Survival analysis for lung cancer patients: A comparison of Cox regression and machine learning models.

Introduction: Survival analysis based on cancer registry data is of paramount importance for monitoring the effectiveness of health care. As new methods arise, the compendium of statistical tools applicable to cancer registry data grows. In recent years, machine learning approaches for survival analysis were developed.

Cardiovascular disease risk after a SARS-CoV-2 infection: A systematic review and meta-analysis.

Objectives: To our knowledge, there is no systematic review examining CVD risks after a SARS-CoV-2 infection over time, while also taking into account disease severity. All evidence on the risk for pulmonary embolism (PE), myocardial infarction (MI), ischaemic stroke (IS), haemorrhagic stroke (HS), and arterial thrombosis following infection was evaluated.

Methods: The protocol was registered with PROSPERO.

Learning debiased graph representations from the OMOP common data model for synthetic data generation.

Background: Generating synthetic patient data is crucial for medical research, but common approaches build up on black-box models which do not allow for expert verification or intervention. We propose a highly available method which enables synthetic data generation from real patient records in a privacy preserving and compliant fashion, is interpretable and allows for expert intervention.

Methods: Our approach ties together two established tools in medical informatics, namely OMOP as a data standard for electronic health records and Synthea as a data synthetization method.

Effect of Metformin on Plasma Exposure of Rifampicin, Isoniazid, and Pyrazinamide in Patients on Treatment for Pulmonary Tuberculosis.

Background: To evaluate the effect of metformin on the plasma levels of rifampicin, isoniazid, and pyrazinamide in patients with drug-sensitive pulmonary tuberculosis being treated with first-line antituberculosis treatment (ATT) and to assess the influence of gene polymorphisms on the metabolic pathway of metformin and plasma levels of antitubercular drugs.

Methods: Nondiabetic adults aged 18-60 years with pulmonary tuberculosis were randomized to either the standard ATT (ATT group) or ATT plus metformin (METRIF group) groups in a phase IIB clinical trial. An intensive pharmacokinetic study with blood collection at 0 hour (predosing), followed by 1, 2, 4, 6, 8, and 12 hours after dosing was conducted during the first month of treatment in a subset of 60 study participants after a minimum of 14 doses.

Healthcare Policies to Eliminate Neglected Tropical Diseases (NTDs) in India: A Roadmap.

The need for systemic healthcare policies to systematically eliminate NTDs globally and in India has been stressed for more than two decades. Yet, the present policies and the research on them do not meet the need. We present an ontological framework, a research roadmap, and a policy brief to address the gap.