Abstract
Aims: This study introduces new digital biomarkers to be used as precise, objective tools to measure and describe the clinical course of patients with alcohol use disorder (AUD).Methods: An algorithm is outlined for the calculation of a new digital biomarker, the recovery and exacerbation index (REI), which describes the current trend in a patient's clinical course of AUD. A threshold applied to the REI identifies the starting point and the length of an exacerbation event (EE). The disease patterns and periodicity are described by the number, length, and distance between EEs. The algorithms were tested on data from patients from previous clinical trials (n = 51) and clinical practice (n = 1,717).Results: Our study indicates that the digital biomarker-based description of the clinical course of AUD might be superior to the traditional self-reported relapse/remission concept and conventional biomarkers due to higher data quality (alcohol measured) and time resolution. We found that EEs and the REI introduce distinct tools to identify qualitative and quantitative differences in drinking patterns (drinks per drinking day, phosphatidyl ethanol levels, weekday and holiday patterns) and effect of treatment time.Conclusions: This study indicates that the disease state—level, trend and periodicity—can be mathematically described and visualized with digital biomarkers, thereby improving knowledge about the clinical course of AUD and enabling clinical decision-making and adaptive care. The algorithms provide a basis for machine-learning-driven research that might also be applied for other disorders where daily data are available from digital health systems.
Highlights
Treatment outcomes are often modest, especially if the desired outcome is long-term, permanent recovery; for alcohol use disorder (AUD), success rates of treatment can be as low as 10% [2], rates are higher if abstinence is not defined as outcome goal [3]
In the Methods section, we first describe the details on how the recovery and exacerbation index was constructed and how we identified a threshold for the identification of exacerbation events, and in the Results section, we describe how—together with the addiction monitoring index (AMI)—they were used to describe the clinical course of 51 patients
To explore how digital biomarkers can describe the clinical course of AUD patients in a detailed way, we analyzed seven patients (A–G) in depth
Summary
In most fields of medicine, objective measurements provide an indispensable basis for any kind of treatment. In the biomedical field it is widely accepted that AUD can be defined as a chronic, relapsing disorder characterized by compulsive drug seeking behavior and continued use, despite well-known harmful consequences, which will lead to longlasting alterations in the brain [4] In this context it is worth mentioning that some researchers disagree with scientists describing drug addiction as a chronic condition [5, 6]. Their concerns are that this formulation privileges biological aspects of dependence to the detriment of psychological and social contributions, and that, resources will only be focused on patients in treatment—excluding the vast majority of still functional individuals with addictive disorders [7], who are the main cause of alcohol related costs. Of the above, long-term measurement-based daily monitoring of the clinical course (alcohol use) should be the key for selecting and planning of treatment
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