The Impact of Model Assumptions on Personalized Lung Cancer Screening Recommendations.

Background: Recommendations regarding personalized lung cancer screening are being informed by natural-history modeling. Therefore, understanding how differences in model assumptions affect model-based personalized screening recommendations is essential.

Design: Five Cancer Intervention and Surveillance Modeling Network (CISNET) models were evaluated.

Competencies for Those Who Coach Physicians: A Modified Delphi Study.

The rapidly evolving coaching profession has permeated the health care industry and is gaining ground as a viable solution for addressing physician burnout, turnover, and leadership crises that plague the industry. Although various coach credentialing bodies are established, the profession has no standardized competencies for physician coaching as a specialty practice area, creating a market of aspiring coaches with varying degrees of expertise. To address this gap, we employed a modified Delphi approach to arrive at expert consensus on competencies necessary for coaching physicians and physician leaders.

Pack-Year Smoking History: An Inadequate and Biased Measure to Determine Lung Cancer Screening Eligibility.

Purpose: Pack-year smoking history is an imperfect and biased measure of cumulative tobacco exposure. The use of pack-year smoking history to determine lung cancer screening eligibility in the current US Preventive Services Task Force (USPSTF) guideline may unintentionally exclude many high-risk individuals, especially those from racial and ethnic minority groups. It is unclear whether using a smoking duration cutoff instead of a smoking pack-year cutoff would improve the selection of individuals for screening.

Risk Model-Based Lung Cancer Screening : A Cost-Effectiveness Analysis.

Background: In their 2021 lung cancer screening recommendation update, the U.S. Preventive Services Task Force (USPSTF) evaluated strategies that select people based on their personal lung cancer risk (risk model-based strategies), highlighting the need for further research on the benefits and harms of risk model-based screening.