Healthcare Resource Utilization and Costs in Patients with Geographic Atrophy Secondary to Age-Related Macular Degeneration
Bibliographic record
Abstract
PURPOSE: Geographic atrophy (GA) is an advanced form of nonexudative age-related macular degeneration (AMD) that lacks treatment options. With considerable interpatient variability in the rate of GA progression due to lesion characteristics, information characterizing the disease burden is limited. The aim of this study was to describe the healthcare resource utilization (HCRU) and costs associated with increasing severity levels of GA. PATIENTS AND METHODS: A retrospective analysis was conducted using claims data from IQVIA's PharMetrics Plus database. Patients with a prevalent GA diagnosis were identified between October 1, 2016 and June 30, 2017 and classified by disease severity and laterality. Disease-specific HCRU and costs by disease severity were assessed during the 12-month follow-up period, with multivariable analyses performed adjusting for baseline characteristics. RESULTS: A total of 28,773 GA cases were identified (mean age = 68.7; 58.5% female), of which 24% and 76% had unilateral and bilateral GA, respectively, with varying levels of recorded severity (in increasing order): early or intermediate (EI) AMD, GA without subfoveal involvement (GAwoSF), and GA with subfoveal involvement (GAwSF). Patients with greater baseline severity in the bilateral group had a significantly higher number of outpatient (OP) visits per year (1.98 EI AMD; 2.57 for GAwoSF; 2.63 for GAwSF). Increasing disease severity was associated with higher patient-related costs in the outpatient setting (mean [SD] of $82 [$157], $110 [$559] for unilateral EI AMD and GAwSF, respectively, and $56 [$94], $64 [$97], $59 [$85] for bilateral EI AMD, GAwoSF, GAwSF, respectively). Similarly, higher payer-related costs were seen in patients with bilateral GAwSF compared to bilateral EI AMD (mean [SD] $280 [$325]; $198 [$262]). CONCLUSION: Study findings demonstrate that patients, with more severe GA at baseline, experience greater HCRU and costs in the outpatient setting. Further research should explore specific contributing factors to the long-term economic burden of GA.
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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".