Lifetime Health Effects and Cost-Effectiveness of Tirzepatide and Semaglutide in US Adults

Abstract

Importance: Newer antiobesity medications lead to greater weight loss and lower cardiometabolic risks. However, the high costs of these medications have raised policy questions about their value and coverage decisions.

Objective: To compare the cost-effectiveness of 4 antiobesity medications with lifestyle modification vs lifestyle modification alone in the US.

Design, setting, and participants: A lifetime cost-effectiveness analysis was conducted in 2024 using the validated Diabetes, Obesity, Cardiovascular Disease Microsimulation model for US adults. Data were included from the 2017-2020 National Health and Nutrition Examination Survey of 4823 individuals (representing 126 million eligible US adults) aged 20 to 79 years who would meet clinical trial inclusion criteria for antiobesity medications. Individual-level simulations projected long-term cardiometabolic outcomes, quality-adjusted life-years (QALYs), and health care expenditures. Probabilistic sensitivity analyses, subgroup analyses (across body mass index [BMI] categories [≥30 or ≥27 and at least 1 weight-related comorbidity], presence of comorbidities), and multiple scenario analyses (varying treatment discontinuation rates, value-based pricing benchmarks) were conducted. Future costs and QALYs were discounted at 3% annually.

Interventions: Lifestyle modification with naltrexone-bupropion, phentermine-topiramate, semaglutide, or tirzepatide vs lifestyle modification alone.

Main outcomes and measures: Obesity, diabetes, and cardiovascular disease cases averted, life-years and QALYs gained, costs incurred (2023 US dollars), and incremental cost-effectiveness ratios.

Results: Among the 126 million eligible US adults, the mean age was 48 (SE, 0.5) years; 51% were female; and the initial mean BMI was 34.7 (SE, 0.2); and 85% had at least 1 weight-related comorbidity. Over a lifetime, tirzepatide would avert 45 609 obesity cases (95% uncertainty interval [UI], 45 092-46 126) per 100 000 individuals and semaglutide would avert 32 087 cases (95% UI, 31 292-32 882) per 100 000 individuals. Tirzepatide would reduce 20 854 incident cases of diabetes (95% UI, 19 432-22 276) per 100 000 individuals and semaglutide would reduce 19 211 cases (95% UI, 17 878-20 544) per 100 000 individuals. Tirzepatide would reduce 10 655 cardiovascular disease cases (95% UI, 10 124-11 186) per 100 000 individuals and semaglutide would reduce 8263 cases (95% UI, 7738-8788) per 100 000 individuals. Despite the largest incremental QALY gains of 0.35 for tirzepatide and 0.25 for semaglutide among all antiobesity medications, the incremental cost-effectiveness ratios were $197 023/QALY and 467 676/QALY, respectively. To reach the $100 000/QALY threshold, their prices would require additional discounts by 30.5% for tirzepatide and 81.9% for semaglutide from their current net prices. Naltrexone-bupropion was cost saving due to its lower cost and had an 89.1% probability of being cost-effective at $100 000/QALY, whereas phentermine-topiramate had a 23.5% probability of being cost-effective at $100 000/QALY. Tirzepatide and semaglutide both had a 0% probability across all QALY threshold ranges examined ($100 000-$200 000/QALY).

Conclusions and relevance: This economic evaluation found that although tirzepatide and semaglutide offered substantial long-term health benefits, they were not cost-effective at current net prices. Efforts to reduce the net prices of new antiobesity medications are essential to ensure equitable access to highly effective antiobesity medications.

Figure 1.. Diabetes, Obesity, Cardiovascular Disease Microsimulation Model

The figure has been modified from the original framework developed by Kim et al to suit the specific context of the current study. Individuals either receive LM or an antiobesity medication and LM. The decision node (solid black square) indicates the treatment decision. The Markov model incorporates 5 health states (blue rectangles) where individuals may reside over time and link to potential cardiovascular disease (CVD) events (brown circles) occurring annually. The solid lines and arrows depict transitions between health states and events; the dotted lines and arrows indicate mortality linked to specific causes or events. The simulation continuously updates each individual’s health metrics, dictating their journey through various health states and the probability of events. ASCVD indicates atherosclerotic cardiovascular disease; CHD, coronary heart disease. ^aOverweight was defined as a body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) between 27 and 29.9 and at least 1 weight-related comorbidity. Obesity was defined as a BMI of 30 or greater. The BMI changes were separately tracked for each individual. ^bIncludes coronary artery bypass graft surgery and percutaneous coronary intervention.

Figure 2.. Probabilistic Sensitivity Analysis for the Cost-Effectiveness of the Antiobesity Medications vs Lifestyle Modification Over a Lifetime

Each data point represents 1 of 1000 Monte Carlo simulations, and the encompassing ellipses illustrate the 95% uncertainty intervals for these results. The solid black circles indicate the mean values for the 1000 simulations. The willingness-to-pay (WTP) thresholds of $100 000, $150 000, and $200 000 per quality-adjusted life-year (QALY) are depicted by dashed lines.