Chrome Extension
WeChat Mini Program
Use on ChatGLM

Data from Age-Group Differences in Human Papillomavirus Types and Cofactors for Cervical Intraepithelial Neoplasia 3 among Women Referred to Colposcopy

crossref(2023)

Cited 0|Views6
No score
Abstract
AbstractBackground: Recommendations for high-risk human papillomavirus (HR-HPV) testing as an adjunct to cytology for cervical cancer screening differ by age group, because HR-HPV tests lack adequate specificity in women aged <30. Here, we assess age-group differences in HPV types and other risk factors for cervical intraepithelial neoplasia (CIN) grade 3 or worse (CIN3+) versus CIN0–2 in women from four colposcopy clinics.Methods: Women ages 18 to 69 (n = 1,658) were enrolled and completed structured interviews to elicit data on behavioral risk factors prior to their examinations. HPV genotyping was done on exfoliated cervical cell samples. We estimated relative risks (RR) for HPV types and cofactors for CIN3+, overall and stratified by age group.Results: After 2 years of follow-up, we identified 178 CIN3+, 1,305 CIN0–2, and 175 indeterminate outcomes. Nonvaccine HR-HPV types were only associated with CIN3+ among women ≥30 (RR = 2.3, 95% CI: 1.5–3.4; <30: RR = 0.9). Among all HR-HPV–positive women, adjusting for age, significant cofactors for CIN3+ included current smoking (RR = 1.5), former smoking (RR = 1.8), regular Pap screening (RR = 0.7), current regular condom use (RR = 0.5), and parity ≥5 (RR = 1.6, Ptrend for increasing parity = 0.07). However, the parity association differed by age group (≥30: RR = 1.8, Ptrend = 0.008; <30: RR = 0.9; Ptrend =.55).Conclusion: Subgroup variation by age in the risk of CIN3+ points to the importance of the timing of exposures in relation to CIN3+ detection.Impact: Future screening strategies need to consider natural history and secular trends in cofactor prevalence in the pursuit of appropriately sensitive and specific screening tools applied to appropriate age groups. Cancer Epidemiol Biomarkers Prev; 21(1); 111–21. ©2011 AACR.
More
Translated text
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined