In one paragraphArticle in Journal of clinical oncology : official journal of the American Society of Clinical 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.
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0citing papers in PubMed
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1 · What the graph read from itWhat 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 registryThe 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 literatureWho cites it
0 citing papers in PubMed.
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4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
33 authors.
Audrey BeaufilsCentre de Recherche sur l'Inflammation (CRI), Université Paris Cité, INSERM, U1149, CNRS, ERL 8252, Paris, France.ORCID 0009-0002-2085-2860 Julien De MartinoDepartment of Pathology-FHU MOSAIC, Beaujon Hospital, Université Paris Cité, INSERM UMR1149, Clichy, France.ORCID 0000-0003-3363-052X Xiaofeng JiangElse Kroener Fresenius Center for Digital Health, Medical Faculty Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany.
Théau BlanchardCentre de Recherche sur l'Inflammation (CRI), Université Paris Cité, INSERM, U1149, CNRS, ERL 8252, Paris, France.ORCID 0009-0009-3343-161X Nicolas FraunhofferCancer Research Center of Marseille (CRCM), INSERM, CNRS, Institute Paoli-Calmettes, Aix-Marseille University, Marseille, France.
Diana MendesCentre de Recherche sur l'Inflammation (CRI), Université Paris Cité, INSERM, U1149, CNRS, ERL 8252, Paris, France.ORCID 0009-0004-4454-1383 Camille PignoletCentre de Recherche sur l'Inflammation (CRI), Université Paris Cité, INSERM, U1149, CNRS, ERL 8252, Paris, France.ORCID 0009-0000-2668-5667 Taib BouregaCentre de Recherche sur l'Inflammation (CRI), Université Paris Cité, INSERM, U1149, CNRS, ERL 8252, Paris, France.ORCID 0000-0003-3704-4384 Asier Rabasco MeneghettiElse Kroener Fresenius Center for Digital Health, Medical Faculty Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany.ORCID 0000-0002-1508-9410 Srividhya SainathElse Kroener Fresenius Center for Digital Health, Medical Faculty Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany.ORCID 0009-0006-6227-747X Miguel AlbuquerqueDepartment of Pathology-FHU MOSAIC, Beaujon Hospital, Université Paris Cité, INSERM UMR1149, Clichy, France.ORCID 0000-0001-7311-1623 Nathalie ColnotDepartment of Pathology-FHU MOSAIC, Beaujon Hospital, Université Paris Cité, INSERM UMR1149, Clichy, France.ORCID 0000-0002-1868-6835 Matthieu TihyCentre de Recherche sur l'Inflammation (CRI), Université Paris Cité, INSERM, U1149, CNRS, ERL 8252, Paris, France.ORCID 0000-0002-9314-4657 Anthony TurpinMedical Oncology Department, University Hospital, Lille, France.
Aurélien LambertMedical Oncology Department, Institut de Cancérologie de Lorraine, Vandoeuvre-lès-Nancy, France.ORCID 0000-0001-9990-1201 Daniel J RenoufDepartment of Medical Oncology, BC Cancer, Vancouver, BC, Canada.
Marjorie MauduitUnicancer, R&D, Paris, France.
Nelson J DusettiCancer Research Center of Marseille (CRCM), INSERM, CNRS, Institute Paoli-Calmettes, Aix-Marseille University, Marseille, France.ORCID 0000-0002-6161-8483 Pascal HammelDigestive and Medical Oncology Department, Hospital Paul Brousse and University Paris-Saclay, Villejuif, France.
Thierry ConroyMedical Oncology Department, Institut de Cancérologie de Lorraine, Vandoeuvre-lès-Nancy, France.ORCID 0000-0001-7548-284X Jean-Baptiste BachetDepartment of Gastroenterology, Pitié-Salpêtrière Hospital-Sorbonne Université, Paris, France.ORCID 0000-0003-4337-286X Louis de MestierDepartment of Pancreatology and Digestive Oncology, APHP Nord, FHU MOSAIC, Beaujon Hospital, Clichy, France.ORCID 0000-0001-9715-9189 Vinciane ReboursDepartment of Pancreatology and Digestive Oncology, APHP Nord, FHU MOSAIC, Beaujon Hospital, Clichy, France.
Jérôme CrosCentre de Recherche sur l'Inflammation (CRI), Université Paris Cité, INSERM, U1149, CNRS, ERL 8252, Paris, France.ORCID 0000-0002-4935-3865 Jakob Nikolas KatherElse Kroener Fresenius Center for Digital Health, Medical Faculty Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany.
Rémy NicolleCentre de Recherche sur l'Inflammation (CRI), Université Paris Cité, INSERM, U1149, CNRS, ERL 8252, Paris, France.ORCID 0000-0001-8084-1173 Funding
X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Hongbiao Carl Lekaye · 1985 to 2026
$347.4MNCI NIH HHS P30 CA008748
6 · The paper itselfAbstract
purposeThe choice of adjuvant chemotherapy in pancreatic ductal adenocarcinoma (PDAC) is mainly guided by patients' general condition. We hypothesized that tumor morphology may predict differential treatment benefit and tested whether deep learning applied to histology images could derive a biomarker of relative benefit from gemcitabine (GEM) versus modified FOLFIRINOX (mFOLFIRINOX) in resected PDAC. PATIENTS AND
methodsStandard whole-slide images from a retrospective multicentric series of 231 patients who underwent curative-intent pancreatectomy and received adjuvant mFOLFIRINOX (n = 54) or GEM (n = 177) were used to train regimen-specific histology models on disease-free survival (DFS), which were then combined into PANCprAId, a biomarker estimating personalized relative benefit from adjuvant GEM versus mFOLFIRINOX. External validation was performed in the randomized PRODIGE-24/CCTG PA6 trial (n = 313).
resultsIn PRODIGE-24/CCTG PA6, the treatment-specific histology scores used to construct PANCprAId stratified outcomes among patients treated with GEM (hazard ratio [HR], 1.69 [95% CI, 1.04 to 2.73];
conclusionHistology-based deep learning can derive a predictive biomarker of relative benefit from adjuvant GEM versus mFOLFIRINOX in resected PDAC.
Indexed as
Antineoplastic Combined Chemotherapy ProtocolsCarcinoma, Pancreatic DuctalDeep LearningPancreatic NeoplasmsAgedBiomarkers, TumorChemotherapy, AdjuvantDeoxycytidineDisease-Free SurvivalFemaleFluorouracilGemcitabineHumansIrinotecanLeucovorinMaleBiomarkers, TumorDeoxycytidineFluorouracilfolfirinoxGemcitabineIrinotecanLeucovorinOxaliplatin
Identifiers
PMID42507965
PMCPMC13557473
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