False positives are not the problem—test misinterpretation is the problem.

Note, if you are a clinician, this is not your fault. You are right to be wary of ordering tests that have high false positive rates, and you are competent even if you do not know what to make of their results.

As a medical community, we lack the tools necessary for interpreting sensitive tests.

To this end, I am highlighting this study [1] on D-dimer interpretation. The results are surprising; values well above “red flag” cutoffs have a likelihood ratio <=1, which means a decreased post-test probability of a pulmonary embolism. These kinds of results could potentially help prevent unnecessary angiograms while also ruling out low-likelihood pulmonary embolisms.

The study isn’t perfect. There was no need to “intervalize” D-dimer, the likelihood ratio should have been adjusted for covariates [2], and post-test probability should have been modeled directly [3,4]. More work is needed.
However, either way, this is the type of study that will make medicine better. It moves us past reflex testing “cascades” toward healthcare as it should be, where we use information optimally for the patient.

References

1.     Kohn MA, Klok FA, van Es N. D-dimer Interval Likelihood Ratios for Pulmonary Embolism. Acad Emerg Med. 2017 Jul;24(7):832-837. doi: 10.1111/acem.13191. Epub 2017 Jun 14. PMID: 28370759. https://lnkd.in/gQrJKNuw

2.     Weisenthal, Samuel J., and Amit K. Chowdhry. “The information mismatch, and how to fix it.” arXiv preprint arXiv:2503.15382 (2025). https://lnkd.in/gjmpF-Az

3.     Harrell, Frank E. Regression modeling strategies: with applications to linear models, logistic regression, and survival analysis. Chapter on Diagnosis. Vol. 608. New York: springer, 2001.

4.     Van Es, J., et al. “A simple decision rule including D‐dimer to reduce the need for computed tomography scanning in patients with suspected pulmonary embolism.” Journal of Thrombosis and Haemostasis 13.8 (2015): 1428-1435.