1. Addressing Global Inequities in Positron Emission Tomography-Computed Tomography (PET-CT) for Cancer Management: A Statistical Model to Guide Strategic Planning
- Author
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Miriam Mikhail Lette, May Abdel-Wahab, Miguel Gallach, Diana Paez, Francesco Giammarile, and Olivier Pellet
- Subjects
Computer science ,MEDLINE ,Cancer Care Facilities ,030204 cardiovascular system & hematology ,Global Health ,Bayesian inference ,Unit (housing) ,03 medical and health sciences ,0302 clinical medicine ,Neoplasms ,Positron Emission Tomography Computed Tomography ,Agency (sociology) ,Medical imaging ,Humans ,Socioeconomic status ,Strategic planning ,Health Equity ,Statistical model ,General Medicine ,Strategic Planning ,Socioeconomic Factors ,Risk analysis (engineering) ,Positron-Emission Tomography ,030220 oncology & carcinogenesis ,Database Analysis ,Nuclear Medicine - Abstract
BACKGROUND According to the World Health Organization (WHO), non-communicable diseases are responsible for 71% of annual global mortality. National governments and international organizations are increasingly considering medical imaging and nuclear medicine access data in strategies to address epidemiologic priorities. Our objective here was to develop a statistical model to assist countries in estimating their needs for PET-CT systems for the management of specific cancer types. MATERIAL AND METHODS We introduce a patient-centered statistical model based on country-specific epidemiological data, PET-CT performance, and evidence-based clinical guidelines for PET-CT use for cancer. The output of the model was integrated into a Bayesian model to rank countries or world regions that would benefit the most from upscaling PET-CT scanners. RESULTS We applied our model to the IMAGINE database, recently developed by the International Atomic Energy Agency (IAEA). Our model indicates that at least 96 countries should upscale their PET-CT services and more than 200 additional PET-CT scanners would be required to fulfill their needs. The model also provides quantitative evidence indicating that low-income countries would benefit the most from increasing PET-CT provision. Finally, we discuss several cases in which the standard unit [number of scanners]/[million inhabitants] to guide strategic planning or address inequities is misleading. CONCLUSIONS Our model may help in the accurate delineation and further reduction of global inequities in access to PET-CT scanners. As a template, the model also has the potential to estimate the costs and socioeconomic impact of implementing any medical imaging modality for any clinical application.
- Published
- 2020