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Clinical characteristics and prognostic analysis of patients with resectable pancreatic cancer exhibiting different enhancement patterns on contrast-enhanced computed tomography
DAI Chuang, LIU Hao-bai, HANG He-xing, XIE Yu, CHEN Bo-zhu, CHENG Hao, QIU Yu-dong
Chinese Journal of Practical Surgery ›› 2026, Vol. 46 ›› Issue (5) : 675-681.
PDF(2639 KB)
PDF(2639 KB)
Clinical characteristics and prognostic analysis of patients with resectable pancreatic cancer exhibiting different enhancement patterns on contrast-enhanced computed tomography
Objective To investigate the clinical characteristics and prognosis of patients with resectable pancreatic ductal adenocarcinoma (PDAC) exhibiting different enhancement patterns on contrast-enhanced computed tomography (CECT). Methods Clinical data of 148 patients with resectable PDAC who underwent surgical treatment at the Department of Pancreatic and Metabolic Surgery, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, between March 2019 and March 2023 was retrospectively analyzed. Independent prognostic risk factors were analyzed. Patients were stratified into low-enhancement and high-enhancement groups based on the optimal cutoff value of ratio3. Survival outcomes and clinical characteristics were then compared between the two groups. Results The portal enhancement ratio, defined as the CT value of tumor-adjacent normal pancreatic parenchyma divided by the CT value of the tumor during the portal phase of CECT (ratio3), was identified as an independent risk factor for both overall survival (OS) and disease-free survival (DFS) in 148 patients. ROC curve analysis revealed that the cut-off value of ratio3 was 1.35, with an area under the curve (AUC) of 0.735 (P<0.001). The median OS and median DFS for all patients were 29.0 months and 21.0 months, respectively. Patients in the low enhancement group (ratio3>1.35, n=110) presented a median OS of 24.0 months and a median DFS of 15.0 months. In contrast, patients in the high enhancement group (ratio3≤1.35, n=38) exhibited a significantly more favorable prognosis, with both median OS and DFS not reached (P<0.001). Significant differences were also observed between the low enhancement group and the high enhancement group in the incidence of preoperative abdominal pain, tumor size and Ki-67 expression levels (all P<0.05). Conclusion Tumor enhancement characteristics on preoperative CECT can serve as a promising prognostic indicator for patients with resectable PDAC. High tumor enhancement is correlated with superior long-term survival, smaller tumor lesions, a lower incidence of preoperative abdominal pain, and reduced Ki-67 expression levels.
pancreatic ductal adenocarcinoma / enhanced computed tomography / enhancement patterns / prognosis / Ki67
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To evaluate whether mutations in pancreatic ductal adenocarcinoma (PDAC) driver genes (KRAS, TP53, SMAD4, and CDKN2A) are associated with pathological characteristics and prognosis.
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There are currently no clinically relevant criteria to predict a futile up-front pancreatectomy in patients with anatomically resectable pancreatic ductal adenocarcinoma.
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张灿, 李加廷, 王鑫龙, 等. 胰腺癌相关生存预测模型研究现状[J]. 中国实用外科杂志, 2022, 42(12): 1432-1435+1440. DOI:10.19538/j.cjps.issn1005-2208.2022.12.17
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Pancreatic cancer is difficult to diagnose early and progresses rapidly. Researchers have found that a cytokine called Interleukin-6 (IL-6) is involved in the entire course of pancreatic cancer, promoting its occurrence and development. From the earliest stages of pancreatic intraepithelial neoplasia to the invasion and metastasis of pancreatic cancer cells and the appearance of tumor cachexia, IL-6 drives oncogenic signal transduction pathways and immune escape that accelerate disease progression. IL-6 is considered a biomarker for pancreatic cancer diagnosis and prognosis, as well as a potential target for treatment. IL-6 antibodies are currently being explored as a hot topic in oncology. This article aims to systematically explain how IL-6 induces the deterioration of normal pancreatic cells, with the goal of finding a breakthrough in pancreatic cancer diagnosis and treatment.
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Preoperative lymph node (LN) status is essential in formulating the treatment strategy among pancreatic cancer patients. However, it is still challenging to evaluate the preoperative LN status precisely now.
