methods Patients with newly diagnosed, histologically confirmed glioblastoma were randomly assigned to receive radiotherapy alone (fractionated focal irradiation in daily fractions of 2 Gy given 5 days per week for 6 weeks, for a total of 60 Gy) or radiotherapy plus continuous daily temozolomide (75 mg per square meter of body-surface area per day, 7 days per week from the first to the last day of radiotherapy), followed by six cycles of adjuvant temozolomide (150 to 200 mg per square meter for 5 days during each 28-day cycle). The primary end point was overall survival. results A total of 573 patients from 85 centers underwent randomization. The median age was 56 years, and 84 percent of patients had undergone debulking surgery. At a median follow-up of 28 months, the median survival was 14.6 months with radiotherapy plus temozolomide and 12.1 months with radiotherapy alone. The unadjusted hazard ratio for death in the radiotherapy-plus-temozolomide group was 0.63 (95 percent confidence interval, 0.52 to 0.75; P<0.001 by the log-rank test). The two-year survival rate was 26.5 percent with radiotherapy plus temozolomide and 10.4 percent with radiotherapy alone. Concomitant treatment with radiotherapy plus temozolomide resulted in grade 3 or 4 hematologic toxic effects in 7 percent of patients.

/pdf/radiotherapy-plus-concomitant-and-adjuvant-temozolomide-for-421wvfhcfx.pdf

Radiotherapy plus Concomitant and Adjuvant Temozolomide for Glioblastoma

BACKGROUND: In 2004, a randomised phase III trial by the European Organisation for Research and Treatment of Cancer (EORTC) and National Cancer Institute of Canada Clinical Trials Group (NCIC) reported improved median and 2-year survival for patients with glioblastoma treated with concomitant and adjuvant temozolomide and radiotherapy. We report the final results with a median follow-up of more than 5 years. METHODS: Adult patients with newly diagnosed glioblastoma were randomly assigned to receive either standard radiotherapy or identical radiotherapy with concomitant temozolomide followed by up to six cycles of adjuvant temozolomide. The methylation status of the methyl-guanine methyl transferase gene, MGMT, was determined retrospectively from the tumour tissue of 206 patients. The primary endpoint was overall survival. Analyses were by intention to treat. This trial is registered with Clinicaltrials.gov, number NCT00006353. FINDINGS: Between Aug 17, 2000, and March 22, 2002, 573 patients were assigned to treatment. 278 (97%) of 286 patients in the radiotherapy alone group and 254 (89%) of 287 in the combined-treatment group died during 5 years of follow-up. Overall survival was 27.2% (95% CI 22.2-32.5) at 2 years, 16.0% (12.0-20.6) at 3 years, 12.1% (8.5-16.4) at 4 years, and 9.8% (6.4-14.0) at 5 years with temozolomide, versus 10.9% (7.6-14.8), 4.4% (2.4-7.2), 3.0% (1.4-5.7), and 1.9% (0.6-4.4) with radiotherapy alone (hazard ratio 0.6, 95% CI 0.5-0.7; p<0.0001). A benefit of combined therapy was recorded in all clinical prognostic subgroups, including patients aged 60-70 years. Methylation of the MGMT promoter was the strongest predictor for outcome and benefit from temozolomide chemotherapy. INTERPRETATION: Benefits of adjuvant temozolomide with radiotherapy lasted throughout 5 years of follow-up. A few patients in favourable prognostic categories survive longer than 5 years. MGMT methylation status identifies patients most likely to benefit from the addition of temozolomide. FUNDING: EORTC, NCIC, Nelia and Amadeo Barletta Foundation, Schering-Plough.

https://www.thelancet.com/pdfs/journals/lanonc/PIIS1470-2045(09)70025-7.pdf

Effects of radiotherapy with concomitant and adjuvant temozolomide versus radiotherapy alone on survival in glioblastoma in a randomised phase III study: 5-year analysis of the EORTC-NCIC trial

https://www.genome.gov/Pages/Newsroom/Webcasts/2010ScienceReportersWorkshop/Panel5_integrated_genome_analysis_subtypes_of_glio.pdf

