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Screening for kidney cancer - A decision analysis

Kumar, Praveen (2022) Screening for kidney cancer - A decision analysis. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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Abstract

Kidney and renal pelvis cancer is the eighth most common cancer in the US. In 2022, 79,000 new cases will be diagnosed, and nearly 13,920 people will die. Kidney cancer accounts for 95% of the kidney and renal pelvis cases, of which 90% cases are renal cell carcinoma (RCC).

In the last decade, screening for RCC using ultrasound imaging was identified as an area for further research. The benefits of screening include shifting the diagnosis towards a stage that is easier to treat; however, critics have argued against screening because of the low prevalence of RCC and risk of overdiagnosis and false positives. This dissertation aims to assess the economic value of screening for RCC in 60-year-old overweight males representing a subgroup at higher risk of developing RCC. Another objective of the dissertation is to estimate the relative contribution of advancements made in RCC management in explaining secular trends in RCC-specific mortality rates.

To answer these questions, we developed a mathematical simulation model to estimate the impact (clinical and economic) of interventions in the population. Chapter two describes the process of developing and calibrating the disease progression model, which is a microsimulation-based discrete event simulation model. The model was calibrated to the RCC-specific incidence and mortality rates for the 1975-2018 period. In Chapter three, we assessed the cost-effectiveness of renal ultrasound as a screening modality for RCC in 60-year-old overweight males. We found that screening for RCC is less likely to be a cost-effective strategy in the target population. In Chapter four, we estimated the relative contribution of advancements such as improved surgical techniques, improved healthcare access, and availability of immunotherapy and targeted therapies in explaining secular trends in RCC mortality. We ran different scenarios to isolate the impact of developments by clinical stage and found that the mortality rate declined primarily due to changes in management for localized and regional stage RCC cases. However, caution is warranted in interpreting effect size for localized cases because it is biased by the rise in incidental detection.


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Details

Item Type: University of Pittsburgh ETD
Status: Unpublished
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Kumar, Praveenprk52@pitt.eduprk520000-0003-4948-968X
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairRoberts, Mark S.mroberts@pitt.edumroberts
Committee MemberSabik, Lindsay M.lsabik@pitt.edulsabik
Committee MemberJalal, Hawre J.hjalal@uottawa.ca
Committee MemberJacobs, Bruce L.blj27@pitt.edublj27
Committee MemberBryce, Cindy L.bryce99@pitt.edubryce99
Date: 10 May 2022
Date Type: Publication
Defense Date: 6 April 2022
Approval Date: 10 May 2022
Submission Date: 25 March 2022
Access Restriction: 2 year -- Restrict access to University of Pittsburgh for a period of 2 years.
Number of Pages: 149
Institution: University of Pittsburgh
Schools and Programs: Graduate School of Public Health > Health Policy & Management
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: cancer, decision analysis, health policy, mathematical model, screening, simulation
Date Deposited: 10 May 2022 18:33
Last Modified: 10 May 2022 18:33
URI: http://d-scholarship.pitt.edu/id/eprint/42409

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