Real-World Healthcare Resource Utilization in Patients with Classical Hodgkin Lymphoma Treated with Pembrolizumab and Nivolumab in the USA
Bibliographic record
Abstract
BACKGROUND: Patients with classical Hodgkin lymphoma (cHL) relapsed or refractory (R/R) disease who relapse after or are ineligible for autologous stem cell transplantation have a poor prognosis. Recently, the anti-PD1 monoclonal antibodies nivolumab and pembrolizumab were approved by the US Food and Drug Administration (FDA; May 2016 and March 2017, respectively) as treatment options for R/R cHL patients. OBJECTIVE: In the absence of comparative clinical trials between these agents, this observational study was conducted to evaluate the healthcare resource utilization (HRU) of patients with cHL initiated on pembrolizumab compared to nivolumab in the USA. PATIENTS AND METHOD: Healthcare insurance claims from Symphony Health's IDV® (Integrated Dataverse) (July 2014-June 2018) were used in this retrospective study. The study population included adult patients with cHL initiated on pembrolizumab or nivolumab (index date). Inverse probability of treatment weighting was used to adjust for differences in patient characteristics between cohorts. All-cause and cHL-related hospitalizations and outpatient visits were measured during the observation (post-index) period and reported per patient-year (PPY). Rates of HRU were compared between cohorts using rate ratios (RRs). RESULTS: A total of 92 and 218 patients initiated on pembrolizumab and nivolumab, respectively, were included in the study population. After weighting, the mean age was similar at 55 years in both cohorts, while the proportion of females was lower in the pembrolizumab cohort (35.3%) compared to the nivolumab cohort (44.1%). Mean Quan-Charlson Comorbidity Index score was well balanced after weighting in the pembrolizumab and nivolumab cohorts (4.2 and 4.3, respectively). During the observation period, patients in the pembrolizumab cohort had significantly lower rates of all-cause hospitalizations (RR [95% CI] 0.33 [0.09-0.80]) and cHL-related hospitalizations (RR [95% CI] 0.14 [0.02-0.37]) than those in the nivolumab cohort. Rates of all-cause and cHL-related outpatient visits were not statistically different between patients in the pembrolizumab and nivolumab cohorts. CONCLUSIONS: In this real-world study, adult cHL patients initiated on pembrolizumab had significantly lower rates of all-cause and cHL-related hospitalizations compared to patients initiated on nivolumab.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".