Evidence map›Paper›PMID 41556438›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2026

Pathomics Signature for Prognosis and CA19-9 Interception in Pancreatic Ductal Adenocarcinoma: A Real-Life, Multi-Center Study.

Qiangda Chen, Zhihang Xu, Yiping Zou, Zhenlai Jiang, Yecheng Li, Taochen He, Hanlin Yin, Jiali Li, Yanfei An, Jiande Han and 13 more

Abstract readMulticenter Study
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

23 authors.

Qiangda ChenDepartment of Pancreatic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.
Zhihang XuDepartment of Pancreatic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.
Yiping ZouPancreas Center, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, State Key Laboratory of Druggability Evaluation and Systematic Translational Medicine, Tianjin Key Laboratory of Digestive Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin, China.
Zhenlai JiangDepartment of Pancreatic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.
Yecheng LiDepartment of General Surgery, The Second Affiliated Hospital of Soochow University, Suzhou, China.
Taochen HeDepartment of Pancreatic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.
Hanlin YinDepartment of Pancreatic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.
Jiali LiDepartment of Pathology, Zhongshan Hospital, Fudan University, Shanghai, China.
Yanfei AnDepartment of Pancreatic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.
Jiande HanDepartment of Pancreatic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.
Yuqi XieDepartment of Pancreatic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.
Wei GanDepartment of Pancreatic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.
Yaolin XuDepartment of Pancreatic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.
Wenquan WangDepartment of Pancreatic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.
Junyi HeDepartment of Pancreatic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.
Haibo WangMedical College of Yangzhou University, Yangzhou, China.
Wenchuan WuDepartment of Pancreatic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.
Zhenyu YeDepartment of General Surgery, The Second Affiliated Hospital of Soochow University, Suzhou, China.
Wenhui LouDepartment of Pancreatic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.
Jihui HaoPancreas Center, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, State Key Laboratory of Druggability Evaluation and Systematic Translational Medicine, Tianjin Key Laboratory of Digestive Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin, China.
Liang LiuDepartment of Pancreatic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.
Jun YuPancreas Center, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, State Key Laboratory of Druggability Evaluation and Systematic Translational Medicine, Tianjin Key Laboratory of Digestive Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin, China.
Ning PuDepartment of Pancreatic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.ORCID https://orcid.org/0000-0002-3123-493X

Funding

Beijing Xisike Clinical Oncology Research Foundation Y-2022METAZQN-0003Beijing Xisike Clinical Oncology Research Foundation Y-Gilead2024-PT-0002Beijing Xisike Clinical Oncology Research Foundation Y-HR2022MS-0251Beijing Xisike Clinical Oncology Research Foundation Y-HR2022QN-0085Fund of Fujian Provincial Key Laboratory of Translational Cancer Medicine TCM2024-2National Natural Science Foundation of China 82272929National Natural Science Foundation of China 82273382National Natural Science Foundation of China 82303443National Natural Science Foundation of China 82473459National Natural Science Foundation of China 82503105National Natural Science Foundation of China 82572967Open Research Fund of Key Laboratory of Gastrointestinal Cancer (Fujian Medical University), Ministry of Education (FMUGIC-202301) FMUGIC-202301Program of Shanghai Academic Research Leader 23XD1400600Science and Technology Planning Project of Yunnan Province 202305AF150148Shanghai Municipal Health Commission 201940019Shanghai Municipal Health Commission 20244Y0023Shanghai Science and Technology Commission Innovative Pharmaceutical Products Application Demonstration Project 24SF1900300
6 · The paper itself

Abstract

Histopathological hematoxylin and eosin (H&E) slides contain valuable prognostic information for pancreatic ductal adenocarcinoma (PDAC), yet systematic feature extraction remains challenging. This multi-center study developed and validated an automated prognostic model using deep learning on digitized whole-slide images from 873 PDAC patients with surgical resection across three academic centers. The CrossFormer architecture achieved superior performance in external validation (area under the curve [AUC] = 0.774), significantly outperforming ResNet-18 (AUC = 0.716), ResNet-50 (AUC = 0.737), and DenseNet-121 (AUC = 0.729). Gradient-weighted Class Activation Mapping identified key prognostic features including desmoplastic stroma, high nuclear-to-cytoplasmic ratio, tumor necrosis, and immune cell infiltration. The pathomics signature effectively stratified patients into low-risk and high-risk groups with significant survival differences (p < 0.001). Critically, carbohydrate antigen 19-9 (CA19-9) retained prognostic value only in low-risk patients (hazard ratio [HR] = 2.70, p < 0.001) but not in high-risk patients (HR = 0.998, p = 0.990). High-risk patients derived substantial benefit from adjuvant chemotherapy (HR = 0.56, p = 0.038), whereas low-risk patients showed no significant benefit (HR = 0.83, p = 0.562). These findings provide actionable clinical insights: treatment intensification for high-risk patients and CA19-9-guided monitoring for low-risk patients. This validated, interpretable model transforms routine H&E slides into quantitative prognostic tools, enabling personalized treatment strategies without additional testing costs.

Indexed as

CA-19-9 AntigenCarcinoma, Pancreatic DuctalPancreatic NeoplasmsAgedDeep LearningFemaleHumansMalePrognosisCA-19-9 Antigendeep learningpancreatic cancerpathological characterpathomicsprognosis

Identifiers

PMID41556438
PMCPMC13042562

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Registered trials

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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.