Evidence map›Paper›PMID 40353934›Full record

ArticleJournal of neuro-oncology2025

Prognostic value of MIB-1 index in meningioma: a retrospective cohort study to establish an optimal cutoff for recurrence and survival.

Ishav Y Shukla, Ali Ebada, Nicholas Bever, Jeffrey I Traylor, Bingchun Wan, Darsh Shah, Samuel L Barnett, Matthew Z Sun

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Article in Journal of neuro-oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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4citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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4 citing papers in PubMed.

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5 · Who and what money

Authors and funding

8 authors.

Ishav Y ShuklaDepartment of Neurological Surgery, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Ali EbadaDepartment of Neurological Surgery, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Nicholas BeverDepartment of Neurological Surgery, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Jeffrey I TraylorDepartment of Neurological Surgery, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Bingchun WanDepartment of Neurological Surgery, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Darsh ShahDepartment of Neurological Surgery, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Samuel L BarnettDepartment of Neurological Surgery, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Matthew Z SunDepartment of Neurological Surgery, University of Texas Southwestern Medical Center, Dallas, TX, USA. Matthew.Sun@UTSouthwestern.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposePredicting long-term outcomes after meningioma resection remains challenging. Ki-67/MIB-1 correlates with recurrence, yet its optimal cutoff is undefined. This study aims to establish a threshold that enhances risk stratification, improves recurrence prediction, and informs postoperative surveillance and adjuvant treatment strategies.

methodsThis is retrospective study of patients who underwent meningioma resection. Receiver operating characteristic (ROC) analysis determined the optimal MIB-1 cutoff for predicting recurrence and survival, providing area under the curve (AUC). This cutoff was then applied in Kaplan-Meier survival analyses and multivariable Cox regressions, controlling for age, sex, tumor diameter, tumor location, extent of resection, and adjuvant radiotherapy.

resultsA total of 404 patients were included. Median age was 55.0 years (range: 16-85) and 72.3% were female. The cohort primarily consisted of WHO Grade 1 (69.6%) and Grade 2 (30.0%) meningiomas. An optimal MIB-1 index cutoff of 4.1% was identified using ROC analysis with the Youden index for predicting recurrence (AUC = 0.661, p < 0.001) and survival (AUC = 0.717, p < 0.001). 241 patients (59.7%) had a MIB-1 < 4.1%, and 163 (40.3%) had a MIB-1 ≥ 4.1%. Patients with MIB-1 ≥ 4.1% had a higher risk of recurrence (HR = 2.9, p = 0.009) and mortality (HR = 2.8, p = 0.036). Patients with MIB-1 ≥ 4.1% demonstrated shorter recurrence-free survival (RFS) (119.0 vs. 129.0 months, p < 0.001) and overall survival (OS) (163.0 vs. 229.0 months, p < 0.001).

conclusionWe identified an optimal and actionable MIB-1 index cutoff of 4.1% which independently predicted recurrence, mortality, and shorter RFS and OS for patients undergoing meningioma resection. As the first study to establish and validate this threshold, our findings highlight its potential as an adjunct prognostic tool to refine risk stratification and guide postoperative management.

Indexed as

Ki-67 AntigenMeningeal NeoplasmsMeningiomaNeoplasm Recurrence, LocalAdolescentAdultAgedAged, 80 and overBiomarkers, TumorFemaleFollow-Up StudiesHumansKaplan-Meier EstimateMaleMiddle AgedPrognosisBiomarkers, TumorKi-67 AntigenBiomarkerMeningiomaMIB-1PrognosisRecurrenceSurvival

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PMID40353934

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