Wang H, Fu TY, Zhang F, Kang FC, Sun ZW. Neutrophil-albumin ratio and multi-phase computed tomography for lymph node metastasis in pancreatic cancer. World J Gastrointest Oncol 2025; 17(12): 113879 [DOI: 10.4251/wjgo.v17.i12.113879]
Corresponding Author of This Article
Zhong-Wei Sun, PhD, Surgery of Vascular and Abdominal Hernia, Affiliated Zhongshan Hospital of Dalian University, No. 6 Jiefang Street, Zhongshan District, Dalian 116001, Liaoning Province, China. go904013705@163.com
Research Domain of This Article
Radiology, Nuclear Medicine & Medical Imaging
Article-Type of This Article
Retrospective Study
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Dec 15, 2025 (publication date) through Dec 14, 2025
Times Cited of This Article
Times Cited (0)
Journal Information of This Article
Publication Name
World Journal of Gastrointestinal Oncology
ISSN
1948-5204
Publisher of This Article
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
Share the Article
Wang H, Fu TY, Zhang F, Kang FC, Sun ZW. Neutrophil-albumin ratio and multi-phase computed tomography for lymph node metastasis in pancreatic cancer. World J Gastrointest Oncol 2025; 17(12): 113879 [DOI: 10.4251/wjgo.v17.i12.113879]
Author contributions: Wang H and Fu TY contribute equally to this study as co-first authors; Wang H, Fu TY, Zhang F and Kang FC contributed to research design, data collection, data analysis, and paper writing; Sun ZW was responsible for research design, funding application, data analysis, reviewing and editing, communication coordination, ethical review, copyright and licensing, and follow-up.
Institutional review board statement: The study was reviewed and approved by the Ordos Central Hospital Institutional Review Board, No. 2025-402.
Informed consent statement: All research participants or their legal guardians provided written informed consent prior to study registration.
Conflict-of-interest statement: No conflict of interest is associated with this work.
Data sharing statement: No other data available.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Zhong-Wei Sun, PhD, Surgery of Vascular and Abdominal Hernia, Affiliated Zhongshan Hospital of Dalian University, No. 6 Jiefang Street, Zhongshan District, Dalian 116001, Liaoning Province, China. go904013705@163.com
Received: September 9, 2025 Revised: October 11, 2025 Accepted: November 6, 2025 Published online: December 15, 2025 Processing time: 93 Days and 0.4 Hours
Abstract
BACKGROUND
Reliable preoperative detection of lymph node metastasis (LNM) in pancreatic cancer remains elusive: Conventional computed tomography (CT) underestimates micrometastases, and carbohydrate antigen 19-9 is hampered by low specificity. The neutrophil-albumin ratio (NAR) simultaneously reflects systemic inflammation and nutritional depletion, but its contribution to LNM prediction in pancreatic cancer is unexplored. We hypothesised that integrating NAR with multi-phase CT findings would significantly improve the accuracy of preoperative LNM assessment in patients undergoing curative-intent resection.
AIM
To determine whether preoperative NAR plus multi-phase CT reliably predicts nodal metastasis in pancreatic cancer.
METHODS
In this single-centre retrospective cohort study (February 2022 to February 2025, Ordos Central Hospital, China), 129 consecutive patients undergoing curative pancreatic resection were histologically classified as LNM+ (n = 61) and LNM- (n = 68). Preoperative NAR and platelet-albumin ratio (PAR) were calculated; optimal cut-offs were determined with X-tile. Multi-phase CT images were re-reviewed by two blinded radiologists. Independent predictors of nodal metastasis were identified by multivariate logistic regression, and model performance was evaluated with receiver operating characteristic (ROC) analysis.
RESULTS
Between the two cohorts, univariate comparison revealed significant divergence in age, tumour diameter, concomitant hemangioma thrombosis, PAR, NAR, and CT-detected nodal status (P < 0.05). Subsequent multivariate modelling identified hemangioma thrombosis, PAR above 6.35, NAR exceeding 0.13, and radiologically positive lymph nodes as independent predictors of nodal metastasis (P < 0.05). ROC evaluation indicated that the NAR-plus-CT-nodes model (model 1) reached an area under the curve (AUC) of 0.758, whereas the four-variable composite (model 3) achieved the best performance with an AUC of 0.830 (95%CI: 0.753-0.890), sensitivity 83.61%, and specificity 67.65%.
