Predictors of Durable Remission After Successful Surgery for Cushing Disease: Results From the Multicenter RAPID Registry.


Journal

Neurosurgery
ISSN: 1524-4040
Titre abrégé: Neurosurgery
Pays: United States
ID NLM: 7802914

Informations de publication

Date de publication:
21 Jun 2024
Historique:
received: 31 01 2024
accepted: 14 04 2024
medline: 21 6 2024
pubmed: 21 6 2024
entrez: 21 6 2024
Statut: aheadofprint

Résumé

Cushing disease (CD) affects mortality and quality of life along with limited long-term remission, underscoring the need to better identify recurrence risk. The identification of surgical or imaging predictors for CD remission after transsphenoidal surgery has yielded some inconsistent results and has been limited by single-center, single-surgeon, or meta-analyses studies. We sought to evaluate the multicenter Registry of Adenomas of the Pituitary and Related Disorders (RAPID) database of academic US pituitary centers to assess whether robust nonhormonal recurrence predictors could be elucidated. Patients with treated CD from 2011 to 2023 were included. The perioperative and long-term characteristics of CD patients with and without recurrence were assessed using univariable and multivariable analyses. Of 383 patients with CD from 26 surgeons achieving postoperative remission, 288 (75.2%) maintained remission at last follow-up while 95 (24.8%) showed recurrence (median time to recurrence 9.99 ± 1.34 years). Patients with recurrence required longer postoperative hospital stays (5 ± 3 vs 4 ± 2 days, P = .002), had larger average tumor volumes (1.76 ± 2.53 cm3 vs 0.49 ± 1.17 cm3, P = .0001), and more often previously failed prior treatment (31.1% vs 14.9%, P = .001) mostly being prior surgery. Multivariable hazard prediction models for tumor recurrence found younger age (odds ratio [OR] = 0.95, P = .002) and Knosp grade of 0 (OR = 0.09, reference Knosp grade 4, P = .03) to be protective against recurrence. Comparison of Knosp grade 0 to 2 vs 3 to 4 showed that lower grades had reduced risk of recurrence (OR = 0.27, P = .04). Other factors such as length of stay, surgeon experience, prior tumor treatment, and Knosp grades 1, 2, or 3 failed to reach levels of statistical significance in multivariable analysis. This multicenter study centers suggests that the strongest predictors of recurrence include tumor size/invasion and age. This insight can help with patient counseling and prognostication. Long-term follow-up is necessary for patients, and early treatment of small tumors may improve outcomes.

Sections du résumé

BACKGROUND AND OBJECTIVE OBJECTIVE
Cushing disease (CD) affects mortality and quality of life along with limited long-term remission, underscoring the need to better identify recurrence risk. The identification of surgical or imaging predictors for CD remission after transsphenoidal surgery has yielded some inconsistent results and has been limited by single-center, single-surgeon, or meta-analyses studies. We sought to evaluate the multicenter Registry of Adenomas of the Pituitary and Related Disorders (RAPID) database of academic US pituitary centers to assess whether robust nonhormonal recurrence predictors could be elucidated.
METHODS METHODS
Patients with treated CD from 2011 to 2023 were included. The perioperative and long-term characteristics of CD patients with and without recurrence were assessed using univariable and multivariable analyses.
RESULTS RESULTS
Of 383 patients with CD from 26 surgeons achieving postoperative remission, 288 (75.2%) maintained remission at last follow-up while 95 (24.8%) showed recurrence (median time to recurrence 9.99 ± 1.34 years). Patients with recurrence required longer postoperative hospital stays (5 ± 3 vs 4 ± 2 days, P = .002), had larger average tumor volumes (1.76 ± 2.53 cm3 vs 0.49 ± 1.17 cm3, P = .0001), and more often previously failed prior treatment (31.1% vs 14.9%, P = .001) mostly being prior surgery. Multivariable hazard prediction models for tumor recurrence found younger age (odds ratio [OR] = 0.95, P = .002) and Knosp grade of 0 (OR = 0.09, reference Knosp grade 4, P = .03) to be protective against recurrence. Comparison of Knosp grade 0 to 2 vs 3 to 4 showed that lower grades had reduced risk of recurrence (OR = 0.27, P = .04). Other factors such as length of stay, surgeon experience, prior tumor treatment, and Knosp grades 1, 2, or 3 failed to reach levels of statistical significance in multivariable analysis.
CONCLUSION CONCLUSIONS
This multicenter study centers suggests that the strongest predictors of recurrence include tumor size/invasion and age. This insight can help with patient counseling and prognostication. Long-term follow-up is necessary for patients, and early treatment of small tumors may improve outcomes.

