Employment, Insurance, and Financial Experiences of Patients with Chronic Graft-versus-Host Disease in North America
Bibliographic record
Abstract
Understanding the socioeconomic impact of chronic graft-versus-host disease (GVHD) on affected patients is essential to help improve their overall well-being. Using data from the Chronic GVHD Consortium, we describe the insurance, employment, and financial challenges faced by these patients and the factors associated with the ability to work/attend school and associated financial burdens. A 15-item cross-sectional questionnaire designed to measure financial concerns, income, employment, and insurance was completed by 190 patients (response rate, 68%; 10 centers) enrolled on a multicenter Chronic GVHD Consortium Response Measures Validation Study. Multivariable logistic regression models examined the factors associated with financial burden and ability to work/attend school. The median age of respondents was 56years, and 87% of the patients were white. A higher proportion of nonrespondents had lower income before hematopoietic cell transplantation and less than a college degree. All but 1 patient had insurance, 34% had faced delayed/denied insurance coverage for chronic GVHD treatments, and 66% reported a financial burden. Patients with a financial burden had greater depression/anxiety and difficulty sleeping. Nonwhite race, lower mental functioning, and lower activity score were associated with a greater likelihood of financial burden. Younger age, early risk disease, and higher mental functioning were associated with a greater likelihood of being able to work/attend school. In this multicenter cohort of patients with chronic GVHD, significant negative effects on finances were observed even with health insurance coverage. Future research should investigate potential interventions to provide optimal and affordable care to at-risk patients and prevent long-term adverse financial outcomes in this vulnerable group.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".