Modeling the impact of increased adherence to asthma therapy.

BACKGROUND: Nonadherence to medications occurs in up to 70% of patients with asthma. The effect of improving adherence is not well quantified. We developed a mathematical model with which to assess the population-level effects of improving medication prescribing and adherence for asthma. METHODS: A mathematical model, calibrated to clinical trial data from the U.S. NHLBI-funded SOCS trial and validated using data from the NHLBI SLIC trial, was used to model the effects of increased prescribing and adherence to asthma controllers. The simulated population consisted of 4,930 individuals with asthma, derived from a sample the National Asthma Survey. Main outcomes were controller use, reliever use, unscheduled doctor visits, emergency department (ED) visits, and hospitalizations. RESULTS: For the calibration, simulated outcomes agreed closely with SOCS trial outcomes, with treatment failure hazard ratios [95% confidence interval] of 0.92 [0.58-1.26], 0.97 [0.49-1.45], and 1.01 [0-1.87] for simulation vs. trial in the in placebo, salmeterol, and triamcinolone arms, respectively. For validation, simulated outcomes predicted mid- and end-point treatment failure rates, hazard ratios 1.21 [0.08-2.34] and 0.83 [0.60-1.07], respectively, for patients treated with salmeterol/triamcinolone during the first half of the SLIC study and salmeterol monotherapy during the second half. The model performed less well for patients treated with salmeterol/triamcinolone during the entire study duration, with mid- and end-point hazard ratios 0.83 [0.00-2.12] and 0.37 [0.10-0.65], respectively. Simulation of optimal adherence and prescribing indicated that closing adherence and prescription gaps could prevent as many as nine million unscheduled doctor visits, four million emergency department visits, and one million asthma-related hospitalizations each year in the U.S. CONCLUSIONS: Improvements in medication adherence and prescribing could have a substantial impact on asthma morbidity and healthcare utilization.

Modeling the effects of omalizumab over 5 years among patients with moderate-to-severe persistent allergic asthma.

OBJECTIVE: Omalizumab is a monoclonal antibody indicated for adults and adolescents with moderate-to-severe persistent allergic asthma whose symptoms are inadequately controlled with inhaled corticosteroids. Omalizumab has been demonstrated to improve health outcomes of asthmatic patients as compared to placebo. However, to date, the trials conducted have been relatively short (less than 1 year) and have been restricted to a limited set of patients who met the clinical study criteria. This study examined the expected effects of omalizumab over 5 years on a representative sample of all patients eligible for omalizumab in the US. METHODS: The Archimedes Asthma Model was used to simulate the following treatment scenarios for US patients age 12 and older with moderate-to-severe persistent allergic asthma: (1) Current asthma treatment (CAT) (treatment according to National Heart, Lung, and Blood Institute (NHLBI) guidelines, without use of omalizumab, and with adherence levels as observed in the National Asthma Survey); (2) Guideline asthma treatment (GAT) without omalizumab (NHLBI guidelines without use of omalizumab, assuming perfect adherence); (3) GAT plus omalizumab; and (4) GAT plus omalizumab with steroid reduction. The simulation was run for 5 years. MAIN OUTCOME MEASURES: Symptom days, asthma exacerbations, emergency room/urgent care (ER/UC) visits, hospitalizations, and medication use. RESULTS: For the full simulated population of omalizumab-eligible patients, the simulation forecasted that omalizumab would decrease cumulative exacerbations by 30%, ER/UC visits by 37%, and hospitalizations by 38% over 5 years. Among responders to omalizumab, assuming that 60.5% of patients respond, the results suggest that omalizumab would decrease cumulative exacerbations by 50%, ER/UC visits by 62%, and hospitalizations by 63% over 5 years. In addition, the simulation predicted that omalizumab would allow 45% of patients who are taking more than the minimum steroid dose to reduce their steroid dose, while maintaining similar asthma control as achieved in the GAT plus omalizumab arm (no steroid dose reduction) and better asthma control than following treatment protocols that do not include omalizumab. CONCLUSION: Based on the results of this simulation, omalizumab is effective for those who respond, reducing serious events by more than 50% among the responder group, while also allowing many patients to reduce their steroid dose.