Expenditures in Young Adults with Hodgkin Lymphoma: NCI-Designated Comprehensive Cancer Centers versus Other Sites
Bibliographic record
Abstract
Abstract Background: Outcomes among Hodgkin lymphoma (HL) patients diagnosed between 22 and 39 years are worse than among those diagnosed <21 years, and have not seen the same improvement over time. Treatment at an NCI-designated Comprehensive Cancer Center (CCC) mitigates outcome disparities, but may be associated with higher expenditures. Methods: We examined cancer-related expenditures among 22- to 39-year-old HL patients diagnosed between 2001 and 2016 using deidentified administrative claims data (OptumLabs Data Warehouse; CCC: n = 1,154; non-CCC: n = 643). Adjusting for sociodemographics, clinical characteristics, and months enrolled, multivariable general linear models modeled average monthly health-plan paid (HPP) expenditures, and incidence rate ratios compared CCC/non-CCC monthly visit rates. Results: In the year following diagnosis, CCC patients had higher HPP expenditures ($12,869 vs. $10,688, P = 0.001), driven by higher monthly rates of CCC nontreatment outpatient hospital visits (P = 0.001) and per-visit expenditures for outpatient hospital chemotherapy ($632 vs. $259); higher CCC inpatient expenditures ($1,813 vs. $1,091, P = 0.001) were driven by 3.1 times higher rates of chemotherapy admissions (P = 0.001). Out-of-pocket expenditures were comparable (P = 0.3). Conclusions: Young adults with HL at CCCs saw higher health-plan expenditures, but comparable out-of-pocket expenditures. Drivers of CCC expenditures included outpatient hospital utilization (monthly rates of non-therapy visits and per-visit expenditures for chemotherapy). Impact: Higher HPP expenditures at CCCs in the year following HL diagnosis likely reflect differences in facility structure and comprehensive care. For young adults, it is plausible to consider incentivizing CCC care to achieve superior outcomes while developing approaches to achieve long-term savings.
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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) | 0.000 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".