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

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.