Abstract
BackgroundPancreatic adenosquamous carcinoma (PASC) is a heterogeneous group of primary pancreatic cancers characterized by the coexistence of both glandular and squamous differentiation. The aim of this study was to develop nomograms to predict survival outcomes in patients with PASC.MethodsIn this retrospective study, data on PASC, including clinicopathological characteristics, treatments, and survival outcomes, were collected from the SEER database between 2000 and 2018. The primary endpoints were overall survival (OS) and cancer-specific survival (CSS). The eligible patients were randomly divided into development cohort and validation cohort in a 7:3 ratio. The nomograms for prediction of OS and CSS were constructed by the development cohort using a LASSO-Cox regression model, respectively. Besides the model performance was internally and externally validated by examining the discrimination, calibration, and clinical utility.ResultsA total of 632 consecutive patients who had been diagnosed with PASC were identified and randomly divided into development (n = 444) and validation (n = 188) cohorts. In the development cohort, the estimated median OS was 7.0 months (95% CI: 6.19–7.82) and the median CSS was 7.0 months (95% CI: 6.15–7.85). In the validation cohort, the estimated median OS was 6.0 months (95% CI: 4.46–7.54) and the median CSS was 7.0 months (95% CI: 6.25–7.75). LASSO-penalized COX regression analysis identified 8 independent predictors in the OS prediction model and 9 independent risk factors in the CSS prediction model: age at diagnosis, gender, year of diagnosis, tumor location, grade, stage, size, lymph node metastasis, combined metastasis, surgery, radiation, and chemotherapy. The Harrell C index and time-dependent AUCs manifested satisfactory discriminative capabilities of the models. Calibration plots showed that both models were well calibrated. Furthermore, decision curves indicated good utility of the nomograms for decision-making.ConclusionNomogram-based models to evaluate personalized OS and CSS in patients with PASC were developed and well validated. These easy-to-use tools will be useful methods to calculate individualized estimate of survival, assist in risk stratification, and aid clinical decision-making.
Highlights
Pancreatic cancer, a deadly disease with a highly metastatic potential and an unfavorable prognosis, is the fourth leading cause of cancer-related mortality in United States [1–3]
As a unique histopathological variant, Pancreatic adenosquamous carcinoma (PASC) presents with more aggressive behaviors and more dismal prognosis compared to pancreatic ductal adenocarcinoma (PDAC), which are deemed to be pathologically relevant to the squamous metaplasia [11, 14–17]
Other studies demonstrate that the overall survival is similar between PASC and PDAC, even though PASCs tend to have more apparent perineural infiltration and increased lymph node involvement compared with PDAC [18]
Summary
Pancreatic cancer, a deadly disease with a highly metastatic potential and an unfavorable prognosis, is the fourth leading cause of cancer-related mortality in United States [1–3]. The primary histological type of pancreatic malignancy is pancreatic ductal adenocarcinoma (PDAC) [7–9]. Pancreatic adenosquamous carcinoma (PASC) is an extremely rare subtype which contains biphenotypic characteristics of both glandular and squamous differentiation as the normal pancreas is histologically devoid of squamous elements, only accounting for 0.4% to 4% of pancreatic cancer [10, 11]. Large population-based analyses with regard to epidemiology and clinical features of PASC are sparse The aim of this current study was to determine epidemiological characteristics and to estimate the individualized prognosis of patients with PASC, pooling data from a population-based database and eventually developing nomograms to predict survival outcomes as well as aid clinical decision-making. Pancreatic adenosquamous carcinoma (PASC) is a heterogeneous group of primary pancreatic cancers characterized by the coexistence of both glandular and squamous differentiation.
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