Developing a model to predict individualised treatment for gonorrhoea: a modelling study.

OBJECTIVE: To develop a tool predicting individualised treatment for gonorrhoea, enabling treatment with previously recommended antibiotics, to reduce use of last-line treatment ceftriaxone. DESIGN: A modelling study. SETTING: England and Wales. PARTICIPANTS: Individuals accessing sentinel health services. INTERVENTION: Developing an Excel model which uses participants' demographic, behavioural and clinical characteristics to predict susceptibility to legacy antibiotics. Model parameters were calculated using data for 2015-2017 from the Gonococcal Resistance to Antimicrobials Surveillance Programme. MAIN OUTCOME MEASURES: Estimated number of doses of ceftriaxone saved, and number of people delayed effective treatment, by model use in clinical practice. Model outputs are the predicted risk of resistance to ciprofloxacin, azithromycin, penicillin and cefixime, in groups of individuals with different combinations of characteristics (gender, sexual orientation, number of recent sexual partners, age, ethnicity), and a treatment recommendation. RESULTS: Between 2015 and 2017, 8013 isolates were collected: 64% from men who have sex with men, 18% from heterosexual men and 18% from women. Across participant subgroups, stratified by all predictors, resistance prevalence was high for ciprofloxacin (range: 11%-51%) and penicillin (range: 6%-33%). Resistance prevalence for azithromycin and cefixime ranged from 0% to 13% and for ceftriaxone it was 0%. Simulating model use, 88% of individuals could be given cefixime and 10% azithromycin, saving 97% of ceftriaxone doses, with 1% of individuals delayed effective treatment. CONCLUSIONS: Using demographic and behavioural characteristics, we could not reliably identify a participant subset in which ciprofloxacin or penicillin would be effective. Cefixime resistance was almost universally low; however, substituting ceftriaxone for near-uniform treatment with cefixime risks re-emergence of resistance to cefixime and ceftriaxone. Several subgroups had low azithromycin resistance, but widespread azithromycin monotherapy risks resistance at population level. However, this dataset had limitations; further exploration of individual characteristics to predict resistance to a wider range of legacy antibiotics may still be appropriate.

Agent-based modelling study of antimicrobial-resistant Neisseria gonorrhoeae transmission in men who have sex with men: towards individualised diagnosis and treatment.

Background Antimicrobial-resistant (AMR) gonorrhoea is a global public health threat. Discriminatory point-of-care tests (POCT) to detect drug sensitivity are under development, enabling individualised resistance-guided therapy. METHODS: An individual-based dynamic transmission model of gonorrhoea infection in MSM living in London has been developed, incorporating ciprofloxacin-sensitive and resistant strains. The time-dependent sexual contact network is captured by periodically restructuring active connections to reflect the transience of contacts. Different strategies to improve treatment selection were explored, including discriminatory POCT and selecting partner treatment based on either the index case or partner susceptibility. Outcomes included population prevalence of gonorrhoea and drug dose counts. RESULTS: It is shown that using POCT to detect ciprofloxacin-sensitive infections could result in a large decrease in ceftriaxone doses (by 70% compared with the reference case in the simulations of this study). It also suggests that ceftriaxone use can be reduced with existing technologies, albeit to a lesser degree; either using index case sensitivity profiles to direct treatment of partners, or testing notified partners with strain discriminatory laboratory tests before treatment, reduced ceftriaxone use in our model (by 27% and 47% respectively). CONCLUSIONS: POCT to detect ciprofloxacin-sensitive gonorrhoea are likely to dramatically reduce reliance on ceftriaxone, but requires the implementation of new technology. In the meantime, the proportion of unnecessary ceftriaxone treatment by testing partners before treatment could be reduced significantly. Alternatively, index case sensitivity profiles could be used to select effective treatments for partners.