Work

Integrated insular phenotype (IIP) versus Berger–Sanai and Yasargil classifications: comparative prognostic value in surgery of insular gliomas

Year: 2025

Type: article

Abstract: Background Surgery of insular gliomas remains one of the most demanding areas in neuro-oncology. Traditional classifications (Berger–Sanai, Yasargil) have limited prognostic value. We evaluated the Integrated Insular Phenotype (IIP), an ordinal system reflecting tumor complexity and its associations with surgical outcomes. Methods We retrospectively analyzed 167 patients with histologically confirmed insular gliomas. For each case, tumor topography was classified according to Berger–Sanai, Yasargil, and IIP systems. Three binary outcomes were assessed: extent of resection (EOR), seizure control, and persistent neurological deficit at day 90. Logistic regression models were applied to evaluate associations, and performance was assessed using odds ratios (OR), AUC, AIC, and LR χ 2 . Results Increasing IIP complexity was associated with reduced likelihood of total/subtotal resection (OR = 3.83; p < 0.001), poorer seizure control (OR = 2.90; p < 0.001), and higher risk of persistent deficits (OR = 2.83; p = 0.004). IIP showed lower AIC and higher LR χ 2 values compared with Berger–Sanai and Yasargil, indicating superior prognostic performance. While Berger–Sanai yielded high point estimates, confidence intervals were wide, and Yasargil produced consistent but less discriminative results. Conclusions In this retrospective cohort, the Integrated Insular Phenotype (IIP) showed superior prognostic performance compared with the Berger–Sanai and Yasargil classifications. IIP more accurately reflected topographic complexity and may assist in balancing oncological radicality with functional safety. Further prospective multicenter validation is warranted.

Source: Acta Neurochirurgica

DOI: 10.1007/s00701-025-06744-9

Author: Valentyn Kliuchka

Institution: Romodanov Neurosurgery Institute of the National Academy of Medical Sciences of Ukraine

Language: English

Topic: Glioma Diagnosis and Treatment

Subfield: Genetics

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $3,990