Andrew Trigg, Bohdana Ratitch, Frank Kruesmann, Madhurima Majumder, Andrejus Parfionovas, Ulrike Krahn
{"title":"Interpretation of Change in Novel Digital Measures: A Statistical Review and Tutorial.","authors":"Andrew Trigg, Bohdana Ratitch, Frank Kruesmann, Madhurima Majumder, Andrejus Parfionovas, Ulrike Krahn","doi":"10.1159/000543899","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Novel clinical measures assessed by a digital health technology tool require thresholds to interpret change over time, such as the minimal clinically important difference. Establishing such thresholds is a key component of clinical validation, facilitating understanding of relevant treatment effects.</p><p><strong>Summary: </strong>Many of the approaches to derive interpretative thresholds for patient-reported outcomes can be applied to digital clinical measures. We present theoretical background to the use of interpretative thresholds, including the distinction between thresholds based on perceived importance versus measurement error, and thresholds for group- versus individual-level interpretations. We then review methods to estimate such thresholds, including anchor-based approaches. We illustrate the methods using data on cough frequency counts as measured by a wearable device in a clinical trial.</p><p><strong>Key messages: </strong>This paper provides an overview of statistical methodologies to estimate thresholds for the interpretation of change.</p>","PeriodicalId":11242,"journal":{"name":"Digital Biomarkers","volume":"9 1","pages":"52-66"},"PeriodicalIF":0.0000,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11919315/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Digital Biomarkers","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1159/000543899","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"Computer Science","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Novel clinical measures assessed by a digital health technology tool require thresholds to interpret change over time, such as the minimal clinically important difference. Establishing such thresholds is a key component of clinical validation, facilitating understanding of relevant treatment effects.
Summary: Many of the approaches to derive interpretative thresholds for patient-reported outcomes can be applied to digital clinical measures. We present theoretical background to the use of interpretative thresholds, including the distinction between thresholds based on perceived importance versus measurement error, and thresholds for group- versus individual-level interpretations. We then review methods to estimate such thresholds, including anchor-based approaches. We illustrate the methods using data on cough frequency counts as measured by a wearable device in a clinical trial.
Key messages: This paper provides an overview of statistical methodologies to estimate thresholds for the interpretation of change.