Back

Cost-effectiveness of dementia insurance for cognitively-unimpaired APOE -ε4 homozygotes: a simulation study

Sato, K.; Nakashima, S.; Niimi, Y.; Iwatsubo, T.

2024-11-12 health economics
10.1101/2024.11.12.24317164 medRxiv
Show abstract

Dementia insurance, a private insurance product covering the first diagnosis of dementia of the insured, may be economical for asymptomatic individuals who are aware of their own high genetic risk of developing Alzheimers disease (AD) in advance. This is a retrospective study conducted based on National Alzheimers Coordinating Center (NACC) data including cognitively unimpaired individuals, aiming to simulate income and expenses of dementia insurance for the insured perspectives. Loss ratio (= total benefits gained / total premium paid) was calculated by APOE-{varepsilon}4 subgroup as a measure of cost-effectiveness, applying the premium rates of actual dementia insurance products being sold in Japan. As a result, for up to 18 years of longitudinal follow-up, the estimated cost-effectiveness improved over the longer observation periods. In individuals in their 60s or older at baseline, the cost-effectiveness was best in the APOE-{varepsilon}4 homozygotes, followed by heterozygotes, and {varepsilon}4-negative individuals. The dementia insurance for {varepsilon}4-homozygotes for observation periods [≥] 10 years in this age group was approximately 3 to 4 times more economical than for {varepsilon}4-negative individuals. Although actively pursuing APOE testing for asymptomatic individuals may not be currently recommended due to the concern of adverse selection in the insurance and the absence of available disease-modifying therapy approved for the preclinical stage of AD, our study may provide an important basis for further investigating the advantages and limitations of dementia insurance for asymptomatic individuals with pathogenic or high-risk genes.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.