Improving Access to Nuclear Medicine in Island Regions: A Cost-Minimization Analysis of Radiopharmaceutical Supply Strategies
Bibliographic record
Abstract
OBJECTIVES: Access to positron emission tomography (PET) services is limited in many island regions because of dependence on externally produced radiopharmaceuticals and associated logistical constraints. This study provides a cost-minimization analysis of 3 alternative supply strategies, with the aim of improving access to these essential diagnostic examinations for underserved populations in remote island settings. METHODS: We conducted a cost-minimization analysis over a 20-year horizon, comparing 3 scenarios in 4 island regions (Corsica, Crete, Sardinia, and Cyprus): (A) full reliance on imported radiopharmaceuticals, (B) local PET-only production via small cyclotrons, and (C) full local production via hybrid cyclotrons. Total costs included investment, fixed, and variable components, and were adjusted using purchasing power parity. Sensitivity analyses explored the effects of transport costs and demand levels. RESULTS: For all regions, local production became the least costly option beyond an initial annual threshold of approximately 650 annual PET examinations. Hybrid cyclotrons were slightly more cost minimizing than PET-only systems, especially in larger populations. For 3 of the 4 islands, local production dominated by year 3 to 8; for Cyprus, this occurred later, depending on demand and transport assumptions. CONCLUSIONS: Local radiopharmaceutical production can be a cost-minimization strategy for improving PET services accessibility in island regions. This analysis may also serve as a transferable decision-making framework for other remote or underserved areas, such as the Canary Islands, rural Australia, or similar settings worldwide.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".