Alastair Hay, Consultant Senior Lecturer in Primary Health Care

1. Alastair Hay, Consultant Senior Lecturer in Primary Health Care The TARGET Programme: strengths, weaknesses, opportunities and lessons learned (so far).

2. What is the problem? • High rates of RTIs in children lead to • Economic burden to health services and parents (and their employers) • Unnecessary use of antibiotics leads to • Increased selective pressure on antimicrobial resistance and • Medicalisation of illness vicious or virtuous circle • Clinical uncertainty drives use but leads to low specificity

3. What does the TARGET team believe is the solution? • Clinical prediction rule? • Yes, but… • What to “predict” (diagnosis vs. prognosis)? • Which symptoms and signs to measure? • How would a prediction rule fit into current clinical practice (simple vs. complex intervention)?

4. Programme overview

5. Programme overview

6. WS3 – CPR study • Research questions • Can baseline characteristics be used to predict the need for hospitalisation in children <12 years presenting to primary care with acute cough? • Do specific bacteria and/or viral microbes (or combinations of microbes) predict poor prognosis?

7. WS3 – CPR study • Design: prospective cohort (derivation and validation) study • Eligibility: Children <12 years presenting to primary care with acute cough • Independent variables • Baseline symptoms and signs + other characteristics (e.g. deprivation) • Detailed microbiology and virology

8. WS3 – CPR study • Dependent variables • Primary – hospitalisation • Secondary - symptom duration, symptom severity, antibiotic prescribing and reconsultations

9. WS3 – CPR study • Challenges • How to determine sample size • Logistics of recruiting a large cohort • Minimising (and/or adjusting for) spectrum bias • Confounding by indication

10. WS3 – CPR study • Sample size methods • Certainty with which strength of association between individual predictors and outcome • Overall precision of the sensitivity and specificity of a validated rule • Ratio of candidate predictors to outcome events

11. WS3 – CPR study • Recruitment logistics • Collaboration • Simple data collection proforma • Web and paper based • Re-imbursement for clinician time

13. WS3 – CPR study • Spectrum bias • Difference in illness (e.g. aetiology) between derivation and validation datasets • Can undermine validation • One potential solution is to anticipate which parameters are most likely to change and • Measure them (e.g. microbiology) • Adjust analysis for them

14. WS3 – CPR study • Confounding by indication • Can potentially be reduced by • Derive and validate in the control arm of a RCT (unlikely to be ethical) • Assume that antibiotic prescribing is not associated with risk of outcome and exclude children prescribed antibiotics • Include all children, look for association between antibiotics and key predictors and model antibiotic effects

15. Summary • Albeit with some limitations, CPRs can be appropriately applied in the infection field. Limitations include • Spectrum bias • Confounding by indication (antibiotic use) • Logistic challenges of recruiting large sample sizes • Collaboration • Use of technology to help manage data • Funders want to support CPR research