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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.
Objective: To evaluate and compare the cost-effectiveness of risk model-based lung cancer screening strategies versus the USPSTF recommendation and to explore optimal risk thresholds.
Design: Comparative modeling analysis.
Data Sources: National Lung Screening Trial; Surveillance, Epidemiology, and End Results program; U.S. Smoking History Generator.
Target Population: 1960 U.S. birth cohort.
Time Horizon: 45 years.
Perspective: U.S. health care sector.
Intervention: Annual low-dose computed tomography in risk model-based strategies that start screening at age 50 or 55 years, stop screening at age 80 years, with 6-year risk thresholds between 0.5% and 2.2% using the PLCOm2012 model.
Outcome Measures: Incremental cost-effectiveness ratio (ICER) and cost-effectiveness efficiency frontier connecting strategies with the highest health benefit at a given cost.
Results Of Base-case Analysis: Risk model-based screening strategies were more cost-effective than the USPSTF recommendation and exclusively comprised the cost-effectiveness efficiency frontier. Among the strategies on the efficiency frontier, those with a 6-year risk threshold of 1.2% or greater were cost-effective with an ICER less than $100 000 per quality-adjusted life-year (QALY). Specifically, the strategy with a 1.2% risk threshold had an ICER of $94 659 (model range, $72 639 to $156 774), yielding more QALYs for less cost than the USPSTF recommendation, while having a similar level of screening coverage (person ever-screened 21.7% vs. USPSTF's 22.6%).
Results Of Sensitivity Analyses: Risk model-based strategies were robustly more cost-effective than the 2021 USPSTF recommendation under varying modeling assumptions.
Limitation: Risk models were restricted to age, sex, and smoking-related risk predictors.
Conclusion: Risk model-based screening is more cost-effective than the USPSTF recommendation, thus warranting further consideration.
Primary Funding Source: National Cancer Institute (NCI).
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http://dx.doi.org/10.7326/M22-2216 | DOI Listing |
Mov Disord Clin Pract
September 2025
Neurology Unit, Neuromotor and Rehabilitation Department, Azienda USL-IRCCS di Reggio Emilia, Reggio Emilia, Italy.
Background: GBA1 variants are the major genetic risk factor for Parkinson's Disease (PD) and account for 5-30% of PD cases depending on the population and age at onset of the disease.
Objectives: The aim of this study was to assess whether Artificial Intelligence (AI) could predict GBA1-mutated genotype in PD (GBA1-PD). Particularly, the main objective was to identify a Machine Learning (ML) model capable of accurately providing a pre-test estimate of GBA1-mutated status, relying on the clinical and demographic variables with the highest predictive value.
Medicine (Baltimore)
September 2025
Department of Critical Care Medicine, Nantong First People's Hospital, Nantong, Jiangsu Province, China.
Background: This study investigates the clinical value of a structured team approach incorporating shared decision-making in managing critically ill pregnant patients within an obstetrics intensive care unit (ICU).
Methods: A randomized controlled trial was conducted with 100 critically ill pregnant women admitted to our hospital's obstetrics ICU between January 2023 and December 2024. Participants were allocated via random number table to either the control group receiving conventional multidisciplinary resuscitation care (n = 50) or the observation group receiving the structured team model with shared decision-making (n = 50).
Neuroradiology
September 2025
Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China.
Purpose: To develop and validate an integrated model based on MR high-resolution vessel wall imaging (HR-VWI) radiomics and clinical features to preoperatively assess periprocedural complications (PC) risk in patients with intracranial atherosclerotic disease (ICAD) undergoing percutaneous transluminal angioplasty and stenting (PTAS).
Methods: This multicenter retrospective study enrolled 601 PTAS patients (PC+, n = 84; PC -, n = 517) from three centers. Patients were divided into training (n = 336), validation (n = 144), and test (n = 121) cohorts.
Front Oncol
August 2025
Department of Digestive Surgery, Xi'an People's Hospital (Xi'an Fourth Hospital), Xi'an, China.
Objective: This study aims to develop a prediction model for invasive metastasis of primary liver cancer based on serum extracellular matrix metalloproteinase-inducing factor (CD147) and interleukin-6 (IL-6).
Methods: Between July 2022 and August 2024, 170 surgically treated primary hepatocellular carcinoma patients at our hospital were recruited. They were divided into a training group ( = 120) and a validation group ( = 50) at a 7:3 ratio.
Oncol Res
September 2025
Department of Urology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China.
Studies have reported the special value of PANoptosis in cancer, but there is no study on the prognostic and therapeutic effects of PANoptosis in bladder cancer (BLCA). This study aimed to explore the role of PANoptosis in BLCA heterogeneity and its impact on clinical outcomes and immunotherapy response while establishing a robust prognostic model based on PANoptosis-related features. Gene expression profiles and clinical data were collected from public databases.
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