Biostatistics & Clinical Data Platform

Head of the Unit

Alice Bonomi, PhD

Biostatistics and Database Management Facility for Research – Clinical Data Platform

The Biostatistics and Database Management Facility for Research – Clinical Data Platform at Centro Cardiologico Monzino plays a pivotal role in supporting the design, collection, management, and analysis of data generated through clinical and translational research studies. The unit ensures a rigorous approach to data management, promoting the quality, integrity, and reproducibility of scientific results.

Drawing on specialized expertise in medical statistics, data management, and data governance, the facility works closely with both clinical and experimental research groups, providing support throughout the entire research process—from study design and protocol development to data analysis and interpretation of results.

In addition, the unit collaborates with engineers and IT specialists to enable the integration and harmonization of data from heterogeneous sources, including electronic health records, clinical registries, biobanks, and omics platforms. This multidisciplinary approach facilitates the creation of comprehensive and interoperable research datasets, supporting increasingly data-driven clinical research and advancing precision medicine initiatives.

Selected Projects

  • Synthetic Data

    As part of ongoing innovation in data management and utilization, the Unit is also involved in the development of projects based on synthetic data. These initiatives aim to generate realistic artificial datasets derived from real-world clinical data, while preserving the essential statistical and clinical characteristics of the original data and ensuring patient privacy protection.

    Synthetic data represent a strategic resource for testing analytical models, developing artificial intelligence algorithms, and enabling the secure sharing of data within scientific collaborations. This approach is part of a broader strategy aimed at promoting ethical, reproducible clinical research and fostering the safe and responsible use of health data.

    Mediation Analysis in Cardiology

    Establishing causal relationships in observational studies remains a major methodological challenge. The Unit applies advanced statistical techniques, such as mediation analysis, to investigate and quantify the mechanisms through which risk factors influence clinical outcomes.

    By identifying and measuring intermediate pathways between exposures and outcomes, mediation analysis provides valuable insights into disease mechanisms, helping researchers better understand the processes underlying cardiovascular conditions and informing more targeted prevention and treatment strategies.

    Statistical Analysis of Omics Data

    The Unit provides support for the management, integration, and analysis of genomic and transcriptomic data, with the goal of identifying novel biomarkers and molecular mechanisms associated with cardiovascular diseases.

    The team contributes to the development of customized statistical models tailored to complex multi-omics datasets and supports the clinical interpretation of findings. Through the integration of advanced bioinformatics and statistical methodologies, the Unit helps translate large-scale molecular data into biologically meaningful insights and clinically relevant applications.

best publications in the last three years

    • Cangiano L, Bonomi A, Cosentino N, Leoni O, Trombara F, Myasoedova VA, Poggio P, Trabattoni D, Agostoni P, Marenzi G. Exploring sex differences in mortality among acute myocardial infarction. Open Heart. 2025 Aug 18;12(2):e003517. doi: 10.1136/openhrt-2025-003517. PMID: 40829892; PMCID: PMC12366619.
    • Frigerio B, Coggi D, Bonomi A, Amato M, Capra N, Colombo GI, Sansaro D, Ravani A, Savonen K, Giral P, Gallo A, Pirro M, Gigante B, Eriksson P, Strawbridge RJ, Mulder DJ, Tremoli E, Veglia F, Baldassarre D; IMPROVE Study Group. Determinants of Carotid Wall Echolucency in a Cohort of European High Cardiovascular Risk Subjects: A Cross-Sectional Analysis of IMPROVE Baseline Data. Biomedicines. 2024 Mar 26;12(4):737. doi: 10.3390/biomedicines12040737. PMID: 38672093; PMCID: PMC11154292.
    • Myasoedova VA, Salvioni E, Bonomi A, Galotta A, Mapelli M, Mattavelli I, Rusconi V, Bertolini F, Campodonico J, Contini MC, Massaiu I, Valerio V, Poggio P, Agostoni P. Prognostic significance of early stage aortic valve disease development in heart failure: insights from the MECKI score cohort. Eur Heart J Open. 2025 Jun 6;5(3):oeaf066. doi: 10.1093/ehjopen/oeaf066. PMID: 40574804; PMCID: PMC12198757.
    • Franchi M, Gennari M, Severgnini G, Biancari F, Bonomi A, De Marco F, Polvani G, Agrifoglio M. Clinical outcomes after transcatheter aortic valve implantation in nonagenarian patients: A retrospective population-based cohort study. Ann Epidemiol. 2025 Feb;102:81-85. doi: 10.1016/j.annepidem.2025.01.005. Epub 2025 Jan 14. PMID: 39818241
    • Mastroiacovo G, Bonomi A, Ludergnani M, Franchi M, Maragna R, Pirola S, Baggiano A, Caglio A, Pontone G, Polvani G, Merlino L. Is EuroSCORE II still a reliable predictor for cardiac surgery mortality in 2022? A retrospective study study. Eur J Cardiothorac Surg. 2022 Jan 1;64(3):ezad294. doi: 10.1093/ejcts/ezad294. PMID: 37669150; PMCID: PMC10722878.

Staff

  • Matteo Franchi, PhD

    Francesco Mattio, MSc

    Arianna Galotta, MSc