Preliminary experience with a new institutional tumor board dedicated to patients with neuroendocrine neoplasms

Nikolaos A Trikalinos1,2, Chet Hammill3, Jingxia Liu4

  • 1Department of Medicine, Division of Oncology, Washington University Medical School Campus, 660 South Euclid Avenue, Box 8069, St. Louis, MO, 63110, USA. ntrikalinos@wustl.edu.

Abstract

Insights

Neuroendocrine Neoplasm (NEN) tumor boards heavily use imaging to guide treatment decisions. Factors like patient or disease presentation did not predict NEN tumor board outcomes.

Area of Science:

  • Oncology
  • Medical Imaging
  • Tumor Board Management

Background:

  • Neuroendocrine neoplasms (NENs) are rare tumors requiring specialized multidisciplinary care.
  • Tumor boards (TBs) are crucial for NEN management, integrating diverse expertise.
  • Understanding NEN tumor board (TB) decision-making is essential for optimizing patient care.

Purpose of the Study:

  • To analyze the decision patterns of neuroendocrine neoplasm tumor boards (NEN-TBs).
  • To identify factors influencing NEN-TB recommendations.
  • To evaluate the impact of imaging and virtual transition on NEN-TB outcomes.

Main Methods:

  • Retrospective review of 652 NEN-TB recommendations from July 2018 to December 2021.
  • Analysis of patient characteristics, tumor origin, grade, and imaging modalities (PET, CT).
  • Assessment of treatment changes, pathology amendments, and clinical trial identification.

Main Results:

  • Imaging review (PET, CT) was central to NEN-TB decisions (97.2%).
  • Significant treatment changes were recommended for 36.1% of patients.
  • No association found between patient/disease factors and TB outcomes.
  • Transition to virtual format during COVID-19 slightly reduced case discussion per session but did not alter outcomes.

Conclusions:

  • NEN-TBs significantly influence treatment for rare NENs, primarily through image review.
  • The virtual transition did not negatively impact NEN-TB decision-making.
  • No patient or disease characteristics predicted NEN-TB recommendations, highlighting the complexity of NEN management.

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