scholarly journals World Health Organization Grading Classification for Pancreatic Neuroendocrine Neoplasms: A Comprehensive Analysis from a Large Chinese Institution

2020 ◽  
Author(s):  
Min Yang ◽  
Lin Zeng ◽  
Neng-wen Ke ◽  
Chun-lu Tan ◽  
Bo-le Tian ◽  
...  
Keyword(s):  
World Health Organization ◽  
World Health ◽  
Neuroendocrine Neoplasms ◽  
The Novel ◽  
Pancreatic Neuroendocrine Neoplasms ◽  
Significant Survival ◽  
Prognostic Stratification ◽  
Long Term Prognosis ◽  
Health Organization ◽  
Survival Differences

Abstract Background Pancreatic neuroendocrine neoplasms (p-NENs) are a group of highly heterogeneous tumors with distinct clinicopathological features and long-term prognosis. In 2017, in order to better stratify patients into prognostic groups and predicting their outcomes, World Health Organization (WHO) officially updated its grading system for p-NENs which distinguished these neoplasms among Grading 1 (G1) pancreatic neuroendocrine tumors (p-NETs), G2 p-NETs, G3 p-NETs and G3 pancreatic neuroendocrine carcinomas (p-NECs). However, this new grading classification for p-NENs has not yet been rigorously validated.Methods Data of patients who were surgically treated and histopathologically diagnosed as p-NENs at West China Hospital of Sichuan University from January 2002 to December 2018 were retrospectively collected and analyzed according the novel WHO 2017 grading classification.Results We eventually enrolled 480 eligible patients with p-NENs in our present study, in which 150 patients with WHO 2017 G1 p-NETs, 158 with G2 p-NETs, 64 with G3 p-NETs and 108 with G3 p-NECs were identified. The estimated 5-year overall survival for patients with G1 p-NETs, G2 p-NETs, G3 p-NETs and G3 p-NECs was 75.8%, 58.4%, 35.1% and 11.1%, with a median survival time of 85.3mons, 67.4mons, 51.3mons and 26.8mons, respectively. Patients with G2 p-NETs present notably worse survival than those with G1 p-NETs (P = 0.03). Survival of G3 p-NETs were significantly worse than that of G1 p-NETs or G2 p-NETs (P < 0.001, P = 0.023, respectively), as well as that when comparing G3 p-NECs with G1 p-NETs or G2 p-NETs (P < 0.001, P < 0.001, respectively). Patients with G3 p-NECs showed statistically shorter survival than those with G3 p-NETs (P < 0.001). Both WHO 2017 and 2010 grading criteria could be independent predictor for the OS of p-NENs (P = 0.016, P = 0.022; respectively). The 95% confidence intervals of WHO 2017 grading classification (0.983–9.454) was slightly smaller than that of WHO 2010 criteria (0.201–13.374), indicating a relatively more accurate predicting ability for the prognosis of p-NENs.Conclusion The WHO 2017 grading classification for p-NENs could successfully allocate patients into four groups with distinct clinical features and significant survival differences, which might be superior to the WHO 2010 criteria for its better prognostic stratification and more accurate predicting ability.

scholarly journals World Health Organization Grading Classification for Pancreatic Neuroendocrine Neoplasms: A Comprehensive Analysis from a Large Chinese Institution

2020 ◽  
Author(s):  
Min Yang ◽  
Lin Zeng ◽  
Neng-wen Ke ◽  
Chun-lu Tan ◽  
Bo-le Tian ◽  
...  
Keyword(s):  
World Health Organization ◽  
World Health ◽  
Neuroendocrine Neoplasms ◽  
The Novel ◽  
Pancreatic Neuroendocrine Neoplasms ◽  
Significant Survival ◽  
Prognostic Stratification ◽  
Long Term Prognosis ◽  
Health Organization ◽  
Survival Differences

