Evidence map›Paper›PMID 42530578›Full record

ArticleEuropean journal of nuclear medicine and molecular imaging2026

Automated Deauville Score computation from baseline [¹⁸F]FDG PET/CT predicts progression-free survival in multiple myeloma: a radiogenomic framework.

Sara Peluso, Stefano Polizzi, Lisa Pagnini, Martina Tarozzi, Ettore Rocchi, Valentino Dragonetti, Vincenza Solli, Daniele Dall'Olio, Marco Talarico, Carolina Terragna and 5 more

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Article in European journal of nuclear medicine and molecular imaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

15 authors.

Sara PelusoDepartment of Medical and Surgical Sciences, University of Bologna, Bologna, 40138, Italy. sara.peluso5@unibo.it.ORCID http://orcid.org/0000-0003-1924-1093
Stefano PolizziData Science and Bioinformatics Laboratory, IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, 40139, Italy.ORCID http://orcid.org/0000-0002-5264-5156
Lisa PagniniDepartment of Medical and Surgical Sciences, University of Bologna, Bologna, 40138, Italy.ORCID http://orcid.org/0009-0009-8081-1252
Martina TarozziDepartment of Medical and Surgical Sciences, University of Bologna, Bologna, 40138, Italy.ORCID http://orcid.org/0000-0002-4240-0542
Ettore RocchiDepartment of Medical and Surgical Sciences, University of Bologna, Bologna, 40138, Italy.ORCID http://orcid.org/0000-0002-7612-2819
Valentino DragonettiDivision of Nuclear Medicine, IEO European Institute of Oncology IRCCS, Milan, Italy.ORCID http://orcid.org/0009-0003-0158-1708
Vincenza SolliDepartment of Medical and Surgical Sciences, University of Bologna, Bologna, 40138, Italy.ORCID http://orcid.org/0000-0002-4828-6955
Daniele Dall'OlioDepartment of Medical and Surgical Sciences, University of Bologna, Bologna, 40138, Italy.ORCID http://orcid.org/0000-0003-0196-6870
Marco TalaricoDepartment of Medical and Surgical Sciences, University of Bologna, Bologna, 40138, Italy.ORCID http://orcid.org/0009-0005-3408-0461
Carolina TerragnaIRCCS Azienda Ospedaliero-Universitaria di Bologna, Istituto di Ematologia "Seràgnoli", Bologna, Italy.ORCID http://orcid.org/0000-0002-4948-4785
Claudia SalaDepartment of Medical and Surgical Sciences, University of Bologna, Bologna, 40138, Italy.ORCID http://orcid.org/0000-0002-4889-1047
Elena ZamagniDepartment of Medical and Surgical Sciences, University of Bologna, Bologna, 40138, Italy.ORCID http://orcid.org/0000-0003-1422-7305
Stefano FantiDepartment of Medical and Surgical Sciences, University of Bologna, Bologna, 40138, Italy.ORCID http://orcid.org/0000-0003-1486-2624
Cristina NanniNuclear Medicine, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy.ORCID http://orcid.org/0000-0003-2000-1599
Gastone CastellaniDepartment of Medical and Surgical Sciences, University of Bologna, Bologna, 40138, Italy.ORCID http://orcid.org/0000-0003-4892-925X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeDeauville Score (DS) assessment from [

methodsA retrospective cohort of 165 newly diagnosed MM patients with baseline FDG PET/CT, CNA profiling, and blood tests was analysed. An automated pipeline computed DS fully automatically for vertebral bone marrow (BM) and long bones (LB), and semi-automatically for focal (FL), paramedullary (PM), and extramedullary (EM) lesions. DS were subdivided into absent (1), low (2-3), and high (4-5) groups and compared via log-rank test. A penalised Cox model with 12 covariates (five DS, three CNAs, haemoglobin, platelet count, age, sex) was evaluated via nested cross-validation for PFS prediction. For inference on individual prognostic contributions, an unpenalised multivariable Cox model was fitted on the full cohort.

resultsIn univariate analyses, high LB, PM and EM DS were significantly associated with shorter PFS. The penalised Cox model achieved a C-index of 0.710 [95% CI: 0.689-0.732] in predicting the risk of progression. In the multivariable analysis, age, haemoglobin, BM DS, PM DS and amp(1q) were identified as independent prognostic factors.

conclusionAutomated DS computation from baseline FDG PET/CT is feasible and, combined with genomic and clinical data, enables a reproducible multimodal approach to prognostic stratification in MM. The pipeline for DS computation is publicly available as an open-source tool (autoDS-PET) at https://github.com/Sara-Peluso/autoDS-PET .

Indexed as

Fluorodeoxyglucose F18GenomicsMultiple MyelomaPositron Emission Tomography Computed TomographyAgedAutomationFemaleHumansMalePrognosisProgression-Free SurvivalRetrospective StudiesFluorodeoxyglucose F18Deauville ScoreFDG PET/CTMultiple myelomaProgression-free survivalQuantitative imagingRadiogenomics

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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.