An economic evaluation of sevelamer in patients new to dialysis
Bibliographic record
Abstract
OBJECTIVE: The overall objective of this study was to estimate the costs and outcomes associated with treatment with sevelamer for hyperphosphataemia compared with calcium-based binders. METHODS: Using published data on mortality and hospitalisation rates, a Markov model was developed to predict health outcomes and associated costs for the treatment of hyperphosphataemia using either sevelamer or calcium binders in chronic kidney disease patients who had recently started haemodialysis. Patient outcomes were modelled for 5 years, and incremental cost-effective ratios (ICERs) were calculated for sevelamer relative to calcium carbonate and calcium acetate binders. The perspective adopted was that of the UK National Health Service. RESULTS: The total 5-year discounted treatment cost for patients treated with sevelamer is pound 24,216, while for the calcium carbonate group total cost was pound 17,695. This is an incremental cost of pound 6521 per sevelamer-treated patient over 5 years. Patients receiving sevelamer can be expected to experience 2.70 quality-adjusted life years (QALYs) compared to 2.46 for those treated with calcium carbonate (i.e. an incremental gain of 0.24 QALYs). This results in an incremental cost per QALY of pound 27,120 and an incremental cost per life year gained of pound 15,508. Results were similar with calcium acetate. CONCLUSION: Together with the unique morbidity and mortality benefits, this study suggests that treatment with sevelamer confers clinical benefits with a modest investment of additional economic resources.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".