Mechanistic Learning for Predicting Survival Outcomes in Head and Neck Squamous Cell Carcinoma.

We employed a mechanistic learning approach, integrating on-treatment tumor kinetics (TK) modeling with various machine learning (ML) models to address the challenge of predicting post-progression survival (PPS)-the duration from the time of documented disease progression to death-and overall survival (OS) in Head and Neck Squamous Cell Carcinoma (HNSCC). We compared the predictive power of model-derived TK parameters versus RECIST and assessed the efficacy of nine TK-OS ML models against conventional survival models. Data from 526 advanced HNSCC patients treated with chemotherapy and cetuximab in the TPExtreme trial were analyzed using a double-exponential model.

Lipid-Lowering Therapy Use When Indicated and Subsequent Ischemic Stroke Severity.

Background: Elevated low-density lipoprotein cholesterol is a risk factor for atherosclerotic cardiovascular disease, including acute ischemic stroke (AIS), due to large- and small-vessel disease. Cholesterol management guidelines recommend lipid-lowering therapy (LLT) to prevent atherosclerotic cardiovascular disease events. This study assessed use of LLT at the time of AIS according to guideline recommendations and determined the association of prestroke LLT use with stroke severity.

A snapshot of cancer in Chile II: an update on research, strategies and analytical frameworks for equity, innovation and national development.

Introduction: Chile has achieved developed nation status and boasts a life expectancy of 81 + years; however, the healthcare and research systems are unprepared for the social and economic burden of cancer. One decade ago, the authors put forward a comprehensive analysis of cancer infrastructure, together with a series of suggestions on research orientated political policy.

Objectives: Provide an update and comment on policy, infrastructure, gender equality, stakeholder participation and new challenges in national oncology.

Influenza vaccine effectiveness against hospitalizations and emergency department or urgent care encounters for children, adolescents, and adults during the 2023-2024 season, United States.

Background: The 2023-2024 influenza season had predominant influenza A(H1N1)pdm09 virus activity, but A(H3N2) and B viruses co-circulated. Seasonal influenza vaccine strains were well-matched to these viruses.

Methods: Using health care encounters data from health systems in 8 states, we evaluated influenza vaccine effectiveness (VE) against influenza-associated medical encounters from October 2023-April 2024.