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Optimizing Strategies for Chlamydia trachomatis and Neisseria gonorrhoeae Screening in Men Who Have Sex With Men: A Modeling Study
Author(s) -
Nicolas Voirin,
Camille Allam,
Caroline Charre,
Christine Fernandez,
Matthieu Godinot,
F. Oria,
Aymeric Pansu,
Christian Chidiac,
H. Salord,
L. Cotte
Publication year - 2019
Publication title -
clinical infectious diseases
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.44
H-Index - 336
eISSN - 1537-6591
pISSN - 1058-4838
DOI - 10.1093/cid/ciz510
Subject(s) - chlamydia trachomatis , medicine , neisseria gonorrhoeae , incidence (geometry) , men who have sex with men , chlamydia , gynecology , medical diagnosis , virology , syphilis , immunology , radiology , biology , microbiology and biotechnology , mathematics , human immunodeficiency virus (hiv) , geometry
Background International guidelines recommend the systematic screening for Neisseria gonorrhoeae (NG) and Chlamydia trachomatis (CT) infections in all men who have sex with men (MSM) who have engaged in unprotected sex. However, the optimal screening strategy remains unclear. We developed a modeling approach to optimize NG/CT screening strategy in MSM. Methods A compartmental model of NG/CT screening and infection was implemented. NG/CT anal, pharyngeal, and urine (APU) samples from MSM attending the sexually transmitted infections clinic were used to estimate the screening rate, prevalence, and incidence in a base case scenario. Different screening strategies (scenarios; S) were then evaluated: APU samples every 12 months (S1); APU samples every 3 months (S2); APU samples every 6 months (S3); anal and pharyngeal (AP) samples every 6 months (S4); and AP samples every 3 months (S5). Results We analyzed 2973 triplet APU samples from 1255 patients. We observed 485 NG and 379 CT diagnoses. NG/CT prevalence and incidence estimates were 12.0/11.1% and 40/29 per 100 person-years, respectively, in the base case scenario. As compared to S2, the reference strategy, the proportions of missed NG/CT diagnoses were 42.0/41.2% with S1, 21.8/22.5% with S3, 25.6/28.3% with S4, and 6.3/10.5% with S5, respectively. As compared to S2, S1 reduced the cost of the analysis by 74%, S3 by 50%, S4 by 66%, and S5 by 33%. The numbers needed to screen for catching up the missed NG/CT diagnoses were 49/67 with S1, 62/82 with S3, 71/87 with S4, and 143/118 with S5. Conclusions S5 appears to be the best strategy, missing only 6.3/10.5% of NG/CT diagnoses, for a cost reduction of 33%.

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