Objectives: To assess which way of measuring methylation of the MGMT promoter best predicts survival when people with glioblastoma are treated with temozolomide.
Search methods: We searched MEDLINE, Embase, BIOSIS, Web of Science Conference Proceedings Citation Index to December 2018, and examined reference lists. For economic evaluation studies we additionally searched NHS Economic Evaluation Database (EED) up to December 2014.
Selection criteria: Eligible studies were longitudinal (cohort) studies of adults with diagnosed glioblastoma treated with temozolomide with/without radiation therapy/surgery. Studies had to have related MGMT status in tumour tissue (assessed by one or more method) with overall survival and presented results as hazard ratios or with su*icient information (e.g. Kaplan-Meier curves) for us to estimate hazard ratios. We focus mainly on studies comparing two or more methods, and list brief details of articles that examined a single method of measuring MGMT promoter methylation. We also sought economic evaluations conducted alongside trials, modelling studies, and cost analysis.
Data collection and analysis: All steps of the identification and data extraction process for multiple-method studies were undertaken by two reviewers independently. We assessed risk of bias and applicability using our own modified and extended version of the QUIPS tool. Comparisons of different techniques, exact promoter regions (CpG sites) and thresholds for interpretation were compared within studies by examining hazard ratios. We performed meta-analyses for comparisons of the three most commonly examined methods (immunohistochemistry (IHC), methylation-specific polymerase chain reaction (MSP) and pyrosequencing (PSQ)), with ratios of hazard ratios, using an imputed value of the correlation between results based on the same individuals.
Main results: We included 32 independent cohorts involving 3474 people in which two or more methods were compared. In meta-analyses of ratios of hazard ratios (RHR), we found evidence that MSP (CpG sites 76 to 80 and 84 to 87) is more prognostic than IHC for MGMT protein at varying thresholds: (RHR = 1.31; 95% confidence interval (CI) 1.01 to 1.71). We also found evidence that PSQ is more prognostic than IHC for MGMT protein at various thresholds (RHR = 1.36; 95% CI 1.01 to 1.84). The data suggest that PSQ (mainly at CpG sites 74 to 78, using various thresholds) is slightly more prognostic than MSP at sites 76 to 80 and 84 to 87 (RHR = 1.14; 95% CI 0.87 to 1.48). Many variants of PSQ have been compared, although we did not see any strong and consistent messages from the results. Targeting multiple CpG sites is likely to be more prognostic than targeting just one. In addition, we identified and summarized 190 articles describing a single method for measuring MGMT promoter methylation status.
Authors' conclusions: Pyrosequencing and methylation-specific PCR appear to be more prognostic for overall survival than immunohistochemistry. Strong evidence is not available to draw conclusions with confidence about the best CpG sites or thresholds for quantitative methods. MSP has been studied mainly for CpG sites 76 to 80 and 84 to 87 and PSQ at CpG sites ranging from 72 to 95. A threshold of 9% for CpG sites 74 to 78 was found to perform better than higher thresholds of 28% or 29% in two of three good quality studies making such comparisons.
|Journal||Cochrane Database of Systematic Reviews|
|Early online date||12 Mar 2021|
|Publication status||E-pub ahead of print - 12 Mar 2021|