Machine learning–based model to predict long-term tumor control and additional interventions following pituitary surgery for Cushing’s disease
The ML algorithm could predict long-term postoperative endocrinological remission in CD with high accuracy, indicating that prognosis may vary not only with previously reported factors such as tumor size, Knosp grade, gross-total resection, and patient age but also with BMI. The decision tree flowchart could potentially stratify patients with CD before ETS, allowing for the selection of personalized treatment options and thereby assisting in determining treatment plans for these patients. This ML model may lead to a deeper understanding of the complex mechanisms of CD by uncovering patterns embedded within the data.
Authors
- Caroline Jane Davidge-Pitts (ORCID: https://orcid.org/0000-0002-9393-7745)
- Fredric B. Meyer (ORCID: https://orcid.org/0000-0002-4310-7962)
- Dana Erickson
- Sukwoo Hong (ORCID: https://orcid.org/0000-0002-3664-9245)
- Bruce E. Pollock (ORCID: https://orcid.org/0000-0002-6148-9079)
- Justine Herndon (ORCID: https://orcid.org/0000-0001-5665-0617)
- Ramin A. Morshed (ORCID: https://orcid.org/0000-0001-8464-6041)
- Abdul Karim Ghaith (ORCID: https://orcid.org/0000-0002-9600-609X)
- Irina Bancos (ORCID: https://orcid.org/0000-0001-9332-2524)
- Miguel Sáez-Alegre (ORCID: https://orcid.org/0000-0002-3903-2726)
- Antonio Bon Nieves
- Jamie J. Van Gompel (ORCID: https://orcid.org/0000-0001-8087-7870)
- Yuki Shinya (ORCID: https://orcid.org/0000-0003-0097-5804)
- Carlos Pinheiro‐Neto (ORCID: https://orcid.org/0000-0003-3921-4658)
- John L. D. Atkinson
- María Peris Celda
- Ryan Nguyen
Institutions
- Mayo Clinic (US)
- WinnMed (US)
- University of Tokyo Hospital (JP)
Publication Details
- Journal
- Journal of neurosurgery
- Published
- 2025-03-14
- DOI
- https://doi.org/10.3171/2024.10.jns241338
- Citations
- 2
- Primary Topic
- Pituitary Gland Disorders and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 2.59