Unmet Medical Needs in Metastatic Lung and Digestive Neuroendocrine Neoplasms.

Unmet medical needs are not infrequent in oncology, and these needs are usually of higher magnitude in rare cancers. The field of neuroendocrine neoplasms (NENs) has evolved rapidly during the last decade, and, currently, a new WHO classification is being implemented and several treatment options are available in the metastatic setting after the results of prospective phase III clinical trials. However, several questions are still unanswered, and decisions in our daily clinical practice should be made with limited evidence. In the 2016 meeting of the advisory board of the European Neuroendocrine Tumor Society (ENETS), the main unmet medical needs in the metastatic NENs setting were deeply discussed, and several proposals to try to solve them are presented in this article, including biomarkers, imaging, and therapy.

Competitive Testing of the WHO 2010 versus the WHO 2017 Grading of Pancreatic Neuroendocrine Neoplasms: Data from a Large International Cohort Study.

BACKGROUND: The World Health Organization (WHO) and the American Joint Cancer Committee (AJCC) modified the grading of pancreatic neuroendocrine neoplasms from a three-tier (WHO-AJCC 2010) to a four-tier system by introducing the novel category of NET G3 (WHO-AJCC 2017). OBJECTIVES: This study aims at validating the WHO-AJCC 2017 and identifying the most effective grading system. METHOD: A total of 2,102 patients were enrolled; entry criteria were: (i) patient underwent surgery; (ii) at least 2 years of follow-up; (iii) observation time up to 2015. Data from 34 variables were collected; grading was assessed and compared for efficacy by statistical means including Kaplan-Meier method, Cox regression analysis, Harrell's C statistics, and Royston's explained variation in univariable and multivariable analyses. RESULTS: In descriptive analysis, the two grading systems demonstrated statistically significant differences for the major category sex but not for age groups. In Cox regression analysis, both grading systems showed statistically significant differences between grades for OS and EFS; however, no statistically significant difference was observed between the two G3 classes of WHO-AJCC 2017. In multivariable analysis for the two models fitted to compare efficacy, the two grading systems performed equally well with substantially similar optimal discrimination and well-explained variation for both OS and EFS. The WHO-AJCC 2017 grading system retained statistically significant difference between the two G3 classes for OS but not for EFS. CONCLUSIONS: The WHO-AJCC 2017 grading system is at least equally performing as the WHO-AJCC 2010 but allows the successful identification of the most aggressive PanNET subgroup. Grading is confirmed as probably the most powerful tool for predicting patient survival.