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Published on: April 18, 2015
Prognostic Predicting Role of Contrast-Enhanced Computed Tomography for Locally Advanced Pancreatic Adenocarcinoma
Chien-Shan Cheng1,2, Wei Liu2,3, Liangping Zhou2,3
1Department of Integrative Oncology, Fudan University Shanghai Cancer Center, Shanghai 200032, China.
Introduction:
Contrast-enhanced computed tomography (CECT) imaging is commonly used to assess pancreatic adenocarcinoma (PAC). However, the value of semiquantitative and quantitative assessments of CECT parameters used to predict survival in PAC remains unknown. This study aims to investigate the prognostic role of pretreatment CECT imaging in patients with locally advanced pancreatic adenocarcinoma (LAPAC).
Materials And Methods:
From June 2013 to May 2017, eighty-six newly diagnosed patients with pathologically and radiologically confirmed LAPAC were retrospectively recruited. All patients were evaluated by CECT and experienced gemcitabine-based chemotherapy. The relationship between overall survival (OS) and clinical factors including age, sex, serum carbohydrate antigen 19-9 value, and CECT findings (including tumour location, tumour volume, peripancreatic involvement, blood vessel involvement, tumour enhanced rate, and distance liver metastasis) was determined using Cox proportional hazard regression models, and a nomogram was constructed for the prediction of 1- and 1.5-year survival rates of patients with LAPAC.
Results:
On univariate analysis, patients who had a tumour enhanced rate (TER) less than 80.465% and those who had a TER ≥ 80.465% are with a 3.587-fold increase in OS (p < 0.001). After multivariate Cox regression, a nomogram was established based on a new model containing the predictive variables of high Ca19-9 level, higher clinical stages, larger tumour volume, the presence of peripancreatic involvement, and liver metastases. The model displayed good accuracy in predicting OS with a C-index of 0.614. The calibration plots also showed a good discrimination and calibration of the nomogram between the predicted and observed survival probabilities.
Conclusion:
Our results showed that TER can be used to predict survival in LAPAC, and we developed a nomogram for determining the prognosis of patients with LAPAC. However, the purposed nomogram still requires external data verification in future applications.
