Screening and Diagnostic tests for Health-related Quality of Life

Objective: The paper describes conceptual framework and methodological issues to find cut-off points considering summative scores with emphasis on Receiver Operating Characteristic (ROC) curve and associated components like area under the curve (AUC), sensitivity and specificity along with scoring and their properties. Material and Methods: To establish presence (or absence) of disease as a basis for treatment decisions, diagnostic tests require meaningful total/domain scores. Problems of evaluation of Health-related Quality of Life (HRQoL) scales and remedial measures by transforming item scores to continuous, monotonic scores following normal distribution satisfying desired properties, undertaking parametric analysis and better utilization of such tests are also suggested. Ethical approval of research is not required for the methodological paper involving no human beings or animals. Results: Paramet­ric method may result in improper ROC curve if data violate the normality assumption or within-group variations are dissimilar (heteroscedasticity). Equivalent non-parametric ROC curve, without involving assumption of normali­ty can be obtained by ROCKIT package containing ROCFIT method along with estimate of AUC and partial area, under certain conditions. If multiple test results from a single case-condition combination are pooled in input, statistical significance of apparent difference between the ROC curves gets overestimated. Conclusion: Transforming HRQoL scores to normally distributed scores with meaningful arithmetic aggregation have promise to improve current assessment practices.