Dataset Information

Integration of Radiomic and Multi-omic Analyses Predicts Survival of Newly Diagnosed IDH1 Wild-Type Glioblastoma.

ABSTRACT: Predictors of patient outcome derived from gene methylation, mutation, or expression are severely limited in IDH1 wild-type glioblastoma (GBM). Radiomics offers an alternative insight into tumor characteristics which can provide complementary information for predictive models. The study aimed to evaluate whether predictive models which integrate radiomic, gene, and clinical (multi-omic) features together offer an increased capacity to predict patient outcome. A dataset comprising 200 IDH1 wild-type GBM patients, derived from The Cancer Imaging Archive (TCIA) (n = 71) and the McGill University Health Centre (n = 129), was used in this study. Radiomic features (n = 45) were extracted from tumor volumes then correlated to biological variables and clinical outcomes. By performing 10-fold cross-validation (n = 200) and utilizing independent training/testing datasets (n = 100/100), an integrative model was derived from multi-omic features and evaluated for predictive strength. Integrative models using a limited panel of radiomic (sum of squares variance, large zone/low gray emphasis, autocorrelation), clinical (therapy type, age), genetic (CIC, PIK3R1, FUBP1) and protein expression (p53, vimentin) yielded a maximal AUC of 78.24% (p = 2.9 × 10^-5). We posit that multi-omic models using the limited set of 'omic' features outlined above can improve capacity to predict the outcome for IDH1 wild-type GBM patients.

SUBMITTER: Chaddad A

PROVIDER: S-EPMC6721570 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Integration of Radiomic and Multi-omic Analyses Predicts Survival of Newly Diagnosed IDH1 Wild-Type Glioblastoma.

Chaddad Ahmad A Daniel Paul P Sabri Siham S Desrosiers Christian C Abdulkarim Bassam B

Cancers 20190810 8

Predictors of patient outcome derived from gene methylation, mutation, or expression are severely limited in IDH1 wild-type glioblastoma (GBM). Radiomics offers an alternative insight into tumor characteristics which can provide complementary information for predictive models. The study aimed to evaluate whether predictive models which integrate radiomic, gene, and clinical (multi-omic) features together offer an increased capacity to predict patient outcome. A dataset comprising 200 IDH1 wild-t ...[more]

PMID: 31405148

Similar Datasets

Project description:BackgroundThe impact of prolonging temozolomide (TMZ) maintenance beyond six cycles in newly diagnosed glioblastoma (GBM) remains a topic of discussion. We investigated the effects of prolonged TMZ maintenance on progression-free survival (PFS) and overall survival (OS).Patients and methodsIn this retrospective single-center cohort study, we included patients with GBM who were treated with radiation therapy with concomitant and adjuvant TMZ. For analysis, patients were considered who either completed six TMZ maintenance cycles (group B), continued with TMZ therapy beyond six cycles (group C), or stopped TMZ maintenance therapy within the first six cycles (group A). Patients with progression during the first six TMZ maintenance cycles were excluded.ResultsClinical data from 107 patients were included for Kaplan-Meier analyses and 102 for Cox regressions. Median PFS times were 8.1 months (95% confidence interval [CI] 6.1-12.4) in group A, 13.7 months (95% CI 10.6-17.5) in group B, and 20.9 months (95% CI 15.2-43.5) in group C. At first progression, response rates of TMZ/lomustine rechallenge were 47% in group B and 13% in group C. Median OS times were 12.7 months (95% CI 10.3-16.8) in group A, 25.2 months (95% CI 17.7-55.5) in group B, and 28.6 months (95% CI 24.4-open) in group C. Nevertheless, multivariate Cox regression for patients in group C compared with group B that accounted for imbalances of other risk factors showed no different relative risk (RR) for OS (RR 0.77, p = .46).ConclusionOur data do not support a general extension of TMZ maintenance therapy beyond six cycles. The Oncologist 2017;22:570-575 IMPLICATIONS FOR PRACTICE: Radiation therapy with concomitant and adjuvant temozolomide (TMZ) maintenance therapy is still the standard of care in patients below the age of 65 years in newly diagnosed glioblastoma. However, in clinical practice, many centers continue TMZ maintenance therapy beyond six cycles. The impact of this continuation is controversial and has not yet been addressed in prospective randomized clinical trials. We compared the effect of more than six cycles of TMZ in comparison with exactly six cycles on overall survival (OS) and progression-free survival (PFS) by multivariate analysis and found a benefit in PFS but not OS. Thus, our data do not suggest prolonging TMZ maintenance therapy beyond six cycles, which should be considered in neurooncological practice.

Dataset Information

Integration of Radiomic and Multi-omic Analyses Predicts Survival of Newly Diagnosed IDH1 Wild-Type Glioblastoma.

Publications

Integration of Radiomic and Multi-omic Analyses Predicts Survival of Newly Diagnosed IDH1 Wild-Type Glioblastoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets