In these two instances, the Status Quo maximized life expectancy per cohort.
While this model was developed to address efficiency concerns and maximize life expectancy per cohort, instances could arise in which concerns about equity override efficiency.
Therefore, in this model, which maximizes life expectancy per cohort, the remaining fraction of a previous cohort would not be selected to receive ART if competing with newly detected individuals who could achieve higher life expectancy.
With more modest capacity increases over time, discontinuing treatment not only maximizes life expectancy per cohort, but also allows more individuals to receive treatment, improving both efficiency and equity.
Although the primary goal of any innovative treatment for prostate cancer is to maximize life expectancy, both patients and clinicians are currently devoting more attention to the impact of current therapies on QoL outcomes [ 3].
With greater capacity increases over time, however, the Status Quo (i.e., not discontinuing treatment) maximizes life expectancy per cohort, yet does not allow more individuals to receive treatment.
The Alternative strategy maximized life expectancy per cohort and the number initiating ART annually unless treatment capacity exceeded 175,000 slots (corresponding to antiretroviral coverage of approximately 85%) or, alternatively, when the annual incidence of newly detected cases was <10,000 per year.
In 2013, discussion shifted to a goal of maximizing healthy life expectancy, which would subsume universal health coverage as a subsidiary target and also include a focus on underlying determinants of health [ 14, 35].
Hence, there is a need to maximize the life expectancy of primary joint implants through understanding cell material interactions.
A problem with the approach is that whilst it might help maximize overall life expectancy from available transplants it discriminates against the old [ 32].
