Leveraging hybrid biomarkers in clinical endpoint prediction

Clinical Studies of Biomarkers in Suicide Prediction

Leveraging Clinical Time-Series Data for Prediction: A Cautionary Tale

In healthcare, patient risk stratification models are often learned using time-series data extracted from electronic health records. When extracting data for a clinical prediction task, several formulations exist, depending on how one chooses the time of prediction and the prediction horizon. In this paper, we show how the formulation can greatly impact both model performance and clinical utili...

Updating clinical endpoint definitions

The 6-Minute Walk Distance (6-MWD) has been the most utilized endpoint for judging the efficacy of pulmonary arterial hypertension (PAH) therapy in clinical trials conducted over the past two decades. Despite its simplicity, widespread use in recent trials and overall prognostic value, the 6-MWD has often been criticized over the past several years and pleas from several PAH experts have emerge...

Vascular Biomarkers in the Prediction of Clinical Cardiovascular Disease

We compared the ability of separately measured intimal-medial thickness and atherosclerotic plaque to predict incident cardiovascular disease. American Indian men and women from the Strong Heart Study who were free of cardiovascular disease were evaluated with carotid ultrasound and cardiovascular disease risk factor assessment. End-diastolic intimal-medial thickness of the common carotid arter...

Surrogate endpoint biomarkers and their modulation in cervical chemoprevention trials.

BACKGROUND Surrogate endpoint biomarkers (SEBs) are used as intermediate indicators of a reduction in cancer incidence in chemoprevention studies. SEBs should be expressed differentially in normal and high risk tissue; appear at a well defined stage of carcinogenesis; be studied with reasonable sensitivity, specificity, and accuracy; and be modulated in chemoprevention trials. The concept of SE...