CONCLUSION
The model 3 (NAR > 0.13, PAR > 6.35, CT nodal positivity, hemangioma thrombosis) provides robust, clinically actionable preoperative identification of pancreatic cancer patients at high risk of LNM.
Core Tip: For the first time, we integrated systemic inflammation-nutrition indices [neutrophil-albumin ratio (NAR), platelet-albumin ratio (PAR)] with multi-phase computed tomography (CT) radiomics to predict lymph node metastasis of pancreatic cancer. The resulting four-marker model (NAR > 0.13, PAR > 6.35, hemangioma thrombosis, CT-positive nodes) achieved an area under the curve of 0.830, surpassing conventional imaging and offering a cost-free, pre-operative tool for personalized surgical planning and neoadjuvant selection.
Citation: Wang H, Fu TY, Zhang F, Kang FC, Sun ZW. Neutrophil-albumin ratio and multi-phase computed tomography for lymph node metastasis in pancreatic cancer. World J Gastrointest Oncol 2025; 17(12): 113879
Pancreatic cancer remains one of the most aggressive gastrointestinal malignancies, with steadily rising incidence and fatality worldwide[1,2]. Population-based data indicate that only 13% of patients survive five years, largely because most present at advanced stages[3,4]. Notably, in China, the globe’s most populous nation, pancreatic cancer has emerged as a key driver of the escalating cancer mortality burden[5]. Radical resection combined with adjuvant chemotherapy is currently the only potential curative strategy. however, approximately 14% to 75% of patients have regional lymph node metastasis (LNM) at the time of diagnosis, which not only significantly reduces the surgical resection rate but also indicates early postoperative recurrence and diminished long-term survival[6,7]. Therefore, accurate preoperative assessment of LNM status is crucial for determining the scope of surgery and whether neoadjuvant therapy is needed. Nevertheless, traditional imaging examinations have insufficient sensitivity and specificity in the identification of metastatic lymph nodes, making it challenging to reliably identify micrometastasis or reactive hyperplastic lymph nodes[8]. Although single serological markers are commonly employed in clinical practice, their predictive value is limited by factors such as biliary obstruction and negative Lewis antigen, resulting in suboptimal specificity[9-12]. Therefore, there is an urgent need to integrate multidimensional and multimodal data to construct a comprehensive model that can significantly improve the accuracy of metastatic lymph nodes prediction.
There has been growing focus on the roles of nutritional status and systemic inflammation in tumorigenesis. The neutrophil-albumin ratio (NAR), a composite indicator reflecting systemic inflammation and nutritional status, has been shown to be significantly correlated with forecasting for multiple solid tumors, consisting of gastric and colon cancers[13-15]. However, the value of NAR in predicting LNM in pancreatic cancer remains unclear. Meanwhile, multi-phase contrast-enhanced computed tomography (CT; including arterial, venous, and delayed phases) provides rich imaging information for the identification of metastatic lymph nodes by comprehensively assessing tumor vascularity, boundary characteristics, and lymph node morphology, further enhancing predictive efficacy[16-18]. Consequently, the purpose of this study was to examine the preoperative prognostic usefulness of NAR in conjunction with multi-phase contrast-enhanced CT imaging features to preoperatively predict LNM in pancreatic cancer. By constructing and comparing clinical, imaging, and combined models, we validated the superiority of this multi-parameter integration strategy, providing a noninvasive and actionable tool for screening high-risk LNM in clinicians, thereby optimizing personalized treatment decisions for pancreatic cancer patients.
MATERIALS AND METHODS
General information
We conducted a retrospective review of 129 pancreatic cancer patients treated at our center from February 2022 to February 2025. Pathology reports designated 61 as node-positive (LNM+) and 68 as node-negative (LNM-). Written informed consent was obtained from all participants (or their legal representatives) after full disclosure, and the institutional ethics committee formally approved the study protocol.
