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利用大型电子健康记录人群评估子宫肌瘤大小和数量差异的风险因素。

Evaluating risk factors for differences in fibroid size and number using a large electronic health record population.

机构信息

Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, United States.

Institute for Medicine and Public Health, Vanderbilt University Medical Center, Nashville, TN, United States.

出版信息

Maturitas. 2018 Aug;114:9-13. doi: 10.1016/j.maturitas.2018.05.003. Epub 2018 May 11.

Abstract

OBJECTIVE

To evaluate individual characteristics of women with fibroids in relation to fibroid size and number.

METHODS

This cross-sectional study involved 2302 women (black and white, age range 18-87) with image- or surgery-confirmed fibroids from the Synthetic Derivative, a database of de-identified demographic and clinical information from patient electronic health records (EHRs) from the Vanderbilt University Medical Center. We performed multivariate regression analyses on the following outcomes: volume of largest fibroid, largest dimension of all fibroids, and number of fibroids (single vs multiple). Candidate risk factors included age at diagnosis, body mass index (BMI), race, type 2 diabetes status, and number of living children (a proxy for parity). We assessed potential effect measure modification by race and both age and BMI using a likelihood ratio test.

RESULTS

Black race was strongly associated with having multiple fibroids (adjusted odds ratio [aOR]: 1.83, 95% confidence interval [CI]: 1.49, 2.24) and larger fibroid volume (adjusted beta: 1.77, 95% CI: 1.38, 2.27) and greater largest dimension (adjusted beta: 1.28, 95% CI: 1.18, 1.38). Having multiple fibroids was most strongly associated with ages 43-47 (aOR = 3.37, 95% CI: 2.55, 4.46) compared with the youngest age group (ages 18-36). Having a larger number of living children was associated with having single a fibroid (aOR: 0.88, 95% CI: 0.78, 0.99).

CONCLUSIONS

Our findings suggest that different underlying etiologies are involved for women developing single versus multiple fibroids and small versus large fibroids. Studies are needed of the mechanisms by which these characteristics influence fibroid formation and growth.

摘要

目的

评估与肌瘤大小和数量相关的子宫肌瘤患者的个体特征。

方法

本横断面研究纳入了 2302 名(黑人和白人,年龄 18-87 岁)来自合成衍生数据库的患有经影像学或手术证实的子宫肌瘤的女性患者,该数据库是范德比尔特大学医学中心患者电子健康记录(EHR)中匿名人口统计学和临床信息的数据库。我们对以下结果进行了多变量回归分析:最大肌瘤体积、所有肌瘤的最大尺寸和肌瘤数量(单发 vs 多发)。候选风险因素包括诊断时年龄、体重指数(BMI)、种族、2 型糖尿病状态和活产子女数(代表生育次数)。我们使用似然比检验评估了种族以及年龄和 BMI 对潜在效应测量的修饰作用。

结果

黑人种族与多发性子宫肌瘤(调整后的优势比 [aOR]:1.83,95%置信区间 [CI]:1.49,2.24)和更大的肌瘤体积(调整后的β:1.77,95% CI:1.38,2.27)和更大的最大尺寸(调整后的β:1.28,95% CI:1.18,1.38)显著相关。与最年轻的年龄组(18-36 岁)相比,多发性子宫肌瘤与 43-47 岁年龄组的相关性最强(aOR=3.37,95% CI:2.55,4.46)。生育更多活产子女与单发肌瘤相关(aOR:0.88,95% CI:0.78,0.99)。

结论

我们的研究结果表明,患有单发或多发子宫肌瘤以及小肌瘤或大肌瘤的女性,其潜在病因不同。需要研究这些特征影响子宫肌瘤形成和生长的机制。

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