Evidence map›Paper›PMID 41832233›Full record

ReviewNPJ precision oncology2026

Integrating transcriptomic data and artificial intelligence to personalize curative treatments for head and neck cancer patients.

Stefano Cavalieri, Loris De Cecco, Dario Monzani, Hisham Mehanna, Renata Ferrarotto, Christian Simon, Robert Haddad, Pierre Saintigny, Christophe Le Tourneau, Lisa Licitra

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in NPJ precision oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Stefano CavalieriHead and Neck Medical Oncology Department, Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Milan, Italy. stefano.cavalieri@istitutotumori.mi.it.
Loris De CeccoIntegrated Biology of Rare Tumors, Department of Experimental Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
Dario MonzaniApplied Research Division for Cognitive and Psychological Science, IEO, European Institute of Oncology IRCCS, Milan, Italy.
Hisham MehannaInstitute of Head and Neck Studies and Education (InHANSE), Dept of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK.
Renata FerrarottoDepartment of Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Christian SimonDepartment of Otolaryngology-Head and Neck Surgery, Centre Hospitalier Universitaire Vaudois (CHUV), UNIL, Lausanne, Switzerland.
Robert HaddadDepartment of Medical Oncology, Division of Head and Neck Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
Pierre SaintignyDepartment of Medical Oncology, Centre Léon Bérard, Lyon, France.
Christophe Le TourneauDepartment of Drug Development and Innovation (D3i), Institut Curie, Paris, France.
Lisa LicitraHead and Neck Medical Oncology Department, Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Milan, Italy.

Funding

ERAPerMed Supporting Personalized Treatment Decisions in Head and Neck Cancer through Big Data - SUPERTREATFondazione Regionale per la Ricerca Biomedica Supporting Personalized Treatment Decisions in Head and Neck Cancer through Big Data - SUPERTREATMinistero della Salute, Italy Ricerca Corrente
6 · The paper itself

Abstract

Personalized treatment in head and neck cancer remains limited despite substantial biological heterogeneity. Using the SuPerTreat project as a case study, we outline a prototype clinical decision support system (CDSS) integrating transcriptomic data and artificial intelligence (AI), and summarize expert consensus on its potential, requirements for accuracy, validation, regulatory alignment, and clinical implementation. This Perspective provides a roadmap to guide future development and responsible integration of CDSS into precision oncology.

Identifiers

PMID41832233
PMCPMC13133119

What OpenQuestion holds

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LicenceCC BY
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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 OpenQuestion graph.