Predictive value of HELPP Score and C-PLAN Index for prognosis in patients undergoing radical resection of pancreatic head Cancer

Predictive value of HELPP Score and C-PLAN Index for prognosis in patients undergoing radical resection of pancreatic head Cancer | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Predictive value of HELPP Score and C-PLAN Index for prognosis in patients undergoing radical resection of pancreatic head Cancer Jian Song, Fan Yang, Wanxiang Wang, Jian Han, Shaohu Bai, Hui Shi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7574852/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Purpose This study aims to investigate the correlation between the Heidelberg Prognostic Pancreatic Cancer (HELPP) score, C-PLAN index, clinicopathological features, and survival outcomes in patients following radical resection of pancreatic head cancer. Additionally, the study seeks to develop a predictive model for postoperative survival and assess its effectiveness. Methods A retrospective analysis was conducted on clinicopathological data from 215 patients diagnosed with pancreatic head cancer who underwent radical pancreaticoduodenectomy at the Department of Hepatobiliary and Pancreatic Surgery, Affiliated Hospital of Inner Mongolia Medical University, and the Department of Hepatobiliary and Pancreatic Surgery, Inner Mongolia Autonomous Region People's Hospital, between January 1, 2011, and December 31, 2023. Univariate and multivariate analyses using the COX proportional hazards model were carried out to determine prognostic factors influencing the overall survival of patients post pancreatic head cancer surgery. Subsequently, a prognostic nomogram was developed utilizing R version 4.2.2. Results The 215 patients had a median survival time of 20.7 months, with cumulative survival rates of 71.6%, 35.8%, and 14.4% at 1, 2, and 3 years post-surgery, respectively. Patients with HELPP scores >3 and C-PLAN scores >2 had a worse prognosis. Multivariate COX regression analysis identified differentiation grade, TNM stage, tumor diameter, HELPP score, and C-PLAN index as independent risk factors influencing prognosis (P < .05). A prognostic nomogram, incorporating these factors, demonstrated strong predictive performance. Conclusions The HELPP score and C-PLAN index exhibit potential as prognostic indicators for predicting patient outcomes following radical resection of pancreatic head cancer. Factors such as differentiation grade, TNM stage, tumor diameter, HELPP score, and C-PLAN index independently influence the prognosis of pancreatic head cancer. A nomogram model incorporating these variables can accurately forecast the long-term survival of patients with pancreatic head cancer. Pancreatic head cancer HELPP score C-PLAN index Nomogram Prognosis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Pancreatic cancer (PC), often dubbed the "king of cancers" ,is a highly aggressive malignancy known for its high recurrence and metastasis rates. Its insidious onset and lack of distinct early symptoms lead to late-stage diagnoses, precluding surgical options and resulting in a dire 5-year survival rate below 5% 1 . Even among the few who undergo radical surgery, the 5-year survival rate hovers at 18%–24% 2-3 . Thus, timely diagnosis and precise prognosis evaluation are pivotal for guiding pancreatic cancer treatment strategies. The HELPP 4 score, a novel prognostic tool for pancreatic cancer patients (Table 1), integrates the ASA classification and conventional biomarkers. Developed by a Heidelberg University professor using data from 1,197 pancreatic cancer patients, it was externally validated with 266 cases at the University Hospital of Verona. This scoring system has shown promise as a prognostic predictor for pancreatic cancer. Introduced in 2023 by Japanese researchers, the C-PLAN 5 index (Table 2) combines nutritional status, inflammatory factors, physical condition, and host metabolism to predict survival in advanced lung cancer. This study aims to assess prognostic risk factors influencing radical resection outcomes in pancreatic head cancer patients by examining the HELPP score, C-PLAN index, preoperative laboratory indicators, pathological characteristics, and TNM staging. Furthermore, the study will develop nomogram prediction models for 1-year, 2-year, and 3-year postoperative outcomes to guide future treatment strategies. Table 1 HELPP Score 4 Parameter Score ASA 1/2 0 3/4 1 CA19-9 <37 kU/L 0 37-＜400Ku/L 1 ≥400 kU/L 2 CEA < 2.5 ng/ml 0 ≥2.5 ng/ml 1 CRP+Alb CRP<5 mg/L 0 CRP 5-< 20 mg/L 1 CRP≥ 20 mg/L 2 CRP≥ 20 mg/L+Alb< 35 g/L 3 PLT ≥ 150×10 9 /L 0 ＜ 150×10 9 /L 2 ASA: American Society of Anesthesiologists; HELPP score is the sum of the above scores. Table 2 C-PLAN Index 5 Parameter Score dNLR ＜ 3.0 0 ≥ 3.0 1 ALB ≥ 35 g/L 0 ＜ 35 g/L 1 LDH < 223 U/L 0 ≥ 223 U/L 1 CRP < 10 mg/L 0 ≥ 10 mg/L 1 PS Score 0-1 0 2-4 1 C-PLAN index is the sum of the above scores. Materials and Methods 1.1 Research subject By searching for keywords such as 'pancreatic head cancer,' 'malignant tumor of the pancreatic head', 'malignant pancreatic tumor' ,and 'occupying lesions of the pancreas' in the medical records system and the operating room anesthesia system, a total of 215 patients diagnosed with pancreatic head cancer and who underwent pancreaticoduodenectomy at the Hepatobiliary Surgery Department of Inner Mongolia Medical University Affiliated Hospital and the Hepatobiliary Surgery Department of Inner Mongolia Autonomous Region People's Hospital from January 1, 2011, to December 31, 2023, were collected. Inclusion criteria: (1) Patients with pancreatic head cancer underwent radical resection surgery; (2) Pathological diagnosis confirmed primary pancreatic cancer with R0 resection; (3) No preoperative radiotherapy, chemotherapy, immunotherapy, or targeted therapy. Exclusion criteria: (1) Perioperative death, postoperative survival time < 30 days; (2) During follow-up, patients died due to non-tumor factors.The study was conducted in accordance with the Declaration of Helsinki. 1.2 Data collection The collected data included: name, gender, age, surgical approach, pathological type and differentiation, tumor size, presence of lymph node metastasis, neural invasion, vascular invasion, ASA classification, performance status (PS score), and TNM staging based on the 8th edition of the American Joint Committee on Cancer (AJCC) pancreatic cancer staging. Serological parameters measured after fasting within one week before surgery included: white blood cell count (WBC), platelet count (PLT), C-reactive protein (CRP), neutrophil count, serum albumin (Alb), lactate dehydrogenase (LDH), carcinoembryonic antigen (CEA), and carbohydrate antigen (CA) 199. Additionally, the HELPP and C-PLAN scores were calculated for the selected patients according to the HELPP score and C-PLAN index scoring criteria. dNLR = [neutrophil count / (white blood cell count - neutrophil count)] × 100%. 1.3 Follow-up All included patients obtained survival data through phone calls, WeChat, or in-person follow-up visits. The follow-up period ended on January 1, 2024. Overall survival (OS) was calculated from the day of surgery to the day of death or to the end of the follow-up period, with survival time measured in months. 1.4 Statistical methods This study used SPSS25.0 software, R version 4.2.2, and MedCalc for statistical analysis. For normally distributed or skewed measurement data, they were expressed as ±s and M(P25～P75), respectively. Cox regression was used for univariate and multivariate analysis, with P < 0.05 indicating statistically significant differences. Additionally, using R software, nomograms based on the results of multivariate analysis were constructed to predict the 1-year, 2-year, and 3-year overall survival (OS) of patients after radical resection of pancreatic head cancer and establish nomograms. Result 2.1 General pathological characteristics This study included a total of 215 patients who underwent radical resection for pancreatic head cancer, of which 132 were male (61.4%) and 83 were female (38.6%). The median age was 62 years, with the youngest being 21 years old and the oldest being 85 years old. The median survival time of the patients was 20.7 months (8.2-58.4 months). By the end of the follow-up period, 205 patients had died and 10 were still alive. The cumulative survival rates at 1, 2, and 3 years post-surgery were 71.6%, 35.8%, and 14.4%, respectively. 