ASSESSING THE SOCIETAL COST-EFFECTIVENESS OF PREOPERATIVE OPTIMIZATION FOR COLON CANCER SURGERY
Ira Leeds*, Jonathan Efron, Bashar Safar, Sandy Fang, Fabian M. Johnston
Surgery, Johns Hopkins University School of Medicine, Baltimore, MD
BACKGROUND
Surgery for colon cancer is common and is associated with complication rates of over 20%. Recent reports have suggested that preoperative optimization efforts targeting a patient's comorbidities (e.g., diabetes, chronic lung disease) is associated with a reduction in postoperative complications. In addition to prospective studies assessing the clinical effectiveness of these programs, the formal cost-effectiveness of these programs outside of subsidized research efforts has not been studied.
METHODS
We constructed a decision analytic model to compare costs and outcomes in a reference case for colon cancer surgery (sigmoid colectomy, probability-weighted laparoscopic versus open) with and without focused preoperative optimization. The reference case risk reduction and average costs for preoperative optimization (RR = 0.69, cost = $747 per patient) was estimated from recent published literature. Life expectancy and quality of life with surgery, the probability and costs of morbidity or mortality, and the probability of long-term postoperative sequelae were modeled using existing public sources. By convention, all future costs ($) and benefits (quality-adjusted life year) reflected a societal perspective and were discounted at 3%. 10,000-iteration probabilistic sensitivity analysis further accounted for uncertainty in probabilities, costs, and utility weights. Given the variability in the intensity of existing preoperative optimization programs, we tested the extremes of the model to identify the greatest justifiable cost of preoperative optimization.
RESULTS
Using reference parameters, we calculated the per individual expected societal total cost of preoperative optimization and sequelae to be $12,395 versus $15,638 of preventable sequelae in those not optimized. Without optimization, those not optimized on average attained 0.02 QALYs less than those optimized. Thus, preoperative optimization was the dominant strategy (lower total costs; higher quality adjusted life years due to lower complication rates). Probabilistic sensitivity analysis demonstrated 100% of simulated strategies to consistently favor preoperative optimization. Testing the extremes of our estimates, we further demonstrated that the breakeven cost of preoperative optimization to remain cost-effective was up to $6,421 per patient (versus $747 per patient in the reference case).
CONCLUSION
Patients with comorbidities may benefit from preoperative optimization prior to colon cancer surgery to reduce postoperative complications. This study demonstrates that their effectiveness is further enhanced by the predicted reduction in total societal costs due to relatively low optimization costs and the reduction in costly postoperative complications. Finally, extreme scenarios suggest that even some of the most resource-intensive programs may be cost-effective under current conditions.
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