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Managing Clinical Heterogeneity: An Argument for Benefit-Based Action Limits
Author(s) -
Sudarshan Ramachandran,
Carola S. König,
Geoffrey Hackett,
Mark Livingston,
Richard C. Strange
Publication year - 2018
Publication title -
journal of engineering and science in medical diagnostics and therapy
Language(s) - English
Resource type - Journals
eISSN - 2572-7966
pISSN - 2572-7958
DOI - 10.1115/1.4039561
Subject(s) - argument (complex analysis) , action (physics) , population , range (aeronautics) , computer science , medicine , psychology , cognitive psychology , data science , risk analysis (engineering) , engineering , physics , environmental health , quantum mechanics , aerospace engineering
The use of reference ranges is well established in medical practice and research. Classically, a range would be derived from the local healthy population and matched in age, gender, and other characteristics to the patients under investigation. However, recruiting suitable controls is problematic and the derivation of the range by excluding 2.5% at each end of the distribution results in 5% of the values being arbitrarily discarded. Thus, the traditional reference range is derived using statistical and not clinical principles. While these considerations are recognized by clinicians, it is often not realized that the application of whole population derived reference ranges to complex pathologies that comprise patient subgroups may be problematic. Such subgroups may be identified by phenotypes including genetic etiology, variations in exposure to a causative agent, and tumor site. In this review, we provide examples of how subgroups can be identified in diverse pathologies and how better management can be achieved using evidence-based action limits rather than reference ranges. We give examples from our clinical experience of problems arising from using the wrong reference ranges for the clinical situation. Identifying subgroups will often enable clinicians to derive specific action limits for treatment that will lead to customized management and researchers a route into the study of complex pathologies.

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