Elderly AML Patients Treated with Intensive Chemotherapy- Developing A Prognostic Scoring System. A Study On 381 Patients From British Columbia
Bibliographic record
Abstract
Abstract Abstract 2561 Introduction. AML in patients above age 60 is associated with adverse outcomes compared to younger patients. This is due to the higher incidence of adverse risk cytogenetic changes, poor performance status and end organ function that precludes patients from receiving intensive chemotherapy. Large population based studies have reported 5yr survival rates of 5–8% even in patients receiving standard ‘3+7’ induction chemotherapy. Our study looks at the effect of disease and patient characteristics on outcomes in elderly AML patients who received remission induction chemotherapy in the hope of predicting which individuals would benefit most from this treatment. Patients and Methods. Retrospective data was collected from 381 patients > age 60 who underwent conventional cytarabine and daunorubicin (7+3) induction and consolidation chemotherapy after clinical evaluation suggesting they were fit for such treatment, from Jan 1990 to Sept 2009. The follow up duration ranged from 6m–19.5 years. The data collected were age, ECOG performance status,Haematopoetic stem cell transplant comorbidity Index (HCI) (Sorror et al Blood 2005;106:2912),WBC at presentation, bone marrow blast percentage, antecedent hematologic disease (AHD), Cytogenetic risk group by MRC(UK) criteria, remission status, date of relapse, mortality and overall survival (OS). Statistical analysis was performed to determine variables affecting OS using Cox regression analysis. Multivariate Cox regression coefficients were used to generate a nomogram to predict OS based on Akaike's information criterion. Results. The CR rates in the 3 MRC risk groups were 95%,75% and 40% respectively. The 8 week mortalities in the 3 risk groups 10%,8%and 29% respectively. The 3 month survival was 85%, 1year 50% and 5yr 16% for the patients as a whole. Multivariate analysis showed that age at diagnosis, WBC, cytogenetic risk group and AHD affect OS while sex, ECOG, HCI and BM blast count do not. Using the 4 variable significantly predicting OS a nomogram was developed. Its ability to predict OS of individual patients was evaluated using bootstrapping of a set of 200 resamples. To use the nomogram, draw a line straight upwards to the points axis to determine the number of points received for each of the 4 variables. The sum of these numbers is located on the Total Points axis, and a line is drawn downward to the survival axes to determine the likelihood of 1-, 3- or 5-year OS Discussion. AML in patients > age 60 is typically associated with a poor outcome after intensive chemotherapy. However, even among this high risk group results are heterogeneous. This is illustrated in our study where the CR rate and induction mortality varied substantially across cytogenetic risk groups. In addition to the cytogenetic risk group we found age, WBC at diagnosis and the present of AHD to have prognostic value in this elderly group. However, the HCI was not predictive of survival in these AML patients > age 60 receiving standard induction and consolidation chemotherapy. The prognostic patient factors identified in multivariate analysis are easily available in newly-diagnosed AML patients, usually before decisions regarding initial therapy must be made. If confirmed in a larger prospective study, the nomogram we have developed will help clinicians predict the expected survival following intensive chemotherapy, thus helping the patient to make an informed choice regarding risk vs benefit. Disclosures: Sutherland: Centocor Ortho Biotech research & Development: Research Funding.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".