Long-term risk of cervical cancer following conization of cervical intraepithelial neoplasia grade 3-A Danish nationwide cohort study.
Freja Laerke SandKirsten FrederiksenChristian MunkSigne Marie JensenSusanne K KjaerPublished in: International journal of cancer (2017)
Using nationwide Danish registries we examined the long-term risk of cervical cancer in women diagnosed with cervical intraepithelial neoplasia grade 3 (CIN3) (including adenocarcinoma in situ (AIS)) on the cone compared to women with a normal cytology test. Initially, we identified women born 1918-1990, who were recorded as living in Denmark between January 1, 1978 and December 31, 2012. From the Pathology Data Bank information on CIN3 on the cone, margins status, histological type of CIN3 and cervical cytology results was extracted. Cox proportional hazard model was used to estimate the relative risk of subsequent cervical cancer. We included 59,464 women with CIN3 on the cone and 1,918,508 women with a normal cytology test. Overall, women diagnosed with CIN3 had a higher risk of subsequent cervical cancer compared to women with normal cytology (HR = 2.06; 95%CI: 1.81-2.35). Analyses according to time since conization showed elevated risks in all time periods, and 25 years or more after conization the relative risk was significantly increased (HR = 2.56; 95%CI: 1.37-4.77). Twenty years or more after conization, also women with negative margins had an increased relative risk (HR = 2.49; 95%CI: 1.12-5.57). In addition, the long-term relative risk of cervical cancer varied with the different histological types of CIN3 and was highest for AIS (HR = 7.50; 95%CI: 1.87-30.01, 10-14 years after conization). In conclusion, women diagnosed with CIN3 on the cone have a long-lasting increased risk of cervical cancer even when the margins on the cone are negative.
Keyphrases
- high grade
- polycystic ovary syndrome
- fine needle aspiration
- pregnancy outcomes
- breast cancer risk
- cervical cancer screening
- squamous cell carcinoma
- ultrasound guided
- cross sectional
- insulin resistance
- pregnant women
- healthcare
- metabolic syndrome
- low birth weight
- adipose tissue
- locally advanced
- big data
- health information
- deep learning
- rectal cancer