Components of metabolic syndrome and prognosis of renal cell cancer

Abstract

Objective: This study analyzes risk associations between metabolic syndrome (MetS) components and the extent and prognosis of renal cell cancer (RCC). The independent effect of each MetS component is unclear, but they may affect RCC prognosis.

Materials and methods: The study included 13,873 RCC patients (7720 men, 6153 women) diagnosed in Finland in 1995–2012. Data on MetS components (hypertension, dyslipidemia, diabetes and obesity) were obtained as recorded diagnoses or drug purchases related to these conditions. Risk of advanced RCC at diagnosis was estimated by logistic regression. Cox proportional hazard regression was used to evaluate risk associations for RCC death by MetS components after diagnosis. Components were analyzed as time-dependent variables, and included in analyses simultaneously to evaluate their independent effects.

Results: During follow-up (median 1.92, SD 4.35 years) 5179 participants died of RCC. Risk of advanced RCC at diagnosis was associated with hypertension [odds ratio (OR) 0.82, 95% confidence interval (CI) 0.74–90] and dyslipidemia (OR 0.52, 95% CI 0.48–0.57). After adjustment for tumor extent, hypertension remained associated with increased risk of RCC death (hazard ratio 1.44, 95% CI 1.35–1.54]. Other MetS components were not independently associated with RCC death when taking hypertension into account. Study limitations include the non-randomized design and lack of smoking status.

Conclusions: The lower risk of advanced disease among hypertensive participants may reflect the higher proportion of incidental renal tumors found through more frequent physician contacts. Nevertheless, hypertension was independently associated with worse RCC survival, whereas other MetS components had no clear prognostic role.

Keywords:

• Epidemiology
• kidney cancer
• metabolic syndrome
• pharmacoepidemiology
• prognosis

Acknowledgement

We are grateful to biostatistician Mika Helminen from University of Tampere Medical School for help with competing the risk regression analysis.

Disclosure statement

Teuvo Tammela received payment for consultation for Astellas, GlaxoSmithKline, Pfizer, Orion Pharma and Amgen. Teemu Murtola received payment for consultation for Astellas and Jansen-Cilag, and lecture fees from Abbvie, Astellas, MSD and Jansen-Cilag. The other authors declare no conflicts of interest.

Additional information

Funding

Funding was received from Pirkanmaa Hospital District, memorial fund of Seppo Nieminen [grant number 150640].