2.2 The relationship between preoperative HELPP score and patients with pancreatic head cancer Patients were divided into high and low groups based on the median score of HELPP, with scores greater than 3 and less than or equal to 3, respectively. The analysis results (Table 3) showed that there were statistically significant differences between patients with HELPP ≤ 3 and HELPP > 3 in terms of lymph node metastasis, nerve invasion, vascular invasion, differentiation degree, TNM staging, and C-PLAN score. Specifically, patients with HELPP > 3 had more advanced TNM stages, more frequent lymph node metastasis, nerve invasion, and vascular invasion, lower differentiation degrees, and higher C-PLAN scores. Table 3 The relationship between HELPP and clinical pathological features of pancreatic head cancer Variable HELPP≤ 3 （n=128） HELPP＞3 （n=87） χ 2 /Z P Value Age（year） ＜ 65 ≥ 65 81(60.9) 47(57.3) 52(39.1) 35(42.7) 0.271 0.603 Sex Male Female 76（57.6） 52（62.7） 56（42.4） 31（37.3） 0.545 0.460 Tumor size （cm） ＜3 ≥3 63（63.0） 65（56.5） 37（37.0） 50（43.5） 0.932 0.334 Lymphatic metastasis No Yes 91（66.4） 37（47.4） 46（33.6） 41（52.6） 7.438 0.006 Nerve invasion No Yes 53（72.6) 75 (52.8） 20（27.4） 67（47.2） 7.835 0.005 Vascular invasion No Yes 107（63.7） 21（44.7） 61（36.3） 26（55.3） 5.509 0.019 Differentiated degree Poor Moderate Well 15（34.9） 60（57.1） 53（79.1） 28（65.1） 45（42.9） 14（20.9） 4.645 0.001 Pathological T-stage T1-T2 T3-T4 78（72.2） 50（46.7） 30（27.8） 57（53.3） 14.500 ＜ 0.001 Pathological N-stage N0 N1-N2 92（67.6） 36（45.6） 44（32.4） 43（54.4） 10.110 0.001 TNM stage I-IIA IIB-IV 78（72.9） 50（46.3） 29（27.1） 58（53.7） 15.787 ＜ 0.001 PLAN ≤ 2 ＞2 120(86.3) 8(10.5) 19(13.7) 68(89.5) 117.200 2 points. The analysis results (Table 4) showed that the preoperative C-PLAN index was statistically significant in relation to lymph node metastasis, TNM staging, differentiation degree, and HELPP score (P < 0.05). Table 4 The relationship between C-PLAN and the clinical pathological features of pancreatic head cancer Variable C-PLAN≤ 2 （n=139） C-PLAN＞2 （n=76） χ 2 /Z P Value Age（year） ＜ 65 ≥ 65 87(65.4) 52(63.4) 46(34.6) 30(36.6) 0.089 0.766 Sex Male Female 80（60.6） 59（71.1） 52（39.4） 24（28.9） 2.448 0.118 Tumor size （cm） ＜3 ≥3 71（71.0） 68（59.1） 29（29.0） 47（40.9） 3.297 0.069 Lymphatic metastasis No Yes 98（71.5） 41（52.6） 39（28.5） 37（47.4） 7.825 0.005 Nerve invasion No Yes 51（69.9) 88 (62.0） 22（30.1） 54（38.0） 1.314 0.252 Vascular invasion No Yes 113（67.3） 26（55.3） 55（32.7） 21（44.7） 2.292 0.130 Differentiated degree Poor Moderate Well 16（37.2） 69（65.7） 54（80.6） 27（62.8） 36（34.3） 13（19.4） 4.470 ＜ 0.001 Pathological T-stage T1-T2 T3-T4 84（77.8） 55（51.4） 24（22.2） 52（48.6） 16.362 ＜ 0.001 Pathological N-stage N0 N1-N2 99（72.8） 40（50.6） 37（27.2） 39（49.4） 10.739 0.001 TNM stage I-IIA IIB-IV 85（79.4） 54（50.0） 29（20.6） 58（50.0） 20.383 ＜ 0.001 HELPP ≤ 3 ＞3 120(93.8) 19(21.8) 8(6.3) 68(78.2) 117.200 <0.001 2.4 Univariate and multivariate Cox regression analysis of prognostic risk factors for patients with pancreatic head cancer The collected clinical indicators were incorporated into the Cox proportional hazards regression risk model. Univariate Cox regression analysis indicated that tumor diameter, TNM staging, lymph node metastasis, nerve invasion, vascular invasion, differentiation degree, T staging, N staging, HELPP score, and C-PLAN index are risk factors affecting poor prognosis after radical resection of pancreatic head cancer. Clinical data with P 3, and C-PLAN index > 2 are independent risk factors for poor prognosis in patients with pancreatic head cancer (Table 5). Additionally, survival analysis was performed on the HELPP score and C-PLAN index. As shown in Figures 1 and 2, patients with HELPP ≤ 3 and C-PLAN ≤ 2 had significantly longer survival times compared to the high-score group. Table 5 Univariate and multivariate Cox regression analysis of prognostic factors for pancreatic head cancer Variable Univariate analysis Multivariate analysis HR（95%CI） P Value HR（95%CI） P Value Age（year） ＜65* / ≥ 65 0.99（0.75，1.32） 0.964 Sex Male*/Female 0.87（0.66，1.16） 0.340 Tumor size（cm） ＜3.0*/≥3.0 1.49（1.13，1.97） 0.005 1.46(1.02,2.08) 0.037 TNM stage I-IIA*/IIB-IV 2.96（2.19，3.99） <0.001 2.93(1.67,5.12) <0.001 Lymphatic metastasis No*/Yes 2.09（1.55，2.81） <0.001 1.64(0.60,4.44) 0.334 Nerve invasion No*/Yes 1.45（1.08，1.96） 0.014 0.92(0.66,1.30) 0.647 Vascular invasion No*/Yes 1.40（1.01，1.95） 0.047 0.92(0.64,1.32) 0.647 Differentiated degree Poor* Moderate Well 0.52（0.36，0.75） <0.001 0.27（0.18，0.42） <0.001 0.74(0.46,1.20) 0.225 0.41(0.24,0.72) 0.002 pT-stage T1-T2*/T3-T4 2.33(1.74, 3.13) <0.001 1.10(0.73,1.66) 0.655 pN-stage N0*/N1-N2 2.32(1.72, 3,14) <0.001 0.50(0.17,1.48) 0.211 HELPP ≤3*/＞3 4.78(3.53, 6.47) <0.001 2.70(1.77,4.13) <0.001 C-PLAN ≤2*/＞2 9.76(6.79, 14.05) <0.001 6.33(3.93,10.20) <0.001 * As a control group, HR stands for relative risk 2.5 Constructing a prognostic nomogram for patients undergoing pancreatic head cancer radical surgery Based on Cox multivariate regression, tumor diameter, TNM stage, differentiation degree, HELPP score, and C-PLAN index were selected as model indicators. A prognostic nomogram was constructed using R4.2.2 software to estimate the 1-, 2-, and 3-year survival rates of patients, as shown in Figure 3. 2.6 Validation and evaluation of the nomogram model The performance of the Nomogram model dataset was evaluated using bootstrap re-sampling, resulting in a C-index of 0.82 (95% CI: 0.79-0.84), which demonstrated high predictive accuracy for predicting the prognosis of pancreatic head cancer. The corrected curves for 1-year, 2-year, and 3-year survival rates were plotted using R software, as shown in Figure 4, illustrating the agreement between the actual and predicted survival rates of patients. The closer the calibration curve is to the diagonal line in the figure, the stronger the practicality of the model in predicting patient survival rates. In this study, the actual 1-year, 2-year, and 3-year survival probabilities of patients were highly consistent with the predicted survival probabilities by the model, indicating that the model has certain predictive value. Additionally, DCA analysis was performed on the predictive model, as shown in Figure 5, revealing that the nomogram prediction model shows a wider range of threshold probabilities, indicating the model's practical value. Discussion Pancreatic cancer, a malignant tumor that strikes fear worldwide, has seen an incidence rate increase of about 1.2% annually since 2000, with a corresponding mortality rate increase of 0.4% 6–7 . Even when TNM staging and pathological morphology are identical, there can be significant differences in prognosis, making it crucial to study the factors influencing patient outcomes. The HELPP score, comprising ASA classification, CA-199, CEA, CRP, albumin, and platelet count, was devised by a Heidelberg University professor. It was formulated based on a cohort of 1,197 pancreatic cancer patients and subsequently validated using a cohort of 266 patients from the University Hospital of Verona. The research findings suggest that the HELPP score has potential as a new prognostic tool for pancreatic cancer, particularly in predicting outcomes for early-stage patients 4 . Notably, among these indicators, ASA classification emerged as the sole clinical parameter independently identified as a prognostic determinant. ASA classification offers a straightforward assessment of a patient's physiological condition, not only anticipating risks related to surgery but also correlating with oncological results post various cancer surgeries 8 – 9 . Alb 10 a circulating protein implicated in plasma inflammatory responses, serves as a valuable indicator for malnutrition assessment in patients due to its diminished levels. Hypoproteinemia is notably prevalent in advanced cancer patients, suggesting its potential utility as a marker for cachexia diagnosis. Recent studies have highlighted the increasing exploration of platelets' role in tumor progression. Platelets contribute to tumor advancement through intricate signaling pathways that bolster inflammatory responses, immune suppression, and angiogenesis. Moreover, platelets release exosomes, acting as mediators that facilitate communication between tumor cells and the tumor microenvironment. Additionally, tumor cells can activate platelets to promote their proliferation further 11 – 12 . This study found that patients with a HELPP score greater than 3 had significantly lower survival rates compared to those with a score of 3 or less. Chinese scholars Xie 13 collected data from 35 early-stage pancreatic cancer patients who underwent radical resection. Using the HELPP scoring system, patients were divided into low-score (≤ 3) and high-score (> 3) groups. The results indicated that preoperative HELPP scores have some predictive value for the prognosis of resectable pancreatic cancer patients, with a score greater than 3 possibly indicating a poor prognosis. Additionally, Li 14 also found in a study of 61 patients who underwent radical resection for pancreatic cancer that patients with a HELPP score greater than 3 had significantly worse prognoses compared to the low-score group. C-PLAN index is a new scoring system that combines five indicators: CRP, PS, LDH, ALB, and dNLR. This table was researched and invented by Japanese scholars 5 in 2023, and it has been validated to have high research value in predicting the overall survival and progression-free survival of advanced lung cancer. In a study by Chinese Scholar Hu 15 involving 147 patients with advanced esophageal cancer, the C-PLAN index was divided into low-score group (< 2 points) and high-score group (≥ 2 points). It was found that the low-score group had significantly better survival than the high-score group, and the C-PLAN index was an independent risk factor affecting prognosis. However, this index has not yet been studied in pancreatic cancer. In this study, 215 patients were divided into low-score group (≤ 2 points) and high-score group (> 2 points). The results showed that the low-score group had significantly better survival prognosis than the high-score group, and the C-PLAN index had a larger AUC value compared to the HELPP score. Based on previous literature, the authors speculated that the C-PLAN index may affect the prognosis of pancreatic cancer patients through the following mechanisms: