Patient-reported outcomes and treatment adherence in type 2 diabetes using natural language processing: Wave 8 of the Observational International Diabetes Management Practices Study.

Aims/introduction: We analyzed patient-reported outcomes of people with type 2 diabetes to better understand perceptions and experiences contributing to treatment adherence.

Materials And Methods: In the ongoing International Diabetes Management Practices Study, we collected patient-reported outcomes data from structured questionnaires (chronic treatment acceptance questionnaire and Diabetes Self-Management Questionnaire) and free-text answers to open-ended questions to assess perceptions of treatment value and side-effects, as well as barriers to, and enablers for, adherence and self-management. Free-text answers were analyzed by natural language processing.

Development of a rare disease algorithm to identify persons at risk of Gaucher disease using electronic health records in the United States.

Background: Early diagnosis of Gaucher disease (GD) allows for disease-specific treatment before significant symptoms arise, preventing/delaying onset of complications. Yet, many endure years-long diagnostic odysseys. We report the development of a machine learning algorithm to identify patients with GD from electronic health records.

Qluster: An easy-to-implement generic workflow for robust clustering of health data.

The exploration of heath data by clustering algorithms allows to better describe the populations of interest by seeking the sub-profiles that compose it. This therefore reinforces medical knowledge, whether it is about a disease or a targeted population in real life. Nevertheless, contrary to the so-called conventional biostatistical methods where numerous guidelines exist, the standardization of data science approaches in clinical research remains a little discussed subject.

Rationale and methodology for a European pooled analysis of postmarketing interventional and observational studies of insulin glargine 300 U/mL in diabetes: protocol of REALI project.

Introduction: Type 2 diabetes mellitus (T2DM) is a common and heterogeneous disease. Using advanced analytic approaches to explore real-world data may identify different disease characteristics, responses to treatment and progression patterns. Insulin glargine 300 units/mL (Gla-300) is a second-generation basal insulin analogue with preserved glucose-lowering efficacy but reduced risk of hypoglycaemia.