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. 2019 Feb 26;321(8):739-740.
doi: 10.1001/jama.2019.0286.

Potential Excessive Testing at Scale: Biomarkers, Genomics, and Machine Learning

Affiliations

Potential Excessive Testing at Scale: Biomarkers, Genomics, and Machine Learning

Kenneth D Mandl et al. JAMA. .
No abstract available

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Conflict of interest statement

Conflict of Interest Disclosures: Dr Manrai reported receiving personal fees from doc.ai outside the submitted work. No other disclosures were reported.

Figures

Figure.
Figure.. Pathways That Promote Increased Application of Biomarkers
A, Statin treatment recommendations changed substantially between the 2004 Adult Treatment Panel (ATP) and the 2013 American College of Cardiology–American Heart Association (ACC/AHA) guidelines. For primary prevention among patients without diabetes and with a 10-year cardiovascular disease risk of 7.5% or more, the guidelines switch amounts to lowering the low-density lipoprotein (LDL) cholesterol threshold from 190 to 70 mg/dL (to convert LDL from mg/dL to mmol/L, multiply by 0.0259). Survey-weighted estimates from the Centers for Disease Control and Prevention National Health and Nutrition Examination Survey (NHANES) 2013–2014 cohort show substantial increases in the population defined as having the risk factor. B, New digital biomarkers are entering clinical care settings. Even with nearly identical testing characteristics, 2 machine learning algorithms to detect diabetic retinopathy using different thresholds along their respective receiver operating characteristic curves will drive substantially different numbers of ophthalmology referrals and possibly treatments.

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