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Improved systemic therapy has made long term (≥ 5 years) overall survival (LTS) after resection of pancreatic ductal adenocarcinoma (PDAC) increasingly common. However, a systematic review on predictors of LTS following resection of PDAC is lacking.The PubMed, Embase, Scopus, and Cochrane CENTRAL databases were systematically searched from inception until March 2023. Studies reporting actual survival data (based on follow-up and not survival analysis estimates) on factors associated with LTS were included. Meta-analyses were conducted by using a random effects model, and study quality was gauged by using the Newcastle-Ottawa Scale (NOS).Twenty-five studies with 27,091 patients (LTS: 2,132, non-LTS: 24,959) who underwent surgical resection for PDAC were meta-analyzed. The median proportion of LTS patients was 18.32% (IQR 12.97-21.18%) based on 20 studies. Predictors for LTS included sex, body mass index (BMI), preoperative levels of CA19-9, CEA, and albumin, neutrophil-lymphocyte ratio, tumor grade, AJCC stage, lymphovascular and perineural invasion, pathologic T-stage, nodal disease, metastatic disease, margin status, adjuvant therapy, vascular resection, operative time, operative blood loss, and perioperative blood transfusion. Most articles received a "good" NOS assessment, indicating an acceptable risk of bias.Our meta-analysis pools all true follow up data in the literature to quantify associations between prognostic factors and LTS after resection of PDAC. While there appears to be evidence of a complex interplay between risk, tumor biology, patient characteristics, and management related factors, no single parameter can predict LTS after the resection of PDAC.© 2024. The Author(s).
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To map from the health assessment questionnaire disability index (HAQ) to the pain visual analogue scale (VAS) for people with rheumatoid arthritis. The estimation sample comprised adults with rheumatoid arthritis and inadequate response to tumour necrosis factor-α inhibitors in a multicentre phase 4 randomised controlled trial. Beta mixture models were estimated with combinations of HAQ and its square, age and sex as independent variables. Bayesian Information Criteria informed the number of components. Model performance (root mean squared error; mean absolute error; pseudo-R) was estimated by k-fold cross validation. Graphs illustrated mean observed and predicted pain VAS, and cumulative distribution of observed and simulated pain VAS values. For face validity, a probabilistic analysis simulated 5000 pain VAS values at four HAQ scores. For external validation, the performance of the preferred specification was assessed using the Rheumatoid Arthritis Medication Study cohort. There were 1055 observations from 158 participants in the estimation sample (mean age: 55.8; 81% female; mean HAQ: 1.72). The preferred specification was a two-component beta mixture model (probability variables: HAQ, age, sex; main regression variable: HAQ). Visual plots illustrated good fit across the HAQ distribution, and a similar cumulative distribution of observed and predicted pain VAS values. Probabilistic analysis demonstrated that the preferred specification handled uncertainty appropriately. External validation demonstrated that the preferred specification performed well in an independent dataset. Beta mixture models provide accurate non-linear estimates of pain VAS from HAQ scores to support evidence synthesis and resource allocation decision-making for people with rheumatoid arthritis.© 2025. The Author(s).
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Tumor treating fields (TTFields) use alternating electric fields to disrupt cancer cell proliferation. Feasibility of TTFields therapy with gemcitabine/nab-paclitaxel was previously demonstrated in patients with advanced pancreatic adenocarcinoma. PANOVA-3 was designed to confirm safety and efficacy of TTFields in patients with unresectable locally advanced pancreatic adenocarcinoma (LA-PAC).
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白睿, 孙备. NCCN胰腺癌临床实践指南(2023.V2版)更新解读[J]. 中国实用外科杂志, 2024, 44(1):85-88. DOI:10.19538/j.cjps.issn1005-2208.2024.01.14.