dNLR = neutrophil count / (white blood cell count - neutrophil count), this indicator is superior to the previously studied NLR because it includes not only lymphocytes but also monocytes and other granulocyte subtypes 16 ; LDH exists in various important organs of the human body and is closely related to inflammatory responses and cell damage and death 17 ; CRP is a type of acute phase protein, considered a predictor of infection, and its levels are influenced by pro-inflammatory factors such as IL-6, leading to increased levels in tumor occurrence, development, and metastasis 18 . Elevated CRP can also participate in non-specific immune inflammatory responses caused by tumor necrosis and create a favorable environment for tumor tissue development. A nomogram is a simple and accurate scoring system that combines multiple factors affecting a disease, and by adding up the scores of each factor in the table, it can predict the survival probability of cancer patients at a certain time point 19 . It not only provides a visual and personalized tool for clinicians to assess disease prognosis but also has significant practical value in clinical decision-making and risk stratification 20 . Therefore, this study will explore the prognostic risk factors affecting patients undergoing radical resection for pancreatic head cancer based on their HELPP scores, C-PLAN index, preoperative examination indicators, pathological characteristics, and TNM staging. It aims to establish Nomogram prediction models for 1-year, 2-year, and 3-year outcomes post-surgery. However, this research is retrospective and involves two centers, which may introduce selection bias. Additionally, the sample size is relatively small. If the sample size can be increased in the future, the results will likely be more convincing. Declarations Supplementary Information Acknowledgements We would like to thanks to everyone in Radical resection of pancreatic head cancer patients and patients families agree to this research, thanks for every one person involved in this reserach, thank you Inner Mongolia Autonomous Region People’s Hospital and Affiliated Hospital Of Inner Mongolia Medical University provides the platform and resources. Data availability No datasets were generated or analysed during the current study. Ethics approval and consent to participate All procedures involving human participants performed in this study were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. This study was approved by the Ethics Committee of the Inner Mongolia Autonomous Region People’s Hospital. All patients and their families signed an ethical authorization form and informed consent before surgery. Clinical trial number Not applicable. Authors’ contributions Jian Song is responsible for writing the paper.Fan Yang and Wanxiang Wang are responsible for collecting patient information and follow-up of the Affiliated Hospital of Inner Mongolia Medical University.Jian Han and Shaohu Bai are responsible for collecting patient data and follow-up from the Inner Mongolia Autonomous Region People's Hospital.Hui Shi is responsible for statistical analysis.Finally, All authors read and approved the final manuscript. Funding No funding Competing interests The authors declare no competing interests. References Sung H, Ferlay J, Siegel RL,et al.Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. 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Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 19 Nov, 2025 Reviews received at journal 16 Nov, 2025 Reviewers agreed at journal 16 Nov, 2025 Reviews received at journal 14 Nov, 2025 Reviewers agreed at journal 13 Nov, 2025 Reviewers agreed at journal 11 Nov, 2025 Reviewers agreed at journal 11 Nov, 2025 Reviewers invited by journal 13 Sep, 2025 Editor assigned by journal 12 Sep, 2025 Submission checks completed at journal 11 Sep, 2025 First submitted to journal 09 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7574852","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":517861578,"identity":"da90a3ac-2c25-4c09-b445-b80c859dee0b","order_by":0,"name":"Jian Song","email":"","orcid":"","institution":"Inner Mongolia Autonomous Region People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jian","middleName":"","lastName":"Song","suffix":""},{"id":517861580,"identity":"1a25096d-618a-456d-a357-2a22b623e743","order_by":1,"name":"Fan Yang","email":"","orcid":"","institution":"Affiliated Hospital Of Inner Mongolia Medical 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Hospital","correspondingAuthor":false,"prefix":"","firstName":"Shaohu","middleName":"","lastName":"Bai","suffix":""},{"id":517861586,"identity":"d13caf3e-fd03-46f6-bc56-40d97992de6d","order_by":5,"name":"Hui Shi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAtElEQVRIiWNgGAWjYDACCeYDBz5U2DCwkaCFLfHhjDNpJGnhUTbmbDlMgrvkZ/ewSTM2nLfnk25+wPCjYhthLQZ3zh6TLtxxO7FN5pgBY8+Z20RokchLk5555nYCm0SCATNjGxFa5GfkmEnztp2zZ5NI/0CcFoYbOcbGvG0HGNskcoi0xeBGGiiQkxOBWgoOEuUX+RnJoKi0s5efkb7xwY8KYhyGDA6QqH4UjIJRMApGAS4AADNoPMeLKB0/AAAAAElFTkSuQmCC","orcid":"","institution":"Inner Mongolia Autonomous Region People’s Hospital","correspondingAuthor":true,"prefix":"","firstName":"Hui","middleName":"","lastName":"Shi","suffix":""}],"badges":[],"createdAt":"2025-09-09 14:23:30","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7574852/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7574852/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":91951790,"identity":"8cefc8ff-f470-4cb0-af2f-081c4385010a","added_by":"auto","created_at":"2025-09-23 06:48:45","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":324560,"visible":true,"origin":"","legend":"","description":"","filename":"PredictivevalueofHELPPScoreandCPLANIndexforprognosisinpatientsundergoingradicalresectionofpancreaticheadCancer.docx","url":"https://assets-eu.researchsquare.com/files/rs-7574852/v1/5ecb0ceaeb780797e080bb34.docx"},{"id":91951798,"identity":"fc5916ce-375b-4fb8-8a25-8bb0ee383e86","added_by":"auto","created_at":"2025-09-23 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1","display":"","copyAsset":false,"role":"figure","size":96082,"visible":true,"origin":"","legend":"\u003cp\u003eThe relationship between HELPP and survival time\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7574852/v1/6b7eadb15ae15742609bf248.png"},{"id":91951796,"identity":"aa092c45-404b-4c1e-bf95-5bf75454f9d4","added_by":"auto","created_at":"2025-09-23 06:48:45","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":76498,"visible":true,"origin":"","legend":"\u003cp\u003eThe relationship between C-PLAN and survival time\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7574852/v1/1fedf86ddc59d4837dda907e.png"},{"id":91953459,"identity":"3040c3f2-9aff-4200-9e30-4e3d74348e2c","added_by":"auto","created_at":"2025-09-23 06:56:45","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":61421,"visible":true,"origin":"","legend":"\u003cp\u003eA nomogram model for predicting the 1-year, 2-year, and 3-year survival rates of patients with pancreatic head cancer.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7574852/v1/e9aea0aa5e07f80e1b0b331a.png"},{"id":91951809,"identity":"33558c52-fc9b-4949-86c0-6f35d434640c","added_by":"auto","created_at":"2025-09-23 06:48:45","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":63405,"visible":true,"origin":"","legend":"\u003cp\u003eCalibration curves for 1-year, 2-year, and 3-year Kaplan-Meier plots\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7574852/v1/bc675a26fae9be9b946a8081.png"},{"id":91953461,"identity":"d2c9b898-ecaa-43b7-ba87-1a3aa5297c03","added_by":"auto","created_at":"2025-09-23 06:56:45","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":48965,"visible":true,"origin":"","legend":"\u003cp\u003eDCA curve chart\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7574852/v1/fb5cf50e758949a5a229a12d.png"},{"id":91956366,"identity":"9bf5d259-1daa-4518-9bbf-189568c46d08","added_by":"auto","created_at":"2025-09-23 07:12:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1166488,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7574852/v1/e62f7892-fef9-4b48-bdda-b21b90ee4c62.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Predictive value of HELPP Score and C-PLAN Index for prognosis in patients undergoing radical resection of pancreatic head Cancer","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePancreatic cancer (PC), often dubbed the \u0026quot;king of cancers\u0026quot; ,is a highly aggressive malignancy known for its high recurrence and metastasis rates. Its insidious onset and lack of distinct early symptoms lead to late-stage diagnoses, precluding surgical options and resulting in a dire 5-year survival rate below 5%\u003csup\u003e1\u003c/sup\u003e. Even among the few who undergo radical surgery, the 5-year survival rate hovers at 18%\u0026ndash;24%\u003csup\u003e2-3\u003c/sup\u003e. Thus, timely diagnosis and precise prognosis evaluation are pivotal for guiding pancreatic cancer treatment strategies. The HELPP\u003csup\u003e4\u003c/sup\u003e score, a novel prognostic tool for pancreatic cancer patients (Table 1), integrates the ASA classification and conventional biomarkers. Developed by a Heidelberg University professor using data from 1,197 pancreatic cancer patients, it was externally validated with 266 cases at the University Hospital of Verona. This scoring system has shown promise as a prognostic predictor for pancreatic cancer. Introduced in 2023 by Japanese researchers, the C-PLAN\u003csup\u003e5\u003c/sup\u003e index (Table 2) combines nutritional status, inflammatory factors, physical condition, and host metabolism to predict survival in advanced lung cancer. This study aims to assess prognostic risk factors influencing radical resection outcomes in pancreatic head cancer patients by examining the HELPP score, C-PLAN index, preoperative laboratory indicators, pathological characteristics, and TNM staging. Furthermore, the study will develop nomogram prediction models for 1-year, 2-year, and 3-year postoperative outcomes to guide future treatment strategies.