Long-term cabergoline use does not predict degree of prolactinoma fibrosis nor significantly impact surgical outcomes

Duration and cumulative dose of presurgical CAB use do not correlate with quantitative measures of tumor fibrosis and do not reliably predict the degree of fibrosis at surgery or the likelihood of surgical remission.

Authors

Institutions

Publication Details

Journal
Pituitary
Published
2026-01-12
DOI
https://doi.org/10.1007/s11102-025-01628-8
Citations
1
Primary Topic
Pituitary Gland Disorders and Treatments
Type
article
Field-Weighted Citation Impact
30.73
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Long-term cabergoline use does not predict degree of prolactinoma fibrosis nor significantly impact surgical outcomes

Odelia Cooper, Ning-Ai Liu, Daniel Richard Gomez, Adam N. Mamelak et al.
1 citations
Pituitary
Pituitary Gland Disorders and Treatments
30.73
article

Long-term cabergoline use does not predict degree of prolactinoma fibrosis nor significantly impact surgical outcomes

Odelia Cooper, Ning-Ai Liu, Daniel Richard Gomez, Adam N. Mamelak, Artak Labadzhyan, R.A. Fox, Anat Ben Shlomo, Vivien Bonert, Yujie Cui, Yaakov Rosenberg
article en
1 citations

Abstract

Duration and cumulative dose of presurgical CAB use do not correlate with quantitative measures of tumor fibrosis and do not reliably predict the degree of fibrosis at surgery or the likelihood of surgical remission.

PituitaryVol. 29(1)
Cedars-Sinai Medical Center (US)
Good health and well-being
Openalex Percentile: Top 2%
Pituitary Gland Disorders and Treatments
30.73
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.