Prognostic Nomogram for patients undergoing radical Pancreaticoduodenectomy for adenocarcinoma of the pancreatic head.

BACKGROUND: Radical pancreaticoduodenectomy is the most common treatment strategy for patients diagnosed with adenocarcinoma of the pancreatic head. Few studies have reported the clinical characteristics and treatment efficacies of patients undergoing radical pancreaticoduodenectomy for adenocarcinoma of the pancreatic head. METHODS: A total of 177 pancreatic head cancer patients who underwent radical pancreaticoduodenectomy and were pathologically confirmed as having pancreatic ductal adenocarcinoma were screened in the West China Hospital of Sichuan University. The multivariate analysis results were implemented to construct a nomogram. The concordance index (c-index), the area under the curve (AUC) and calibration were utilized to evaluate the predictive performance of the nomogram. RESULTS: The prognostic nutritional index (PNI), the lymph node ratio (LNR) and the American Joint Committee on Cancer (AJCC) staging served as independent prognostic factors and were used to construct the nomogram. The c-indexes of the nomogram were 0.799 (confidence interval (CI), 0.741-0.858) and 0.732 (0.657-0.807) in the primary set and validation set, respectively. The AUCs of the nomogram at 1 and 3 years were 0.832 and 0.783, which were superior to the AJCC staging values of 0.759 and 0.705, respectively. CONCLUSIONS: The nomogram may be used to predict the prognosis of radical resection for adenocarcinoma of the pancreatic head. These findings may represent an effective model for the developing an optimal therapeutic schedule for malnourished patients who need early effective nutritional intervention and may promote the treatment efficacy of resectable adenocarcinoma of the pancreatic head.

Clinical Features and Long-Term Survival of Metastatic Hepatic Neuroendocrine Neoplasms Secondary to Gastroenteropancreatic Site: An Analysis by Applying the Grading Classification.

METHOD: Data of patients who were surgically treated and clinicopathologically diagnosed as (MH)-NENs secondary to (GEP)-NENs at West China Hospital of Sichuan University from January 2006 to December 2018 were retrospectively collected and analyzed by the grading classification for (GEP)-NENs. RESULTS: We identified 150 patients with (MH)-NENs secondary to (GEP)-NENs, including 10 patients with G1 NETs, 26 with G2 NETs, 33 with G3 NETs, and 81 with G3 NECs. There were significant differences between patients with G1/G2/G3 NETs and those with G3 NECs, such as age at diagnosis (P=0.041), synchronous liver lesion (P=0.032), incidental diagnosis (P=0.014), tumor largest diameter (P=0.047), vascular invasion (P=0.017), and extrahepatic metastatic disease (P=0.029). The estimated 3-year overall survival for patients with G1 NETs, G2 NETs, G3 NETs, and G3 NECs was 100%, 79.4%, 49.5%, and 20.7%, respectively (P < 0.001). The survival of G1 NETs or G2 NETs was significantly better than that of G3 NETs (P=0.013, P=0.037, respectively) and G3 NECs (P=0.001, P < 0.001; respectively). Patients with G3 NECs present notably worse survival than those with G3 NETs (P=0.012), while survival comparison between G1 NETs and G2 NETs was not statistically different (P=0.131). The grading classification for (GEP)-NENs was an effective independent predictor of survival for (MH)-NENs secondary to (GEP)-NENs (hazard ratio: 4.234; 95% confidence intervals: 1.984-6.763; P=0.003). CONCLUSION: Our demonstration revealed that the grading classification for (GEP)-NENs could well stratify (MH)-NENs secondary to (GEP)-NENs into prognostic groups and supported its wide use in clinical practice.

Survivals of patients with pancreatic neuroendocrine carcinomas: An in-depth analysis by the American Joint Committee on Cancer 8th tumor-node-metastasis staging manual.

Recently, the American Joint Committee on Cancer (AJCC) 8th staging manual stipulated the World Health Organization (WHO) G3 pancreatic neuroendocrine carcinomas (p-NECs) should all be classified by the system for pancreatic exocrine adenocarcinomas, which had ignored the heterogeneity of G3 p-NECs. We focused on demonstrating whether the heterogeneous subgroups of G3 p-NECs would influence the accurate application of AJCC 8th staging systems.G3 p-NECs were divided into well-differentiated and poorly-differentiated subgroups, whose clinical features and overall survival (OS) were compared. Survival analysis by applying 2 new AJCC 8th staging systems to well-differentiated G3 p-NECs were performed to validate whether these subgroup patients should also be staged by the system proposed for all G3 p-NECs.We enrolled 172 patients who were histopathologically diagnosed as G3 p-NECs, including 64 well-differentiated G3 p-NECs and 108 poorly-differentiated ones, whose patient demographics and tumor characteristics present no notably differences (P > .05), except their Ki-67 index and mitotic rate (P = .031, P = .025; respectively). The estimated OS of well-differentiated G3 p-NECs was significantly better than those of poorly-differentiated tumors (P < .001). When applying the new AJCC system for all G3 p-NECs to well-differentiated G3 tumors, 18, 22, 12, and 12 patients were respectively distributed in the new AJCC Stage I, Stage II, Stage III, and Stage IV. Using the AJCC 8th staging system for WHO G1/G2 pancreatic neuroendocrine tumors (p-NETs) to well-differentiated G3 p-NECs, there were 5, 25, 22, and 12 patients classified from the new AJCC Stage I to Stage IV, respectively. The system for G1/G2 p-NETs could significantly differentiate the survival differences between each new stage of well-differentiated G3 p-NECs (P < .05), while comparisons of survivals between Stage II with Stage III or Stage III with Stage IV by the system for G3 p-NECs were not statistically different (P = .334, P = .073; respectively).G3 p-NECs were heterogeneous with well-differentiated and poorly-differentiated subgroups. Both AJCC 8th staging systems proposed for all G3 p-NECs and G1/G2 p-NETs were practical for well-differentiated G3 p-NECs, while the one originally applied to G1/G2 p-NETs appeared to be superior in performance due to its better prognostic stratification and more accurate predicting ability.