\u003c/p\u003e\n\u003cp\u003eTable 1 \u0026nbsp;HELPP Score\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"99%\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003eParameter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003eScore\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003eASA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;1/2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;3/4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003eCA19-9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026lt;37 kU/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 37-＜400Ku/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026ge;400 kU/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003eCEA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026lt; 2.5 ng/ml\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026ge;2.5 ng/ml\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003eCRP+Alb\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; CRP\u0026lt;5 mg/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;CRP 5-\u0026lt; 20 mg/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;CRP\u0026ge; 20 mg/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;CRP\u0026ge; 20 mg/L+Alb\u0026lt; 35 g/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003ePLT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026ge; 150\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;＜\u0026nbsp;150\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eASA: American Society of Anesthesiologists; HELPP score is the sum of the above scores.\u003c/p\u003e\n\u003cp\u003eTable 2 \u0026nbsp;C-PLAN Index\u003csup\u003e5\u003c/sup\u003e\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003eParameter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003eScore\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003edNLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;＜\u0026nbsp;3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026ge; 3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003eALB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026ge; 35 g/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;＜\u0026nbsp;35 g/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003eLDH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026lt; 223 U/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026ge; 223 U/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003eCRP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026lt; 10 mg/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026ge; 10 mg/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003ePS Score\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;0-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;2-4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eC-PLAN index is the sum of the above scores.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003e1.1\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eResearch subject\u003c/strong\u003e By searching for keywords such as \u0026apos;pancreatic head cancer,\u0026apos; \u0026apos;malignant tumor of the pancreatic head\u0026apos;, \u0026apos;malignant pancreatic tumor\u0026apos; ,and \u0026apos;occupying lesions of the pancreas\u0026apos; in the medical records system and the operating room anesthesia system, a total of 215 patients diagnosed with pancreatic head cancer and who underwent pancreaticoduodenectomy at the Hepatobiliary Surgery Department of Inner Mongolia Medical University Affiliated Hospital and the Hepatobiliary Surgery Department of Inner Mongolia Autonomous Region People\u0026apos;s Hospital from January 1, 2011, to December 31, 2023, were collected. Inclusion criteria: (1) Patients with pancreatic head cancer underwent radical resection surgery; (2) Pathological diagnosis confirmed primary pancreatic cancer with R0 resection; (3) No preoperative radiotherapy, chemotherapy, immunotherapy, or targeted therapy. Exclusion criteria: (1) Perioperative death, postoperative survival time \u0026lt; 30 days; (2) During follow-up, patients died due to non-tumor factors.The study was conducted in accordance with the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.2\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eData collection\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThe collected data included: name, gender, age, surgical approach, pathological type and differentiation, tumor size, presence of lymph node metastasis, neural invasion, vascular invasion, ASA classification, performance status (PS score), and TNM staging based on the 8th edition of the American Joint Committee on Cancer (AJCC) pancreatic cancer staging. Serological parameters measured after fasting within one week before surgery included: white blood cell count (WBC), platelet count (PLT), C-reactive protein (CRP), neutrophil count, serum albumin (Alb), lactate dehydrogenase (LDH), carcinoembryonic antigen (CEA), and carbohydrate antigen (CA) 199. Additionally, the HELPP and C-PLAN scores were calculated for the selected patients according to the HELPP score and C-PLAN index scoring criteria. dNLR = [neutrophil count / (white blood cell count - neutrophil count)] \u0026times; 100%.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.3\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eFollow-up\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eAll included patients obtained survival data through phone calls, WeChat, or in-person follow-up visits. The follow-up period ended on January 1, 2024. Overall survival (OS) was calculated from the day of surgery to the day of death or to the end of the follow-up period, with survival time measured in months.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.4\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eStatistical methods\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThis study used SPSS25.0 software, R version 4.2.2, and MedCalc for statistical analysis. For normally distributed or skewed measurement data, they were expressed as \u0026plusmn;s and M(P25～P75), respectively. Cox regression was used for univariate and multivariate analysis, with P \u0026lt; 0.05 indicating statistically significant differences. Additionally, using R software, nomograms based on the results of multivariate analysis were constructed to predict the 1-year, 2-year, and 3-year overall survival (OS) of patients after radical resection of pancreatic head cancer and establish nomograms.\u003c/p\u003e"},{"header":"Result","content":"\u003cp\u003e\u003cstrong\u003e2.1\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eGeneral pathological characteristics\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThis study included a total of 215 patients who underwent radical resection for pancreatic head cancer, of which 132 were male (61.4%) and 83 were female (38.6%). The median age was 62 years, with the youngest being 21 years old and the oldest being 85 years old. The median survival time of the patients was 20.7 months (8.2-58.4 months). By the end of the follow-up period, 205 patients had died and 10 were still alive. The cumulative survival rates at 1, 2, and 3 years post-surgery were 71.6%, 35.8%, and 14.4%, respectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2\u003c/strong\u003e \u003cstrong\u003eThe relationship between preoperative HELPP score and patients with pancreatic head cancer\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003ePatients were divided into high and low groups based on the median score of HELPP, with scores greater than 3 and less than or equal to 3, respectively. The analysis results (Table 3) showed that there were statistically significant differences between patients with HELPP \u0026le; 3 and HELPP \u0026gt; 3 in terms of lymph node metastasis, nerve invasion, vascular invasion, differentiation degree, TNM staging, and C-PLAN score. Specifically, patients with HELPP \u0026gt; 3 had more advanced TNM stages, more frequent lymph node metastasis, nerve invasion, and vascular invasion, lower differentiation degrees, and higher C-PLAN scores.\u003c/p\u003e\n\u003cp\u003eTable 3 \u0026nbsp; The relationship between HELPP and clinical pathological features of pancreatic head cancer\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"99%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003eHELPP\u0026le; 3\u003c/p\u003e\n \u003cp\u003e（n=128）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003eHELPP＞3\u003c/p\u003e\n \u003cp\u003e（n=87）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e/Z\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u0026nbsp;\u003c/em\u003eValue\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 32px;\"\u003e\n \u003cp\u003eAge（year）\u003c/p\u003e\n \u003cp\u003e＜\u0026nbsp;65\u003c/p\u003e\n \u003cp\u003e\u0026ge; 65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e81(60.9)\u003c/p\u003e\n \u003cp\u003e47(57.