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. Author manuscript; available in PMC: 2020 Nov 1.
Published in final edited form as: Gynecol Oncol. 2019 Sep 5;155(2):294–300. doi: 10.1016/j.ygyno.2019.08.032

Table 3.

Associations between metabolic syndrome, its components, and tumor grade for selected histotypes of ovarian and fallopian tube cancer, SEER-Medicare linked data (1994–2013)

Serous
High Grade
n=4 622
Serous
Low Grade
n=1 119
Pc Endometrioid
High Grade
n=472
Endometrioid
Low Grade
n=532
Pc Other Epithelial
High Grade
n=1 978
Other Epithelial
Low Grade
n=420
Pc Pd
ORb 95% CI ORb 95% CI ORb 95% CI ORb 95% CI ORb 95% CI ORb 95% CI
Metabolic Syndromea
(≥3 vs.<3) 0.73 0.68–0.79 0.85 0.72–1.00 0.31 1.03 0.81–1.30 0.83 0.66–1.04 0.24 0.91 0.81–1.03 1.05 0.82–1.36 0.50 0.01
Number of metabolic syndrome components 0.63 0.12 0.86 0.09
0 -- Ref -- Ref -- Ref -- Ref -- Ref -- Ref
1 1.22 1.12–1.33 1.30 1.10–1.54 1.27 0.98–1.66 1.53 1.17–1.98 1.41 1.24–1.61 1.50 1.13–2.00
2 1.19 1.09–1.30 1.41 1.19–1.67 1.26 0.96–1.64 1.67 1.29–2.16 1.41 1.24–1.62 1.43 1.06–1.91
≥3 0.85 0.77–0.94 1.08 0.88–1.33 1.23 0.91–1.67 1.18 0.87–1.60 1.20 1.03–1.40 1.44 1.03–2.00
Components of Metabolic Syndrome
Overweight/obesity 0.71 0.63–0.80 0.83 0.65–1.05 0.38 0.78 0.54–1.14 0.69 0.49–0.99 0.52 0.85 0.71–1.01 1.13 0.80–1.59 0.17 0.53
Impaired fasting glucose 0.79 0.74–0.85 0.80 0.69–0.92 0.68 0.91 0.73–1.13 0.80 0.65–0.98 0.55 0.91 0.82–1.02 0.98 0.78–1.24 0.70 0.14
Hypertension 0.93 0.87–1.00 1.17 1.02–1.33 0.09 1.08 0.88–1.33 1.64 1.33–2.02 0.001 1.22 1.10–1.35 1.29 1.03–1.61 0.98 0.01
High triglycerides 1.10 1.03–1.17 1.29 1.13–1.47 0.43 1.37 1.12–1.68 1.07 0.89–1.29 0.22 1.16 1.05–1.28 1.30 1.05–1.61 0.47 0.34

n=number, OR= odds ratio, CI=confidence interval

a

Metabolic syndrome was defined as diagnoses for 3 or more components of metabolic syndrome (central adiposity or overweight/obesity, impaired fasting glucose [including type II diabetes], hypertension, high triglycerides, low HDL cholesterol) and/or a diagnosis of ‘dysmetabolic syndrome.’ Women meeting this definition were compared to a referent group of those not meeting it (i.e., including those with diagnoses for only one or two of the components). When comparing the number of metabolic syndrome components with which women were diagnosed, those without diagnoses for any of the components are the reference group (‘dysmetabolic syndrome’ not considered in this categorization).

b

Logistic regression models were run separately for each exposure and each case group (comparing to controls as the reference). Models were adjusted for diagnosis date, age, race, geographic location, state Medicare buy-in, medical history of smoking or tobacco use, and length of Medicare enrollment.

c

Chi-square test P values to assess heterogeneity by grade within histotypes. For each histotype, we used case-only logistic regression models comparing women with low grade tumors to women with high grade tumors (reference group) to obtain effect estimate p values for metabolic syndrome and each of its components.

d

Chi square test P values to assess heterogeneity by histotype among high grade cancers. We used case-only non-ordinal multinomial logistic models comparing women with high grade endometrioid tumors and high grade other epithelial tumors to those with high grade serous tumors (reference) and obtained effect estimate p values for metabolic syndrome and each of its components.