PURPOSE: The reasons why a specific subset of glioblastoma (GBM) patients survive longer than others is still unclear. This study analyzed a cohort of long-term and very-long-term GBM survivors to determine which genetic alterations or patient's characteristics influence survival time. METHODS: We retrospectively reviewed a cohort of GBM patients treated at our institution over the last 20 years, stratifying patients in three groups: those with a survival time ≥ 36 months and < 120 months (LTS), ≥120 months (VLTS), and < 36 months, respectively. Clinical (age, sex, focality, resection degree, Karnofsky performance status), and immunohistochemical and molecular data (Ki-67 expression and multiple genes alterations) were collected. We then utilized principal component analysis, logistic regression, and Cox proportional hazard models to identify those variables associated with survival. RESULTS: Younger age at presentation (HR = 0.36, 95% CI 0.21-0.67, p = .001), and MGMT promoter [(MGMTp), methylated, HR = 0.57, CI 0.34-0.96, p = .034) were associated with higher odds of VLTS survival. The multivariate analysis showed how the combination of younger age (< 50 years), Ki-67 < 10%, and the coexistence of TERTp not mutated, MGMTp methylated, and IDH1/2 mutated in the same patient are also associated with higher odds of survival (HR = 0.10, CI 0.01-0.74, p = .025). CONCLUSIONS: We confirmed younger age at presentation and MGMTp methylation as the only independent factors associated with VLTS. The exceptional survival of our VLTS patients is probably associated with different, still understudied, gene mutations, or with the coexistence of multiple factors.

Over ten years overall survival in glioblastoma: A different disease?

Marton E;Siddi F;CURZI, CHRISTIAN;Scarpa B;D' Avella D;Longatti P;Feletti A.
2019

Abstract

PURPOSE: The reasons why a specific subset of glioblastoma (GBM) patients survive longer than others is still unclear. This study analyzed a cohort of long-term and very-long-term GBM survivors to determine which genetic alterations or patient's characteristics influence survival time. METHODS: We retrospectively reviewed a cohort of GBM patients treated at our institution over the last 20 years, stratifying patients in three groups: those with a survival time ≥ 36 months and < 120 months (LTS), ≥120 months (VLTS), and < 36 months, respectively. Clinical (age, sex, focality, resection degree, Karnofsky performance status), and immunohistochemical and molecular data (Ki-67 expression and multiple genes alterations) were collected. We then utilized principal component analysis, logistic regression, and Cox proportional hazard models to identify those variables associated with survival. RESULTS: Younger age at presentation (HR = 0.36, 95% CI 0.21-0.67, p = .001), and MGMT promoter [(MGMTp), methylated, HR = 0.57, CI 0.34-0.96, p = .034) were associated with higher odds of VLTS survival. The multivariate analysis showed how the combination of younger age (< 50 years), Ki-67 < 10%, and the coexistence of TERTp not mutated, MGMTp methylated, and IDH1/2 mutated in the same patient are also associated with higher odds of survival (HR = 0.10, CI 0.01-0.74, p = .025). CONCLUSIONS: We confirmed younger age at presentation and MGMTp methylation as the only independent factors associated with VLTS. The exceptional survival of our VLTS patients is probably associated with different, still understudied, gene mutations, or with the coexistence of multiple factors.
File in questo prodotto:
File Dimensione Formato  
Over ten years overall survival.pdf

non disponibili

Tipologia: Published (publisher's version)
Licenza: Accesso privato - non pubblico
Dimensione 769.12 kB
Formato Adobe PDF
769.12 kB Adobe PDF Visualizza/Apri   Richiedi una copia
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3315409
Citazioni
  • ???jsp.display-item.citation.pmc??? 6
  • Scopus 22
  • ???jsp.display-item.citation.isi??? 18
  • OpenAlex ND
social impact