MODELING INDIVIDUAL UTILITY FROM COLORECTAL CANCER SCREENING
Method: We modeled an individual who considered colorectal cancer screening as a means to increase his/her expected utility. Every year, the individual could choose between screening and not screening for disease. An individual who screened realized a large probability of no change in life-years (associated with a negative screening test, or positive screening test with late diagnosis), small probability of additional life-years (associated with early diagnosis), and small probability of screening test complications. An individual who did not screen realized no change in survival probabilities. We estimated expected utility by summing the probability distributions for life-years survived in each scenario, each multiplied by individual utility as a function of remaining life expectancy. We included a standard gamble to personalize utility for an individual’s degree of risk aversion. Using data from the Surveillance, Epidemiology, and End Results[SEER] survey between 2000-2011, we applied our model to screening using colonoscopy, flexible sigmoidoscopy, and fecal occult blood testing[FOBT]. We categorized individuals by age, race, and gender. We estimated expected utility for every possible combination of screening (method[colonoscopy, every 1-20 years; flexible sigmoidoscopy, every 1-10 years; FOBT, every 1-3 years], start age[20-85 years], stop age[20-85 years]) as compared with no screening, and rank-ordered results, to help understand how individual preferences impact screening decisions.
Result: For a 50-year-old average-risk white female who required a 2-month increase in life expectancy to be willing to accept the potential risks of colonoscopy, the model predicted that she would choose to undergo colonoscopy every 16 years, beginning at age 53. At higher risk aversion (4-month required increase in life expectancy), the model predicted that she would prefer flexible sigmoidoscopy every 10 years, beginning at age 55. Therefore, although informed individuals may screen less-often than guideline-recommended, they still should choose regular screening. FOBT was predicted only when survival probabilities were poorly understood, such as when mean population benefits were assumed to occur with certainty.
Conclusion: Quantitative models may help individualize colorectal cancer screening preferences. Future research should consider potential to improve patient adherence, and how to reduce the gap between individual-preferred vs. guideline-recommended frequency.