Farshad Nassiri 1 , 2 , Yasin Mamatjan 2 , Suganth Suppiah 1 , 2 , Jetan H Badhiwala 2 , Sheila Mansouri 2 , Shirin Karimi 2 , Olli Saarela 3 , Laila Poisson 4 , Irina Gepfner-Tuma 5 , Jens Schittenhelm 6 , Ho-Keung Ng 7 , Houtan Noushmehr 8 , Patrick Harter 9 , Peter Baumgarten 10 , Michael Weller 11 , Matthias Preusser 12 , Christel Herold-Mende 13 , Marcos Tatagiba 14 , Ghazaleh Tabatabai 5 , Felix Sahm 15 , Andreas von Deimling 15 , Kenneth Aldape , Karolyn Au , Jill Barnhartz-Sloan , Wenya Linda Bi , Priscilla K Brastianos , Nicholas Butowski , Carlos Carlotti , Michael D Cusimano , Francesco DiMeco , Katharine Drummond , Ian F Dunn , Evanthia Galanis , Caterina Giannini , Roland Goldbrunner , Brent Griffith , Rintaro Hashizume , C Oliver Hanemann , Christel Herold-Mende , Craig Horbinski , Raymond Y Huang , David James , Michael D Jenkinson , Christine Jungk , Timothy J Kaufman , Boris Krischek , Daniel Lachance , Christian Lafougère , Ian Lee , Jeff C Liu , Yasin Mamatjan , Tathiane M Malta , Christian Mawrin , Michael McDermott , David Munoz , Farshad Nassiri , Houtan Noushmehr , Ho-Keung Ng , Arie Perry , Farhad Pirouzmand , Laila M Poisson , Bianca Pollo , David Raleigh , Felix Sahm , Andrea Saladino , Thomas Santarius , Christian Schichor , David Schultz , Nils O Schmidt , Warren Selman , Andrew Sloan , Julian Spears , James Snyder , Suganth Suppiah , Ghazaleh Tabatabai , Marcos Tatagiba , Daniela Tirapelli , Joerg C Tonn , Derek Tsang , Michael A Vogelbaum , Andreas von Deimling , Patrick Y Wen , Tobias Walbert , Manfred Westphal , Adriana M Workewych , Gelareh Zadeh , Gelareh Zadeh 1 , 2 , 16 , Kenneth D Aldape 1 , 2 , 17 , International Consortium on Meningiomas
June 03 2019
June 03 2019
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.
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.
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.
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.