Header

UZH-Logo

Maintenance Infos

DNA methylation profiling to predict recurrence risk in meningioma: development and validation of a nomogram to optimize clinical management


Nassiri, Farshad; Mamatjan, Yasin; Suppiah, Suganth; Weller, Michael; et al (2019). DNA methylation profiling to predict recurrence risk in meningioma: development and validation of a nomogram to optimize clinical management. Neuro-Oncology, 21(7):901-910.

Abstract

BACKGROUND
Variability in standard-of-care classifications precludes accurate predictions of early tumor recurrence for individual patients with meningioma, limiting the appropriate selection of patients who would benefit from adjuvant radiotherapy to delay recurrence. We aimed to develop an individualized prediction model of early recurrence risk combining clinical and molecular factors in meningioma.
METHODS
DNA methylation profiles of clinically annotated tumor samples across multiple institutions were used to develop a methylome model of 5-year recurrence-free survival (RFS). Subsequently, a 5-year meningioma recurrence score was generated using a nomogram that integrated the methylome model with established prognostic clinical factors. Performance of both models was evaluated and compared with standard-of-care models using multiple independent cohorts.
RESULTS
The methylome-based predictor of 5-year RFS performed favorably compared with a grade-based predictor when tested using the 3 validation cohorts (ΔAUC = 0.10, 95% CI: 0.03-0.018) and was independently associated with RFS after adjusting for histopathologic grade, extent of resection, and burden of copy number alterations (hazard ratio 3.6, 95% CI: 1.8-7.2, P < 0.001). A nomogram combining the methylome predictor with clinical factors demonstrated greater discrimination than a nomogram using clinical factors alone in 2 independent validation cohorts (ΔAUC = 0.25, 95% CI: 0.22-0.27) and resulted in 2 groups with distinct recurrence patterns (hazard ratio 7.7, 95% CI: 5.3-11.1, P < 0.001) with clinical implications.
CONCLUSIONS
The models developed and validated in this study provide important prognostic information not captured by previously established clinical and molecular factors which could be used to individualize decisions regarding postoperative therapeutic interventions, in particular whether to treat patients with adjuvant radiotherapy versus observation alone.

Abstract

BACKGROUND
Variability in standard-of-care classifications precludes accurate predictions of early tumor recurrence for individual patients with meningioma, limiting the appropriate selection of patients who would benefit from adjuvant radiotherapy to delay recurrence. We aimed to develop an individualized prediction model of early recurrence risk combining clinical and molecular factors in meningioma.
METHODS
DNA methylation profiles of clinically annotated tumor samples across multiple institutions were used to develop a methylome model of 5-year recurrence-free survival (RFS). Subsequently, a 5-year meningioma recurrence score was generated using a nomogram that integrated the methylome model with established prognostic clinical factors. Performance of both models was evaluated and compared with standard-of-care models using multiple independent cohorts.
RESULTS
The methylome-based predictor of 5-year RFS performed favorably compared with a grade-based predictor when tested using the 3 validation cohorts (ΔAUC = 0.10, 95% CI: 0.03-0.018) and was independently associated with RFS after adjusting for histopathologic grade, extent of resection, and burden of copy number alterations (hazard ratio 3.6, 95% CI: 1.8-7.2, P < 0.001). A nomogram combining the methylome predictor with clinical factors demonstrated greater discrimination than a nomogram using clinical factors alone in 2 independent validation cohorts (ΔAUC = 0.25, 95% CI: 0.22-0.27) and resulted in 2 groups with distinct recurrence patterns (hazard ratio 7.7, 95% CI: 5.3-11.1, P < 0.001) with clinical implications.
CONCLUSIONS
The models developed and validated in this study provide important prognostic information not captured by previously established clinical and molecular factors which could be used to individualize decisions regarding postoperative therapeutic interventions, in particular whether to treat patients with adjuvant radiotherapy versus observation alone.

Statistics

Citations

Dimensions.ai Metrics
38 citations in Web of Science®
39 citations in Scopus®
Google Scholar™

Altmetrics

Downloads

11 downloads since deposited on 08 Jan 2020
8 downloads since 12 months
Detailed statistics

Additional indexing

Contributors:International Consortium on Meningiomas
Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Clinic for Neurology
Dewey Decimal Classification:610 Medicine & health
Scopus Subject Areas:Health Sciences > Oncology
Health Sciences > Neurology (clinical)
Life Sciences > Cancer Research
Language:English
Date:11 July 2019
Deposited On:08 Jan 2020 09:45
Last Modified:29 Jul 2020 11:37
Publisher:Oxford University Press
ISSN:1522-8517
OA Status:Hybrid
Free access at:PubMed ID. An embargo period may apply.
Publisher DOI:https://doi.org/10.1093/neuonc/noz061
PubMed ID:31158293

Download

Hybrid Open Access

Download PDF  'DNA methylation profiling to predict recurrence risk in meningioma: development and validation of a nomogram to optimize clinical management'.
Preview
Content: Accepted Version
Filetype: PDF
Size: 1MB
View at publisher