Predicting STI Diagnoses Amongst MSM and Young People Attending Sexual Health Clinics in England: Triage Algorithm Development and Validation Using Routine Clinical Data

Carina King*, Gwenda Hughes, Martina Furegato, Hamish Mohammed, John Were, Andrew Copas, Richard Gilson, Maryam Shahmanesh, Catherine H. Mercer

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

Background: Sexual health (SH) services increasingly need to prioritise those at greatest risk of sexually transmitted infections (STIs). We used SH surveillance data to develop algorithms to triage individuals attending SH services within two high-risk populations: men who have sex with men (MSM) and young people (YP). Methods: Separate multivariable logistic regression models for MSM and YP were developed using surveillance data on demographics, recent sexual history, prior STI diagnoses and drug/alcohol use from five clinics in 2015–2016 to identify factors associated with new STI diagnoses. The models were prospectively applied in one SH clinic in May 2017 as an external validation. Findings: 9530 YP and 1448 MSM SH episodes informed model development. For YP, factors associated with new STI diagnosis (overall prevalence: 10.6%) were being of black or mixed white/black ethnicity; history of chlamydia diagnosis (previous year); and multiple partners/new partner (previous 3-months). The YPs model had reasonable performance (c-statistic: 0.703), but poor discrimination when externally validated (c-statistic: 0.539). For MSM, being of South Asian ethnicity; being born in Europe (excluding the UK); and condomless anal sex or drug use (both in previous 3-months) were associated with STI diagnosis (overall prevalence: 22.0%). The MSM model had a c-statistic of 0.676, reducing to 0.579 on validation. Interpretation: SH surveillance data, including limited behavioural data, enabled triage algorithms to be developed, but its implementation may be problematic due to poor external performance. This approach may be more suitable to self-triage, including online, ensuring patients are directed towards appropriate services. Funding: NIHR HTA programme (12/191/05).

Original languageEnglish
Pages (from-to)43-51
Number of pages9
JournalEClinicalMedicine
Volume4-5
DOIs
Publication statusPublished - 1 Oct 2018

Bibliographical note

Funding Information:
We would like to thank the staff at all the clinics who took part in the enhanced GUMCAD phase 2 pilot (Bedford, Bristol, Barnet, Southend and Croydon) and all the staff at Claude Nicol for taking part in the external validation pilot (specifically Dr. Daniel Richardson, Ms. Laura Clark and Ms. Catherine Hendrickx). We would like to acknowledge Dr. Alex Pollard and Mr. Alex Langrish (Brighton and Sussex Medical School) for participant recruitment during the pilot, and Mrs. Sarika Desai (Public Health England) for input into the analysis methods. We would like to acknowledge the remaining investigators on the SANTE project: Dr. Carrie Llewellyn (Brighton and Sussex Medical School), Dr. Fiona Burn, Dr. Alison Rodger, Dr. Julia Bailey, Dr. Alison Howarth (University College London), Prof. Charles Abraham (University of Exeter) and Dr. Anupama Roy. Funding was provided by the National Institute for Health Research Health Technology Assessment programme (12/191/05). The funders did not have any role in the study design, data collection, analysis, interpretation or writing of the manuscript. Authors declare no conflicts of interest. The manuscript was conceived by CK, MS, GH, CM, AC and RG. The model development was conducted by CK, with input from MS, CM, GH, AC, RG, MF and HM. The enhanced GUMCAD pilot was overseen by GH, HM, JW and MF. The design of the prospective external validation was done by CK, MS, RG, GH, CM and AC and overseen by CK, MS and RG. Data management and analysis for algorithm development and validation was conducted by CK. The manuscript was drafted by CK, with significant input from CM and GH. All authors read and commented on the final manuscript.

Funding Information:
Funding was provided by the National Institute for Health Research Health Technology Assessment programme ( 12/191/05 ). The funders did not have any role in the study design, data collection, analysis, interpretation or writing of the manuscript.

Keywords

  • MSM
  • Predictive model
  • Routine data
  • STI
  • Triage
  • Young people

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