Rethinking ME/CFS Diagnostic Reference Intervals via Machine Learning, and the Utility of Activin B for Defining Symptom Severity. (Lidbury 2019)

[Murph]

Diagnostics (Basel). 2019 Jul 19;9(3). pii: E79. doi: 10.3390/diagnostics9030079.
Rethinking ME/CFS Diagnostic Reference Intervals via Machine Learning, and the Utility of Activin B for Defining Symptom Severity.
Lidbury BA1, Kita B2, Richardson AM3, Lewis DP4, Privitera E4, Hayward S5, de Kretser D2,6, Hedger M5.
Author information

Abstract
Biomarker discovery applied to myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), a disabling disease of inconclusive aetiology, has identified several cytokines to potentially fulfil a role as a quantitative blood/serum marker for laboratory diagnosis, with activin B a recent addition. We explored further the potential of serum activin B as a ME/CFS biomarker, alone and in combination with a range of routine test results obtained from pathology laboratories. Previous pilot study results showed that activin B was significantly elevated for the ME/CFS participants compared to healthy (control) participants. All the participants were recruited via CFS Discovery and assessed via the Canadian/International Consensus Criteria. A significant difference for serum activin B was also detected for ME/CFS and control cohorts recruited for this study, but median levels were significantly lower for the ME/CFS cohort.

Random Forest (RF) modelling identified five routine pathology blood test markers that collectively predicted ME/CFS at ≥62% when compared via weighted standing time (WST) severity classes. A closer analysis revealed that the inclusion of activin B to the panel of pathology markers improved the prediction of mild to moderate ME/CFS cases. Applying correct WST class prediction from RFA modelling, new reference intervals were calculated for activin B and associated pathology markers, where 24-h urinary creatinine clearance, serum urea and serum activin B showed the best potential as diagnostic markers. While the serum activin B results remained statistically significant for the new participant cohorts, activin B was found to also have utility in enhancing the prediction of symptom severity, as represented by WST class.
KEYWORDS:
activin; biomarker; chronic fatigue syndrome; cytokine; machine learning; myalgic encephalomyelitis; pathology; reference intervals
PMID: 31331036 DOI: 10.3390/diagnostics9030079

 

[nandixon]

This study is actually pretty funny. Basically, they screwed up in their pilot study and were using a bad assay method to determine activin B levels, which came to light when they did this larger study and obtained the opposite results from the pilot study. And in order to make lemonade out of lemons they then did a bunch of curve fitting ("machine learning") to try to show that activin B might still have some utility by combining it with some other common laboratory test results to try to come up with a diagnostic test for ME/CFS severity...