MULTIPREVENT: Integrated screening for smoking-related multimorbidity using low-dose chest computed tomography.
A large lung screening platform is expanding to simultaneously detect and predict risk for five smoking-related diseases using advanced AI integration.
This protocol paper describes MULTIPREVENT, a large prospective cohort study leveraging the existing MOLTEST-BIS lung cancer screening infrastructure to extend integrated multimorbidity screening combining LDCT radiomics, spirometry, biomarkers, and Illumina Global Screening Array genomic profiling in 3000 heavy smokers with two follow-up timepoints through 2032. AI-based integration of all data streams is planned to develop predictive risk models for lung cancer, cardiovascular disease, COPD, osteoporosis, and diabetes simultaneously, positioning the study as a foundational platform for population-based multimorbidity prevention.
What the study was
- Study design
- Protocol paper (prospective epidemiological cohort)
- Population
- 3000 participants from the MOLTEST-BIS lung cancer screening cohort (aged 50-79, ≥30 pack-years), followed up in 2025-2027 and 2030-2032
- Sample size
- 3000
- Category
- Prevention
- Maturity
- Exploratory
- Journal
- Public Health
Why it surfaced
Well-designed multicohort precision prevention protocol integrating imaging, biomarkers, and genomics; note as protocol paper only — no outcome data yet.
A plain-language summary of published research — not medical advice. Talk to a clinician about your own care.