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What are the merits of a multi-omic approach to diagnosing PTSD?

Molecular Psychiatry volume 25, pages 3127–3128 (2020)Cite this article

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The clinicians and researchers of the PTSD Systems Biology Consortium have carried out an admirable study [1]. Their attempt at finding a diagnostic tool for post-traumatic stress disorder based on biological data clearly is highly original, labor-intensive, and potentially very influential work. It is also of interest far beyond the field of PTSD. With no less than a million markers tested, combined and boiled down in sophisticated ways, it appears the authors marshalled everything biological psychiatry and artificial intelligence can currently muster in order to find a diagnostic tool for a psychiatric disorder. To me, this project represents the state of the art in our field’s many decades long quest for biological methods suitable for diagnostic use and with an impact on clinical practice—a search that, so far, has been largely frustrating.

The authors rightly emphasize the sensitivity (85%) and specificity (77%) of their method. However, additional key characteristics are welcome in analyzing a diagnostic instrument (Table 1), for example: Cohen’s kappa as measurement of a test’s ability to find the diagnosis beyond chance. The likelihood ratio (LR+) that is the ratio of the percentage of correct positive diagnoses to the percentage of false positives. The positive predictive value (PPV) as the proportion of true-positives among all positive test results and thus an approximation of an instrument’s usefulness in clinical practice. Applied to the figures presented in the paper, the instrument’s PPV amounts to 79%, indicating that about four in five patients with a positive diagnosis will indeed have PTSD. Cohen’s kappa turns out to be 0.62, and the (positive) likelihood ratio is 3.67. In commonly used definitions [2, 3], these values signify substantial (kappa) and small (LR) diagnostic advances, respectively.

Table 1 Test properties by PTSD prevalence: 50%, as in the actual study, and the same test applied to virtual samples with prevalences of 25% as well as 12.5% (underlined).
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  1. Department of Psychiatry and Psychotherapy, University of Cologne Medical School, Cologne, Germany

    Christopher Baethge

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Baethge, C. What are the merits of a multi-omic approach to diagnosing PTSD?. Mol Psychiatry 25, 3127–3128 (2020). https://doi.org/10.1038/s41380-020-0694-8

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