Avaliação do desempenho de indicadores com base na metodologia ROC (Receiver Operating Characteristic)

Dissertação de mestrado em Bioinformática

Nonparametric estimation of time-dependent ROC curves conditional on a continuous covariate

The receiver-operating characteristic (ROC) curve is the most widely used measure for evaluating the performance of a diagnostic biomarker when predicting a binary disease outcome. The ROC curve displays the true positive rate (or sensitivity) and the false positive rate (or 1-specificity) for different cut-off values used to classify an individual as healthy or diseased. In time-to-event studies, however, the disease status (e.g. death or alive) of an individual is not a fixed characteristic, and it varies along the study. In such cases, when evaluating the performance of the biomarker, several issues should be taken into account: first, the time-dependent nature of the disease status; and second, the presence of incomplete data (e.g. censored data typically present in survival studies). Accordingly, to assess the discrimination power of continuous biomarkers for time-dependent disease outcomes, time-dependent extensions of true positive rate, false positive rate, and ROC curve have been recently proposed. In this work, we present new nonparametric estimators of the cumulative/dynamic time-dependent ROC curve that allow accounting for the possible modifying effect of current or past covariate measures on the discriminatory power of the biomarker. The proposed estimators can accommodate right-censored data, as well as covariate-dependent censoring. The behavior of the estimators proposed in this study will be explored through simulations and illustrated using data from a cohort of patients who suffered from acute coronary syndrome.

Aplicação da metodologia ROC na avaliação de desempenho de índices de gravidade clínica em unidades de neonatologia de Portugal

Tese de Doutoramento em Engenharia Industrial e de Sistemas

Screening for depression and anxiety disorders from pregnancy to postpartum with the EPDS and STAI

The Edinburgh Postnatal Depression Scale (EPDS) and the State Anxiety Inventory (STAI-S) are widely used self-report measures that still need to be further validated for the perinatal period. The aim of this study was to examine the screening performance of the EPDS and the STAI-S in detecting depressive and anxiety disorders at pregnancy and postpartum. Women screening positive on EPDS (EPDS ≥ 9) or STAI-S (STAI-S ≥ 45) during pregnancy (n = 90), as well as matched controls (n = 58) were selected from a larger study. At 3 months postpartum, 99 of these women were reassessed. At a second stage, women were administered a clinical interview to establish a DSM-IV-TR diagnosis. Receiver operator characteristics (ROC) analysis yielded areas under the curve higher than .80 and .70 for EPDS and STAI-S, respectively. EPDS and STAI-S optimal cut-offs were found to be lower at postpartum (EDPS = 7; STAI-S = 34) than during pregnancy (EPDS = 9; STAI-S = 40). EPDS and STAI-S are reasonably valid screening tools during pregnancy and the postpartum.