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

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 2

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)? 3

Programme overview 4

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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? 6

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 7

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

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 9

WS3 – CPR study Sample size methods 1.Certainty with which strength of association between individual predictors and outcome 2.Overall precision of the sensitivity and specificity of a validated rule 3.Ratio of candidate predictors to outcome events 10

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

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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 13

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 14

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