Inclusion criteria: (1) Individuals who underwent curative resection with postoperative pathology verifying nodal involvement; (2) Cases in which final histology clearly documented both nodal status and tumor subtype; (3) Patients whose contrast-enhanced CT scan was performed within four weeks preceding surgery; (4) Patients who had no history of radiotherapy or chemotherapy; and (5) Patients who had no liver metastasis or other distant metastasis.
Exclusion criteria: (1) Concurrent malignancies; (2) Severe cardiac, pulmonary, hepatic, or renal impairment; (3) Systemic infectious diseases; (4) CT imaging examination showed unclear lesion boundaries or difficult differential diagnosis; and (5) Missing clinical records.
Data collection
Patient demographic and clinicopathological data were collected, including age, sex, body mass index (BMI), chemotherapy history, history of hemangioma thrombosis, tumor diameter, tumor location, pathological classification, and preoperative laboratory parameters such as carbohydrate antigen 19-9 (CA19-9), carcinoembryonic antigen (CEA), neutrophil count, platelet count, and serum albumin.
Variable truncation value: CA19-9 and CEA were assigned according to conventional laboratory reference intervals, with corresponding cutoff values of 37 U/mL and 5 U/mL, respectively. At the same time, the NAR and platelet-albumin ratio (PAR) were calculated, and the optimal cutoff points were determined using X-tile 3.6.1 software to convert them into binary variables: NAR threshold 0.13, PAR threshold 6.35.
Pathological classifications: Pathological classifications included pancreatic ductal adenocarcinoma, intraductal papillary mucinous neoplasm, and pancreatic neuroendocrine tumor.
Diagnosis of enhanced CT
A consistent enhanced CT imaging technique was used for imaging evaluation of all enrolled patients. In order to guarantee proper emptying of the digestive tract and to prevent imaging artifacts, patients were advised to fast for 5 hours before the examination. Each patient was inquired about any iodine allergy history and prepared for emergency situations. The patient was placed in the typical supine posture for the examination, with the head supported and both arms lifted. Positioning markers were placed in the breast area to define the scan area. A 5 mm-thick plain chest scan was performed, extending from the lung apex to the inferior margin of the liver, to obtain baseline breast imaging. Iohexol contrast agent (2 mL/kg) was then administered intravenously at a rate of 2 mL/second. Dynamic scans were performed 28 seconds (arterial phase), 65 seconds (venous phase), and 3 minutes (delayed phase) after injection to comprehensively assess tumor vascularity, morphological details, and contrast agent metabolism. All scans were uploaded to an imaging workstation for post-processing. Tumor localization and qualitative analysis were performed by measuring parameters such as CT values and lesion size, combined with multi-phase enhancement characteristics.
All patients' CT imaging assessments (including lymph node status and tumor staging) were retrospectively reviewed in a double-blind manner by two radiologists with extensive experience in diagnosing lymphatic lesions at our hospital. Inconsistent results were resolved by a chief physician with 15 years of experience in diagnosing lymphatic lesions. The average of the two measurements was used for relevant quantitative parameters. During CT examinations, venous phase imaging serves as the primary basis for determining lymph node status because it more clearly distinguishes the boundary between tumor and normal tissue and accurately assesses the extent of venous invasion. Tumor T category is also based on the maximum tumor diameter measured on venous phase CT.
Statistical analysis
Analyses were run in SPSS 21.0. Normally distributed continuous variables are expressed as mean ± SD and compared using the t-test; categorical variables are reported as n (%) and compared using the χ2 test. Variables showing significance were entered into a forward-stepwise binary logistic regression to identify independent predictors of nodal metastasis. Receiver operating characteristic (ROC) curves were generated in MedCalc, and the area under the curve (AUC) was used to assess discriminatory ability. A two-sided P < 0.05 was defined statistical significance.
RESULTS
Baseline data
Baseline comparison of the 129 patients showed that age, hemangioma thrombus, tumor size, PAR, NAR and CT-reported nodal status differed significantly between the LNM+ (n = 61) and LNM- (n = 68) groups (P < 0.05). Other variables, such as gender, BMI, tumor location, pathological type, CA19-9, CEA, and CT report T status did not differ significantly between both groups (P > 0.05; Table 1).
