Colorectal cancer (CRC) is the third leading cause of cancer mortality among both men and women in the United States despite prevention efforts. A better tool for predicting colorectal cancer risk may help identify high risk patients who could benefit from chemopreventive medication, but the best statistical method for reducing survival models in large datasets is controvertible.
The first project compared several variable selection methodologies in their ability to produce parsimonious, accurate prediction models in large datasets. The second investigation created a model for predicting colorectal cancer risk using a large prospective dataset of almost 200,000 participants. The final project was a cost-effectiveness analysis that explored the potential benefits of sulindac-difluoromethylornithine as an adjunct to colonoscopy for the prevention of CRC.
A modified version of Forward Stepwise Regression based on model discrimination (Forward Stepwise C-Statistic) produced slightly more accurate prediction models than traditional forms of stepwise regression based on the F Statistic or Harrell’s Stepdown. New, gender-specific colorectal cancer risk calculators were created using Forward Stepwise C-statistic and achieved bias corrected C-Statistics (95% CI) of 0.69 (0.673-0.698) and 0.68 (0.668-0.694) in men and women, respectively. Age was the overriding risk factor for both men and women. The cost effectiveness analysis revealed that screening colonoscopy is both less expensive and results in more quality adjusted life years than any of the following strategies: no prevention, colonoscopy + chemoprevention, and chemoprevention alone. This finding persisted across one-way sensitivity analyses as well high risk patient scenarios.
Forward Stepwise C-Statistic can produce reduced statistical models that are slightly more accurate than traditional stepwise regression or Harrell’s Stepdown, but the slight gain in accuracy may not be worth the additional computational burden in some instances. Head to head comparisons between the new colorectal cancer risk calculator and existing calculators are necessary to prove that the new model is better. The overriding influence of age in the new model suggests that current strategies to screen patients based on age may not be unreasonable. The results demonstrate that chemoprevention with sulindac-difluoromethylornithine should not be considered for patients without a hereditary cancer syndrome.