. 2018 Jan;34(1):66–76. doi: 10.6515/ACS.201801_34(1).20170901B

Table 2. Multivariate logistic regression model to assess the associations between uterine leiomyoma and VTE.

	VTE case	Control	Adjusted odds ratio^{Model 1} (95 % CI)	p value	Adjusted odds ratio^{Model 2} (95 % CI)	p value
Before matching data
Non-leiomyoma	2166 (94.92%)	375659 (95.68%)	1 (reference)		1 (reference)
Leiomyoma	116 (5.08%)	16955 (4.32%)	1.464 (1.2-1.78)	0.0001	1.547 (1.27-1.88)	< 0.0001
Frequency matching data
Non-leiomyoma	2166 (94.92%)	8798 (96.38%)	1 (reference)		1 (reference)
Leiomyoma	116 (5.08%)	330 (3.62%)	1.485 (1.17-1.88)	0.0011	1.486 (1.19-1.86)	0.0005
Propensity score matching data
Non-leiomyoma	2116 (95.02%)	8334 (95.90%)	1 (reference)		1 (reference)
Leiomyoma	111 (4.98%)	356 (4.10%)	1.287 (1.03-1.61)	0.025	1.26 (1.01-1.57)	0.0405

Model 1 adjusted for uterine leiomyoma and the significantly different variables in Table 1. Model 2 adjusted for uterine leiomyoma, age and propensity score.

VTE, venous thromboembolism.