Integrated Genomic Analysis Identifies Clinically Relevant Subtypes of Glioblastoma Characterized by Abnormalities in PDGFRA, IDH1, EGFR, and NF1

The Cancer Genome Atlas Network recently cataloged recurrent genomic abnormalities in glioblastoma multiforme (GBM). We describe a robust gene expression-based molecular classification of GBM into Proneural, Neural, Classical, and Mesenchymal subtypes and integrate multidimensional genomic data to establish patterns of somatic mutations and DNA copy number. Aberrations and gene expression of EGFR, NF1, and PDGFRA/IDH1 each define the Classical, Mesenchymal, and Proneural subtypes, respectively. Gene signatures of normal brain cell types show a strong relationship between subtypes and different neural lineages. Additionally, response to aggressive therapy differs by subtype, with the greatest benefit in the Classical subtype and no benefit in the Proneural subtype. We provide a framework that unifies transcriptomic and genomic dimensions for GBM molecular stratification with important implications for future studies.

Statistical methods in cancer research

Background: Despite notable technical advances in therapy for malignant gliomas during the past decade, improved patient survival has not been clearly documented, suggesting that pretreatment prognostic factors influence outcome more than minor modifications in therapy. Age, performance status, and tumor histopathology have been identified as the pretreatment variables most predictive of survival outcome. However, an analysis of the association of survival with both pretreatment characteristics and treatment-related variables is necessary to assure reliable evaluation of new approaches for treatment of malignant glioma

Recursive partitioning analysis of prognostic factors in three radiation therapy oncology group malignant glioma trials

BACKGROUND Despite notable technical advances in therapy for malignant gliomas during the past decade, improved patient survival has not been clearly documented, suggesting that pretreatment prognostic factors influence outcome more than minor modifications in therapy. Age, performance status, and tumor histopathology have been identified as the pretreatment variables most predictive of survival outcome. However, an analysis of the association of survival with both pretreatment characteristics and treatment-related variables is necessary to assure reliable evaluation of new approaches for treatment of malignant glioma. PURPOSE This study of malignant glioma patients used a non-parametric statistical technique to examine the associations of both pretreatment patient and tumor characteristics and treatment-related variables with survival duration. This technique was used to identify subgroups with survival rates sufficiently different to create improvements in the design and stratification of clinical trials. METHODS We used a recursive partitioning technique to analyze survival in 1578 patients entered in three Radiation Therapy Oncology Group malignant glioma trials from 1974 to 1989 that used several radiation therapy (RT) regimens with and without chemotherapy or a radiation sensitizer. This approach creates a regression tree according to prognostic variables that classifies patients into homogeneous subsets by survival. Twenty-six pretreatment characteristics and six treatment-related variables were analyzed. RESULTS The years). Patients younger than 50 years old were categorized by histology (astrocytomas with anaplastic or atypical foci [AAF] versus glioblastoma multiforme [GBM]) and subsequently by normal or abnormal mental status for AAF patients and by performance status for those with GBM. For patients aged 50 years or older, performance status was the most important variable, with normal or abnormal mental status creating the only significant split in the poorer performance status group. Treatment-related variables produced a subgroup showing significant differences only for better performance status GBM patients over age 50 (by extent of surgery and RT dose). Median survival times were 4.7-58.6 months for the 12 subgroups resulting from this analysis, which ranged in size from 32 to 256 patients. CONCLUSIONS This approach permits examination of the interaction between prognostic variables not possible with other forms of multivariate analysis. IMPLICATIONS The recursive partitioning technique can be employed to refine the stratification and design of malignant glioma trials.

John Horton

Papers

Recursive partitioning analysis of prognostic factors in three radiation therapy oncology group malignant glioma trials

Recursive Partitioning Analysis of Prognostic Factors in Three Radiation Therapy Oncology Group Malignant Glioma Trials