Abstract Background: Pancreatic neuroendocrine neoplasms (p-NENs) are a group of highly heterogeneous tumors with distinct clinicopathological features and long-term prognosis. In 2017, in order to better stratify patients into prognostic groups and predicting their outcomes, World Health Organization (WHO) officially updated its grading system for p-NENs which distinguished these neoplasms among Grading 1 (G1) pancreatic neuroendocrine tumors (p-NETs), G2 p-NETs, G3 p-NETs and G3 pancreatic neuroendocrine carcinomas (p-NECs). However, this new grading classification for p-NENs has not yet been rigorously validated.Methods: Data of patients who were surgically treated and histopathologically diagnosed as p-NENs at West China Hospital of Sichuan University from January 2002 to December 2018 were retrospectively collected and analyzed according the novel WHO 2017 grading classification.Results: We eventually enrolled 480 eligible patients with p-NENs in our present study, in which 150 patients with WHO 2017 G1 p-NETs, 158 with G2 p-NETs, 64 with G3 p-NETs and 108 with G3 p-NECs were identified. The estimated 5-year overall survival for patients with G1 p-NETs, G2 p-NETs, G3 p-NETs and G3 p-NECs was 75.8%, 58.4%, 35.1% and 11.1%, with a median survival time of 85.3mons, 67.4mons, 51.3mons and 26.8mons, respectively. Patients with G2 p-NETs present notably worse survival than those with G1 p-NETs (P=0.03). Survival of G3 p-NETs were significantly worse than that of G1 p-NETs or G2 p-NETs (P<0.001, P=0.023, respectively), as well as that when comparing G3 p-NECs with G1 p-NETs or G2 p-NETs (P<0.001, P<0.001, respectively). Patients with G3 p-NECs showed statistically shorter survival than those with G3 p-NETs (P<0.001). Both WHO 2017 and 2010 grading criteria could be independent predictor for the OS of p-NENs (P=0.016, P=0.022; respectively). The 95% confidence intervals of WHO 2017 grading classification (0.983-9.454) was slightly smaller than that of WHO 2010 criteria (0.201-13.374), indicating a relatively more accurate predicting ability for the prognosis of p-NENs.Conclusion: The WHO 2017 grading classification for p-NENs could successfully allocate patients into four groups with distinct clinical features and significant survival differences, which might be superior to the WHO 2010 criteria for its better prognostic stratification and more accurate predicting ability.

scholarly journals World Health Organization grading classification for pancreatic neuroendocrine neoplasms: a comprehensive analysis from a large Chinese institution

BMC Cancer ◽  
2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Min Yang ◽  
Lin Zeng ◽  
Neng-wen Ke ◽  
Chun-lu Tan ◽  
Bo-le Tian ◽  
...  
Keyword(s):  
World Health Organization ◽  
World Health ◽  
Neuroendocrine Neoplasms ◽  
The Novel ◽  
Pancreatic Neuroendocrine Neoplasms ◽  
Significant Survival ◽  
Prognostic Stratification ◽  
Long Term Prognosis ◽  
Health Organization ◽  
Survival Differences

Abstract Background Pancreatic neuroendocrine neoplasms (p-NENs) are a group of highly heterogeneous tumors with distinct clinicopathological features and long-term prognosis. In 2017, in order to better stratify patients into prognostic groups and predicting their outcomes, World Health Organization (WHO) officially updated its grading system for p-NENs which distinguished these neoplasms among Grading 1 (G1) pancreatic neuroendocrine tumors (p-NETs), G2 p-NETs, G3 p-NETs and G3 pancreatic neuroendocrine carcinomas (p-NECs). However, this new grading classification for p-NENs has not yet been rigorously validated. Methods Data of patients who were surgically treated and histopathologically diagnosed as p-NENs at West China Hospital of Sichuan University from January 2002 to December 2018 were retrospectively collected and analyzed according the novel WHO 2017 grading classification. Results We eventually enrolled 480 eligible patients with p-NENs in our present study, in which 150 patients with WHO 2017 G1 p-NETs, 158 with G2 p-NETs, 64 with G3 p-NETs and 108 with G3 p-NECs were identified. The estimated 5-year overall survival for patients with G1 p-NETs, G2 p-NETs, G3 p-NETs and G3 p-NECs was 75.8, 58.4, 35.1 and 11.1%, with a median survival time of 85.3mons, 67.4mons, 51.3mons and 26.8mons, respectively. Patients with G2 p-NETs present notably worse survival than those with G1 p-NETs (P = 0.03). Survival of G3 p-NETs were significantly worse than that of G1 p-NETs or G2 p-NETs (P < 0.001, P = 0.023, respectively), as well as that when comparing G3 p-NECs with G1 p-NETs or G2 p-NETs (P < 0.001, P < 0.001, respectively). Patients with G3 p-NECs showed statistically shorter survival than those with G3 p-NETs (P < 0.001). Both WHO 2017 and 2010 grading criteria could be independent predictor for the OS of p-NENs (P = 0.016, P = 0.022; respectively). The 95% confidence intervals of WHO 2017 grading classification (0.983–9.454) was slightly smaller than that of WHO 2010 criteria (0.201–13.374), indicating a relatively more accurate predicting ability for the prognosis of p-NENs. Conclusion The WHO 2017 grading classification for p-NENs could successfully allocate patients into four groups with distinct clinical features and significant survival differences, which might be superior to the WHO 2010 criteria for its better prognostic stratification and more accurate predicting ability.

