Effect Modification by Social Determinants of Pharmacogenetic Medication Interactions on 90-Day Hospital Readmissions within an Integrated U.S. Healthcare System.
Effect Modification by Social Determinants of Pharmacogenetic Medication Interactions on 90-Day Hospital Readmissions within an Integrated U.S. Healthcare System.
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DOI：
10.3390/jpm12071145
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发表时间：
2022-07-15
影响因子：
--
通讯作者：
David, Sean P.
中科院分区：
文献类型：
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作者：
Saulsberry, Loren;Singh, Lavisha;Pruitt, Jaclyn;Ward, Christopher;Wake, Dyson T.;Gibbons, Robert D.;Meltzer, David O.;O'Donnell, Peter H.;Cruz-Knight, Wanda;Hulick, Peter J.;Dunnenberger, Henry M.;David, Sean P.
本研究建立在我们先前的工作，证明了药物遗传学相互作用和90天再入院之间的关联。在2010年至2020年跟踪的19，999名成年人的更大，更多样化的研究人群中，我们使用13个基因的药物遗传学面板进行了测试，我们纳入了额外的协变量，以评估社会决定因素和医学共病的总体贡献，并确定基因-x-药物相互作用对中度90天再入院（主要结局）的存在。单变量logistic回归分析表明，与90天再入院最强的相关性是首次入院后30天内根据临床药物基因组学实施联盟（CPIC）指南开具的药物数量（CPIC药物）（5+ CPIC药物，比值比（OR）= 7.66，95%置信区间5.45-10.77）（p < 0.0001），主要合并症（5+合并症，OR 3.36，2.61-4.32）（p < 0.0001），年龄（65岁以上，OR = 2.35，1.77-3.12）（p < 0.0001），失业（OR = 2.19，1.88-2.64）（p < 0.0001），黑人/非裔美国人（OR 2.12，1.47-3.07）（p < 0.0001），家庭收入中位数（OR = 1.63，1.03-2.58）（p = 0.035），男性（OR = 1.47，1.21-1.80）（p = 0.0001），以及一种或多种基因-X-药物相互作用（定义为具有相应可操作药物遗传学变异的患者的处方CPIC药物）（OR = 1.41，1.18-1.70）。健康保险与90天再入院风险无关。种族、收入、就业状况和基因-X-药物相互作用在多变量逻辑回归模型中是稳健的。在调整这些协变量后，具有一种或多种确定的基因-x-药物相互作用的患者90天再入院的几率降低了10%（OR = 1.31，1.08-1.59）（p = 0.006）。虽然种族和基因-x-药物相互作用之间的相互作用在统计学上不显著，但白色患者发生基因-x-药物相互作用的可能性（35.2%）高于未再次入院的黑人/非洲裔美国人患者（25.9%）（p < 0.0001）。这些结果突出了社会决定因素和医疗复杂性对再入院风险的主要贡献，这些决定因素可能会改变基因-X-药物相互作用对再住院风险的影响。
The present study builds on our prior work that demonstrated an association between pharmacogenetic interactions and 90-day readmission. In a substantially larger, more diverse study population of 19,999 adults tracked from 2010 through 2020 who underwent testing with a 13-gene pharmacogenetic panel, we included additional covariates to evaluate aggregate contribution of social determinants and medical comorbidity with the presence of identified gene-x-drug interactions to moderate 90-day hospital readmission (primary outcome). Univariate logistic regression analyses demonstrated that strongest associations with 90 day hospital readmissions were the number of medications prescribed within 30 days of a first hospital admission that had Clinical Pharmacogenomics Implementation Consortium (CPIC) guidance (CPIC medications) (5+ CPIC medications, odds ratio (OR) = 7.66, 95% confidence interval 5.45–10.77) (p < 0.0001), major comorbidities (5+ comorbidities, OR 3.36, 2.61–4.32) (p < 0.0001), age (65 + years, OR = 2.35, 1.77–3.12) (p < 0.0001), unemployment (OR = 2.19, 1.88–2.64) (p < 0.0001), Black/African-American race (OR 2.12, 1.47–3.07) (p < 0.0001), median household income (OR = 1.63, 1.03–2.58) (p = 0.035), male gender (OR = 1.47, 1.21–1.80) (p = 0.0001), and one or more gene-x-drug interaction (defined as a prescribed CPIC medication for a patient with a corresponding actionable pharmacogenetic variant) (OR = 1.41, 1.18–1.70). Health insurance was not associated with risk of 90-day readmission. Race, income, employment status, and gene-x-drug interactions were robust in a multivariable logistic regression model. The odds of 90-day readmission for patients with one or more identified gene-x-drug interactions after adjustment for these covariates was attenuated by 10% (OR = 1.31, 1.08–1.59) (p = 0.006). Although the interaction between race and gene-x-drug interactions was not statistically significant, White patients were more likely to have a gene-x-drug interaction (35.2%) than Black/African-American patients (25.9%) who were not readmitted (p < 0.0001). These results highlight the major contribution of social determinants and medical complexity to risk for hospital readmission, and that these determinants may modify the effect of gene-x-drug interactions on rehospitalization risk.
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影响因子：
1.9
作者：
Takahashi PY;Ryu E;Bielinski SJ;Hathcock M;Jenkins GD;Cerhan JR;Olson JE
通讯作者：
Olson JE
DOI：
10.1037/hea0000242
发表时间：
2016-04
期刊：
Health psychology : official journal of the Division of Health Psychology, American Psychological Association
影响因子：
--
作者：
Williams DR;Priest N;Anderson NB
通讯作者：
Anderson NB
影响因子：
3.7
作者：
David V;Fylan B;Bryant E;Smith H;Sagoo GS;Rattray M
通讯作者：
Rattray M
影响因子：
1.9
作者：
Takahashi, Paul Y.;Ryu, Euijung;Bielinski, Suzette J.
通讯作者：
Bielinski, Suzette J.
DOI：
10.1016/j.lana.2022.100220
发表时间：
2022-06
期刊：
Lancet regional health. Americas
影响因子：
--
作者：
Bilal U;Jemmott JB;Schnake-Mahl A;Murphy K;Momplaisir F
通讯作者：
Momplaisir F