Evidence map›Paper›PMID 38317237›Full record

ReviewJournal of translational medicine2024

Standardizing digital biobanks: integrating imaging, genomic, and clinical data for precision medicine.

Valentina Brancato, Giuseppina Esposito, Luigi Coppola, Carlo Cavaliere, Peppino Mirabelli, Camilla Scapicchio, Rita Borgheresi, Emanuele Neri, Marco Salvatore, Marco Aiello

Abstract readReview
In one paragraph

Review in Journal of translational medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

42 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Best practices for using biological data in psychological research.Journal of mood and anxiety disorders · 2026
    Review
  4. Review
  5. Article
  6. Review
  7. Review
  8. Review
  9. bioRxiv : the preprint server for biology · 2026
    Article
  10. Establishing a Cervical Cytology Biorepository: A Protocol for Advancing Translational Cervical Cancer Research through Biobanking.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2026
    Article
  11. Article
  12. Review
  13. Article
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  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Valentina Brancato *IRCCS SYNLAB SDN, 80143, Naples, Italy.
Giuseppina Esposito *Bio Check Up S.R.L, 80121, Naples, Italy.
Luigi CoppolaIRCCS SYNLAB SDN, 80143, Naples, Italy.
Carlo CavaliereIRCCS SYNLAB SDN, 80143, Naples, Italy.
Peppino MirabelliUOS Laboratori di Ricerca e Biobanca, AORN Santobono-Pausilipon, Via Teresa Ravaschieri, 8, 80122, Naples, Italy.
Camilla ScapicchioAcademic Radiology, Department of Translational Research, University of Pisa, via Roma, 67, 56126, Pisa, Italy.
Rita BorgheresiAcademic Radiology, Department of Translational Research, University of Pisa, via Roma, 67, 56126, Pisa, Italy.
Emanuele NeriAcademic Radiology, Department of Translational Research, University of Pisa, via Roma, 67, 56126, Pisa, Italy.
Marco SalvatoreIRCCS SYNLAB SDN, 80143, Naples, Italy.
Marco AielloIRCCS SYNLAB SDN, 80143, Naples, Italy. marco.aiello@synlab.it.ORCID 0000-0002-3676-0664

Funding

HORIZON EUROPE Research and Innovation program - EUCAIM 101100633Ministero della Salute Ricerca CorrenteMinistero dello Sviluppo Economico, Infrastructure to support Biobanking for Research in Integrated Diagnostics - IBRID I63D22000550005
6 · The paper itself

Abstract

Advancements in data acquisition and computational methods are generating a large amount of heterogeneous biomedical data from diagnostic domains such as clinical imaging, pathology, and next-generation sequencing (NGS), which help characterize individual differences in patients. However, this information needs to be available and suitable to promote and support scientific research and technological development, supporting the effective adoption of the precision medicine approach in clinical practice. Digital biobanks can catalyze this process, facilitating the sharing of curated and standardized imaging data, clinical, pathological and molecular data, crucial to enable the development of a comprehensive and personalized data-driven diagnostic approach in disease management and fostering the development of computational predictive models. This work aims to frame this perspective, first by evaluating the state of standardization of individual diagnostic domains and then by identifying challenges and proposing a possible solution towards an integrative approach that can guarantee the suitability of information that can be shared through a digital biobank. Our analysis of the state of the art shows the presence and use of reference standards in biobanks and, generally, digital repositories for each specific domain. Despite this, standardization to guarantee the integration and reproducibility of the numerical descriptors generated by each domain, e.g. radiomic, pathomic and -omic features, is still an open challenge. Based on specific use cases and scenarios, an integration model, based on the JSON format, is proposed that can help address this problem. Ultimately, this work shows how, with specific standardization and promotion efforts, the digital biobank model can become an enabling technology for the comprehensive study of diseases and the effective development of data-driven technologies at the service of precision medicine.

Indexed as

Biological Specimen BanksPrecision MedicineGenomicsHumansReproducibility of ResultsBig dataBiobankingClinical decision support systems (CDSS)Data integrationImagingNGSPathomicsPrecision medicineRadiomicsStandardization

Identifiers

PMID38317237
PMCPMC10845786

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.