PB1821 REAL‐WORLD HEALTHCARE RESOURCE UTILIZATION (HRU) AND COSTS OF DIFFUSE LARGE B‐CELL LYMPHOMA (DLBCL) PATIENTS INITIATED ON ANTI‐CANCER THERAPIES IN THE UNITED STATES (US)
Bibliographic record
Abstract
Background: DLBCL, the most common type of non‐Hodgkin lymphoma in the US, is associated with significant HRU and healthcare costs. In October 2015, DLBCL administrative claims were differentiated from primary mediastinal large B‐cell lymphoma (PMBCL) with the advent of ICD‐10‐CM disease‐specific codes, allowing a more detailed examination of real‐world HRU and costs in patients with DLBCL. Aims: This study aimed to describe real‐world HRU and costs among patients diagnosed with DLBCL who initiated anti‐cancer therapies using a US claim database. Methods: A retrospective database analysis was conducted using the Optum Clinformatics TM Data Mart database (01/2013–03/2018). Patients with ≥1 inpatient or ≥2 outpatient encounters with an ICD‐10‐CM diagnosis code for DLBCL (or an antecedent ICD‐10‐CM diagnosis of other lymphoma, which may have been assigned before DLBCL confirmation) after October 1 st , 2015 (index date for incident patients) were classified as (1) incident if they had no prior ICD‐9‐CM diagnosis code for unspecified DLBCL or PMBCL, or as (2) prevalent if they had a prior ICD‐9‐CM code for unspecified DLBCL or PMBCL before October 2015 (index date for prevalent patients). Patients ≥18 years of age as of the index date with ≥12 months of continuous enrollment pre‐index date (baseline period) were included. Patients with any ICD‐10‐CM diagnosis for PMBCL or baseline diagnoses of Hodgkin lymphoma, multiple myeloma, or other selected lymphomas were excluded. Patients were observed up to the earliest date of end of data availability or end of continuous enrollment in health plans. All‐cause HRU (including inpatient stays, outpatient [OP] visits, emergency room visits, and other visits) and associated costs, including pharmacy costs, were computed per patient per year (PPPY) and reported for all treated patients and those treated with R‐CHOP (i.e., most used 1L treatment). Results: Among 4,074 DLBCL patients (3,201 incident; 873 prevalent), median (IQR) age was 73 (65–80) years; 46% were female. Incident and prevalent patients had mean Charlson comorbidity index scores of 2.7 and 2.3, respectively. Mean ± standard deviation [SD] total healthcare costs (medical and pharmacy costs) were $137,156 ± 123,753 and $127,202 ± 98,282 for all treated incident patients and those treated with R‐CHOP, respectively. Corresponding OP costs (including costs of administered therapies) were $88,202 ± 89,417 and $87,616 ± 77,362, respectively, and were the main drivers of total healthcare costs. Although similar trends were observed for prevalent patients, mean total healthcare costs were lower for all treated prevalent patients ($81,669 ± 114,414) relative to all treated incident patients; however follow‐up periods were longer for prevalent patients (∼2.5 years) compared to incident patients (∼11 months). A sensitivity analysis restricting patients’ evaluation periods up to 12 months (mean follow‐up periods of 8 months for incident and 11 months for prevalent patients) yielded more similar results (mean ± SD total healthcare costs for all treated patients: $169,776 ± 113,618 incident; $140,786 ± 86,428 prevalent) and highlighted increased costs incurred within the first year following a DLBCL diagnosis. Associated HRU results are presented in the Table below. Summary/Conclusion: Overall, this study highlighted the considerable economic burden of patients with DLBCL, particularly within the first year following diagnosis. image
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".