Document Type : Research Articles
Department of Medical Oncology, Yuzuncu Yil University Medical School, 65090, Van, Turkey.
Department of Radiation Oncology, University of Health Sciences, Okmeydani Training and Research Hospital, 34384, Istanbul, Turkey.
Department of Medical Oncology, University of Health Sciences, Okmeydani Training and Research Hospital, 34384, Istanbul, Turkey.
Background: Neuroendocrine tumors are a heterogeneous group of tumors that can originate from all of the
neuroendocrine cells in the body, mostly from the gastrointestinal tract. In addition to early diagnosis, streaming
patients into appropriate prognostic groups is an important component of treatment. In this study, we examined the
factors that affect survival in patients we followed in our center between 2000-2016. Methods: The demographic data,
clinical and pathological features of patients were obtained from their medical files. TNM staging and tumor grading
were performed according to AJCC and WHO 2010 classification. SPSS 15.0 for Windows programme was used for
statistical analysis. Results: 85 patients (32 male, 53 female) were included into the study. The median age of the patients
was 55,7 (27-83) years. Eighty percent of the tumors were of gastroenteropancreatic system, most commonly stomach
(27.1%) origin. Nineteen patients (22.4%) died during follow-up. In univariate analysis; age (p<0,001), stage (p=0.002),
primary tumor localization (p=0.005), grade (p<0.001), Ki-67 value (p<0.001), number of metastases (p=0.001) and
type of surgery (p<0.001) were found to be factors affecting survival. Age (p=0.024) and Ki67 (p <0.001) were the
independent prognostic factors for survival in multivariate analysis. For the cut-off value of 6%, Ki-67 had a sensitivity
of 83.3% and specifity of 71.4% for survival determination. Conclusion: Ki-67 ratio and age were the most important
factors affecting survival in neuroendocrine tumors in our study. Ki-67 ratio has a high sensitivity and specificity for
predicting survival, a cut-off value of 6% may be used to predict survival.