Litcius/Paper detail

Missing values and inconclusive results in diagnostic studies – A scoping review of methods

Katharina Stahlmann, Johannes B. Reitsma, Antonia Zapf

2023Statistical Methods in Medical Research10 citationsDOIOpen Access PDF

Abstract

Most diagnostic studies exclude missing values and inconclusive results from the analysis or apply simple methods resulting in biased accuracy estimates. This may be due to the lack of availability or awareness of appropriate methods. This scoping review aimed to provide an overview of strategies to handle missing values and inconclusive results in the reference standard or index test in diagnostic accuracy studies. Conducting a systematic literature search in MEDLINE, Cochrane Library, and Web of Science, we could identify many articles proposing methods for addressing missing values in the reference standard. There are also several articles describing methods regarding missing values or inconclusive results in the index test. The latter encompass imputation, frequentist and Bayesian likelihood, model-based, and latent class methods. While methods for missing values in the reference standard are regularly applied in practice, this is not true for methods addressing missing values and inconclusive results in the index test. Our comprehensive overview and description of available methods may raise further awareness of these methods and will enhance their application. Future research is needed to compare the performance of these methods under different conditions to give valid and robust recommendations for their usage in various diagnostic accuracy research scenarios.

Topics & Concepts

Missing dataComputer scienceFrequentist inferenceData miningImputation (statistics)Bayesian probabilityStatisticsData scienceMachine learningArtificial intelligenceBayesian inferenceMathematicsStatistical Methods and Bayesian InferenceStatistical Methods in Clinical TrialsMeta-analysis and systematic reviews