vascular endothelial growth factor receptor–tyrosine kinase inhibitor (VEGFR-TKI)-based sequential therapy. (2) Methods: A prospectively maintained database of 145 patients with mRCC treated between 2008 and 2018 was analyzed to predict the CSS of patients receiving sunitinib and second- and third-line therapies according to current standards of practice. A nomogram based on four independent clinical predictors (Eastern Cooperative Oncology Group status, International Metastatic RCC Database Consortium score, the Morphology, Attenuation, Size and Structure criteria and Response Evaluation Criteria in Solid Tumors response criteria) was calculated. The corresponding 1- to 10-year CSS probabilities were then determined from the nomogram. (3) Results: The median age was 60 years (95% CI 57.9–61.4). The disease was metastatic at diagnosis in 59 (40.7%), and 86 (59.3%) developed metastasis during follow-up. Patients were followed for a median 48 (IQR 72; 95% CI 56–75.7) months after first-line VEGFR-TKI initiation. The concordance probability estimator value for the nomogram is 0.778 ± 0.02 (mean ± SE). (4) Conclusions: A nomogram to predict CSS in patients with CC mRCC that incorporates patient status, clinical risk classification and response criteria to first-line VEGFR-TKI at 3 months is presented. This new tool may be useful to clinicians assessing the risk and prognosis of patients with mRCC.

Details

1009240
Title
Predicting Survival of Metastatic Clear Cell Renal Cell Cancer Treated with VEGFR-TKI-Based Sequential Therapy
Author
Angulo, Javier C 1   VIAFID ORCID Logo  ; Larrinaga, Gorka 2   VIAFID ORCID Logo  ; Lecumberri, David 3 ; Iturregui, Ane Miren 3   VIAFID ORCID Logo  ; Jon Danel Solano-Iturri 4 ; Lawrie, Charles H 5   VIAFID ORCID Logo  ; Armesto, María 6   VIAFID ORCID Logo  ; Dorado, Juan F 7 ; Nunes-Xavier, Caroline E 8   VIAFID ORCID Logo  ; Pulido, Rafael 9   VIAFID ORCID Logo  ; Manini, Claudia 10   VIAFID ORCID Logo  ; López, José I 11   VIAFID ORCID Logo 

 Clinical Department, Faculty of Medical Sciences, European University of Madrid, 28905 Getafe, Spain 
 Biobizkaia Health Research Institute, 48903 Barakaldo, Spain; [email protected] (C.E.N.-X.); [email protected] (R.P.); [email protected] (J.I.L.); Department of Nursing, Faculty of Medicine and Nursing, University of the Basque Country (UPV/EHU), 48940 Leioa, Spain 
 Department of Urology, Urduliz University Hospital, 48610 Urduliz, Spain; [email protected] (D.L.); [email protected] (A.M.I.) 
 Pathology Department, Cruces University Hospital, 48903 Barakaldo, Spain; [email protected] 
 Molecular Oncology Group, Biogipuzkoa Health Research Institute, 20014 San Sebastián, Spain; [email protected] (C.H.L.); [email protected] (M.A.); IKERBASQUE, Basque Foundation for Science, 48009 Bilbao, Spain; Radcliffe Department of Medicine, University of Oxford, Oxford OX3 9DU, UK; Sino-Swiss Institute of Advanced Technology (SSIAT), Shanghai University, Shanghai 201800, China 
 Molecular Oncology Group, Biogipuzkoa Health Research Institute, 20014 San Sebastián, Spain; [email protected] (C.H.L.); [email protected] (M.A.) 
 PeRTICA Statistical Solutions, Plaza de la Constitución, 2, 28943 Fuenlabrada, Spain; [email protected] 
 Biobizkaia Health Research Institute, 48903 Barakaldo, Spain; [email protected] (C.E.N.-X.); [email protected] (R.P.); [email protected] (J.I.L.); Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, 0379 Oslo, Norway 
 Biobizkaia Health Research Institute, 48903 Barakaldo, Spain; [email protected] (C.E.N.-X.); [email protected] (R.P.); [email protected] (J.I.L.); IKERBASQUE, Basque Foundation for Science, 48009 Bilbao, Spain 
10  Pathology Department, S. Giovanni Bosco Hospital, 10154 Turin, Italy; [email protected] 
11  Biobizkaia Health Research Institute, 48903 Barakaldo, Spain; [email protected] (C.E.N.-X.); [email protected] (R.P.); [email protected] (J.I.L.) 
Publication title
Cancers; Basel
Volume
16
Issue
16
First page
2786
Publication year
2024
Publication date
2024
Publisher
MDPI AG
Place of publication
Basel
Country of publication
Switzerland
Publication subject
e-ISSN
20726694
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Online publication date
2024-08-07
Milestone dates
2024-07-24 (Received); 2024-08-05 (Accepted)
Publication history
 
 
   First posting date
07 Aug 2024
ProQuest document ID
3097834127
Document URL
https://www.proquest.com/scholarly-journals/predicting-survival-metastatic-clear-cell-renal/docview/3097834127/se-2?accountid=208611
Copyright
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2024-10-21
Database
ProQuest One Academic