The Economic Burden of Anti-Vascular Endothelial Growth Factor on Patients and Caregivers in the UK, Europe, and North America
Bibliographic record
Abstract
INTRODUCTION: Intravitreal (IVT) injections of anti-vascular endothelial growth factor (VEGF) agents are the standard of care for neovascular age-related macular degeneration (nAMD) and diabetic macular edema (DME). While demonstrated to be effective, these treatments potentially place a significant burden on patients owing to their cost and frequency of treatment visits required for administration. The objective of this study was to investigate the economic burden of treatment on patients with nAMD/DME and their informal caregivers in seven countries. METHODS: Data were collected from patients and caregivers in the USA, UK, Canada, Italy, Spain, Germany, and France using a survey between September and December 2022. Each survey collected data to facilitate calculating economic burden, combining the total financial costs (i.e., direct costs to receive treatment) and productivity losses associated with attending treatment appointments over a 6-month period. Quality of life data were collected using validated instruments. RESULTS: In total, 194 patients and 194 caregivers reported currently receiving (or caring for someone who receives) anti-VEGF treatment. Across all countries, the modal frequency of anti-VEGF treatment was every 4 weeks, except for patients with DME (every 8 weeks). The largest, mean 6-month economic burden on the pooled population of patients with nAMD/DME was reported in Italy (€1244) and on caregivers it was in the USA (€3069). Economic burden was lower for respondents receiving fewer anti-VEGF injections. CONCLUSIONS: More durable therapies for nAMD/DME would reduce treatment burden and have a sizeable impact financially on patients with nAMD/DME and their caregivers.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".