ArticleZhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences2018
[Trajectory modeling for estimating the trend of human papillomavirus infection status among men who have sex with men].
Article in Zhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed, 1 citations in OpenAlex.
- Application progress of latent class growth models in dynamic prevention and control strategies for acquired immunodeficiency syndrome.Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2024Review
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6 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
objectiveTo investigate whether trajectory model can be used to explore the trend of anal human papillomavirus (HPV) infection status among HIV-negative men who have sex with men (MSM).
methodsHIV-negative MSM were recruited by using the "snowball" method from 1st September 2016 to 30th September 2017 in Urumqi. The subjects were followed-up every six months since enrollment. The cell samples in anal canal were collected and the 37-type HPV test kits were used for identification and classification of HPV infection at both baseline and follow-up visits. Taking the cumulative number of different types of HPV as the dependent variable and follow-up visits as the independent variable, the trajectory model was established for the study subjects who completed baseline, 6 months and 12 months follow-up. The model was used to simulate the trend of HPV infection status when the subjects were divided into 1, 2, 3 and 4 subgroups. Bayesian information criterion (BIC), log Bayes factor and average posterior probability (AvePP) were used to evaluate the fitting effect.
resultsA total of 400 HIV-negative MSM were recruited at baseline and 187 subjects completed baseline and two follow-ups. The fitting effect attained best when the variation trend was divided into two subgroups. The first subgroup accounted for 54.5%(102/187) of the total, and the curve of change in HPV infection was decreasing; the second subgroup accounted for 45.5%(85/187) of the total, and the curve of change in HPV infection was increasing.
conclusionsTrajectory model can effectively distinguish the trend of HPV infection status in HIV-negative MSM to identify the high-risk group of HPV infection.
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