Impact of Mutations in Epigenetic Modifiers in Acute Myeloid Leukemia: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Objectives: Mutations in epigenetic modifiers including IDH (Isocitrate dehydrogenase), DNMT3A (DNA Methyltransferase 3 Alpha), TET2 (Ten-Eleven Translocation 2), ASXL1 (Additional Sex Combs-Like 1), and EZH2 (Enhancer of Zeste Homolog 2) have been recently recognized in patients with Acute Myeloid Leukemia (AML). The DNMT3A and IDH were found to be associated with poor prognosis in most studies; however, there is no meta-analysis evaluating other mutations in the epigenetic modifiers. We performed a systematic review and meta-analysis to evaluate the prognostic significance of mutations in the epigenetic modifiers on the Overall Survival (OS) of patients with AML. Methods: We searched for studies evaluating epigenetic mutations in AML (up to August 2018) in PubMed. Two reviewers independently screened all citations and later abstracted data using a common data collection form. Risk of bias was assessed using Newcastle-Ottawa Scale (NOS) and Cohen kappa coefficient (k) was calculated to assess the agreement. Hazard ratio (HR) and 95% confidence interval (CI) of outcomes were extracted and random effects model was used to pool the results. Statistical heterogeneity was calculated using Cochran I2 and tested using chi-squared tests. Results: A total of 9543 citations were retrieved from the search strategy; of which 9415 were excluded after title screening and 37 articles were excluded after abstract screening. A review of full text excluded additional 49 articles for incomplete data and missing analysis on OS. Forty-two articles were identified for the systematic review and meta-analysis (IDH n=15, DNMT3A n=12, TET2 n=8, ASXL1 =7), all of which were fair to good quality studies based on the NOS. The analysis of IDH mutation included 15 articles covering 5100 patients with a median age of 55 years. The frequency of IDH mutations ranged from 7 to 33%. The pooled HR indicated that IDH mutation conferred significantly worse OS (HR = 1.54; 95% CI: 1.15-2.06) though with a substantial heterogeneity (I2 = 85%). Mutation analysis of DNMT3A was based on 12 articles including 5418 patients with a median age of 52 years. The proportion of patients with this mutation ranged from 14 to 34%. Results indicated a worse OS with a pooled HR of 1.35; 95% CI 1.16-1.56, and a substantial heterogeneity (I2=71%). For the ASXL1 mutation, our analysis included 4115 adult and pediatric patients from 7 studies. The pooled HR indicated that ASXL1 mutation conferred a significantly worse OS (HR = 1.88; 95% CI: 1.49‒2.36); however, with a moderate heterogeneity (I2 = 43%). The TET2 mutation analysis was based on eight studies with a total of 3286 patients. The pooled HR indicated that TET2 mutation conferred a significantly worse OS (HR = 1.39; 95% CI: 1.18‒1.63); with a low heterogeneity (I2 = 28%). Conclusions: Epigenetic mutations in IDH, DNMT3A, ASXL1 and TET2 adversely impact OS in patients with AML. These mutations in the epigenetic modifiers should be considered in the initial evaluation of patients with AML and in the decision on post induction management. Disclosures Al-Khabori: Shire (Takeda): Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees; SOBI: Honoraria; AstraZeneca: Honoraria; NovoNardisk: Membership on an entity's Board of Directors or advisory committees; Roche: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees; Servier: Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.021 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".