The presence of lymph node metastases in patients with pancreatic cancer was the dependent variable in a binary logistic regression analysis of the six statistically relevant characteristics in Table 1. Hemangioma thrombosis, PAR > 6.35, NAR > 0.13, and positive lymph nodes on CT scan (P < 0.05) were identified as independent risk factors for LNM in patients with pancreatic cancer after adjusting for confounding variables (tumor size and age; P < 0.05; Tables 2 and 3).
The results showed that NAR levels had the strongest predictive power, CT-reported lymph node status and PAR levels had intermediate predictive power, and hemangioma thrombosis had the weakest predictive power. Three models were constructed: Model 1 combined NAR with CT-reported lymph node status (positive), model 2 combined hemangioma thrombosis with PAR, and model 3 combined all four indicators. Comparison revealed that the combined NAR with CT-reported lymph node status (positive) had a stronger predictive power than the combined hemangioma thrombosis with PAR. Independent risk markers, including hemangioma thrombosis, PAR > 6.35, NAR > 0.13, and CT-reported lymph node status (positive), can be used as evidence-based standards for the identification of early high-risk patients and focused care (Table 4 and Figure 1).
LNM in pancreatic cancer is a key factor affecting patient prognosis and treatment decisions, but traditional imaging and single serum markers are still limited by insufficient sensitivity or specificity in preoperative assessment[19,20]. This study is the first to investigate the predictive value of preoperative NAR combined with multi-phase enhanced CT imaging features for pancreatic cancer LNM, constructing a multi-parameter joint prediction model. The findings demonstrated that hemangioma thrombosis, positive lymph nodes on CT, NAR > 0.13, and PAR > 6.35 were independent risk factors for lymph node metastases. The four-indicator joint model (model 3) had the highest predictive efficacy (AUC = 0.830), significantly outperforming any single indicator or combination of two indicators, suggesting that a multimodal integration strategy can significantly improve the accuracy of preoperative assessment.
It has been demonstrated that NAR, a composite measure of nutritional status and systemic inflammatory response, is substantially linked to poor prognosis and enhanced tumor invasiveness in a range of malignant tumors[21]. According to the study's findings, NAR > 0.13 was a reliable indicator of lymph node metastases in cases with pancreatic cancer. This association may be achieved through the following mechanisms: On the one hand, neutrophil leukemia can induce the formation of an immunosuppressive microenvironment by secreting proinflammatory factors (such as IL-6 and TGF-β), and furthermore, it promotes angiogenesis and extracellular matrix remodeling by releasing neutrophil extracellular traps[22,23]. On the other hand, low albumin levels not only reflect the state of nutritional depletion, but may also create favorable conditions for tumor cell metastasis by reducing intravascular colloidal osmotic pressure[24-26]. Likewise, the likelihood of LNM was substantially correlated with PAR > 6.35, suggesting that platelet activation is a key factor in pancreatic cancer metastasis[27]. Specifically, elevated platelets can drive epithelial-mesenchymal transition and lymph angiogenesis by secreting cytokines such as TGF-β[28,29].
CT imaging is the preferred examination for preoperative staging of pancreatic cancer, but conventional imaging still relies on subjective morphological criteria, which are susceptible to false positives and false negatives. This study, through a comprehensive analysis of multi-phase enhanced CT (arterial, venous, and delayed phases), found that hemangioma thrombosis and CT-reported lymph node positivity were independent predictors, suggesting that abnormal tumor blood supply and local invasiveness may increase the possibility of metastases from lymph nodes. When pancreatic cancer is detected with intrahemangioma thrombosis on imaging, this sign not only indicates that the tumor has invaded local vessels but, more importantly, promotes LNM through the pathological mechanism of "endothelial damage-coagulation activation-inflammatory cascade": Thrombus releases factors such as tissue factor and vascular endothelial growth factor, which damage the basement membrane, while neutrophil extracellular traps form, exacerbating the inflammatory response and creating a favorable microenvironment for tumor cell metastasis[30-32].