Giant Primary Neuroendocrine Neoplasms of the Liver: Report of 2 Cases With Molecular Characterization

2019 ◽  
Vol 27 (8) ◽  
pp. 893-899
Author(s):  
Laura G. Pastrián ◽  
Ignacio Ruz-Caracuel ◽  
Raul S. Gonzalez
Keyword(s):  
World Health Organization ◽  
Neuroendocrine Tumor ◽  
Large Cell ◽  
The Other ◽  
World Health ◽  
Neuroendocrine Neoplasms ◽  
Molecular Testing ◽  
Well Differentiated ◽  
Grade 3 ◽  
Health Organization

Primary neuroendocrine neoplasms of the liver have occasionally been reported in the liver, though many reports do not convincingly exclude metastases. In this article, we report 2 “giant” hepatic neuroendocrine lesions without evidence of a primary elsewhere after clinical workup. One occurred in a 21-year-old male; the lesion was a large cell neuroendocrine carcinoma measuring 24 cm. The patient died of disease in 10 months. The other occurred in a 25-year-old patient, was 18 cm wide, and was diagnosed as a well-differentiated neuroendocrine tumor, World Health Organization grade 3. The patient died of disease after 30 months. Molecular testing demonstrated only the presence of TP53 mutations in common. These cases expand our knowledge of seemingly primary neuroendocrine neoplasms of the liver, in particular, giant cases measuring more than 8 cm. Guidelines for clinical workup and therapy for these lesions remain unclear, but future thorough workup of such cases is necessary for specific characterization.

Classification and Prognostic Stratification of Bronchopulmonary Neuroendocrine Neoplasms

2019 ◽  
Vol 110 (5) ◽  
pp. 393-403 ◽  
Author(s):  
Naomi Oka ◽  
Atsuko Kasajima ◽  
Björn Konukiewitz ◽  
Akira Sakurada ◽  
Yoshinori Okada ◽  
...  
Keyword(s):  
Disease Free Survival ◽  
Mitotic Count ◽  
World Health ◽  
Neuroendocrine Neoplasms ◽  
Prognostic Impact ◽  
Ki67 Index ◽  
Prognostic Stratification ◽  
Net G3 ◽  
Health Organization

The accuracy and reproducibility of the World Health Organization (WHO) 2015 classification of bronchopulmonary neuroendocrine neoplasms (BP-NENs) is disputed. The aim of this study is to classify and grade BP-NENs using the WHO 2019 classification of digestive system NENs (DiS-NEN-WHO 2019), and to analyze its accuracy and prognostic impact. Two BP-NEN cohorts from Japan and Germany, 393 tumors (88% surgically resected), were reviewed and the clinicopathological data of the resected tumors (n = 301) correlated to patients’ disease-free survival (DFS). The DiS-NEN-WHO 2019 stratified the 350 tumors into 91 (26%) neuroendocrine tumors (NET) G1, 52 (15%) NET G2, 15 (4%) NET G3, and 192 (55%) neuroendocrine carcinomas (NEC). NECs, but not NETs, were immunohistochemically characterized by abnormal p53 (100%) and retinoblastoma 1 (83%) expression. The Ki67 index, which was on average 4 times higher than mitotic count (p < 0.0001), was prognostically more accurate than the mitotic count. NET G3 patients had a worse outcome than NET G1 (p < 0.01) and NET G2 patients (p = 0.02), respectively. No prognostic difference was detected between NET G3 and NEC patients after 5 year DFS. It is concluded that stratifying BP-NEN patients according to the DiS-NEN-WHO 2019 classification results in 3 prognostically well-defined NET groups, if grading is solely based on Ki67 index. Mitotic count alone may underestimate malignant potential of NETs.

scholarly journals A Review on Automatic Covid-19 Lung Infection Detection from Different Imaging Techniques

2021 ◽  
Vol 9 (VII) ◽  
pp. 3850-3856
Author(s):  
Sangeeta Singh
Keyword(s):  
World Health Organization ◽  
Virus Disease ◽  
Imaging Techniques ◽  
World Health ◽  
The Novel ◽  
Corona Virus ◽  
The World ◽  
Health Organization ◽  
High Level ◽  
Precision Rate

Corona Virus Disease-2019 commonly known as COVID-19 which has been defined by the Novel Corona Virus. It is a family of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) and was first detected during respiratory outbreak. It was first reported to the World Health Organization on December 31, 2019. On January 30, 2020, the World Health Organization declared the COVID-19 eruption a global health emergency. As of 27-May-2021 169,095,283 confirmed cases have been reported in the world and 2, 73, 67, 935 cases in India. It is required to identify the infection with high precision rate but there are lots of deficiency in the diagnosing system that may resulted false alarm rate. Initially it could be detected through throat saliva but now it can also be identified thought the impairment in lungs from computerized tomographical imaging technique. This paper reviewed various researches over COVID-19 diagnosis approach as well as the syndrome in respiratory organs. There are so many imaging techniques through which lungs impairments can be detected that may diagnose COVID-19 with high level of accuracy. CT scan image is the best alternative for diagnosing COVID-19.

Sign in / Sign up

Export Citation Format

Share Document