Prognostic Implication of Framingham Risk Score As a Comorbidity Measure on Treatment Outcomes Following First-Line Tyrosine Kinase Inhibitor in Newly Diagnosed CML Patients
Bibliographic record
Abstract
Introduction Comorbidities, including cardiovascular (CV) disease and risk factors, are crucial in selecting tyrosine kinase inhibitors (TKIs) for chronic myeloid leukemia (CML) patients (pts). About 40-60% of CML pts have at least 1 comorbid condition, and 30% present with CV risk factors at diagnosis. While the Framingham Risk Score (FRS) assesses the 10-year CV risk events in general population and is suggested to be accounted in the TKI selection in CML pts, prospective data on its impact on TKI choice and outcomes is limited. Patients and method The TCGA-GTA project, started in November 2020, is an ongoing, prospective, non-interventional registry study of newly diagnosed CML patients in the Greater Toronto Area, Canada. At initial evaluation, comorbidities and FRS were assessed. Pts with low FRS have ≤10% CV risk at 10 years, intermediate risk is 10-20%, and high risk is >20%. Event-free survival (EFS), failure-free survival (FFS), and TKI-switch-free survival were compared between pts with low FRS (FRSlow) and those with intermediate to high FRS (FRSint/hi). Events included TKI switch, treatment failure (TF), or death, with TF defined by European LeukemiaNet (ELN) 2013 guidelines. Results From Nov 2020 to Jun 30, 2024, the study enrolled 101 newly diagnosed CML pts. Of these, 74.3% were in the FRSlow group and 25.7% in the FRSint/hi group. The median age was 49 years, with the FRSint/hi cohort being older (67.5 vs. 41 years, p<0.001). Males constituted 59% of the the FRSlow group vs. 81% of the FRSint/high group (p=0.057). Chronic phase presentation was seen in 96% of the FRSlow group and 92.3% of the FRSint/hi group. High-risk cytogenetic abnormalities were present in 9.5% of the FRSlow group and 7.7% of the FRSint/hi group. The median SOKAL score was 0.8 in the FRSlow and 0.9 in the FRSint/hi group (p=0.198). The median EUTOS score was 1.25 in the FRSlow and 1.80 in FRSint/hi group (p=0.001). Comorbidities were present in 44% of patients, with hypertension (27.7%) and hyperlipidemia (25.7%) being most common, followed by diabetes mellitus (12.9%), chronic lung disease (11.9%), and vascular disease (9.9%), including coronary artery disease, stroke and peripheral vascular disease. Comorbidities were more prevalent in the FRSint/hi cohort (80.8% vs. 30.7%, p<0.001), with a median of 3 vs. 0 comorbidities per patient. Imatinib was more frequently prescribed in the FRSint/hi group (69.2% vs. 14.9%), while 2nd generation (2G) TKI were more common in the FRSlow group including nilotinib (40.5%) and dasatinib (36.5%). With a median follow-up of 21.3 months, the FRSint/hi group had more adverse events (AEs) (56% vs. 38.6%, p=0.161), including gastrointestinal AEs (19.2% vs. 5.4%, p=0.049) and fatigue (15.4% vs. 1.4%, p=0.016). Overall, 66% of pts achieved BCR::ABL1 <10% at 3 months, 60.5% achieved BCR::ABL1 <1% at 6 months, and 71.9% achieved BCR::ABL1 <0.1% at 12 months. These molecular response rates were higher in the FRSlow group but the differences were not statistically significant. Twenty-seven percent experienced TF, and 31% required a TKI switch, with higher rates in the FRSint/hi cohort. Resistance was the main reason for switching therapy (17.6% in the FRSlow vs. 23.1% in FRSint/hi), followed by intolerance (12.2% in FRSlow vs. 15.4% in the FRSint/hi). At 12 months, EFS and FFS were 69.6% and 75.4% in the FRSlow group vs. 57.2% and 66% in the FRSint/hi group. The probability of remaining on the 1L TKI was also higher in the FRSlow group (67% vs. 49.8%, p=0.142). Progression to advanced phase was similar between the groups (4-5% at 12 months). Multivariable analysis showed that the type of TKI was the only independent factor associated with EFS, FFS, and TKI-switch/discontinuation-free survival, with 2G-TKIs demonstrating superior outcomes compared to imatinib. Conclusion FRS is a key tool for evaluating CV comorbidities and guiding the choice of 1L TKI in CML practice, with FRSint/hi group more likely to receive imatinib. However, intolerance and resistance to imatinib remain significant issues in the FRSint/hi group, and FRS itself does not independently predict treatment outcomes. The type of 1L TKI drug is the most important independent factor influencing treatment outcomes, with 2G-TKIs showing superior results compared to imatinib. Therefore, there is an unmet need for alternative treatments with better efficacy and tolerability, such as asciminib, in the FRSint/hi group.
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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 | 0.003 |
| 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 | 0.001 | 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".