Addressing Global Inequities in Positron Emission Tomography-Computed Tomography (PET-CT) for Cancer Management: A Statistical Model to Guide Strategic Planning
Miguel Gallach, Miriam Mikhail Lette, May Abdel-Wahab, Francesco Giammarile, Olivier Pellet, Diana Paez
Nuclear Medicine and Diagnostic Imaging Section, International Atomic Energy Agency, Vienna International Centre, Vienna, Austria
Med Sci Monit 2020; 26:e926544
Available online: 2020-08-20
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.
Keywords: Cancer Care Facilities, Nuclear Medicine, Positron-Emission Tomography, Socioeconomic Factors