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Medication use and kidney cancer survival: a population-based study


Several studies demonstrate that use of commonly-prescribed medications is associated with improved survival in various malignancies. Methods of classifying medication use in many of these studies, however, do not account for intermittent or cumulative use. Moreover, there are limited data in kidney cancer. Therefore, we performed a population-based cohort study utilizing healthcare databases in Ontario, Canada. We identified patients aged ≥65 with an incident diagnosis of kidney cancer between 1997-2013 and examined use of nine putative anti-neoplastic medications using prescription claims. Cox proportional hazard models evaluated the association of medication exposure on cancer-specific and overall survival. We conducted three separate analyses: the effect of cumulative duration of exposure to the study medications on outcomes, the effect of current exposure (in a binary nature), and the effect of exposure at diagnosis. During the 16-year study period, we studied 9124 patients. Increasing cumulative use of angiotensin-converting enzyme inhibitors, non-steroidal anti-inflammatory drugs (NSAIDs), and selective serotonin reuptake inhibitors were associated with markedly improved cancer-specific survival; increasing use of NSAIDs was associated with markedly improved overall survival. These results were generally discordant with analyses evaluating the effect of current use and exposure at diagnosis. In conclusion, pharmacoepidemiology studies may be sensitive to the method of analysis; cumulative use analyses may be the most robust as it accounts for intermittent use and supports a dose-outcome relationship. Prospective studies are needed to confirm whether patients diagnosed with kidney cancer should be started on an angiotensin-converting enzyme inhibitor, NSAID, or selective serotonin reuptake inhibitor to improve survival.



Nayan M, Juurlink DN, Austin PC, Macdonald EM, Finelli A, Kulkarni GS, Hamilton RJ; Canadian Drug Safety and Effectiveness Research Network (CDSERN). Int J Cancer. 2018; 142(9):1776-85. Epub 2017 Dec 11.