At $821,000 per QALY gained, omalizumab is not cost-effective. Although no consensus defines the threshold that represents acceptable value for money, cost-effectiveness ratios are often placed in context by comparisons with other interventions, such as hemodialysis for chronic renal failure.45
The “dialysis threshold” that is frequently quoted is $93,500 per QALY in 2002 US dollars. Accordingly, an intervention costing $821,000 per QALY is not considered attractive value for money.
Not surprisingly, the cost-effectiveness of omalizumab is highly sensitive to price assumptions. Holding all other model parameters at their baseline value, monthly drug costs of less than $100 and $200 per month would be required to clear $50,000 and $100,000 per QALY gained, respectively. This would translate into annual drug costs of $1200 to $2400 for a 70-kg person with an IgE level of 200 IU/mL. In addition, the cost-effectiveness of omalizumab is sensitive to assumptions in improvement in HRQOL. Based on existing clinical trials, omalizumab improved HRQOL. When effects were modeled assuming HRQOL is improved by 7.2% more than when taking an ICS alone, the cost-effectiveness ratio is close to $207,000. The cost-effectiveness ratio was less sensitive to other input data assumptions, such as reduction in exacerbations, reduction in hospital resource use, increase in baseline acute event rate, and dampening of the ICS effect.
Similar to Oba and Salzman’s cost-effectiveness study of omalizumab,15
we find that the incremental cost associated with omalizumab is higher than is commonly used as a benchmark for an acceptable incremental cost. Because our analysis measures cost per QALY rather than cost to improve the AQLQ score by 0.5 points for an entire year, it is easier to compare the cost of omalizumab with the costs of other therapeutics and interventions. The analysis by Brown et al does use the unit of cost per QALY but has other shortcomings. Although the study used for analysis includes a total of 206 subjects in the omalizumab group, the analysis by Brown et al only includes the 68 subjects who responded to omalizumab, defined as having a 0.5-point or greater improvement in the Mini-AQLQ (Brown et al16
and Ayres et al46
). Thus this analysis is a narrow analysis and does not represent the real-world setting in which omalizumab response cannot be predicted before treatment. In addition, this analysis used utilities that might not be accurate because they were transformed from values from the Mini-AQLQ, and the utilities were based on an open-label trial that could result in biased responses to the AQLQ.16,46
Our findings have significant implications for the allocation of health care resources in the treatment of severe asthma. Because of the substantial clinical benefits seen in randomized control trials, omalizumab is potentially a valuable therapeutic strategy in populations whose prognosis is otherwise poor and for whom few satisfactory alternatives exist. For these individuals, the usual parameters by which cost-effectiveness is judged might be different from those used in healthier populations. For example, studies of cost-effectiveness in the treatment of advanced cancer have demonstrated that society is willing to pay more to prolong and improve the life of very ill patients, regardless of whether the interventions are less cost-effective than those used in healthier patients.47-50
Nevertheless, based on our analysis, the incremental cost-effectiveness ratio for omalizumab falls far outside the range considered reasonable for all but the most severely ill patients.
A few limitations to this study deserve mention. Perhaps most notable is the fact that this analysis is based on a model. The logistic and financial obstacles, however, to conducting a clinical trial comparing omalizumab with placebo and comparing long-term costs and outcomes would be difficult to surmount. A model-based approach permits the extrapolation of costs and health effects beyond the time horizon of a single clinical study. Second, a model-based approach can be used to anticipate the results of new clinical investigations and to guide clinicians and policymakers in judging the quality and interpreting the policy relevance of the outcomes. In addition to relating biologic and clinical information, a model can provide quantitative insight into the relative importance of different components of a treatment strategy and investigate how results will change if values of key parameters are affected. By identifying the most important sources of uncertainty, a model can also be used to help prioritize and guide data collection efforts.
Another limitation of the Asthma Policy Model is that there might be concern that FEV1 percent predicted might not fully predict prognosis. Nevertheless, based on previously analyses, we found that FEV1 percent predicted is associated with symptoms, acute exacerbations, costs, and quality of life. In addition, using FEV1 percent predicted as an asthma severity index has several advantages of objectivity and reproducibility and is an underlying physiologic driver of clinical events. Furthermore, the rates of exacerbation predicted in our model are lower than the rates in the clinical trials, likely because our model predicts rates of exacerbation of a general population rather than a population in a randomized control trial that is selected for being more sick; however, we addressed this concern by examining the effect of changing our assumptions for the baseline exacerbation rates for the population in sensitivity analyses. Moreover, we do not include indirect costs, such as lost productivity, in our analysis. The Panel on Cost-Effectiveness in Health and Medicine recommends not to do so. Instead, indirect costs are incorporated in the measure of QALYs.
To summarize, omalizumab does not provide sufficient clinical benefit and resource savings to justify its current price in a general population of patients with severe asthma. The projected cost-effectiveness ratio might fall within an accepted value range for interventions within the United States if the cost for omalizumab decreases significantly.
This analysis and the development of the model on which it is based were supported by the National Heart, Lung, and Blood Institute. Although we gratefully acknowledge its support and scientific advice, the agency played no significant role in the design or conduct of the study. No limitations on publication were imposed, nor was any prepublication review required.