Hypertension and hyperglycaemia are positively correlated with local invasion of early cervical cancer
Background
Metabolic disorders are involved in the development of numerous cancers, but their association with the progression of cervical cancer is unclear. This study aims to investigate the association between metabolic disorders and the pathological risk factors and survival in patients with early cervical cancer.
Methods
Patients with FIGO IB1 (2009) primary cervical cancer who underwent radical hysterectomy and systematic pelvic lymph node dissection at our institution from October 2014 to December 2017 were included retrospectively. Clinical data regarding the metabolic syndrome and surgical pathology of the patient were collected. The correlations between metabolic disorders (hypertension, hyperglycemia, and obesity) and clinicopathological characteristics as well as survival after surgery were analyzed.
Results
The study included 246 patients with clinical IB1 cervical cancer, 111 (45.1%) of whom had at least one of the comorbidities of hypertension, obesity, or hyperglycemia. Hypertension was positively correlated with parametrial invasion and poorly differentiated histology; hyperglycemia was positively correlated with stromal invasion; obesity was negatively associated with lymph node metastasis; but arbitrary disorder did not show any correlation with pathologic features. Hypertension was an independent risk factor for parametrial invasion (OR=6.54, 95% CI: 1.60-26.69); hyperglycemia was an independent risk factor for stromal invasion (OR=2.05, 95% CI: 1.07-3.95); and obesity was an independent protective factor for lymph node metastasis (OR=0.07, 95% CI: 0.01-0.60). Moreover, the patients with hypertension had a significantly lower 5-year OS rate (70.0% vs. 95.3%, P<0.0001) and a significantly lower 5-year PFS rate than those without hypertension (70.0% vs. 91.2%, P=0.010).
Conclusion
Hypertension and hyperglycemia are positively associated with local invasion of early cervical cancer, which need to be verified in multi-center, large scale studies.