Selection of neuroendocrine markers in diagnostic workup of neuroendocrine neoplasms: The real‐world data and machine learning model algorithms
The combination of synaptophysin, INSM1, and CD56 has the best performance in diagnostic workup of all NENs, although chromogranin may be selected for NETS. The random forests and neural network models support the common practice rule of requiring at least two out of three markers to be positive for optimal marker utilization.
Authors
- Adebowale Adeniran (ORCID: https://orcid.org/0000-0001-9820-632X)
- Guoping Cai (ORCID: https://orcid.org/0000-0002-8725-5940)
- Haiming Tang (ORCID: https://orcid.org/0000-0001-7058-349X)
- Nanfei Sun (ORCID: https://orcid.org/0000-0002-4010-1514)
- Minhua Wang (ORCID: https://orcid.org/0000-0002-2283-7050)
- Patricia V. Hernandez (ORCID: https://orcid.org/0000-0002-7340-3631)
- Haoran Xia
Institutions
- Georgia Institute of Technology (US)
- Washington University in St. Louis (US)
- Yale Cancer Center (US)
- Yale University (US)
- University of Houston - Clear Lake (US)
Publication Details
- Journal
- Cancer Cytopathology
- Published
- 2025-04-27
- DOI
- https://doi.org/10.1002/cncy.70018
- Primary Topic
- Neuroendocrine Tumor Research Advances
- Type
- article
- Field-Weighted Citation Impact
- 0.00