Systematic review, meta-analysis and economic modelling of ...

Appendix 93. Two reviewers will make decisions on the final composition of included studies, assessed from a hardcopy of the item. The decisions will be coded and recorded on the Reference Manager database by theProject Manager.4. Authors will be contacted, if appropriate, to clarify details and obtain missing data.5. The quality of each study will be assessed against recognised criteria [23–28].6. Data extraction will be undertaken independently with discrepancies being discussed by the dataextractors. Those that cannot be resolved at this stage will be referred to the rest of the project team.Data extractionThe following data will be extracted from each study: population characteristics (age, gender, CADrisk factors, prevalence of known CAD), setting (emergency department, general ward, cardiologyward), characteristics of the index investigation (biomarker, exercise ECG or CT coronary angiography),characteristics of the reference standard and/or outcome measure, methods used to measure outcomes,duration of follow-up, study quality criteria (independence of the reference standard, blinding of theintervention and reference standard), prevalence of MI, CAD and adverse events, true positives, falsepositives, false negatives and true positives for each outcome. If raw data are not reported we will attemptto calculate these from the reported diagnostic parameters or, in the case of important recent studies, wewill contact the authors for clarification.Data synthesisWhere appropriate, we will combine data to provide pooled estimates of the accuracy of investigationsfor MI, CAD and adverse events. Where appropriate data exist we will use Bayesian evidence synthesis tocharacterise the uncertainty associated with the parameters of interest. Where possible, we will examinethe use of baseline characteristics (i.e. covariates) to explain any heterogeneity between studies. We willthen attempt to identify the study, or homogeneous studies, that most closely reflects the current typicalNHS population and practice.The model used to analyse the data will depend on characteristics of the data obtained. For example, ifdiagnostic thresholds can be assumed constant across studies then simple methods of pooling sensitivityand specificity will be conducted [29]. If there is implicit or explicit evidence that diagnostic thresholdsdiffer between primary studies, then sensitivity and specificity cannot be considered independent andsimultaneous modelling will be required [30]. A detailed assessment of heterogeneity will be conducted inall instances. If possible, meta-regression will be used to explore whether heterogeneity can be explainedby study population characteristics, the characteristics of the intervention, the definition of the outcomeor the study quality, although the feasibility of this will depend on the number of individual studiesidentified and the quality of reporting. Where exploration of covariates is not possible, or (unexplained)heterogeneity remains after the incorporation of covariates into the model(s), random effects will beincorporated to allow for such variability in results between studies.Covariate effects, unexplainable variability and uncertainty in parameter estimates will all be reflected inthe results using cutting-edge meta-analysis approaches. Since the outputs from these analyses will beused in the decision modelling all such sources of variation and uncertainty will be accurately reflected inthe decision modelling [31].Decision analysis modellingWe will develop our existing decision analysis models [11,32] to evaluate two specific decisions in theinvestigation of suspected ACS:1. Which biomarkers should be measured (and when) in patients presenting with suspected ACS?2. Should exercise ECG or CT coronary angiography be used to identify CAD in patients with troponinnegative suspected ACS?182NIHR Journals Library