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Development and validation of a life expectancy calculator for US patients with prostate cancer.
Chase, Elizabeth C; Bryant, Alex K; Sun, Yilun; Jackson, William C; Spratt, Daniel E; Dess, Robert T; Schipper, Matthew J.
Afiliación
  • Chase EC; Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.
  • Bryant AK; Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA.
  • Sun Y; Department of Radiation Oncology, University Hospitals/Case Western Reserve University, Cleveland, OH, USA.
  • Jackson WC; Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA.
  • Spratt DE; Department of Radiation Oncology, University Hospitals/Case Western Reserve University, Cleveland, OH, USA.
  • Dess RT; Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA.
  • Schipper MJ; Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.
BJU Int ; 130(4): 496-506, 2022 10.
Article en En | MEDLINE | ID: mdl-35373440
OBJECTIVE: To develop and validate an accurate, usable prediction model for other-cause mortality (OCM) in patients with prostate cancer diagnosed in the United States. MATERIALS AND METHODS: Model training was performed using the National Health and Nutrition Examination Survey 1999-2010 including men aged >40 years with follow-up to the year 2014. The model was validated in the Prostate, Lung, Colon, and Ovarian Cancer Screening Trial prostate cancer cohort, which enrolled patients between 1993 and 2001 with follow-up to the year 2015. Time-dependent area under the curve (AUC) and calibration were assessed in the validation cohort. Analyses were performed to assess algorithmic bias. RESULTS: The 2420 patient training cohort had 459 deaths over a median follow-up of 8.8 years among survivors. The final model included eight predictors: age; education; marital status; diabetes; hypertension; stroke; body mass index; and smoking. It had an AUC of 0.75 at 10 years for predicting OCM in the validation cohort of 8220 patients. The final model significantly outperformed the Social Security Administration life tables and showed adequate predictive performance across race, educational attainment, and marital status subgroups. There is evidence of major variability in life expectancy that is not captured by age, with life expectancy predictions differing by 10 or more years among patients of the same age. CONCLUSION: Using two national cohorts, we have developed and validated a simple and useful prediction model for OCM for patients with prostate cancer treated in the United States, which will allow for more personalized treatment in accordance with guidelines.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Neoplasias de la Próstata Tipo de estudio: Guideline / Observational_studies / Prognostic_studies / Qualitative_research Límite: Child / Humans / Male País/Región como asunto: America do norte Idioma: En Revista: BJU Int Asunto de la revista: UROLOGIA Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Neoplasias de la Próstata Tipo de estudio: Guideline / Observational_studies / Prognostic_studies / Qualitative_research Límite: Child / Humans / Male País/Región como asunto: America do norte Idioma: En Revista: BJU Int Asunto de la revista: UROLOGIA Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos