Comparison of Time to Next Treatment, Health Care Resource Utilization, and Costs in Patients with Chronic Lymphocytic Leukemia Initiated on Front-line Ibrutinib or Chemoimmunotherapy
Bibliographic record
Abstract
BACKGROUND: Studies assessing ibrutinib's economic burden versus chemoimmunotherapy (CIT) focused on pharmacy costs but not medical costs. This study compared time to next treatment (TTNT), health care resource utilization (HRU), and total direct costs among patients with chronic lymphocytic leukemia (CLL) initiating front-line ibrutinib single agent (Ibr) or CIT. MATERIALS AND METHODS: Optum Clinformatics Extended DataMart De-Identified Databases were used to identify adults with ≥ 2 claims with a CLL diagnosis initiating front-line Ibr or CIT from February 12, 2014 to June 30, 2017. Inverse probability of treatment weighting was used to control for potential differences in baseline characteristics between the Ibr and CIT cohorts. Two periods were considered: entire front-line therapy (until initiation of second-line therapy) and first 6 months of front-line therapy. Comparisons with a subgroup of CIT patients initiating bendamustine/rituximab (BR) were also conducted. RESULTS: TTNT was significantly longer for Ibr (N = 322) relative to CIT (N = 839; hazard ratio, 0.54; P = .0163; Kaplan-Meier rates [24 months]: Ibr = 88.6%, CIT = 75.9%) and the subset of CIT patients treated with BR (N = 455; hazard ratio, 0.54; P = .0208; Kaplan-Meier rates [24 months]: Ibr = 89.0%, BR = 79.0%). During the entire front-line therapy, Ibr patients had significantly fewer monthly days with outpatient visits (rate ratio = 0.75; P = .0200). Ibrutinib's higher pharmacy costs (mean monthly cost difference [MMCD] = $6,849; P < .0001) were offset by lower medical costs (MMCD = -$10,615; P < .0001), yielding net savings (MMCD = -$3,766; P < .0001) versus CIT. Ibr was associated with net savings (MMCD = -$5,569; P < .0001) versus BR. Cost savings and reductions in HRU were more pronounced during the first 6 months of front-line therapy. CONCLUSION: During front-line CLL treatment, Ibr was associated with longer TTNT, fewer monthly days with outpatient visits, and net monthly total cost reduction versus CIT and BR.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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".