Browsing by Author "Milks, M. Wesley"

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    A multistate transition model for statin‐induced myopathy and statin discontinuation
    (Wiley, 2021) Zhu, Yuxi; Chiang, Chien-Wei; Wang, Lei; Brock, Guy; Milks, M. Wesley; Cao, Weidan; Zhang, Pengyue; Zeng, Donglin; Donneyong, Macarius; Li, Lang; Biostatistics and Health Data Science, Richard M. Fairbanks School of Public Health
    The overarching goal of this study was to simultaneously model the dynamic relationships among statin exposure, statin discontinuation, and potentially statin-related myopathic outcomes. We extracted data from the Indiana Network of Patient Care for 134,815 patients who received statin therapy between January 4, 2004, and December 31, 2008. All individuals began statin treatment, some discontinued statin use, and some experienced myopathy and/or rhabdomyolysis while taking the drug or after discontinuation. We developed a militate model to characterize 12 transition probabilities among six different states defined by use or discontinuation of statin and its associated myopathy or rhabdomyolysis. We found that discontinuation of statin therapy was common and frequently early, with 44.4% of patients discontinuing therapy after 1 month, and discontinuation is a strong indicator for statin-induced myopathy (risk ratio, 10.8; p < 0.05). Women more likely than men (p < 0.05) and patients aged 65 years and older had a higher risk than those aged younger than 65 years to discontinue statin use or experience myopathy. In conclusion, we introduce an innovative multistate model that allows clear depiction of the relationship between statin discontinuation and statin-induced myopathy. For the first time, we have successfully demonstrated and quantified the relative risk of myopathy between patients who continued and discontinued statin therapy. Age and sex were two strong risk factors for both statin discontinuation and incident myopathy.
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    Transferrin predicts trimethylamine-N-oxide levels and is a potential biomarker of cardiovascular disease
    (BMC, 2022-05-10) Bean, Lamuel D.; Wing, Jeffrey J.; Harris, Randall E.; Smart, Suzanne M.; Raman, Subha V.; Milks, M. Wesley; Medicine, School of Medicine
    Introduction: Trimethylamine-N-oxide (TMAO) is a circulating biomarker associated with cardiovascular disease (CVD). Production of TMAO is facilitated by gut microbiota and dependent on micronutrients such as choline, betaine, and L-carnitine, present in foods such as red meat and eggs. Hypothesis: We sought to predict serum TMAO quartile levels among healthy individuals at increased risk of CVD using clinical data via an ordinal logistic model. Methods: Data from participants (n = 127) enrolled in a longitudinal observational study on CVD were used to build a predictive model for TMAO using ordinal logistic regression with demographic variables and 40 other variables considered related to CVD risk. First, univariate models for each covariate were tested (with serum TMAO quartiles as the dependent variable), and only variables with P < 0.30 were evaluated further. Second, demographic variables (age, gender, white vs. non-white race) were included in a multivariable model with each previously identified independent variable controlling for potential confounding. Last, the final model included fixed demographics and candidates from the confounder-adjusted model with P < 0.10. Results: Eight candidate variables were included in the final model, with only transferrin, high-density lipoprotein cholesterol (HDL-C) and race (white vs. non-white) showing significant associations with TMAO. Participants had 0.16 (Q2), 0.31 (Q3), and 0.20 (Q4) odds of being in a higher TMAO quartile compared with participants in the lowest transferrin quartile. Non-white participants had 2.92 times higher odds of being in the highest TMAO quartile compared to white individuals. Participants in the second quartile of HDL-C had 2.68 times higher odds of being in a higher TMAO quartile compared with participants in the lowest HDL-C quartile. Conclusions: Transferrin demonstrated a significant predictive association with TMAO and may represent a novel potential biomarker of increased CVD risk worthy of further study. These results warrant further examination of iron, metabolism, homeostasis, and gut microbiome to better understand and mitigate known increased CVD risk.