Health Economic Evaluation Model for Ovarian Cancer Risk Management Through Preimplantation Genetic Testing for Monogenic Disorders (PGT-M)
Author(s)
Mana AKAI1, Saki Ozeki, BS2, Ryutaro Sakai, BS3, Seiya Taniguchi, BS3, Kensuke Moriwaki, BS, MS, PhD4, Tsuguo Iwatani, MD, PhD5, Nao Suzuki, MD, PhD5.
1Student, Ritsumeikan University, Kusatsu, Japan, 2Ritsumeikan university, Kusatsu, Japan, 3Ritsumeikan University, Kusatsu, Japan, 4Ritsumeikan University, Kyoto, Japan, 5St. Marianna University School of Medicine, Kawasaki, Japan.
1Student, Ritsumeikan University, Kusatsu, Japan, 2Ritsumeikan university, Kusatsu, Japan, 3Ritsumeikan University, Kusatsu, Japan, 4Ritsumeikan University, Kyoto, Japan, 5St. Marianna University School of Medicine, Kawasaki, Japan.
OBJECTIVES: Individuals who carry pathogenic variants of the BRCA1/2 genes have an increased risk of developing cancer, particularly a very high risk of ovarian cancer. The BRCA1/2 genes are inherited by the children of carriers, and PGT-M is a method for controlling this genetic risk. This study aimed to evaluate the impact of PGT-M on health outcomes, specifically focusing on life expectancy as an indicator of ovarian cancer risk control.
METHODS: A Markov model was constructed by dividing ovarian cancer-related prognosis into five states, and long-term survival estimates were calculated for the PGT-M group and the natural pregnancy group. In the natural pregnancy group, it was assumed that BRCA1/2 mutations occur with a 50% probability, increasing the risk of ovarian cancer. On the other hand, in the PGT-M group, survival was assumed to follow standard risk, and the expected additional years of life gained by controlling BRCA1/2 mutations were evaluated. Additionally, sensitivity analysis was conducted to assess the impact of uncertainty in the odds ratio for cancer incidence.
RESULTS: In cases where the mutation was positive, the expected survival years for the naturally conceived group with BRCA1 mutations, the naturally conceived group with BRCA2 mutations, and the PGT-M group were 81.458 years, 86.802 years, and 87.974 years, respectively.
CONCLUSIONS: When risk control for BRCA1/2 mutations is performed using PGT-M, compared to the natural pregnancy group with these mutations, overall survival is extended and survival in cancer-bearing states is shortened. Therefore, when considering the difference in utility values between cancer-free and cancer-bearing states, a certain improvement in quality-adjusted life years (QALYs) is expected. To verify the cost-effectiveness of this technology in the future, it will be necessary to estimate not only the utility values but also the medical costs associated with this technology and ovarian cancer.
METHODS: A Markov model was constructed by dividing ovarian cancer-related prognosis into five states, and long-term survival estimates were calculated for the PGT-M group and the natural pregnancy group. In the natural pregnancy group, it was assumed that BRCA1/2 mutations occur with a 50% probability, increasing the risk of ovarian cancer. On the other hand, in the PGT-M group, survival was assumed to follow standard risk, and the expected additional years of life gained by controlling BRCA1/2 mutations were evaluated. Additionally, sensitivity analysis was conducted to assess the impact of uncertainty in the odds ratio for cancer incidence.
RESULTS: In cases where the mutation was positive, the expected survival years for the naturally conceived group with BRCA1 mutations, the naturally conceived group with BRCA2 mutations, and the PGT-M group were 81.458 years, 86.802 years, and 87.974 years, respectively.
CONCLUSIONS: When risk control for BRCA1/2 mutations is performed using PGT-M, compared to the natural pregnancy group with these mutations, overall survival is extended and survival in cancer-bearing states is shortened. Therefore, when considering the difference in utility values between cancer-free and cancer-bearing states, a certain improvement in quality-adjusted life years (QALYs) is expected. To verify the cost-effectiveness of this technology in the future, it will be necessary to estimate not only the utility values but also the medical costs associated with this technology and ovarian cancer.
Conference/Value in Health Info
2025-11, ISPOR Europe 2025, Glasgow, Scotland
Value in Health, Volume 28, Issue S2
Code
MT24
Topic
Economic Evaluation, Health Technology Assessment, Medical Technologies
Disease
Genetic, Regenerative & Curative Therapies, Oncology