BACKGROUND: Grades II and III gliomas have unpredictable rates of progression, making management decisions difficult. Currently, several clinical and radiological characteristics are utilized to predict progression and survival but collectively are suboptimal. METHODS: In this study, we analyzed a set of 108 nonenhancing hemispheric grade II-III gliomas. Demographic variables, including patient age, tumor diameter, extent of resection, and performance status, were combined with molecular data (IDH mutation status [mIDH], 1p/19q codeletion, PTEN deletion, and EGFR amplification). A complete dataset for all variables was compiled for 70 of the 108 patients. Both univariable and multivariable analyses were performed to determine whether the molecular data singly or in combination offer advantages over tumor type and grade for prediction of overall survival (OS) and/or progression-free rate (PFR). RESULTS: Patient age, clinical variables (tumor diameter, extent of resection, performance status), and pathology (tumor type and grade) were not predictive of OS or PFR. IDH mutation status alone was predictive of longer OS and PFR for the entire group of tumors; 1p/19q deletion alone was predictive of OS but not PFR. In the multivariable analysis, none of the clinical or demographic factors were predictive of OS or PFR. IDH mutation status, 1p/19q codeletion, and PTEN deletion were predictive of OS (P = .003, P = .005, P = .02, respectively). Both mIDH (P < .001) and the interaction term of 1p/19q and PTEN (P < .001) were found to be predictive of PFR. CONCLUSIONS: We conclude that the combination of mIDH, 1p/19q codeletion, and PTEN deletion may be particularly effective in discriminating good prognosis from poor prognosis hemispheric gliomas. We propose that such a scheme merits testing on larger prospective cohorts. Should our findings be confirmed, routine clinical analysis of hemispheric gliomas for mIDH, 1p/19q codeletion, and PTEN deletion would be justified.
BACKGROUND: Grades II and III gliomas have unpredictable rates of progression, making management decisions difficult. Currently, several clinical and radiological characteristics are utilized to predict progression and survival but collectively are suboptimal. METHODS: In this study, we analyzed a set of 108 nonenhancing hemispheric grade II-III gliomas. Demographic variables, including patient age, tumor diameter, extent of resection, and performance status, were combined with molecular data (IDH mutation status [mIDH], 1p/19q codeletion, PTEN deletion, and EGFR amplification). A complete dataset for all variables was compiled for 70 of the 108 patients. Both univariable and multivariable analyses were performed to determine whether the molecular data singly or in combination offer advantages over tumor type and grade for prediction of overall survival (OS) and/or progression-free rate (PFR). RESULTS:Patient age, clinical variables (tumor diameter, extent of resection, performance status), and pathology (tumor type and grade) were not predictive of OS or PFR. IDH mutation status alone was predictive of longer OS and PFR for the entire group of tumors; 1p/19q deletion alone was predictive of OS but not PFR. In the multivariable analysis, none of the clinical or demographic factors were predictive of OS or PFR. IDH mutation status, 1p/19q codeletion, and PTEN deletion were predictive of OS (P = .003, P = .005, P = .02, respectively). Both mIDH (P < .001) and the interaction term of 1p/19q and PTEN (P < .001) were found to be predictive of PFR. CONCLUSIONS: We conclude that the combination of mIDH, 1p/19q codeletion, and PTEN deletion may be particularly effective in discriminating good prognosis from poor prognosis hemispheric gliomas. We propose that such a scheme merits testing on larger prospective cohorts. Should our findings be confirmed, routine clinical analysis of hemispheric gliomas for mIDH, 1p/19q codeletion, and PTEN deletion would be justified.
Authors: Arie Perry; C Ryan Miller; Meena Gujrati; Bernd W Scheithauer; Sandro Casavilca Zambrano; Sarah C Jost; Ravi Raghavan; Jiang Qian; Elizabeth J Cochran; Jason T Huse; Eric C Holland; Peter C Burger; Marc K Rosenblum Journal: Brain Pathol Date: 2008-04-29 Impact factor: 6.508
Authors: Edward F Chang; Aaron Clark; Randy L Jensen; Mark Bernstein; Abhijit Guha; Giorgio Carrabba; Debabrata Mukhopadhyay; Won Kim; Linda M Liau; Susan M Chang; Justin S Smith; Mitchel S Berger; Michael W McDermott Journal: J Neurosurg Date: 2009-08 Impact factor: 5.115
Authors: J G Cairncross; K Ueki; M C Zlatescu; D K Lisle; D M Finkelstein; R R Hammond; J S Silver; P C Stark; D R Macdonald; Y Ino; D A Ramsay; D N Louis Journal: J Natl Cancer Inst Date: 1998-10-07 Impact factor: 13.506
Authors: D Williams Parsons; Siân Jones; Xiaosong Zhang; Jimmy Cheng-Ho Lin; Rebecca J Leary; Philipp Angenendt; Parminder Mankoo; Hannah Carter; I-Mei Siu; Gary L Gallia; Alessandro Olivi; Roger McLendon; B Ahmed Rasheed; Stephen Keir; Tatiana Nikolskaya; Yuri Nikolsky; Dana A Busam; Hanna Tekleab; Luis A Diaz; James Hartigan; Doug R Smith; Robert L Strausberg; Suely Kazue Nagahashi Marie; Sueli Mieko Oba Shinjo; Hai Yan; Gregory J Riggins; Darell D Bigner; Rachel Karchin; Nick Papadopoulos; Giovanni Parmigiani; Bert Vogelstein; Victor E Velculescu; Kenneth W Kinzler Journal: Science Date: 2008-09-04 Impact factor: 47.728
Authors: Daniel Gorovets; Kasthuri Kannan; Ronglai Shen; Edward R Kastenhuber; Nasrin Islamdoust; Carl Campos; Elena Pentsova; Adriana Heguy; Suresh C Jhanwar; Ingo K Mellinghoff; Timothy A Chan; Jason T Huse Journal: Clin Cancer Res Date: 2012-03-13 Impact factor: 13.801
Authors: Koichi Ichimura; Danita M Pearson; Sylvia Kocialkowski; L Magnus Bäcklund; Raymond Chan; David T W Jones; V Peter Collins Journal: Neuro Oncol Date: 2009-05-12 Impact factor: 12.300
Authors: Hai Yan; D Williams Parsons; Genglin Jin; Roger McLendon; B Ahmed Rasheed; Weishi Yuan; Ivan Kos; Ines Batinic-Haberle; Siân Jones; Gregory J Riggins; Henry Friedman; Allan Friedman; David Reardon; James Herndon; Kenneth W Kinzler; Victor E Velculescu; Bert Vogelstein; Darell D Bigner Journal: N Engl J Med Date: 2009-02-19 Impact factor: 176.079
Authors: David N Louis; Hiroko Ohgaki; Otmar D Wiestler; Webster K Cavenee; Peter C Burger; Anne Jouvet; Bernd W Scheithauer; Paul Kleihues Journal: Acta Neuropathol Date: 2007-07-06 Impact factor: 17.088
Authors: Victor A Levin; Peter J Tonge; James M Gallo; Marc R Birtwistle; Arvin C Dar; Antonio Iavarone; Patrick J Paddison; Timothy P Heffron; William F Elmquist; Jean E Lachowicz; Ted W Johnson; Forest M White; Joohee Sul; Quentin R Smith; Wang Shen; Jann N Sarkaria; Ramakrishna Samala; Patrick Y Wen; Donald A Berry; Russell C Petter Journal: Neuro Oncol Date: 2015-11 Impact factor: 12.300