Validation of Prognostic Models for Renal Cell Carcinoma Recurrence, Cancer-Specific Mortality, and All-Cause Mortality.

Autor:	Robert A; School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada., Mallick R; School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada., McIsaac DI; School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada.; Department of Anesthesiology and Pain Medicine, University of Ottawa and The Ottawa Hospital, Ottawa, Ontario, Canada., Lavallée LT; School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada.; Division of Urology, University of Ottawa, Ottawa, Ontario, Canada., Bhindi B; Division of Urology, University of Calgary, Calgary, Alberta, Canada., Heng D; Division of Medical Oncology, University of Calgary, Calgary, Alberta, Canada., Wood LA; Division of Medical Oncology, QEII Health Sciences Center, Halifax, Nova Scotia, Canada., Rendon R; Department of Urology, Dalhousie University, Halifax, Nova Scotia, Canada., Tanguay S; Division of Urology, McGill University, Montreal, Quebec, Canada., Finelli A; Division of Urology, Departments of Surgery and Surgical Oncology, Princess Margaret Cancer Centre, University Health Network and University of Toronto, Toronto, Ontario, Canada., Bansal RK; Division of Urology, McMaster Institute of Urology, McMaster University, Hamilton, Ontario, Canada., Lalani AK; Department of Oncology, Juravinski Cancer Centre, McMaster University, Hamilton, Ontario, Canada., Basappa N; Department of Oncology, University of Alberta, Cross Cancer Institute, Edmonton, Alberta, Canada., Mannas MP; Urologic Sciences, The University of British Columbia, Vancouver, British Columbia, Canada.; Vancouver Prostate Centre, Vancouver, British Columbia, Canada., Nayak JG; Section of Urology, Department of Surgery, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada.; Men's Health Clinic Manitoba, Winnipeg, Manitoba, Canada., Bjarnason GA; Odette Cancer Centre, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada., Lattouf JB; Department of Surgery, University of Montreal, Montreal, Quebec, Canada., Pouliot F; Division of Urology, CHU of Québec and Laval University, Quebec City, Quebec, Canada., Richard PO; Division of Urology, Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, Quebec, Canada., Tajzler C; Ri-MUHC, McGill University, Montreal, Quebec, Canada., Breau RH; School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada.; Division of Urology, University of Ottawa, Ottawa, Ontario, Canada.
Jazyk:	angličtina
Zdroj:	The Journal of urology [J Urol] 2024 Dec 02, pp. 101097JU0000000000004348. Date of Electronic Publication: 2024 Dec 02.
DOI:	10.1097/JU.0000000000004348
Abstrakt:	Purpose: Postoperative prognostic tools allow for improved prediction of future recurrence risk, patient counseling, and assessment of eligibility for adjuvant treatments and ensure appropriate follow-up surveillance. The purpose of this analysis was to validate existing prognostic models for patients with kidney cancer. Materials and Methods: The Canadian Kidney Cancer information system is a prospective cohort of patients managed at 14 institutions since January 1, 2011, to present. The Canadian Kidney Cancer information system was used to assess 15 predictive models for kidney cancer recurrence, 6 for cancer-specific mortality, and 4 for all-cause mortality in patients with a solitary, nonmetastatic kidney tumor treated with surgery (partial or radical nephrectomy). Discrimination was measured using c-statistics, 5-year calibration plots for calibration, and decision curve analysis at 5 years after surgery for net benefit when considering adjuvant therapy. Results: Seven thousand one hundred seventy-four patients were included. For kidney cancer recurrence, c-statistics ranged from 0.62 to 0.83, depending on whether the model was derived and applied to all patients without further stratification, specific risk groups, or specific histological subtypes. Cancer-specific mortality models had c-statistics ranging from 0.60 to 0.89 and all-cause mortality models from 0.60 to 0.73. Using decision curve analysis in patients with clear-cell renal cell carcinoma, the best models for choosing adjuvant therapy to prevent recurrence and cancer-related death were the Mayo Clinic prediction models. Conclusions: Model performance varied considerably with some suitable for clinical use. If using prediction models to select adjuvant therapy, the Mayo Clinic models were best when applied to a large contemporary cohort of Canadian patients.
Databáze:	MEDLINE
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