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e52(39.1)\u003c/p\u003e\n \u003cp\u003e35(42.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e0.271\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e0.603\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 32px;\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e76（57.6）\u003c/p\u003e\n \u003cp\u003e52（62.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e56（42.4）\u003c/p\u003e\n \u003cp\u003e31（37.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e0.545\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e0.460\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 32px;\"\u003e\n \u003cp\u003eTumor size\u0026nbsp;（cm）\u003c/p\u003e\n \u003cp\u003e＜3\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026ge;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e63（63.0）\u003c/p\u003e\n \u003cp\u003e65（56.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e37（37.0）\u003c/p\u003e\n \u003cp\u003e50（43.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e0.932\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e0.334\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 32px;\"\u003e\n \u003cp\u003eLymphatic metastasis\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e91（66.4）\u003c/p\u003e\n \u003cp\u003e37（47.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e46（33.6）\u003c/p\u003e\n \u003cp\u003e41（52.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e7.438\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 32px;\"\u003e\n \u003cp\u003eNerve invasion\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e53（72.6)\u003c/p\u003e\n \u003cp\u003e75 (52.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e20（27.4）\u003c/p\u003e\n \u003cp\u003e67（47.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e7.835\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 32px;\"\u003e\n \u003cp\u003eVascular invasion\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e107（63.7）\u003c/p\u003e\n \u003cp\u003e21（44.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e61（36.3）\u003c/p\u003e\n \u003cp\u003e26（55.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e5.509\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 32px;\"\u003e\n \u003cp\u003eDifferentiated degree\u003c/p\u003e\n \u003cp\u003ePoor\u003c/p\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003cp\u003eWell\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e15（34.9）\u003c/p\u003e\n \u003cp\u003e60（57.1）\u003c/p\u003e\n \u003cp\u003e53（79.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e28（65.1）\u003c/p\u003e\n \u003cp\u003e45（42.9）\u003c/p\u003e\n \u003cp\u003e14（20.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e4.645\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 32px;\"\u003e\n \u003cp\u003ePathological T-stage\u003c/p\u003e\n \u003cp\u003eT1-T2\u003c/p\u003e\n \u003cp\u003eT3-T4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e78（72.2）\u003c/p\u003e\n \u003cp\u003e50（46.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e30（27.8）\u003c/p\u003e\n \u003cp\u003e57（53.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e14.500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cem\u003e＜\u003c/em\u003e\u003cem\u003e0.001\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003ePathological N-stage\u003c/p\u003e\n \u003cp\u003eN0\u003c/p\u003e\n \u003cp\u003eN1-N2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e92（67.6）\u003c/p\u003e\n \u003cp\u003e36（45.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e44（32.4）\u003c/p\u003e\n \u003cp\u003e43（54.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e10.110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 32px;\"\u003e\n \u003cp\u003eTNM stage\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; I-IIA\u003c/p\u003e\n \u003cp\u003eIIB-IV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e78（72.9）\u003c/p\u003e\n \u003cp\u003e50（46.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e29（27.1）\u003c/p\u003e\n \u003cp\u003e58（53.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e15.787\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cem\u003e＜\u003c/em\u003e\u003cem\u003e0.001\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 32px;\"\u003e\n \u003col\u003e\n \u003cli\u003ePLAN\u003c/li\u003e\n \u003c/ol\u003e\n \u003cp\u003e\u0026le; 2\u003c/p\u003e\n \u003cp\u003e＞2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e120(86.3)\u003c/p\u003e\n \u003cp\u003e8(10.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e19(13.7)\u003c/p\u003e\n \u003cp\u003e68(89.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e117.200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026lt;0.001\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e2.3\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eThe relationship between preoperative C-PLAN index and patients with pancreatic head cancer\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003ePatients were divided into two groups based on a C-PLAN index of \u0026le;2 points and \u0026gt;2 points. The analysis results (Table 4) showed that the preoperative C-PLAN index was statistically significant in relation to lymph node metastasis, TNM staging, differentiation degree, and HELPP score (P \u0026lt; 0.05).\u003c/p\u003e\n\u003cp\u003eTable 4 \u0026nbsp; The relationship between C-PLAN and the clinical pathological features of pancreatic head cancer\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"99%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003eC-PLAN\u0026le; 2\u003c/p\u003e\n \u003cp\u003e（n=139）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003eC-PLAN＞2\u003c/p\u003e\n \u003cp\u003e（n=76）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e/Z\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e Value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 32px;\"\u003e\n \u003cp\u003eAge（year）\u003c/p\u003e\n \u003cp\u003e＜\u0026nbsp;65\u003c/p\u003e\n \u003cp\u003e\u0026ge; 65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e87(65.4)\u003c/p\u003e\n \u003cp\u003e52(63.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e46(34.6)\u003c/p\u003e\n \u003cp\u003e30(36.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e0.089\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.766\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 32px;\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; 80（60.6）\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; 59（71.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e52（39.4）\u003c/p\u003e\n \u003cp\u003e24（28.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e2.448\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.118\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 32px;\"\u003e\n \u003cp\u003eTumor size\u0026nbsp;（cm）\u003c/p\u003e\n \u003cp\u003e＜3\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026ge;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e71（71.0）\u003c/p\u003e\n \u003cp\u003e68（59.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e29（29.0）\u003c/p\u003e\n \u003cp\u003e47（40.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e3.297\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.069\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 32px;\"\u003e\n \u003cp\u003eLymphatic metastasis\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e98（71.5）\u003c/p\u003e\n \u003cp\u003e41（52.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e39（28.5）\u003c/p\u003e\n \u003cp\u003e37（47.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e7.825\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 32px;\"\u003e\n \u003cp\u003eNerve invasion\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e51（69.9)\u003c/p\u003e\n \u003cp\u003e88 (62.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e22（30.1）\u003c/p\u003e\n \u003cp\u003e54（38.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e1.314\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.252\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 32px;\"\u003e\n \u003cp\u003eVascular invasion\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e113（67.3）\u003c/p\u003e\n \u003cp\u003e26（55.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e55（32.7）\u003c/p\u003e\n \u003cp\u003e21（44.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e2.292\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.130\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 32px;\"\u003e\n \u003cp\u003eDifferentiated degree\u003c/p\u003e\n \u003cp\u003ePoor\u003c/p\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003cp\u003eWell\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e16（37.2）\u003c/p\u003e\n \u003cp\u003e69（65.7）\u003c/p\u003e\n \u003cp\u003e54（80.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e27（62.8）\u003c/p\u003e\n \u003cp\u003e36（34.3）\u003c/p\u003e\n \u003cp\u003e13（19.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e4.470\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cem\u003e＜\u003c/em\u003e\u003cem\u003e0.001\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 32px;\"\u003e\n \u003cp\u003ePathological T-stage\u003c/p\u003e\n \u003cp\u003eT1-T2\u003c/p\u003e\n \u003cp\u003eT3-T4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e84（77.8）\u003c/p\u003e\n \u003cp\u003e55（51.