Cost-effectiveness analysis of interventions for tuberculosis control: DALYs versus QALYs.

The emergence of multi-drug-resistant tuberculosis (MDR-TB) in the European region and the high costs (nearly <euro>536 million) generated by the nearly 72,000 notified TB cases in the EU are the factors driving the need for development and implementation of new tools against TB. In this context, cost-effectiveness analyses applying quality-adjusted life-years (QALYs) or disability-adjusted life-years (DALYs) as outcome measures for economic evaluation of improved approaches to TB control are increasingly important. While the methodology applied to derive the effectiveness data is commonly reported, less information is given regarding the derivation of utility weights in the calculation of QALYs for TB treatment. To date, despite the particular complexities of the disease, TB health effects have not been fully measured and there is no agreement on how disutility of TB disease should be accounted for. Consequently, disutility values in published studies vary considerably, and often appear to lack empirical evidence. As the need for a solid heath-economics rationale for investment in new tools against TB grows, adequate and comprehensive methods for assessing the impairments caused by different types of TB must be developed. Focusing on the assessment of DALYs as a measure of outcome in economic evaluation, we have built an exemplary model calculation applying the original TB data for Germany as reported to the Robert Koch Institute. Our work demonstrates that the use of standard equations provided in the scientific literature probably results in an underestimation of lost DALYs compared with probabilistic techniques. Providing distributions around epidemiological averages, coupled with Monte Carlo simulation to address uncertainty, may result in more realistic values. In line with a previous recommendation by the World Health Organization, it appears worthwhile to consider this more intricate approach to providing healthcare resource allocation decisions, particularly for TB.