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. 2016 Aug 5;55(4):139-44.
doi: 10.3413/Nukmed-0778-15-11. Epub 2016 Apr 19.

Trends in the utilization of nuclear medicine and radiopharmaceuticals in an aging population

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Trends in the utilization of nuclear medicine and radiopharmaceuticals in an aging population

Mao-Chin Hung et al. Nuklearmedizin. .

Abstract

Aim: To investigate the trends in the utilization of nuclear medicine procedures and radiopharmaceuticals in an aging population and to establish the prediction models.

Methods: Based on Taiwan's National Health Insurance Research Database, a longitudinal study was conducted from 2000 to 2012. Descriptive statistics were adopted to analyze the frequencies and distributions of nuclear medicine procedures. Multiple linear regression analysis was applied to establish the prediction model for the utilization of nuclear medicine.

Results: The utilization of myocardial perfusion imaging increased most significantly, i.e. 250 per million population (pmp) increment annually, followed by the whole-body bone scan (176 pmp) and whole-body PET scan (100 pmp) in Taiwan during the period of 2000-2012. The use rate of nuclear medicine procedure which the first quartile (Q1) of age at examination above 35 years fits the regression model: Use rate expected year = 0.03 Q1 of age at examination × use rate baseline year + 14797 life expectancy expected year / life expectancy baseline year - 15030. Adversely, the use rate of procedure which Q1 of age at examination below 35 years fits the model: Use rate expected year = 0.01 Q1 of age at examination × use rate baseline year - 4565 life expectancy expected year / life expectancy baseline year + 4749. In addition, the similar models were found in the applications of radiopharmaceuticals.

Conclusion: This study demonstrates the age at examination and life expectancy can be used to predict the utilities of nuclear medicine procedures and radiopharmaceuticals in an aging population. Nuclear medicine practice applied in the geriatrics would increase significantly with the aging of population.

Keywords: Nuclear medicine; life expectancy; prediction model; radiopharmaceuticals.

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