Economic Burden and Health-Related Quality of Life Associated with Current Treatments for Anaemia in Patients with CKD not on Dialysis: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: The cost and health-related quality of life (HRQoL) burden associated with treatments for anaemia of chronic kidney disease (CKD) is not well characterized among non-dialysis-dependent (NDD) patients. OBJECTIVE: Our objective was to review the literature on costs and HRQoL associated with current treatments for anaemia of CKD among NDD patients. METHODS: The Cochrane Library, MEDLINE, Embase, NHS EED, and NHS HTA databases were searched for original studies published in English between 1 January 2000 and 17 March 2017. The following inclusion criteria were applied: adult population; primary focus was anaemia of CKD; patients received iron supplementation, red blood cell transfusion, or erythropoiesis-stimulating agents (ESAs); and reported results on HRQoL and/or costs. Studies that included NDD patients, did not compare different treatments, and had relevant designs were retained. HRQoL and cost outcomes were summarized in a narrative synthesis. RESULTS: In total, 16 studies met the inclusion criteria: six randomized controlled trials, four prospective single-arm trials, three retrospective studies, one prospective observational study, one simulation study, and one cross-sectional survey. All included ESAs. Treatment of anaemia (compared with no treatment) was associated with HRQoL improvements in five of six studies and lower costs in four of four studies. Treatment aiming for higher haemoglobin targets (compared with lower targets) resulted in modest HRQoL improvements, higher healthcare resource utilization (HRU), and higher costs. CONCLUSIONS: In NDD patients, untreated anaemia of CKD leads to higher costs, higher HRU, and lower HRQoL compared with initiating anaemia treatment. Relative to aiming for lower haemoglobin targets with ESAs, higher targets conferred modest HRQoL improvements and were associated with higher HRU.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".