Full metadata record
DC Field | Value | Language |
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dc.contributor.author | 정지은 | - |
dc.date.accessioned | 2021-11-30T02:20:35Z | - |
dc.date.available | 2021-11-30T02:20:35Z | - |
dc.date.issued | 2021-06 | - |
dc.identifier.citation | JOURNAL OF PERSONALIZED MEDICINE, v. 11, no. 6, Article no. 541, 10pp | en_US |
dc.identifier.issn | 2075-4426 | - |
dc.identifier.uri | https://www.proquest.com/docview/2544883606?accountid=11283 | - |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/166584 | - |
dc.description.abstract | Objective: This nested case-control study aimed to investigate the effects of VEGFA polymorphisms on the development of bisphosphonate-related osteonecrosis of the jaw (BRONJ) in women with osteoporosis. Methods: Eleven single nucleotide polymorphisms (SNPs) of the VEGFA were assessed in a total of 125 patients. Logistic regression was performed for multivariable analysis. Machine learning algorithms, namely, fivefold cross-validated multivariate logistic regression, elastic net, random forest, and support vector machine, were developed to predict risk factors for BRONJ occurrence. Area under the receiver-operating curve (AUROC) analysis was conducted to assess clinical performance. Results: The VEGFA rs881858 was significantly associated with BRONJ development. The odds of BRONJ development were 6.45 times (95% CI, 1.69-24.65) higher among carriers of the wild-type rs881858 allele compared with variant homozygote carriers after adjusting for covariates. Additionally, variant homozygote (GG) carriers of rs10434 had higher odds than those with wild-type allele (OR, 3.16). Age ˃= 65 years (OR, 16.05) and bisphosphonate exposure ˃= 36 months (OR, 3.67) were also significant risk factors for BRONJ occurrence. AUROC values were higher than 0.78 for all machine learning methods employed in this study. Conclusion: Our study showed that the BRONJ occurrence was associated with VEGFA polymorphisms in osteoporotic women. | en_US |
dc.description.sponsorship | This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2018R1D1A1B07049959) and Institute of Information and Communications Technology Planning and Evaluation (IITP) grant funded by the Korea Government (no. 2020-0-01343, Artificial Intelligence Convergence Research Center, Hanyang University ERICA). | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | MDPI | en_US |
dc.subject | bisphosphonate-related osteonecrosis | en_US |
dc.subject | VEGFA | en_US |
dc.subject | gene polymorphism | en_US |
dc.subject | machine learning | en_US |
dc.title | Machine Learning Approaches for Predicting Bisphosphonate-Related Osteonecrosis in Women with Osteoporosis Using VEGFA Gene Polymorphisms | en_US |
dc.type | Article | en_US |
dc.relation.no | 6 | - |
dc.relation.volume | 11 | - |
dc.identifier.doi | 10.3390/jpm11060541 | - |
dc.relation.page | 1-10 | - |
dc.relation.journal | JOURNAL OF PERSONALIZED MEDICINE | - |
dc.contributor.googleauthor | Kim, Jin-Woo | - |
dc.contributor.googleauthor | Yee, Jeong | - |
dc.contributor.googleauthor | Oh, Sang-Hyeon | - |
dc.contributor.googleauthor | Kim, Sun-Hyun | - |
dc.contributor.googleauthor | Kim, Sun-Jong | - |
dc.contributor.googleauthor | Chung, Jee-Eun | - |
dc.contributor.googleauthor | Gwak, Hye-Sun | - |
dc.relation.code | 2021009025 | - |
dc.sector.campus | E | - |
dc.sector.daehak | COLLEGE OF PHARMACY[E] | - |
dc.sector.department | DEPARTMENT OF PHARMACY | - |
dc.identifier.pid | jechung | - |
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