Abstract / Description of output
Background: MGMT methylation in glioblastoma predicts response to temozolomide but dichotomizing methylation status may mask the true prognostic value of quantitative MGMT methylation. This study evaluated whether extent of MGMT methylation interacts with the effect of temozolomide on overall survival.
Methods: We included consecutive glioblastoma patients aged ≥16 years diagnosed (April 2012- May 2020) at a neuro-oncology center. All patients had quantitative MGMT methylation measured using pyrosequencing. Those with MGMT methylated tumors were stratified into high and low methylation groups based on a cut-off using Youden index on 2-year survival. Our accelerated
failure time survival models included extent of MGMT methylation, age, post-operative Karnofsky performance score, extent of resection, temozolomide regimen and radiotherapy.
Results: There were 414 patients. Optimal cut-off point using Youden index was 25.9% MGMT methylation. The number of patients in the unmethylated, low and high methylation groups was 223 (53.9%), 81 (19.6%) and 110 (26.6%), respectively. In the adjusted model, high (hazard ratio [HR] 0.60, 95% confidence intervals [CI] 0.46-0.79, p=0.005) and low (HR 0.67, 95%CI 0.50-0.89, p<0.001) methylation groups had better survival compared to unmethylated group. There was no evidence for interaction between MGMT methylation and completed temozolomide regimen (interaction term for low methylation p=0.097; high methylation p=0.071). This suggests no strong effect of MGMT status on survival in patients completing temozolomide regimen. In patients not
completing the temozolomide regimen, higher MGMT methylation predicted better survival (interaction terms p<0.001).
Conclusions: Quantitative MGMT methylation may provide additional prognostic value. This is important when assessing clinical and research therapies.
Methods: We included consecutive glioblastoma patients aged ≥16 years diagnosed (April 2012- May 2020) at a neuro-oncology center. All patients had quantitative MGMT methylation measured using pyrosequencing. Those with MGMT methylated tumors were stratified into high and low methylation groups based on a cut-off using Youden index on 2-year survival. Our accelerated
failure time survival models included extent of MGMT methylation, age, post-operative Karnofsky performance score, extent of resection, temozolomide regimen and radiotherapy.
Results: There were 414 patients. Optimal cut-off point using Youden index was 25.9% MGMT methylation. The number of patients in the unmethylated, low and high methylation groups was 223 (53.9%), 81 (19.6%) and 110 (26.6%), respectively. In the adjusted model, high (hazard ratio [HR] 0.60, 95% confidence intervals [CI] 0.46-0.79, p=0.005) and low (HR 0.67, 95%CI 0.50-0.89, p<0.001) methylation groups had better survival compared to unmethylated group. There was no evidence for interaction between MGMT methylation and completed temozolomide regimen (interaction term for low methylation p=0.097; high methylation p=0.071). This suggests no strong effect of MGMT status on survival in patients completing temozolomide regimen. In patients not
completing the temozolomide regimen, higher MGMT methylation predicted better survival (interaction terms p<0.001).
Conclusions: Quantitative MGMT methylation may provide additional prognostic value. This is important when assessing clinical and research therapies.
| Original language | English |
|---|---|
| Journal | Neuro-Oncology Advances |
| Early online date | 19 Nov 2021 |
| DOIs | |
| Publication status | E-pub ahead of print - 19 Nov 2021 |
Keywords / Materials (for Non-textual outputs)
- glioblastoma
- mgmt
- effect modification
- Survival