title: A stage-for-stage and grade-for-grade analysis of cancer-specific mortality rates in renal cell carcinoma according to age: a competing-risks regression analysis.
abstract: BACKGROUND
  The association of advanced age and cancer control outcomes shows discordant findings.
  
  
  OBJECTIVE
  To evaluate the effect of age on cancer control outcomes in a large population-based cohort of patients diagnosed with renal cell carcinoma (RCC) of all stages.
  
  
  METHODS
  Using the Surveillance Epidemiology and End Results database, 36 333 patients with RCC were identified. The population was stratified according to age:<50, 50-59, 60-69, 70-79, and ≥80 yr. The effect of age on cancer control outcomes was evaluated using competing-risks regression models. Analyses were repeated stage for stage and grade for grade.
  
  
  METHODS
  Cancer-specific mortality (CSM) was measured.
  
  
  CONCLUSIONS
  Age categories 50-59, 60-69, 70-79, and ≥80 yr respectively portended a 1.4-, 1.5-, 1.6-, and 1.9-fold higher risk of CSM than age category <50 yr (all p < 0.001). The effect of advanced age was particularly detrimental in patients with stage I disease: 1.8-, 2.3-, 3.2-, and 3.8-fold higher CSM risk for the same age groups, respectively (all p<0.001). The effect of age on CSM was at its peak in patients with stage I, low-grade RCC (1.6-, 2.2-, 3.6-, and 4.3-fold, respectively; all p<0.001) and remained elevated in stage I, high-grade RCC (2.2-, 2.6-, 2.4-, and 3.0-fold higher, respectively; all p<0.05). Conversely, its effect was virtually absent in patients with stage II-IV RCC.
  
  
  CONCLUSIONS
  Our data suggest that stage I RCC may behave in a more aggressive fashion in elderly patients. Further studies are required to confirm the current findings.
authors.affiliation: Cancer Prognostics and Health Outcomes Unit, University of Montreal Health Center, Montreal, Canada.
authors.forename: Maxine
authors.initials: M
authors.lastname: Sun
authors.forename: Firas
authors.initials: F
authors.lastname: Abdollah
authors.forename: Marco
authors.initials: M
authors.lastname: Bianchi
authors.forename: Quoc-Dien
authors.initials: QD
authors.lastname: Trinh
authors.forename: Claudio
authors.initials: C
authors.lastname: Jeldres
authors.forename: Zhe
authors.initials: Z
authors.lastname: Tian
authors.forename: Shahrokh F
authors.initials: SF
authors.lastname: Shariat
authors.forename: Hugues
authors.initials: H
authors.lastname: Widmer
authors.forename: Kevin
authors.initials: K
authors.lastname: Zorn
authors.forename: Mani
authors.initials: M
authors.lastname: Menon
authors.forename: Francesco
authors.initials: F
authors.lastname: Montorsi
authors.forename: Paul
authors.initials: P
authors.lastname: Perrotte
authors.forename: Pierre I
authors.initials: PI
authors.lastname: Karakiewicz
mesh_terms: D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D002292:Carcinoma, Renal Cell / Q000401:mortality* / Q000473:pathology* / Q000628:therapy; D005260:Female; D006801:Humans; D007680:Kidney Neoplasms / Q000401:mortality* / Q000473:pathology* / Q000628:therapy; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D060787:Neoplasm Grading; D009367:Neoplasm Staging; D016017:Odds Ratio; D011379:Prognosis; D012044:Regression Analysis; D018570:Risk Assessment; D012307:Risk Factors; D018426:SEER Program; D013997:Time Factors; D014481:United States / Q000453:epidemiology