Identifiants

pubmed: 38905223
doi: 10.1227/neu.0000000000003042
pii: 00006123-990000000-01223
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Barrow Neurological Foundation

Informations de copyright

Copyright © Congress of Neurological Surgeons 2024. All rights reserved.

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Auteurs

Matthew C Findlay (MC)

Department of Neurosurgery, Clinical Neurosciences Center, University of Utah, Salt Lake City, Utah, USA.
School of Medicine, University of Utah, Salt Lake City, Utah, USA.

Sam Tenhoeve (S)

Department of Neurosurgery, Clinical Neurosciences Center, University of Utah, Salt Lake City, Utah, USA.
School of Medicine, University of Utah, Salt Lake City, Utah, USA.

Jeremiah Alt (J)

Department of Otolaryngology-Head and Neck Surgery, University of Utah, Salt Lake City, Utah, USA.

Robert C Rennert (RC)

Department of Neurosurgery, Clinical Neurosciences Center, University of Utah, Salt Lake City, Utah, USA.

William T Couldwell (WT)

Department of Neurosurgery, Clinical Neurosciences Center, University of Utah, Salt Lake City, Utah, USA.

James Evans (J)

Department of Neurosurgery, Thomas Jefferson University, Philadelphia, Pennsylvania, USA.

Sarah Collopy (S)

Department of Neurosurgery, Thomas Jefferson University, Philadelphia, Pennsylvania, USA.

Won Kim (W)

Department of Neurosurgery, University of California Los Angeles, Los Angeles, California, USA.

William Delery (W)

Department of Neurosurgery, University of California Los Angeles, Los Angeles, California, USA.

Donato Pacione (D)

Department of Neurosurgery, New York University, Lagone Medical Center, New York, New York, USA.

Albert Kim (A)

Department of Neurosurgery, Washington University School of Medicine, St. Louis, Missouri, USA.

Julie M Silverstein (JM)

Department of Neurosurgery, Washington University School of Medicine, St. Louis, Missouri, USA.
Division of Endocrinology, Metabolism, & Lipid Research, Washington University School of Medicine, St. Louis, Missouri, USA.

Michael R Chicoine (MR)

Department of Neurosurgery, University of Missouri, Columbia, Missouri, USA.

Paul Gardner (P)

Department of Neurosurgery, University of Pittsburgh Medical Center, Pittsburg, Pennsylvania, USA.

Lauren Rotman (L)

Department of Neurosurgery, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.

Kevin C J Yuen (KCJ)

Department of Neurosurgery, Barrow Neurological Institute, Phoenix, Arizona, USA.

Garni Barkhoudarian (G)

Department of Neurosurgery, Providence Medical Center, Los Angeles, California, USA.

Juan Fernandez-Miranda (J)

Department of Neurosurgery, Stanford University, Palo Alto, California, USA.

Carolina Benjamin (C)

Department of Neurosurgery, University of Miami Miller School of Medicine, Miami, Florida, USA.

Varun R Kshettry (VR)

Department of Neurosurgery, Cleveland Clinic Foundation, Cleveland, Ohio, USA.

Gabriel Zada (G)

Department of Neurosurgery, University of Southern California, Los Angeles, California, USA.

Jamie Van Gompel (J)

Department of Neurosurgery, Mayo Clinic, Rochester, Minnesota, USA.

Michael H S Catalino (MHS)

Department of Neurosurgery, University of Virginia, Charlottesville, Virginia, USA.

Andrew S Little (AS)

Department of Neurosurgery, Barrow Neurological Institute, Phoenix, Arizona, USA.

Michael Karsy (M)

Global Neurosciences Institute, Philadelphia, Pennsylvania, USA.
Department of Neurosurgery, Drexel University College of Medicine, Philadelphia, Pennsylvania, USA.

Classifications MeSH