In this study, three preoperative prediction models were constructed. A systematic comparison revealed that a four-indicator combined model (model 3), integrating inflammatory and nutritional markers (NAR and PAR) with imaging and serological features, demonstrated the most accurate prediction performance, with an AUC of 0.830 and a sensitivity of 83.61%, significantly outperforming the predictive performance of traditional single-imaging models (AUC = 0.650-0.750). Furthermore, regarding indicator threshold setting, this study innovatively employed X-tile software to objectively determine the optimal cutoff values for NAR and PAR, effectively avoiding the potential subjective bias associated with the traditional mean ± SD approach. Notably, all predictive variables in this model were derived from routine preoperative examinations, allowing for the generation of personalized risk scores without incurring additional medical costs, demonstrating significant clinical utility. Based on this scoring system, clinicians can implement precise intervention strategies: For patients with high-risk scores, priority can be given to intensive treatment options such as expanded lymph node dissection or neoadjuvant chemotherapy[33]; while for patients with low-risk scores, unnecessary overtreatment can be avoided, truly achieving the goal of personalized precision medicine.
CONCLUSION
In conclusion, positive lymph nodes on a multi-phase contrast-enhanced CT scan and a preoperative NAR > 0.13 can be utilized to accurately predict the metastasis of lymph nodes in pancreatic cancer. The four-marker combined model (NAR, PAR, hemangioma thrombus, and CT lymph node status) has high predictive efficacy and can provide a reliable basis for preoperative risk stratification and individualized treatment decisions. However, due to the single-center, retrospective design, potential unmeasured confounders, and the lack of long-term follow-up data, the generalizability and stability of this model require further validation. To further confirm the generalizability of the model, multicenter prospective studies are required in the future.
Footnotes
Provenance and peer review: Unsolicited article; Externally peer reviewed.
Peer-review model: Single blind
Specialty type: Oncology
Country of origin: China
Peer-review report’s classification
Scientific Quality: Grade B
Novelty: Grade C
Creativity or Innovation: Grade B
Scientific Significance: Grade C
P-Reviewer: Kawachi S, PhD, Japan S-Editor: Lin C L-Editor: A P-Editor: Zhao S
Coppola A, La Vaccara V, Farolfi T, Asbun HJ, Boggi U, Conlon K, Edwin B, Ferrone C, Jonas E, Kokudo N, Perez EM, Satoi S, Sparrelid E, Stauffer J, Zerbi A, Takemura N, Lai Q, Almerey T, Bernon M, Cammarata R, Djoumi Y, Gallagher T, Ghorbani P, Ginesini M, Hashimoto D, Kauffmann EF, Kleive D, Lluís N, González RM, Napoli N, Nappo G, Nebbia M, Ricchitelli S, Sahakyan MA, Yamamoto T, Coppola R, Caputo D. Preoperative carbohydrate antigen 19.9 level predicts lymph node metastasis in resectable adenocarcinoma of the head of the pancreas: a further plea for biological resectability criteria.Int J Surg. 2024;110:6092-6099.
[RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)][Cited by in Crossref: 5][Cited by in RCA: 9][Article Influence: 9.0][Reference Citation Analysis (0)]
Hua X, Wang MD, Ni WQ, Long ZQ, Wang SF, Duan FF, Zhang C, Huang X, Xu F, Xia W, Chen JY, Gao YS. Development and validation of a prognostic nomogram incorporating neutrophil-to-albumin ratio for predicting overall survival in patients with nasopharyngeal carcinoma undergoing concurrent chemoradiotherapy.Heliyon. 2025;11:e40881.
[RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)][Cited by in RCA: 3][Reference Citation Analysis (0)]
Ocskay K, Vinkó Z, Németh D, Szabó L, Bajor J, Gódi S, Sarlós P, Czakó L, Izbéki F, Hamvas J, Papp M, Varga M, Török I, Mickevicius A, Sallinen V, Maldonado ER, Galeev S, Mikó A, Erőss B, Imrei M, Hegyi PJ, Faluhelyi N, Farkas O, Kanizsai P, Miseta A, Nagy T, Hágendorn R, Márton Z, Szakács Z, Szentesi A, Hegyi P, Párniczky A. Hypoalbuminemia affects one third of acute pancreatitis patients and is independently associated with severity and mortality.Sci Rep. 2021;11:24158.
[RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)][Cited by in Crossref: 30][Cited by in RCA: 38][Article Influence: 9.5][Reference Citation Analysis (0)]