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e24（22.2）\u003c/p\u003e\n \u003cp\u003e52（48.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e16.362\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cem\u003e＜\u003c/em\u003e\u003cem\u003e0.001\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003ePathological N-stage\u003c/p\u003e\n \u003cp\u003eN0\u003c/p\u003e\n \u003cp\u003eN1-N2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e99（72.8）\u003c/p\u003e\n \u003cp\u003e40（50.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e37（27.2）\u003c/p\u003e\n \u003cp\u003e39（49.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e10.739\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 32px;\"\u003e\n \u003cp\u003eTNM stage\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; I-IIA\u003c/p\u003e\n \u003cp\u003eIIB-IV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e85（79.4）\u003c/p\u003e\n \u003cp\u003e54（50.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e29（20.6）\u003c/p\u003e\n \u003cp\u003e58（50.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e20.383\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cem\u003e＜\u003c/em\u003e\u003cem\u003e0.001\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 32px;\"\u003e\n \u003cp\u003eHELPP\u003c/p\u003e\n \u003cp\u003e\u0026le; 3\u003c/p\u003e\n \u003cp\u003e＞3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e120(93.8)\u003c/p\u003e\n \u003cp\u003e19(21.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e8(6.3)\u003c/p\u003e\n \u003cp\u003e68(78.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e117.200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026lt;0.001\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e2.4\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eUnivariate and multivariate Cox regression analysis of prognostic risk factors for patients with pancreatic head cancer\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThe collected clinical indicators were incorporated into the Cox proportional hazards regression risk model. Univariate Cox regression analysis indicated that tumor diameter, TNM staging, lymph node metastasis, nerve invasion, vascular invasion, differentiation degree, T staging, N staging, HELPP score, and C-PLAN index are risk factors affecting poor prognosis after radical resection of pancreatic head cancer. Clinical data with P \u0026lt; 0.10 in univariate analysis were included in the multivariate Cox regression model, which showed that tumor diameter \u0026ge; 3.0 cm, TNM staging of IIB-IV, low differentiation, HELPP score \u0026gt; 3, and C-PLAN index \u0026gt; 2 are independent risk factors for poor prognosis in patients with pancreatic head cancer (Table 5). Additionally, survival analysis was performed on the HELPP score and C-PLAN index. As shown in Figures 1 and 2, patients with HELPP \u0026le; 3 and C-PLAN \u0026le; 2 had significantly longer survival times compared to the high-score group.\u003c/p\u003e\n\u003cp\u003eTable 5 \u0026nbsp;Univariate and multivariate Cox regression analysis of prognostic factors for pancreatic head cancer\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"99%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 26px;\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 36px;\"\u003e\n \u003cp\u003eUnivariate analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 37px;\"\u003e\n \u003cp\u003eMultivariate analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36px;\"\u003e\n \u003cp\u003eHR（95%CI）\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u003cem\u003eP\u003c/em\u003e Value\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 37px;\"\u003e\n \u003cp\u003eHR（95%CI）\u0026nbsp; \u0026nbsp; \u0026nbsp; \u003cem\u003eP\u0026nbsp;\u003c/em\u003eValue\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003eAge（year）\u003c/p\u003e\n \u003cp\u003e＜65* / \u0026ge; 65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.99（0.75，1.32）\u0026nbsp; \u0026nbsp;0.964\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003cp\u003eMale*/Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.87（0.66，1.16）\u0026nbsp; \u0026nbsp;0.340\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003eTumor size（cm）\u003c/p\u003e\n \u003cp\u003e＜3.0*/\u0026ge;3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.49（1.13，1.97）\u0026nbsp; \u0026nbsp;0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.46(1.02,2.08) \u0026nbsp; \u0026nbsp; \u0026nbsp;0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003eTNM stage\u003c/p\u003e\n \u003cp\u003eI-IIA*/IIB-IV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.96（2.19，3.99）\u0026nbsp; \u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.93(1.67,5.12) \u0026nbsp; \u0026nbsp; \u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003eLymphatic metastasis\u003c/p\u003e\n \u003cp\u003eNo*/Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.09（1.55，2.81）\u0026nbsp; \u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.64(0.60,4.44) \u0026nbsp; \u0026nbsp; \u0026nbsp;0.334\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003eNerve invasion\u003c/p\u003e\n \u003cp\u003eNo*/Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.45（1.08，1.96）\u0026nbsp; \u0026nbsp;0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.92(0.66,1.30) \u0026nbsp; \u0026nbsp; \u0026nbsp;0.647\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003eVascular invasion\u003c/p\u003e\n \u003cp\u003eNo*/Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.40（1.01，1.95）\u0026nbsp; \u0026nbsp;0.047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.92(0.64,1.32) \u0026nbsp; \u0026nbsp; \u0026nbsp;0.647\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003eDifferentiated degree\u003c/p\u003e\n \u003cp\u003ePoor*\u003c/p\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003cp\u003eWell\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.52（0.36，0.75）\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026lt;0.001\u003c/p\u003e\n \u003cp\u003e0.27（0.18，0.42）\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.74(0.46,1.20) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0.225\u003c/p\u003e\n \u003cp\u003e0.41(0.24,0.72) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003epT-stage\u003c/p\u003e\n \u003cp\u003eT1-T2*/T3-T4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.33(1.74, 3.13) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.10(0.73,1.66) \u0026nbsp; \u0026nbsp; \u0026nbsp;0.655\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003epN-stage\u003c/p\u003e\n \u003cp\u003eN0*/N1-N2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.32(1.72, 3,14) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.50(0.17,1.48) \u0026nbsp; \u0026nbsp; \u0026nbsp;0.211\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003eHELPP\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026le;3*/＞3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4.78(3.53, 6.47) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.70(1.77,4.13) \u0026nbsp; \u0026nbsp; \u003cem\u003e\u0026lt;0.001\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003eC-PLAN\u003c/p\u003e\n \u003cp\u003e\u0026le;2*/＞2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e9.76(6.79, 14.05) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e6.33(3.93,10.20) \u0026nbsp; \u0026nbsp;\u003cem\u003e\u0026lt;0.001\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e* As a control group, HR stands for relative risk\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.5 Constructing a prognostic nomogram for patients undergoing pancreatic head cancer radical surgery\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eBased on Cox multivariate regression, tumor diameter, TNM stage, differentiation degree, HELPP score, and C-PLAN index were selected as model indicators. A prognostic nomogram was constructed using R4.2.2 software to estimate the 1-, 2-, and 3-year survival rates of patients, as shown in Figure 3.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.6 Validation and evaluation of the nomogram model\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThe performance of the Nomogram model dataset was evaluated using bootstrap re-sampling, resulting in a C-index of 0.82 (95% CI: 0.79-0.84), which demonstrated high predictive accuracy for predicting the prognosis of pancreatic head cancer. The corrected curves for 1-year, 2-year, and 3-year survival rates were plotted using R software, as shown in Figure 4, illustrating the agreement between the actual and predicted survival rates of patients. The closer the calibration curve is to the diagonal line in the figure, the stronger the practicality of the model in predicting patient survival rates. In this study, the actual 1-year, 2-year, and 3-year survival probabilities of patients were highly consistent with the predicted survival probabilities by the model, indicating that the model has certain predictive value. Additionally, DCA analysis was performed on the predictive model, as shown in Figure 5, revealing that the nomogram prediction model shows a wider range of threshold probabilities, indicating the model\u0026apos;s practical value.