Prediction of medication-related osteonecrosis of the jaws using machine learning methods from estrogen receptor 1 polymorphisms and clinical information.

Objective: The purpose of this study was to evaluate the effect of estrogen receptor 1 (ESR1) polymorphisms on the development of medication-related osteonecrosis of the jaws (MRONJ) in women with osteoporosis. Methods: A total of 125 patients taking bisphosphonates was evaluated the relationship between MRONJ occurrence and single nucleotide polymorphisms (SNPs) of ESR1. Clinical information was collected, including current age, treatment duration, and comorbidity. Univariate and Multivariable regression analyzes were performed to evaluate the independent predictive factors for MRONJ occurrence. Predictive models were constructed using machine learning methods such as Lasso regression, Random forest (RF), and Support vector machine (SVM). The area under the receiver-operating curve (AUROC) was used to evaluate the performance of a binary classifier. Result: Two SNPs of ESR1 (rs4870056 and rs78177662) were significantly associated with MRONJ development. Patients with variant allele (A) of rs4870056 showed 2.45 times (95% CI, 1.03-5.87) the odds of MRONJ occurrence compared to those with wild-type homozygote (GG) after adjusting covariates. Additionally, carriers with variant allele (T) of rs78177662 had higher odds than those with wild-type homozygote (CC) (adjusted odds ratio (aOR), 2.64, 95% CI, 1.00-6.94). Among demographic variables, age ≥ 72 years (aOR, 3.98, 95% CI, 1.60-9.87) and bisphosphonate exposure ≥48 months (aOR, 3.16, 95% CI, 1.26-7.93) were also significant risk factors for MRONJ occurrence. AUROC values of machine learning methods ranged between 0.756-0.806 in the study. Conclusion: Our study showed that the MRONJ occurrence was associated with ESR1 polymorphisms in osteoporotic women.

Nutrition Therapy by Nutrition Support Team: A Comparison of Multi-Chamber Bag and Customized Parenteral Nutrition in Hospitalized Patients.

This study aimed to investigate the activity of a nutrition support team (NST) and the trends of multi-chamber bag (MCB) and customized parenteral nutrition (PN) with NST consultations in South Korea. Data were obtained from the National Inpatient Sample Cohort between 2015 and 2020. Three datasets were constructed for NST consultation, MCB-PN product prescriptions, and aseptic preparation of total PN. The intersections of the NST consultation and each PN dataset were compiled into MCB-PN with NST or customized PN with a NST sub-dataset, respectively. Using personal identifiers, the patients' characteristics were evaluated in the NST cohort. A total of 91,384 reimbursements and 70,665 patients were included. The NST activity had increased by more than 50% over 6 years. Approximately 70% and 11%, respectively, of the NST cohort were classified into two subgroups: MCB-PN with NST (M-NST) and customized PN with NST (C-NST). M-NST had many elderly patients with cancer and showed a higher in-hospital mortality than C-NST (12.6% vs. 9.5%). C-NST included a larger number of patients under the age of 5 years, and the hospitalization period was more extended than M-NST (26.2 vs. 21.2 days). The present study showed that NST activities and the proportion of PN with NST consultation are gradually increasing in South Korea.

Machine Learning Approaches for Predicting Bisphosphonate-Related Osteonecrosis in Women with Osteoporosis Using VEGFA Gene Polymorphisms.

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.