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Prediction of Competing Mortality for Decision-making Between Surgery or Observation in Elderly Patients With T1 Kidney Cancer

  • Alessandro Larcher
    Correspondence
    Address correspondence to: Alessandro Larcher, M.D., Cancer Prognostics and Health Outcomes Unit, 264 Blvd. Rene-Levesque E. Room 228, Montreal, QC H2X 1P1, Canada.
    Affiliations
    Cancer Prognostics and Health Outcomes Unit, University of Montreal Health Center, Montreal, QC, Canada

    Division of Oncology, Unit of Urology, URI, IRCCS Ospedale San Raffaele, Milan, Italy
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  • Vincent Trudeau
    Affiliations
    Cancer Prognostics and Health Outcomes Unit, University of Montreal Health Center, Montreal, QC, Canada

    Department of Urology, University of Montreal Health Center, Montreal, QC, Canada
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  • Paolo Dell'Oglio
    Affiliations
    Cancer Prognostics and Health Outcomes Unit, University of Montreal Health Center, Montreal, QC, Canada

    Division of Oncology, Unit of Urology, URI, IRCCS Ospedale San Raffaele, Milan, Italy
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  • Zhe Tian
    Affiliations
    Cancer Prognostics and Health Outcomes Unit, University of Montreal Health Center, Montreal, QC, Canada

    Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada
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  • Katharina Boehm
    Affiliations
    Cancer Prognostics and Health Outcomes Unit, University of Montreal Health Center, Montreal, QC, Canada

    Martini-Clinic, Prostate Cancer Center Hamburg-Eppendorf, Hamburg, Germany
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  • Nicola Fossati
    Affiliations
    Division of Oncology, Unit of Urology, URI, IRCCS Ospedale San Raffaele, Milan, Italy

    Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, NY
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  • Umberto Capitanio
    Affiliations
    Division of Oncology, Unit of Urology, URI, IRCCS Ospedale San Raffaele, Milan, Italy
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  • Alberto Briganti
    Affiliations
    Division of Oncology, Unit of Urology, URI, IRCCS Ospedale San Raffaele, Milan, Italy
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  • Francesco Montorsi
    Affiliations
    Division of Oncology, Unit of Urology, URI, IRCCS Ospedale San Raffaele, Milan, Italy
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  • Pierre Karakiewicz
    Affiliations
    Cancer Prognostics and Health Outcomes Unit, University of Montreal Health Center, Montreal, QC, Canada

    Department of Urology, University of Montreal Health Center, Montreal, QC, Canada
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Published:November 21, 2016DOI:https://doi.org/10.1016/j.urology.2016.08.069

      Objective

      To predict the risk of cancer-specific mortality (CSM) or other-cause mortality (OCM) for T1 kidney cancer patients, aiming at identifying those who would benefit from surgery over observation.

      Patients and Methods

      Overall, 11,192 T1 kidney cancer patients treated with surgery or observation in the Surveillance, Epidemiology, and End Results-Medicare database were assessed. A competing risk regression (CRR) model was fitted to predict CSM and OCM after surgery or observation. Covariates consisted of age, gender, race, Charlson comorbidity index (CCI), history of acute kidney injury or chronic kidney disease, tumor size, and year of diagnosis.

      Results

      At a median follow-up of 64 months, the 5-year rates of CSM and OCM were 6.7% and 24%, respectively. At CRR predicting CSM, surgery (hazard ratio [HR] 0.46; P < .0001) and year of diagnosis (HR 0.96; P < .0001) were associated with lower CSM risk. Conversely, age (HR 1.05; P < .0001), CCI (HR 1.07; P < .0001), and tumor size (HR 1.03; P < .0001) were associated with higher CSM risk. At CRR predicting OCM, surgery (HR 0.66; P < .0001), female gender (HR 0.83; P < .0001), Other race (HR 0.82; P < .0001), and year of diagnosis (HR 0.95; P < .0001) were associated with lower OCM risk. Conversely, age (HR 1.06; P < .0001), African American race (HR 1.16; P < .01), CCI (HR 1.17; P < .0001), and acute kidney injury or chronic kidney disease (HR 1.35; P < .0001) were associated with higher OCM risk.

      Conclusion

      The benefit of surgery over observation was more pronounced in younger and healthier patients with larger tumors. The proposed model can aid in clinical decision-making, providing crucial information on CSM and OCM risk after either treatment modality.
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