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003ePancreatic cancer, a malignant tumor that strikes fear worldwide, has seen an incidence rate increase of about 1.2% annually since 2000, with a corresponding mortality rate increase of 0.4%\u003csup\u003e6\u0026ndash;7\u003c/sup\u003e. Even when TNM staging and pathological morphology are identical, there can be significant differences in prognosis, making it crucial to study the factors influencing patient outcomes.\u003c/p\u003e\u003cp\u003eThe HELPP score, comprising ASA classification, CA-199, CEA, CRP, albumin, and platelet count, was devised by a Heidelberg University professor. It was formulated based on a cohort of 1,197 pancreatic cancer patients and subsequently validated using a cohort of 266 patients from the University Hospital of Verona. The research findings suggest that the HELPP score has potential as a new prognostic tool for pancreatic cancer, particularly in predicting outcomes for early-stage patients\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Notably, among these indicators, ASA classification emerged as the sole clinical parameter independently identified as a prognostic determinant. ASA classification offers a straightforward assessment of a patient's physiological condition, not only anticipating risks related to surgery but also correlating with oncological results post various cancer surgeries\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Alb\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e a circulating protein implicated in plasma inflammatory responses, serves as a valuable indicator for malnutrition assessment in patients due to its diminished levels. Hypoproteinemia is notably prevalent in advanced cancer patients, suggesting its potential utility as a marker for cachexia diagnosis. Recent studies have highlighted the increasing exploration of platelets' role in tumor progression. Platelets contribute to tumor advancement through intricate signaling pathways that bolster inflammatory responses, immune suppression, and angiogenesis. Moreover, platelets release exosomes, acting as mediators that facilitate communication between tumor cells and the tumor microenvironment. Additionally, tumor cells can activate platelets to promote their proliferation further\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThis study found that patients with a HELPP score greater than 3 had significantly lower survival rates compared to those with a score of 3 or less. Chinese scholars Xie\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e collected data from 35 early-stage pancreatic cancer patients who underwent radical resection. Using the HELPP scoring system, patients were divided into low-score (\u0026le;\u0026thinsp;3) and high-score (\u0026gt;\u0026thinsp;3) groups. The results indicated that preoperative HELPP scores have some predictive value for the prognosis of resectable pancreatic cancer patients, with a score greater than 3 possibly indicating a poor prognosis. Additionally, Li \u003csup\u003e14\u003c/sup\u003ealso found in a study of 61 patients who underwent radical resection for pancreatic cancer that patients with a HELPP score greater than 3 had significantly worse prognoses compared to the low-score group.\u003c/p\u003e\u003cp\u003eC-PLAN index is a new scoring system that combines five indicators: CRP, PS, LDH, ALB, and dNLR. This table was researched and invented by Japanese scholars\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e in 2023, and it has been validated to have high research value in predicting the overall survival and progression-free survival of advanced lung cancer. In a study by Chinese Scholar Hu\u003csup\u003e15\u003c/sup\u003e involving 147 patients with advanced esophageal cancer, the C-PLAN index was divided into low-score group (\u0026lt;\u0026thinsp;2 points) and high-score group (\u0026ge;\u0026thinsp;2 points). It was found that the low-score group had significantly better survival than the high-score group, and the C-PLAN index was an independent risk factor affecting prognosis. However, this index has not yet been studied in pancreatic cancer. In this study, 215 patients were divided into low-score group (\u0026le;\u0026thinsp;2 points) and high-score group (\u0026gt;\u0026thinsp;2 points). The results showed that the low-score group had significantly better survival prognosis than the high-score group, and the C-PLAN index had a larger AUC value compared to the HELPP score. Based on previous literature, the authors speculated that the C-PLAN index may affect the prognosis of pancreatic cancer patients through the following mechanisms: dNLR\u0026thinsp;=\u0026thinsp;neutrophil count / (white blood cell count - neutrophil count), this indicator is superior to the previously studied NLR because it includes not only lymphocytes but also monocytes and other granulocyte subtypes\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e; LDH exists in various important organs of the human body and is closely related to inflammatory responses and cell damage and death\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e; CRP is a type of acute phase protein, considered a predictor of infection, and its levels are influenced by pro-inflammatory factors such as IL-6, leading to increased levels in tumor occurrence, development, and metastasis\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Elevated CRP can also participate in non-specific immune inflammatory responses caused by tumor necrosis and create a favorable environment for tumor tissue development.\u003c/p\u003e\u003cp\u003eA nomogram is a simple and accurate scoring system that combines multiple factors affecting a disease, and by adding up the scores of each factor in the table, it can predict the survival probability of cancer patients at a certain time point\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. It not only provides a visual and personalized tool for clinicians to assess disease prognosis but also has significant practical value in clinical decision-making and risk stratification\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eTherefore, this study will explore the prognostic risk factors affecting patients undergoing radical resection for pancreatic head cancer based on their HELPP scores, C-PLAN index, preoperative examination indicators, pathological characteristics, and TNM staging. It aims to establish Nomogram prediction models for 1-year, 2-year, and 3-year outcomes post-surgery. However, this research is retrospective and involves two centers, which may introduce selection bias. Additionally, the sample size is relatively small. If the sample size can be increased in the future, the results will likely be more convincing.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eSupplementary Information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe would like to thanks to everyone in Radical resection of pancreatic head cancer patients and patients families agree to this research, thanks for every one person involved in this reserach, thank you Inner Mongolia Autonomous Region People’s Hospital and Affiliated Hospital Of Inner Mongolia Medical University provides the platform and resources.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNo datasets were generated or analysed during the current study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll procedures involving human participants performed in this study were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. This study was approved by the Ethics Committee of the Inner Mongolia Autonomous Region People’s Hospital. All patients and their families signed an ethical authorization form and informed consent before surgery.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJian Song \u0026nbsp;is responsible for writing the paper.Fan Yang and Wanxiang Wang are responsible for collecting patient information and follow-up of the Affiliated Hospital of Inner Mongolia Medical University.Jian Han and Shaohu Bai are responsible for collecting patient data and follow-up from the Inner Mongolia Autonomous Region People's Hospital.Hui Shi is responsible for statistical analysis.Finally, All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eSung H, Ferlay J, Siegel RL,et al.Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021 May;71(3):209-249. doi: 10.3322/caac.21660.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eZhang W, Ji L, Zhong X, et al. Two Novel Nomograms Predicting the Risk and Prognosis of Pancreatic Cancer Patients With Lung Metastases: A Population-Based Study. Front Public Health. 2022 May 31;10:884349. doi: 10.3389/fpubh.2022.884349.\u003c/li\u003e\n \u003cli\u003eInagaki K, Kunisho S, Takigawa H, et al. Role of tumor-associated macrophages at the invasive front in human colorectal cancer progression. Cancer Sci. 2021 Jul;112(7):2692-2704. doi: 10.1111/cas.14940.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eHank T, Hinz U, Reiner T, et al. A Pretreatment Prognostic Score to Stratify Survival in Pancreatic Cancer. Ann Surg. 2022 Dec 1;276(6):e914-e922. doi: 10.1097/SLA.0000000000004845.\u003c/li\u003e\n \u003cli\u003eSonehara K, Ozawa R, Hama M, et al. C-PLAN index as a prognostic factor for patients with previously untreated advanced non-small cell lung cancer who received combination immunotherapy: A multicenter retrospective study. Thorac Cancer. 2023 Feb;14(6):636-642. doi: 10.1111/1759-7714.14798.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eMa X, Zou W, Sun Y. Prognostic Value of Pretreatment Controlling Nutritional Status Score for Patients With Pancreatic Cancer: A Meta-Analysis. Front Oncol. 