Abstract Library

#4621 Clinical presentation and outcomes of sporadic neuroendocrine neoplasms in young adults: International multicentre analysis

Introduction: Most neuroendocrine neoplasms (NEN) are sporadic. Early disease onset has been increasingly observed in NEN.

Conference:

Presenting Author: Malczewska-Herman A

Authors: Malczewska-Herman A, Pavel M, Rinke A, Holmager P, Opalinska M,

Keywords: neuroendocrine neoplasm, sporadic, young adults, prognosis, survival,

#4155 [177Lu]Lu-DOTA-TATE in newly diagnosed patients with advanced grade 2 and grade 3, well-differentiated gastroenteropancreatic neuroendocrine tumors: Primary analysis of the phase 3 randomised NETTER-2 study

Introduction: There is no universally accepted first line (1L) therapy for higher grade, well-differentiated gastroenteropancreatic neuroendocrine tumors (GEP-NETs).

Conference:

Presenting Author: de Herder W

Authors: de Herder W, Halperin D, Myrehaug S, Herrmann K, Pavel M,

Keywords: [177Lu]Lu-DOTA-TATE, Lutathera, Gastroenteropancreatic Neuroendocrine Tumor, NETTER-2,

#3636 Texture analysis in the prediction of progression-free survival (PFS) in patients with progressive neuroendocrine tumors (NETs) treated with lanreotide autogel (LAN) in the prospective, open-label, non-comparative, phase 2 CLARINET FORTE trial

Introduction: Tumor texture analysis may provide new imaging biomarkers for PFS prediction in patients with NETs.

Conference:

Presenting Author:

Authors: Dromain C, Truong Thanh X, Grandoulier A, Pavel M,

Keywords: texture analysis, progression-free survival, neuroendocrine tumor,

#3234 Dissociated response as a new biomarker of treatment response in neuroendocrine tumors: Results from phase 3 of the RAISE project

Introduction: RAISE aimed to find a surrogate endpoint to early predict treatment efficacy in patients with neuroendocrine tumors (NET). Dissociated response is the inhomogeneous response of the different lesions of a patient. Its prognostic value remains unclear.

Conference: 18th Annual ENETS Concerence (2021)

Presenting Author: Dromain C

Authors: Dromain C, Pavel M, Ronot M, Schaefer N, Mandair D,

Keywords: neuroendocrine tumor, dissociated response, progression-free survival, prediction,

#3229 The use of deep learning models to predict progression-free survival in patients with neuroendocrine tumors: Results from phase 3 of the RAISE project

Introduction: Response Evaluation Criteria in Solid Tumors (RECIST) assesses treatment response via tumor progression in patients with neuroendocrine tumors (NET). RAISE combined deep learning models (DLM) with sum of the longest diameter (SLD) of liver lesions and chromogranin A (CgA) to find a surrogate endpoint for RECIST to early predict progression-free survival (PFS).

Conference: 18th Annual ENETS Concerence (2021)

Presenting Author: Pavel M

Authors: Pavel M, Dromain C, Ronot M, Schaefer N, Mandair D,

Keywords: neuroendocrine tumor, deep learning models, progression-free survival, prediction,