The Impact from Frontline CLL Chemo Immunotherapy Regimen Outcomes Based on Patient Tolerability
Bibliographic record
Abstract
Abstract Background: The addition of anti-CD20 monoclonal antibodies to chemotherapy regimens for Chronic Lymphocytic Leukemia (CLL) has led to significant improvements in response and survival (Burger, O'Brian, Nat Rev Clin Oncol 2018). However, toxicities with treatment exist and real world evidence suggests that tolerability of treatment protocols may differ than those established by clinical trials (Mato et. al. Am Soc Hematology 2017), making clinical treatment decisions challenging. This study retrospectively reviewed the tolerability of three front line chemo-immunotherapy options utilized at the Saskatchewan Cancer Agency (SCA): Fludarabine, Cyclophosphamide and Rituximab (FCR) for fit patients, Bendamustine plus Rituximab (BR) for older but fit patients or younger but frail and Obinutuzumab plus Chlorambucil (O-Chlor) for older and/or frail patients. SCA guidelines suggest the choice of treatment regimen should be based on patient age and fitness, a surrogate for ability to tolerate full dose treatment. However, neither these two criteria nor what constitutes tolerability is defined, resulting in a subjective assessment of fitness, a common problem in real world settings (Bouret et al, Hematologica 2013). We hypothesized that choice of treatment without these definitions would lead to poor choice of regimen selection and inferior patient outcome. Methods: We retrospectively reviewed the electronic medical records of CLL patients receiving front line chemo immunotherapy treatment at the SCA between 2015-2018. Patients' ability to tolerate treatment was assessed by the number of cycles completed, total dose intensity received, dose delays or change in therapy. Regimen tolerability was compared to physician calculated Cumulative Illness Rating Scale (CIRS) scores (an objective fitness measure) however, this was calculated after treatment regimen was determined. Kaplan-Meier analysis, univariable and multivariable Cox regression models were utilized to analyze the effect of tolerability and regimen received on patient outcome as defined by death due to CLL or progressive disease. Results: Ninety-six patient charts were reviewed. Regimen tolerability is shown in Table 1. A dose intensity of ≥ 75% was achieved by 91.3%, 69.9% and 48.7% of patients treated with FCR, BR and O-Chlor respectively. Dose intensity was statistically different among all 3 treatments (p=0.002) and specifically between FCR and BR (p=0.048). The number of cycles received for the 3 treatment groups were also statistically different most notably between FCR and O-Chlor (p=0.01) CIRS score of ≤ or > 6 was not different between the 3 groups. Median survival was statistically different between FCR (34.5 mo.), BR (36.1 mo.) and O-Chlor (25.4mo), (p=0.02) by Kaplan Meir Analysis. Univariate Cox regression analysis demonstrated the following statistically significant risk differences for death from CLL or disease progression; 1) Higher risk for O-Chlor versus BR [Hazard Ratio (HR)= 5.16, 95% confidence interval (CI): (1.65-16.13), P=0.004), 2) Lower risk for DI ≥ 75% for a 3 regimens [HR=0.19, 95% CI: (0.08-0.44), P=0.001], 3) each additional cycle of treatment received lowered the risk of death from CLL or disease progression by 33% [HR=0.67, 95% CI:(0.56-0.80), P<0.0001] and 4) if an additional cycle of treatment required dose reduction, the event rate decreased by 23% [HR=0.77, 95% CI: (0.59-0.99), P=0.047]. Multivariable Cox regression analysis demonstrated that only the regimen received and not specific tolerability remained statistically significant for patient outcomes. Conclusions: Dose intensity and the number of cycles received independently affected patient outcome indicating that certain aspects of regimen tolerability are important to consider when making treatment decisions. These results add to the growing body of real world evidence for front line CLL chemo immunotherapy. Disclosures Elemary: Roche: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Lundbeck: Membership on an entity's Board of Directors or advisory committees.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".