Decision modeling to estimate the impact of gastric bypass surgery on life expectancy for the treatment of morbid obesity

Abstract

Objective: To create a decision analytic model to estimate the balance between treatment risks and benefits for patients with morbid obesity.

Design: Decision analytic Markov state transition model with multiple logistic regression models as inputs. Data from the 2005 National Inpatient Survey were used to calculate in-hospital mortality risk associated with bariatric surgery and then adjusted for 30-day mortality. To calculate excess mortality associated with obesity, we used the 1991-1996 National Health Interview Survey linked to the National Death Index. Bariatric surgery was assumed to influence mortality only through its impact on the excess mortality associated with obesity, and the efficacy of surgery was estimated from a recent large observational trial.

Intervention: Gastric bypass surgery. Main Outcome Measure Life expectancy.

Results: Our base case, a 42-year-old woman with a body mass index of 45, gained an additional 2.95 years of life expectancy with bariatric surgery. No surgical treatment was favored in our base case when the 30-day surgical mortality exceeded 9.5% (baseline 30-day mortality, 0.2%) or when the efficacy of bariatric surgery for reducing mortality decreased to 2% or less (baseline efficacy, 53%).

Conclusions: The optimal decision for individual patients varies based on the balance of risk between perioperative mortality, excess annual mortality risk associated with increasing body mass index, and the efficacy of surgery; however, for the average morbidly obese patient, gastric bypass improves life expectancy.

Figure 1

Figure 1a. Annual predicted death rate for men by age and BMI category Figure 1b. Annual predicted death rate for women by age and BMI category

Figure 2

30-day predicted probability of death after bariatric surgery for men and women by age.

Figure 3

Figure 3a. Change in life expectancy with bariatric surgery for women at different ages and BMIs. Figure 3b. Change in life expectancy with bariatric surgery for men at different ages and BMIs.

Figure 4

2-way sensitivity analysis for 30-day probability of death after surgery for women at age 42 and men at age 44. In the region to the lower right, below the line, where the probability of death is low and body mass index is higher, bariatric surgery is preferred. To the upper left, when the probability of death is higher and the body mass index is lower, no surgery is the preferred strategy. The line indicates the threshold between the two strategies. The dark circles indicate the base case values for each parameter.

Figure 5

3-way sensitivity analysis for the impact of surgery on the relative risk of death (1-efficacy) at varying ages and BMIs by gender. The shaded areas are where the surgery is the preferred strategy. For higher relative risks of death (or lower efficacies), above the shaded areas, no surgery is preferred. For example, for a 45 year-old woman with a BMI of 40, when the relative risk of death after surgery is greater than 0.98 (efficacy of surgery is less than 0.02), no surgical treatment is the preferred strategy. When the relative risk of death after surgery is less than 0.98 (efficacy of surgery is greater than 0.02), bariatric surgery is the strategy with the greatest gain in life expectancy.

Figure 6

Sensitivity analysis exploring effect of bariatric surgery on patients with lower BMIs between 30 and 35.