Genome-Wide Genotype-Based Risk Model for Survival in Acute Myeloid Leukemia Patients with Normal Karyotype.
Bibliographic record
Abstract
Abstract Abstract 2526 Introduction: Single nucleotide polymorphism (SNP) is an inter-individual genetic variation which could explain inter-individual differences of response/survival to chemotherapy. The present study was attempted to build up risk model of survival for acute myeloid leukemia (AML) patients with normal karyotype (AML-NK). Methods and materials: A total of 247 patients with AML-NK was included into the study. Genome-wide SNP array (Affymetrix SNP-array 6.0) was performed in the discovery set (n=118), and genotypes were analyzed for overall survival (OS). After identifying significant SNPs for OS in single SNP analyses, risk model was constructed. Replication was performed in an independent validation cohort (n=129). Results: Out of 632,957 autosomal SNPs meeting genotype data filtration criteria, a total of 82 SNPs were selected and passed into the next step of validation in an independent cohort. In the risk model generation step, finally 4 SNPs (rs2826063, rs12791420, rs11623492 and rs2575369) were meeting stringent criteria for SNP selection as follows: 1) p-value < 0.10 from Cox proportional hazards regression model in adjustment with age and WBC counts at diagnosis; 2) minor allele frequency > 0.05; 3) call rate > 95.0%; 4) high linkage disequilibrium r2 < 0.8. These 4 SNPs were introduced into the risk model, and patients was grouped into 2 groups according to the number of deleterious variables including 4 SNPs and 2 clinical variables (i.e. age and WBC counts at presentation): risk score 0–2 as a low risk (n=80) and 3–6 as a high risk (n=38). The risk model could stratify the patients according to their OS in discovery (p=1.053656•10−4) and in validation set (p=5.38206•10−3). The risk model showed a higher AUC than those being incorporated only clinical or only 4 SNPs, suggesting improved prognostic stratification power of combined model. Conclusion: Genome-wide SNP based risk model obtained from 247 patients with AML-NK can identify high risk group of patients with poor survival using genome wide SNP data. (Clinicaltrials.govIdentifier:NCT01066338) Disclosures: No relevant conflicts of interest to declare.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".