Pulmonary neuroendocrine carcinoid tumors: Is there a predictive role to the Ki 67 index?

• Main Authors: Ana Karina Patane, Gabriela Guma, Mercedes Rayá, Adolfo Rosales, Walter Astorino, Moisés Rosenberg
• Format: Article
• Language: English
• Published: Wolters Kluwer Medknow Publications 2021-01-01
• Series: Annals of Thoracic Medicine
• Subjects: ki 67 index; lung carcinoids; predictive value
• Online Access: http://www.thoracicmedicine.org/article.asp?issn=1817-1737;year=2021;volume=16;issue=3;spage=274;epage=279;aulast=Patane

INTRODUCTION: There are several factors predicting evolution in carcinoid tumors (CT) to date including the Ki67 role. AIMS: The aim of this study is to identify a KI67 cut-off point for a population of CT and determine its prognostic implication in global and disease-free survival. METHODS: Hematoxylin-eosin slides of 102 CT were revised. The percentage of cells expressing Ki 67 was determined manually. STATISTICAL ANALYSIS: The variables were compared with the t-test or the Wilcoxon test according to their distribution, the categorical ones with Chi-square or Fisher's test. The best cut-off point was established by constructing receiver operating characteristic curves, then using that value as a dichotomous variable. RESULTS: 72 typical carcinoids (TC) and 30 atypical carcinoids (AC) were analyzed; 66% were female. Median age (TC 38 vs. AC 51, P = 0.001), Ki67 expression (TC 0.63 vs. AC 2, P = 0.003), tumor size (TC 2.5 vs. AC 2.6, P = 0.001), the percentage relapse (TC 3.4% vs. AC 23%, P = 0.006), and the number of deaths (TC 1 vs. AC 4, P = 0.042) were significantly higher in the AC subgroup. The best cut-off point for Ki 67 was 0.755 (area under the curve AUC 0.564, 95% confidence interval 0.270–0.857), with no significant differences found in the disease-free and overall survival curves when considering values < or ≥ at the established cut-off point. The best cut-off point of the Ki-67 when exclusively analyzing AC was 1.18. When using this value as a predictive variable, a marginal statistical association was observed between Ki-67 expression, mortality (P = 0.077), and the frequency of relapses (P = 0.054). CONCLUSIONS: Histological type is the best predictor of prognosis in the carcinoid tumor group. In the AC subgroup, the marginal association between mortality, frequency of relapses and Ki values 67 ≥ 1.18 has clinical relevance future analyses are required to determine the real predictive value of this variable.