A cost-effectiveness and cost-utility study of lung transplants /
Bibliographic record
Abstract
Introduction. Lung recipients are faced with life-threatening complications which may impede in reaching an acceptable overall clinical and HRQOL level. Furthermore, the reported costs associated with the rigid follow-up care and expensive drug regimen raises the question whether this intervention is cost-effective. Objectives. To determine the incremental cost-effectiveness (C/E) and cost-utility (C/U) of lung transplantation (L-Tx) according to the health system perspective. Methods. A C/E and C/U analysis of L-Tx was carried out on 124 patients accepted unto the Quebec L-Tx waiting list (1997--2001). Survival was presented in mean life years (LY). HRQOL and utility were assessed using the SF-36 and standard gamble; they were studied cross-sectionally and longitudinally on a group of patients. Utility was used in the computation of the QALY. The economic impact of L-Tx was based on direct medical costs for 3 time periods: the waiting list, the transplant procedure and post-transplant phase. In the incremental C/E and C/U ratio, the costs for the procedure and follow-up care were compared to those during the waiting list, which served as an estimate for costs without transplantation. Estimates were modeled beyond the study period based on registry data. Simulating different person-time experiences during the waiting time (1 to 6 years) and post-transplant phase (1 to 8 years) tested key assumptions. Costs were based on provincial and national data and were discounted at a rate of 5%. Results. The estimates were based on the 1,090.0 and 1,421.5 person-months contributed by the cohort (N = 124) to the waiting list and post-transplant phase (N = 91), respectively. The mean LYs and QALYs gained were 0.57 (95% CI: 0.36--0.78) and 0.62 (95% CI: 0.36--0.78), respectively. HRQOL was higher on average for all domains in lung recipients versus candidates. Utility scores were also higher in recipients as compared to candidates: 0.76 (95% CI: 0.69, 0.83) versus 0.17 (95% CI: 0.12, 0.22). The estimated total average cost per patient without Tx was $15,015 or $1,708 (95% CI: $1,327--$2,090) per month. The L-Tx program induced an additional screening cost of $9,622 per patient. The average cost of a transplant procedure was $49,314 (95% CI: $39,216--$69,465). The average post-Tx follow-up cost per patient per month in the first, second, third and fourth year was $2,804 ($1,840--$3,792), $1,643 ($1,090--$2,291), $1,749 ($804--$2,690) and $971 ($768--$1,175), respectively.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".