FRAIL-HRU-AML: Impact of Frailty Assessment on Health Resource Utilization in Acute Myeloid Leukemia Patients: A Population-Based Study from Ontario, Canada
Bibliographic record
Abstract
Introduction The management of acute myeloid leukemia (AML) involves significant healthcare resource utilization (HRU) due to frequent and prolonged hospitalizations for chemotherapy and supportive care. Frailty, which encompasses overall fitness beyond just comorbidities, is associated with poorer outcomes in various cancers. Assessing frailty can enhance treatment decision-making in oncology by adding valuable context to disease-specific factors. However, the specific impact of frailty on HRU in AML has not been well studied. Therefore, this study aims to evaluate the impact of frailty on HRU in AML patients. Methods This retrospective cohort study from population-based health administrative databases in Ontario, Canada (ICES) included all patients (pts) ≥18 years newly diagnosed (ND) with AML between 2006 and 2021 and treated within 90 days after diagnosis. Patients were followed from date of first chemotherapy to 1- year after maximum follow up until March 31, 2023, for HRU outcomes. Patients were censored at the time of allogenic stem cell transplant (ASCT). The primary predictor, frailty was measured using McIsaac's frailty index (MFI) and categorized as fit (FT), pre-frail (PFR), or frail (FR). HRU outcomes included length of stay for all hospitalizations in days (Total-LOS), intensive care unit stay in days (ICU-LOS), and number of hospital admissions including emergency visits (HA) within first year after starting chemotherapy. These outcomes were measured as per person year (PPY) to adjust for variability in length of follow-up. Association of frailty with HRU outcomes was measured as rate ratios (RR) using multivariable negative binomial models. Model co-variates included age, sex, rurality, neighborhood income quintile, Ontario marginalization (ON-MARG), co- morbidities, ethnicity, prior non-AML malignancy, and treatment intensity {classified as intensive (IT) or non-intensive (NIT) based on standard practices}. Results This study included 5450 pts with ND- AML, with a median age of 65 years (IQR 54-74), 55.8% being males. 3543 (65%) patients received IT and 1907 (35%) received NIT. In entire cohort, 1750 (32.1%) patients were FT, 1874 (34.4%) PFR, and 1826 (33.5%) FR. In 2,035 (37%) patients ≤ 60 years, 44.5% (905) were FT, 36.7% (746) PFR, and 18.9% (384) FR. In 3,415 (63%) patients > 60 years of age, 24.7% (845) patients were FT, 33.0% (1,128) PFR and 42.2% (1,442) FR. 39.0% (683) of FT, 28.7% (537) of PFR, and 18.7% (342) of FR patients underwent ASCT. Median follow up for entire cohort was 13 months (IQR: 4-34). Median overall survival (months) was 12.5 (95% CI: 12.0-13.2) in the entire cohort, 17.6 (95% CI: 16.2-19.1) in FT, 13.7 (95% CI: 12.6-15) in PFR, and 8.5 (95% CI: 7.6-9.3) for FR patients. On univariate analysis, the total LOS (days) was longer for FT patients: 62.04 (95% CI: 61.62-62.46) for FT, 52.29 (95% CI: 51.91-52.68) for PFR, and 55.69 (95% CI: 55.25-56.13) for FR patients, with statistical significance (p<0.0001). However, ICU-LOS (days) was longer (p<0.0001) for FR patients with a median ICU-LOS of 3.15 (95% CI: 3.05-3.26) for FR, 2.41 (95% CI: 2.33-2.49) for PFR, and 2.32 (95% CI: 2.24-2.40) for FT patients. Similarly, HAs were more frequent in FR patients, 5.63 (95% CI: 5.49-5.77) for FR, 4.99 (95% CI: 4.88-5.11) for PFR, and 5.18 (95% CI: 5.06-5.30) for FT patients, showing statistical significance (p<0.0001). On multivariable analysis for total-LOS, frail patients had significantly higher total- LOS (RR-1.17, 95% CI- 1.06-1.29, p=0.0009), compared to, FT patients (ref.). Advanced age, sex, intensity of chemotherapy and presence of secondary AML were not significantly associated with total- LOS. Frailty was also associated with higher ICU- LOS (RR-1.81, 95% CI- 1.35-2.4, p<0.001) compared to fit patients (ref.). Patients older than 65 years also had higher ICU-LOS (p<0.001) and female patients had lower ICU-LOS. Intensity of treatment had no significant association with ICU-LOS. Similarly, FR patients had significantly higher HA (RR-1.12, 95% CI- 1.05-1.20, p=0.0005) than FT patients (ref.). Advanced age above 65 years of age, those receiving IT and patients with secondary AML also showed independent association with increased HA. Conclusion Frailty is independently associated with higher total-LOS, ICU-LOS and HA in ND- AML patients within 1 year of starting chemotherapy after adjusting for advanced age, sex, intensity of chemotherapy and secondary 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".