A Framework for Comparative Evaluation of Dosimetric Methods to Triage a Large Population Following a Radiological Event.

BACKGROUND

To prepare for a possible major radiation disaster involving large numbers of potentially exposed people, it is important to be able to rapidly and accurately triage people for treatment or not, factoring in the likely conditions and available resources. To date, planners have had to create guidelines for triage based on methods for estimating dose that are clinically available and which use evidence extrapolated from unrelated conditions. Current guidelines consequently focus on measuring clinical symptoms (e.g., time-to-vomiting), which may not be subject to the same verification of standard methods and validation processes required for governmental approval processes of new and modified procedures. Biodosimeters under development have not yet been formally approved for this use. Neither set of methods has been tested in settings involving large-scale populations at risk for exposure. OBJECTIVE: To propose a framework for comparative evaluation of methods for such triage and to evaluate biodosimetric methods that are currently recommended and new methods as they are developed. METHODS: We adapt the NIH model of scientific evaluations and sciences needed for effective translational research to apply to biodosimetry for triaging very large populations following a radiation event. We detail criteria for translating basic science about dosimetry into effective multi-stage triage of large populations and illustrate it by analyzing 3 current guidelines and 3 advanced methods for biodosimetry. CONCLUSIONS: This framework for evaluating dosimetry in large populations is a useful technique to compare the strengths and weaknesses of different dosimetry methods. It can help policy-makers and planners not only to compare the methods' strengths and weaknesses for their intended use but also to develop an integrated approach to maximize their effectiveness. It also reveals weaknesses in methods that would benefit from further research and evaluation.