Supplementary Table 2. Multivariate logistic regression model to assess the associations between uterine leiomyoma and VTE. We carried out a sensitivity analysis in diagnosis of uterine leiomyoma and VTE identified using a stringent criterion. The analysis showed that the association between uterine leiomyoma and VTE was in agreement with the results in Table 2. Sensitivity table:

	VTE case#	Control	Adjusted odds ratioModel 1 (95 % CI)	p-value	Adjusted odds ratioModel 2 (95 % CI)	p-value
Before matching data
Non-leiomyoma	1550 (96.15%)	377760 (96.05%)	1 (reference)		1 (reference)
Leiomyoma*	62 (3.85%)	15524 (3.95%)	1.417 (1.087-1.846)	0.01	1.444 (1.107-1.883)	0.0067
Frequency matching data
Non-leiomyoma	1550 (96.15%)	6243 (96.82%)	1 (reference)		1 (reference)
Leiomyoma*	62 (3.85%)	205 (3.18%)	1.645 (1.190-2.274)	0.0026	1.371 (1.015-1.851)	0.0397
Propensity score matching data
Non-leiomyoma	1536 (96.3%)	6158 (97.13%)	1 (reference)		1 (reference)
Leiomyoma*	59 (3.7%)	182 (2.87%)	1.456 (1.071-1.979)	0.0164	1.464 (1.081-1.982)	0.0137

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

* The diagnosis of leiomyoma was confirmed by gynecologic ultrasound. ^# The diagnosis of VTE was confirmed using patients received anticoagulation therapy.

VTE, venous thromboembolism.