EAU 2018: Cost Benefit Analysis Favors Sonographic Screening For Renal Tumors
This was completed as a Markov model assessing the cost effectiveness of screening with ultrasound for renal tumors in the general population over 60 years of age.
⁃ It is unclear why they chose age 60 as the cutoff. Many RCC patients are younger!
Healthcare cost estimates were based on US healthcare system. Hence, it may not be generalizable to all healthcare systems. Prices were quoted in US dollars.
Mathematical framework and Markov model assessed potential clinical outcomes of a 60 year old patient with and without US screening for RCC. Quality Adjusted Life Year (QALY) and financial costs were the outputs of the model.
Key findings from the study were that the average costs for the screening strategy was USD $137.4 and USD $31.4 for non-screening. Screening and non-screening strategy would add an average of 21.7396 and 21.7385 QALY, respectively. An increase of 0.001 QALY equates to Incremental Cost Effectiveness Ratio (ICER) of USD $86,495.32 per QALY. Currently, the cost which is considered cost effective for 1 QALY point is approximately US $27,548.21. Hence, it is not currently cost effect.
The two variables most influential on the model output were prevalence of RCC and US cost. Both of these are highly variable.
On sensitivity analysis, if the cost of doing an ultrasound is brought down to USD $35.81, then screening may be cost effective.
Per the authors, this is the sole cost benefit analysis evaluating US screening for RCC in the targeted therapy era.
However, there are many variables and decision choices that need to be further examined. Sensitivity analysis for age-cutoff should be determined – as 60 is too old for RCC. Additionally, the cost of exams and treatments vary significantly by healthcare system, so the generalizability is limited. Lastly, the prevalence of RCC continues to change as more incidental lesions are identified even in the absence of screening – they do account for this, noting that increasing prevalence actually leads to improved cost effectiveness.
While an interesting study, additional work needs to be done to flesh out their Markov model.
Speaker: S. Roizman
Co-Author(s): Leshno M., Haifler M., Rappaport Y.H., Haifler M., Hode Rappaport Y., Zisman A.
Written by: Thenappan Chandrasekar, MD, Clinical Fellow, University of Toronto, Twitter: @tchandra_uromd at the 2018 European Association of Urology Meeting EAU18, 16-20 March, 2018 Copenhagen, Denmark