We appreciate the thoughtful comments of Drs. Van den Ende, Bisoffi, and Basinga, and we thank them for their general support of our manuscript’s ideas. The authors point out that treatment of individuals without TB disease does not induce resistance to anti-TB medications. At the individual level, this is undoubtedly true. However, a key concern – not discussed at length in our manuscript – is that large-scale treatment of false-positives at the population level greatly increases the distribution of TB drugs, with potential adverse consequences. These include stock-outs or “stretching” (1) of drugs for people with active TB, and sharing of medicine with symptomatic friends or family members (2) where directly-observed therapy is not strict. Thus, we would argue that increased circulation of anti-TB drugs from false-positive diagnosis increases the population-level risk of drug resistance, even when the individual being treated is not affected.

We agree with the comments regarding the importance of distinguishing between marginal and mean cases to avoid Blackstone-type errors. Thus, the authors make a key point that a threshold probability of 1/30 does not imply that 29 of 30 diagnoses are incorrect in the aggregate. Nevertheless, it remains true that a marginal diagnosis on an individual patient with a post-test probability of 1/30 would be wrong 29 times out of 30, and that the expected-utility framework discussed would advocate for treatment of such patients. The authors make an important distinction between expected-utility thresholds and cost-effectiveness analysis; however, given that this particular threshold analysis (3) included costs and effectiveness measures, it can be shown that a corresponding cost-effectiveness analysis should reach the same conclusion. Thus, in the end, economists working under either framework would recommend that patients or physicians accept a (marginal) diagnosis that is expected to be wrong 29 times out of 30. This recommendation is appropriate from a classical economic perspective, but is unlikely to find acceptance among physicians.

Finally, Dr. Van den Ende and colleagues point out that physicians’ intuitive weights differ dramatically from calculated weights based on their accurate knowledge of TB biology. We would argue that neither the calculated nor intuitive weights are erroneous; rather, the authors’ analysis (3) elegantly shows that physicians are not rational in their decision-making. Nevertheless, physicians’ intuitive weights must be considered, as these weights – not calculated weights – ultimately guide their decisions. As we argue, “[w]hen local preferences seem inappropriate to policy-makers, educational efforts or recommendations for empiric therapy should be prioritized over scale-up of novel diagnostics.” Ultimately, if new diagnostics do not live up to physicians’ intuitive expectations, they are unlikely to be used, regardless of how irrational those intuitive weights may be.

David Dowdy, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA

Adithya Cattamanchi, San Francisco General Hospital, San Francisco, USA

Karen Steingart, Curry International Tuberculosis Center, San Francisco, USA


References
1. Rookkapan K, Chongsuvivatwong V, Kasiwong S, Pariyawatee S, Kasetcharoen Y, et al. (2005) Deteriorated tuberculosis drugs and management system problems in lower southern thailand. The International Journal of Tuberculosis and Lung Disease 9(6): 654-660.

2. Goldsworthy RC, Schwartz NC, Mayhorn CB. (2008) Beyond abuse and exposure: Framing the impact of prescription-medication sharing. Am J Public Health 98(6): 1115-1121.

3. Basinga P, Moreira J, Bisoffi Z, Bisig B, Van den Ende J. (2007) Why are clinicians reluctant to treat smear-negative tuberculosis? an inquiry about treatment thresholds in rwanda. Medical Decision Making 27(1): 53-60.