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....
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BMJ Publishing Group
2021-06-01
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| Series: | BMJ Open |
| Online Access: | https://bmjopen.bmj.com/content/11/6/e042893.full |
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| author | Hamish Mohammed Helen Fifer Jonathan Ross Maya Gobin Katy M E Turner Lucy Findlater Oliver Geffen Obregon |
| author_facet | Hamish Mohammed Helen Fifer Jonathan Ross Maya Gobin Katy M E Turner Lucy Findlater Oliver Geffen Obregon |
| author_sort | Hamish Mohammed |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-79d0e68715b44a8dbc11dfb31f2e59d9 |
| institution | Kabale University |
| issn | 2044-6055 |
| language | English |
| publishDate | 2021-06-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| series | BMJ Open |
| spelling | doaj-art-79d0e68715b44a8dbc11dfb31f2e59d92024-11-20T09:20:10ZengBMJ Publishing GroupBMJ Open2044-60552021-06-0111610.1136/bmjopen-2020-042893Developing a model to predict individualised treatment for gonorrhoea: a modelling studyHamish Mohammed0Helen Fifer1Jonathan Ross2Maya Gobin3Katy M E Turner4Lucy Findlater5Oliver Geffen Obregon6The National Institute for Health Research Health Protection Research Unit in Blood Borne and Sexually Transmitted Infections at University College London in partnership with the UK Health Security Agency, London, UKReference Microbiology, Public Health England, London, UKInstitute of Microbiology and Infection, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK1 Population Health Sciences, University of Bristol, Bristol, UK2 NIHR Health Protection Research Unit in Behavioural Science and Evaluation, School of Population Health Sciences, University of Bristol, Bristol, UKUK Health Security Agency South of England, Bristol, UKHIV & STI Department, Public Health England, London, UKObjective 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.https://bmjopen.bmj.com/content/11/6/e042893.full |
| spellingShingle | Hamish Mohammed Helen Fifer Jonathan Ross Maya Gobin Katy M E Turner Lucy Findlater Oliver Geffen Obregon Developing a model to predict individualised treatment for gonorrhoea: a modelling study BMJ Open |
| title | Developing a model to predict individualised treatment for gonorrhoea: a modelling study |
| title_full | Developing a model to predict individualised treatment for gonorrhoea: a modelling study |
| title_fullStr | Developing a model to predict individualised treatment for gonorrhoea: a modelling study |
| title_full_unstemmed | Developing a model to predict individualised treatment for gonorrhoea: a modelling study |
| title_short | Developing a model to predict individualised treatment for gonorrhoea: a modelling study |
| title_sort | developing a model to predict individualised treatment for gonorrhoea a modelling study |
| url | https://bmjopen.bmj.com/content/11/6/e042893.full |
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