A systematic review of multi-variate time series approaches to extract predictive asthma biomarkers from routinely collected diary data

Objectives Longitudinal data is commonly acquired in asthma studies, to help assess asthma progression in patients, and to determine predictors of future outcomes, including asthma exacerbations and asthma control. Different methods exist for quantifying temporal behaviour in routinely collected diary variables to obtain meaningful predictive biomarkers of asthma outcomes. The aims of this systematic review were to evaluate the methods for extracting biomarkers from longitudinally collected diary data in asthma and investigate associations between the extracted measures and asthma patient reported outcomes (PROs). Setting A systematic review of MEDLINE, EMBASE, CINAHL and the Cochrane Library was conducted, using index terms relating to diary variables and asthma outcomes. Studies that focused on preschool children were excluded, to avoid confounding asthma with multi-factorial preschool wheeze. Study quality and risk of bias were assessed using the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) and the Prediction model Risk Of Bias ASessment Tool (PROBAST), respectively. Participants Adults and/or children of school age (≥5 years old), with clinician-diagnosed asthma Primary outcomes Asthma PROs, namely asthma exacerbations, asthma control, asthma-related quality of life and asthma severity Results 24 full-text articles met the inclusion criteria and were included in the review. Generally, higher levels of variability in the diary variables were associated with poorer outcomes, especially increased asthma exacerbation risk, and poor asthma control. There was increasing interest in nonparametric methods to quantify complex behaviour of diary variables (6/24). TRIPOD and PROBAST highlighted a lack of consistent reporting of model performance measures and potential for model bias. Discussion Routinely collected diary variables aid in generating asthma assessment tools, including surrogate endpoints, for clinical trials, and predictive biomarkers of adverse outcomes, warranting monitoring through remote sensors. Studies consistently lacked robust reporting of model performance. Future research should utilise diary variable-derived biomarkers. Article Summary Strengths and limitations of this study Only one reviewer was involved in screening the titles and abstracts for inclusion into the systematic review. ### Competing Interest Statement Franz Aaron Clemeno and Matthew Richardson do not report any conflicts of interest. Salman Siddiqui reports grants from the UK Medical Research Council and the Eingineering and Physical Sciences Research Council, and personal fees from GSK, AstraZeneca, Roche, Novartis, Chiesi, CSL Behring, Areteia Therapeutics and Owlstone Medical, outside of the submitted work. ### Funding Statement This project was supported by the NIHR Imperial Biomedical Research Centre (BRC) and the NIHR Leicester BRC. The views expressed are those of the author(s) and not necessarily those of the NIHR or Department of Health and Social Care. Franz Aaron Clemeno is funded by a University of Leicester, College of Life Sciences PhD Studentship. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: N/A I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present work are contained in the manuscript.