2022 Jan 20;11:770894. doi: 10.3389/fonc.2021.770894.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eSiegel RL, Giaquinto AN, Jemal A. Cancer statistics, 2024. CA Cancer J Clin. 2024 Jan-Feb;74(1):12-49. doi: 10.3322/caac.21820. Epub 2024 Jan 17. Erratum in: CA Cancer J Clin. 2024 Mar-Apr;74(2):203. doi: 10.3322/caac.21830.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eBhargavan R, Philip FA, Km JK,et al. Comparison of Modified Frailty Index, Clinical Frailty Scale, ECOG Score, and ASA PS Score in Predicting Postoperative Outcomes in Cancer Surgery: A Prospective Study. Indian J Surg Oncol. 2024 Dec;15(4):938-945. doi: 10.1007/s13193-024-01995-x.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eJonas N, Hsu CH, Yousef S, et al. The bariatric frailty score as a superior scoring system compared to the American Society of Anesthesiologists (ASA) score in prediction of serious complications after bariatric surgery procedures. Surg Endosc. 2025 Jul;39(7):4505-4512. doi: 10.1007/s00464-025-11853-8.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eNakanishi T, Matsuda T, Yamashita K, et al. Alb-dNLR Score as a Novel Prognostic Marker for Patients With Locally Advanced Rectal Cancer Undergoing Neoadjuvant Chemoradiotherapy. Anticancer Res. 2024 Jan;44(1):229-237. doi: 10.21873/anticanres.16806.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eRen W, Zhang H, Cheng L, et al. Clinical significance of prognostic nutritional index (PNI)-monocyte-to-lymphocyte ratio (MLR)-platelet (PLT) score on postoperative outcomes in non-metastatic clear cell renal cell carcinoma. BMC Surg. 2023 May 10;23(1):117. doi: 10.1186/s12893-023-02001-x.\u003c/li\u003e\n \u003cli\u003eChen JP, Huang QD, Wan T, et al. Combined score of pretreatment platelet count and CA125 level (PLT-CA125) stratified prognosis in patients with FIGO stage IV epithelial ovarian cancer. J Ovarian Res. 2019 Jul 31;12(1):72. doi: 10.1186/s13048-019-0544-y.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eXie Y, Hang H X, Li G, et al. Analysis of the value of the Heidelberg pancreatic prognostic score in evaluating the prognosis of patients after pancreatic cancer resection [J]. Chinese Journal of Practical Surgery, 2022, 4(05): 585-589. DOI: 10.19538/j.cjps.issn100-2208.2022.05.21.\u003c/li\u003e\n \u003cli\u003eLi J, Lin Q, Lin H, et al. The preoperative HELPP score can be used as a prognostic assessment tool for resectable pancreatic cancer patients, and may be applicable to patients in China as well. Gland Surg. 2025 Jun 30;14(6):1112-1127. doi: 10.21037/gs-2025-132. Epub 2025 Jun 11.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eHu R, Guo H J, Wang Y, et al. Clinical study of C-PLAN index as a prog indicator for immunotherapy with immune checkpoint inhibitors in advanced esophageal cancer [J]. Journal of Practical Clinical Medicine, 2024, 2801): 1-6 12.\u003c/li\u003e\n \u003cli\u003eYang Y, Xu H, Yang G, et al. The value of blood biomarkers of progression and prognosis in ALK-positive patients with non-small cell lung cancer treated with crizotinib. Asia Pac J Clin Oncol. 2020 Feb;16(1):63-69. doi: 10.1111 /ajco.1 3284.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eXiong A, Xu J, Wang S, et al. On-treatment lung immune prognostic index is predictive for first-line PD-1 inhibitor combined with chemotherapy in patients with non-small cell lung cancer. Front Immunol. 2023 May 25;14:1173025. doi: 10.3389/fimmu.2023.1173025.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eZhu M, Ma Z, Zhang X, et al. C-reactive protein and cancer risk: a pan-cancer study of prospective cohort and Mendelian randomization analysis. BMC Med. 2022 Sep 19;20(1):301. doi: 10.1186/s12916-022-02506-x.\u003c/li\u003e\n \u003cli\u003eTong C, Miao Q, Zheng J, et al. A novel nomogram for predicting the decision to delayed extubation after thoracoscopic lung cancer surgery. Ann Med. 2023 Dec;55(1):800-807. doi: 10.1080/07853890.2022.2160490.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eZhang W, Ji L, Wang X, et al. Nomogram Predicts Risk and Prognostic Factors for Bone Metastasis of Pancreatic Cancer: A Population-Based Analysis. Front Endocrinol (Lausanne). 2022 Mar 9;12:752176. doi: 10.3389/f endo. 2021. 752176. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"world-journal-of-surgical-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"wjso","sideBox":"Learn more about [World Journal of Surgical Oncology](http://wjso.biomedcentral.com)","snPcode":"12957","submissionUrl":"https://submission.nature.com/new-submission/12957/3","title":"World Journal of Surgical Oncology","twitterHandle":"@OncoBioMed","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Pancreatic head cancer, HELPP score, C-PLAN index, Nomogram, Prognosis","lastPublishedDoi":"10.21203/rs.3.rs-7574852/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7574852/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose \u003c/strong\u003eThis study aims to investigate the correlation between the Heidelberg Prognostic Pancreatic Cancer (HELPP) score, C-PLAN index, clinicopathological features, and survival outcomes in patients following radical resection of pancreatic head cancer. Additionally, the study seeks to develop a predictive model for postoperative survival and assess its effectiveness.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods \u003c/strong\u003eA retrospective analysis was conducted on clinicopathological data from 215 patients diagnosed with pancreatic head cancer who underwent radical pancreaticoduodenectomy at the Department of Hepatobiliary and Pancreatic Surgery, Affiliated Hospital of Inner Mongolia Medical University, and the Department of Hepatobiliary and Pancreatic Surgery, Inner Mongolia Autonomous Region People's Hospital, between January 1, 2011, and December 31, 2023. Univariate and multivariate analyses using the COX proportional hazards model were carried out to determine prognostic factors influencing the overall survival of patients post pancreatic head cancer surgery. Subsequently, a prognostic nomogram was developed utilizing R version 4.2.2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults \u003c/strong\u003eThe 215 patients had a median survival time of 20.7 months, with cumulative survival rates of 71.6%, 35.8%, and 14.4% at 1, 2, and 3 years post-surgery, respectively. Patients with HELPP scores \u0026gt;3 and C-PLAN scores \u0026gt;2 had a worse prognosis. Multivariate COX regression analysis identified differentiation grade, TNM stage, tumor diameter, HELPP score, and C-PLAN index as independent risk factors influencing prognosis (P \u0026lt; .05). A prognostic nomogram, incorporating these factors, demonstrated strong predictive performance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions \u003c/strong\u003eThe HELPP score and C-PLAN index exhibit potential as prognostic indicators for predicting patient outcomes following radical resection of pancreatic head cancer. Factors such as differentiation grade, TNM stage, tumor diameter, HELPP score, and C-PLAN index independently influence the prognosis of pancreatic head cancer. A nomogram model incorporating these variables can accurately forecast the long-term survival of patients with pancreatic head cancer.\u003c/p\u003e","manuscriptTitle":"Predictive value of HELPP Score and C-PLAN Index for prognosis in patients undergoing radical resection of pancreatic head Cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-23 06:48:40","doi":"10.21203/rs.3.rs-7574852/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2025-11-19T11:26:16+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-16T09:26:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"179361998410524277804369734085867929008","date":"2025-11-16T06:44:07+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-15T01:10:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"127055057631002039334005798481551693368","date":"2025-11-13T08:43:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"76558194038266941976481863905339214165","date":"2025-11-12T00:43:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"150698062079814830139769978724004083866","date":"2025-11-12T00:23:24+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-13T10:30:38+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-13T03:20:11+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-12T00:11:39+00:00","index":"","fulltext":""},{"type":"submitted","content":"World Journal of Surgical Oncology","date":"2025-09-09T14:19:12+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"world-journal-of-surgical-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"wjso","sideBox":"Learn more about [World Journal of Surgical Oncology](http://wjso.biomedcentral.com)","snPcode":"12957","submissionUrl":"https://submission.nature.com/new-submission/12957/3","title":"World Journal of Surgical Oncology","twitterHandle":"@OncoBioMed","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a6d7e02c-eab3-4eb0-b0a5-143cf7d13609","owner":[],"postedDate":"September 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-09-23T06:48:41+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-23 06:48:40","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7574852","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7574852","identity":"rs-7574852","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}