Presence of Comorbidities Do Not Predict Early Mortality or Survival in Older Patients (≥60 Years) with Acute Myeloid Leukemia (AML) Undergoing Intensive Induction Therapy.
Bibliographic record
Abstract
Abstract Older patients with AML undergoing intensive therapy are at a substantial risk of early mortality. These patients frequently have accompanying comorbid conditions, which may contribute towards mortality. The impact of comorbidities on early mortality or survival in older patients with AML is not known. Using the Charlson Comorbidity (CCI) and the Adult Comorbidity Evaluation-27 (ACE-27) indices, we evaluated the impact of comorbidities in 291 newly diagnosed patients ≥ 60 years (APL excluded) with AML (median 68 years; range 60–86) treated with intensive therapy at the Princess Margaret Hospital between Jan 1998 and Dec 2005. Cytogenetics risk categories (MRC-UK classification) at diagnosis: good, 4%; intermediate, 61%; adverse, 20%; and suboptimal/not done, 15%. A preceding hematological disorder was present in 29% patients and 11% had therapy-related AML. ECOG performance status was: 0, 10%; 1, 72%; 2, 16%; and 3, 2%. Of the study patients, 264 (91%) received uniform induction therapy with daunorubicin and cytarabine as described previously (Gupta et al., Cancer, 2005:2082). Median follow-up of survivors was 18 months. ACE-27 was more sensitive in picking up mild comorbidities compared to CCI (121 vs. 64, p<0.0001). Moderate to severe comorbidities according to CCI and ACE-27 were found in 68 (23%) and 88 (30%) patients, respectively. With induction therapy, 159 (54%) patients achieved CR. Early mortality, defined as death due to any cause within 8 weeks from the start of induction, was 18%. Median survival was 317 days (95% CI 274–368) and the probability of 2-year survival was 21% (95% CI 16–26). Patient, disease, and treatment-related factors associated with early mortality and survival were determined using multivariable Cox proportional hazards regression. Only ECOG performance status was associated with early mortality. Notably, age, cytogenetics and comorbidity indices were not associated with early mortality. Poor risk cytogenetics, (p<0.0001), Hb <92 g/L (p<0.0001), WBC count >30 × 109/l (p<0.0001), ECOG PS of 2/3 (p=0.03) and abnormal AST level (p=0.03) at diagnosis were independent factors for overall survival, while age and comorbidity indices were not. We conclude that approximately one third of older patients undergoing intensive induction therapy have significant comorbidities. Early mortality in these patients is influenced by performance status but not by age or the presence of comorbidities, highlighting the need for further research on frailty resulting from the effects of AML. We validated the findings of our previous study (Gupta et al., Cancer, 2005:2082) in a larger data set, demonstrating that survival of these patients is determined by disease biology, rather than age. Age and the presence of comorbidities should not be used as exclusion criteria in determining the candidacy for intensive therapy in older patients with AML.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".