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Accurate risk stratification is critical for guiding personalized treatment in resectable pancreatic cancer (RPC). This retrospective study assessed the utility of habitat radiomics for predicting recurrence-free survival (RFS) in RPC patients.A total of 455 RPC patients were divided into training and external test sets from January 2018 to July 2024. Tumors were segmented into subregions using habitat radiomics to capture localized heterogeneity. Seven machine learning models, including random survival forest (RSF), were compared using Harrell's C-index. The optimal model underwent further validation through time-dependent ROC and Kaplan-Meier (KM) analyses. Shapley additive explanations (SHAP) and survival local interpretable model-agnostic explanations (SurvLIME) were applied to enhance model interpretability.The RSF model based on habitat radiomics achieved a C-index of 0.828 in the training cohort and 0.702, 0.680 in external test sets, outperforming whole-tumor radiomics (p<0.05). Time-dependent ROC analysis showed AUCs of 0.71, 0.83, and 0.79 at 0.5, 1, and 2 years in the first test set, and 0.65, 0.79, and 0.75 in the second test set. KM analysis revealed that the predicted low-risk groups had significantly longer RFS compared to the predicted high-risk groups in both external test sets (all p<0.05). Interpretability analysis identified key variables, including Feature 1, Feature 5, Feature 2, and Feature 4 from Habitat Subregion 1, and Feature 3 from Habitat Subregion 3.The habitat radiomics RSF machine learning model improves prognostic accuracy and interpretability for postoperative RPC, providing a promising tool for personalized management.Copyright © 2025 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.
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To develop an efficient prognostic model based on preoperative magnetic resonance imaging (MRI) radiomics for patients with pancreatic ductal adenocarcinoma (PDAC), the preoperative MRI data of PDAC patients in two independent centers (defined as development cohort and validation cohort, respectively) were collected retrospectively, and the radiomics features of tumors were then extracted. Based on the optimal radiomics features which were significantly related to overall survival (OS) and progression-free survival (PFS), the score of radiomics signature (Rad-score) was calculated, and its predictive efficiency was evaluated according to the area under receiver operator characteristic curve (AUC). Subsequently, the clinical-radiomics nomogram which incorporated the Rad-score and clinical parameters was developed, and its discrimination, consistency and application value were tested by calibration curve, concordance index (C-index) and decision curve analysis (DCA). Moreover, the predictive value of the clinical-radiomics nomogram was compared with traditional prognostic models. A total of 196 eligible PDAC patients were enrolled in this study. The AUC value of Rad-score for OS and PFS in development cohort was 0.724 and 0.781, respectively, and the value of Rad-score was negatively correlated with PDAC's prognosis. Moreover, the developed clinical-radiomics nomogram showed great consistency with the C-index for OS and PFS in development cohort was 0.814 and 0.767, respectively. In addition, the DCA demonstrated that the developed nomogram displayed better clinical predictive usefulness than traditional prognostic models. We concluded that the preoperative MRI-based radiomics signature was significantly related to the poor prognosis of PDAC patients, and the developed clinical-radiomics nomogram showed better predictive ability, it might be used for individualized prognostic assessment of preoperative patients with PDAC.AJCR Copyright © 2022.
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This study aimed to investigate the prognostic significance of PET/CT radiomics to predict overall survival (OS) in patients with resectable pancreatic ductal adenocarcinoma (PDAC).
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Neoadjuvant treatment (NAT), including chemotherapy (NAC) and chemoradiation therapy (NACRT), is a promising approach to treat pancreatic cancer (PC). Alterations in serum carbohydrate antigen 19-9 (CA19-9) following NAT have been studied as outcome indicators. The impact of adding radiation therapy (RT) to NAT on the prognostic significance of changes in CA19-9 is unclear. This study compares changes in CA19-9 levels following NAC vs. NACRT with regard to prognosis.Patients with resectable or borderline resectable PC who underwent curative resection after either NAC or NACRT were enrolled. A cutoff value of 100 U/mL for post-NAT CA19-9 was established, and its association with prognosis was investigated in both the NAC and NACRT groups.No significant difference was observed in survival between the NAC and NACRT groups. While both groups showed clear stratification according to the CA19-9 cutoff for overall survival and disease-free survival, a significant difference in survival after recurrence (SAR) was observed only in the NAC group. Among patients with post-NAT CA19-9 levels <100 U/mL, the NAC group had a significantly higher 2-year survival rate and more favorable SAR than did the NACRT group. Conversely, among patients with values above the cutoff, no significant prognostic differences were observed between the two groups.The prognostic significance of post-NACRT CA19-9 values is suboptimal compared to post-NAC CA19-9 values.Copyright © 2025 IAP and EPC. Published by Elsevier B.V. All rights reserved.
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