Evidence map›Paper›PMID 41049608›Full record

ArticleResearch (Washington, D.C.)2025

Noninvasive Computed Tomography-Based Quantification of Tumor Fibrosis Predicts Pancreatic Cancer Response to Gemcitabine/Nab-Paclitaxel.

Qiuxia Yang, Yize Mao, Yulong Han, Kailai Li, Wanming Hu, Jianyao Zhou, Xuejun Gong, Shuxiang Huang, Rong Zhang, Lizhi Liu and 10 more

Abstract read
In one paragraph

Article in Research (Washington, D.C.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Dual-energy CT extracellular volume fraction for predicting the chemotherapeutic response in pancreatic ductal adenocarcinoma.Cancer imaging : the official publication of the International Cancer Imaging Society · 2026
    Article
  3. Article
  4. Article
  5. Article
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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

20 authors.

Qiuxia YangDepartment of Radiology, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou 510060, China.ORCID https://orcid.org/0009-0008-7954-6319
Yize MaoDepartment of Pancreatobiliary Surgery, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou 510060, China.
Yulong HanNational-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Thoracic Surgery Department of the First Affiliated Hospital, Shenzhen University Medical School, Shenzhen University, Shenzhen 518055, China.
Kailai LiDepartment of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou 510282, China.
Wanming HuDepartment of Pathology, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou 510060, China.
Jianyao ZhouDepartment of Radiology, Affiliated Dongguan Hospital, Southern Medical University, Dongguan, China.
Xuejun GongDivision of Pancreatic Surgery, Department of General Surgery, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China.
Shuxiang HuangNational-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Thoracic Surgery Department of the First Affiliated Hospital, Shenzhen University Medical School, Shenzhen University, Shenzhen 518055, China.
Rong ZhangDepartment of Radiology, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou 510060, China.
Lizhi LiuDepartment of Radiology, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou 510060, China.
Ningning NiuState Key Laboratory of Systems Medicine for Cancer, Ren Ji Hospital, Shanghai Cancer Institute, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Yixiong LiDivision of Pancreatic Surgery, Department of General Surgery, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China.
Liandong JiDivision of Pancreatic Surgery, Department of General Surgery, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China.
Xiaoping YiDepartment of Radiology, Xiangya Hospital, Central South University, Changsha, Hunan, China.
Wufeng XueNational-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Thoracic Surgery Department of the First Affiliated Hospital, Shenzhen University Medical School, Shenzhen University, Shenzhen 518055, China.
Dong NiSchool of Artificial Intelligence, Shenzhen University, Shenzhen 518060, China.
Wenjun MaoDepartment of Thoracic Surgery, the Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi People's Hospital, Wuxi Medical Center, Nanjing Medical University, Wuxi 214023, China.
Peng LuoDepartment of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou 510282, China.
Dong LuoDivision of Pancreatic Surgery, Department of General Surgery, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China.
Jun ChengNational-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Thoracic Surgery Department of the First Affiliated Hospital, Shenzhen University Medical School, Shenzhen University, Shenzhen 518055, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pancreatic ductal adenocarcinoma (PDAC) carries a dismal prognosis. Chemotherapy remains the mainstay for unresectable cases, yet regimens like AG (gemcitabine/nab-paclitaxel) exhibit heterogeneous efficacy. Tumor fibrosis has emerged as a potential predictor of treatment response but lacks validated noninvasive assessment methods. To address this, in this multicenter study, tumor fibrosis was quantified in 361 patients with resectable PDAC from SYSUCC, XYCSU, and TCGA cohorts using deep learning-based tissue segmentation on hematoxylin and eosin-stained whole-slide images. Fibrosis was defined as stromal proportion, and its association with overall survival (OS) was evaluated. Transcriptomic profiling was performed in 51 XYCSU cases to validate the biological relevance of fibrosis quantification. A radiomics model (RM) was then developed using preoperative contrast-enhanced computed tomography (CT) scans from SYSUCC to predict fibrosis and externally validated in XYCSU. Clinical utility was assessed in an independent cohort of 295 unresectable PDAC patients treated with AG, FOLFIRINOX, or SOXIRI. High fibrosis correlated with prolonged OS across resectable cohorts (all

Identifiers

PMID41049608
PMCPMC12491862

What Socratic 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 Socratic graph.