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AIM: In this study, we aimed to review the demographic histopathological and clinical findings and long-term results of our GEP-NET cases, as well as to re-evaluate our cases according to the new classification systems.
MATERIAL AND METHOD: 46 patients diagnosed as GEPNETs were presented. Immunohistochemical studies were performed in all cases. The cases were divided into 3 groups according to their embryogenic origin (Foregut, Midgut and Hindgut). All cases re-evaluated according to recent WHO (2019) and AJCC (2017) TNM calcification. Investigation was made to find differences between the embryonic origins and to find correlation between stage and grading systems with each other.
RESULTS: The most common localization was appendix (52.3%) The distribution of cases according to embryologic origin were as follows: foregut tumors 13 cases (27.7%), midgut tumors 27 cases (57.4%) and hindgut tumors in 6 cases (12.8%). The Ki-67 ratio was evaluated in all patients, with a mean of 6.34%±2.51 (range: 1-80). The Ki-67 ratio was less than 3% in 82.6% of patients. Mitotic count was less than 2 per/10 HPF in 76% of patients. According to WHO 2019 most of patients were Grade 1 Neuroendocrine Tumor (65.2%) and there were only 2 Neuroendocrine Carcinoma (NEC) cases. According to AJCC 2017 most cases were Stage 1 (52.1%) and only 4 cases were Stage 4. The grades and stages of our cases were statistically significantly correlated. Overall survival did not differ significantly with regard to embryologic origin (log-rank test, p=0.062). The median overall survival was 106±7.4 months. The 5-year cumulative survival rate was 84.1±5.6 years. Seven patients died during this time with a median time of 5 months (range: 1-31 months). In the Cox regression analysis, the percentage of Ki- 67 was found to have a statistically significant effect on overall survival (p=0.000)
CONCLUSION: Correlation was noticed between WHO 2019 and AJCC 2017 classification for grade and stage and controlled trials must be undertaken to develop a single diagnostic algorithm and to change the future management of such patients.