A dynamic comprehensive geriatric assessment demonstrates improvement in patient fitness after induction and predicts survival and treatment tolerability among older adults with newly diagnosed acute myeloid leukemia
Bibliographic record
Abstract
Abstract Introduction: A comprehensive geriatric assessment (CGA) is recommended in older adults (OAs, age>60 years) with acute myeloid leukemia (AML) by the EuropeanLeukemia Net (ELN) 2025 Fitness panel (Venditti, Blood Advances, 2025). The CGA has been evaluated in patients (pts) treated with intensive regimens (Klepin, Blood, 2013) and hypomethylating agents (HMA) (Ritchie, Blood Advances, 2022) though data in the current era with HMA+venetoclax (HMA+ven) as the standard of care are limited. Furthermore, change in pt fitness after induction therapy is poorly described despite unanimous ELN panel agreement on the importance of the topic. Finally, the CGA domain of nutrition is understudied in AML. Specifically, sarcopenia, defined as low muscle mass and strength (Cruz-Jentoft, The Lancet, 2019), has to date not been incorporated into a CGA. To fill these gaps in knowledge, we conducted a prospective observational trial (NCT05458258) of a CGA at diagnosis and at the end of induction therapy in OAs with newly diagnosed AML with the hypothesis that sarcopenia would predict early death (ED). Methods: Our prior Trial in Progress abstract (Yates, Blood, 2023) describes the study schema in full. In brief, pts underwent a CGA prior to and after induction (28-40 days after). The primary outcome, ED, was defined as death within 60 days of treatment initiation or from date of diagnosis for those who aimed to start treatment but died before treatment initiation. Secondary outcomes included length of stay (LOS), unscheduled readmissions, and treatment tolerability (defined as ability to finish 2 cycles of HMA+ven within 3 months of treatment start). Subgroup analyses were conducted among those fit by performance status (ECOG PS<2) and excluding those who died before treatment initiation. Multivariable analyses controlled for age, ELN 2024 Less Intensive risk (ELN 2024), and ECOG PS. Results: We recruited 82 pts between 3/1/2023-4/18/2025 with 79 pts included in the final analysis (2 withdrew, 1 diagnosis changed). Data cut off for this pre-planned interim analysis was 7/8/2025. Median age was 73 years (range, 60-93) with most patients being White (79%) and male (58%). ELN 2024 categories were Favorable (56%), Intermediate (27%), and Adverse (17%). Mutations in TP53 (17%), IDH1/2 (20%), NPM1 (17%), FLT-3 ITD (13%), and NRAS/KRAS (17%) were observed. Most pts were treated with less-intensive regimens (83%), primarily HMA+ven (67%). CGA impairments at diagnosis were prevalent despite 79% of pts having ECOG PS 0-2: functional status (instrumental activities of daily living (IADL), 43%), physical function (short physical performance battery (SPPB), 60%), malnutrition (patient-generated subjective global assessment (PG-SGA), 80%), sarcopenia (skeletal muscle index (kg/m2) at L1 from computed tomography and grip strength; impaired if both low, 24%), comorbidities (Charlson Comorbidity Index (CCI), 61%), and cognition (MOCA, 70%). The ED rate was 28% for the whole cohort and 20% when excluding the 8 pts who died before initiating induction. Median follow up and median OS for the whole cohort was 8 months and 14.7 months, respectively. No CGA variables were associated with increased ED rates in multivariable analyses though sarcopenia (Odds Ratio (OR): OR=2.1, 95% CI 0.69-6.44; p=0.19), 6-minute walk test ((6MWT): (OR=0.99, 95% CI 0.98-1.00; p=0.05), and SPPB (OR=7.41, 95% CI 0.67-82.6; p=0.1) neared statistical significance. In multivariable analysis in the whole cohort and subgroups the Timed Up and Go (TUG) test (OR=2.61; 95% CI 1.05-6.48; p=0.04) was the strongest predictor of OS. In multivariable models sarcopenia and TUG predicted treatment tolerability and unscheduled readmissions while IADLs and MOCA were the strongest predictors of LOS. When comparing CGA variables at diagnosis and post-induction therapy significant changes in ECOG PS (mean change=+0.44; p<0.01) and MOCA (mean change +1.03; p=0.02) were found. Furthermore, evaluable pts had clinically meaningful improvements in 6MWT (>50 meters; Ma, JCO, 2025) (62%) and MOCA (>2 points; Wong, JCN, 2017) (56%) at the end of induction. Conclusions: In a cohort of OAs with AML primarily fit by ECOG PS, a CGA uncovered significant impairments in fitness which were associated with survival, treatment tolerability, LOS, and readmissions independent of age, treatment intensity, or ECOG PS. Fitness, particularly cognition and physical function, may improve upon undergoing induction therapy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".