A Prognostic Score of Overall Survival In Adults with Acute Myeloid Leukemia
Bibliographic record
Abstract
Abstract Abstract 2730 Background: Acute myeloid leukemia (AML) is a malignant myeloid disorder with heterogeneous outcomes. A number of factors have been shown to be prognostic; age, white blood cell (WBC), prior malignancy, performance status (Eastern Cooperative Oncology Group; ECOG) and cytogenetics. Methods: We planned to develop and validate a prognostic score for the 5-year (y) overall survival (OS) of adults with AML receiving intensive induction chemotherapy. We used Cox model to estimate the regression coefficients and Kaplan-Meier to estimate the 5-y OS. We used Cox-Snell, Schoenfeld and deviance residuals for model diagnostics and bootstrap validation to estimate the performance measures; Harrell's concordance and deviance residuals. Results: We retrospectively analyzed 779 patients treated between 1998–2008, using a prospectively collected database. The median age was 58 y. Most patients had intermediate risk cytogenetics (61%) and good performance status (ECOG 0–1: 79%). The median follow up for the surviving patients was 26.7 months (95% CI 18.8–32.9 months). The 5-y OS was 26% (22- 30%). All variables were statistically significant in the multivariable Cox regression model; age (y) (Hazard Ratio, HR 1.02; 95% CI 1.018–1.034), WBC (1*10^9/L) (HR 1.004; 1.002–1.006), prior malignancy (HR 1.58; 1.26–2.00), ECOG (ECOG 2 HR 1.41; 1.06–1.88, ECOG 3–4 HR 9.99; 4.72–21.18) and cytogenetics (intermediate risk HR 2.49; 1.41–4.39, poor risk HR 4.74; 2.65–8.50). The score divided patients into four risk groups; good (n=47), intermediate (n=129), poor (n=198) and extremely poor (n=87). The estimated 5-y OS was 0.70 (95% CI: 0.53–0.81), 0.37 (0.28–0.46), 0.15 (0.10–0.21) and 0.03 (0.01–0.10) respectively. The model showed good discrimination with large differences between survival curves and good Harrell concordance of 0.69. It showed good calibration using Cox-Snell and deviance residuals. In the intermediate risk cytogenetic group, the model showed good discrimination with over 45% difference in 5-y OS between the good and extremely poor groups. Conclusions: Our study confirmed the prognostic impact of the 5 variables reported in the literature. Using these factors, we developed a score to predict long term OS that showed good discrimination and calibration. The score added further discrimination in the intermediate risk cytogenetic group. Prospective external validation of the score is needed. 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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".