Disparities of age-based cancer-specific survival improvement with various clinicopathologic characteristics for kidney cancer

Abstract

Introduction: Whether or not age is a predictor of kidney cancer survival is currently unknown but debated. It is also unknown whether improved kidney cancer survival is associated with age with particular clinicopathologic characteristics. The aim of this study was to evaluate kidney cancer survival in four age-based subgroups of patients by analyzing the Surveillance, Epidemiology, and End Results-registered database.

Methods: Age-based survival disparity by sex, race, marital status, year of diagnosis, pathological grade, histological type, and stage was measured. The impact of age and further parameters on disease specific mortality was evaluated by multivariate Cox proportional hazards regression analyses.

Results: Results showed that 8-year cancer-specific survival was 79.6% in those aged ≤49 years, 70.6% in those aged 50-64 years, 65.3% in those aged 65-74 years, and 56.0% in those aged 75-84 years. These differences were significant as judged by a univariate log-rank test (P<0.001) and multivariate Cox regression (P<0.001). Age-based survival improvement was most obvious in patients diagnosed from 2005 to 2009 and with the following clinicopathologic characteristics: female, white race, low pathological grade, and localized stage. There was no obvious disparity of age-based survival improvement with regard to marital status or histologic type. No age-based survival improvement was observed in patients of the black race, pathological grade IV, or distant stage (P=0.05, P=0.07, and P=0.07, respectively).

Conclusion: These data suggest that age is an independent prognostic factor for survival in patients with kidney cancer and that age-based survival improvement is associated with particular clinicopathologic characteristics.

Keywords: SEER; age groups; epidemiology; prognosis; renal tumor.

Figure 1

The distribution of the age at kidney cancer diagnosis from 1990 to 2009.

Figure 2

The distribution of patients by age at diagnosis using a GaussAmp fitting curve according to different periods of diagnosis.

Figure 3

Survival curves in patients with kidney cancer according to different age subgroups.

Figure 4

Multivariate-adjusted HRs and 95% CIs for cancer-specific death associated with year of diagnosis according to age.

Figure 5

Multivariate-adjusted HRs and 95% CIs for cancer-specific death associated with age according to year of diagnosis (A), pathological grade (B), histological type (C), and sex (D). Abbreviations: CCR, clear cell carcinoma; N-CCR, non-clear cell carcinoma.

Figure 6

Multivariate-adjusted HRs and 95% CIs for cancer-specific death associated with age according to race (A), marital status at diagnosis (B), and stage (C).