SLRs Could Benefit From a New Approach to Study Identification: A Case Study

OBJECTIVES: Systematic literature reviews (SLR) that adhere to gold-standard guidelines, as prescribed by HTA bodies, remain a vital but time-consuming exercise. Researchers and Companies alike would benefit from additional, indicative, early SLR outputs mapping the study landscape, ahead of the conclusion of the review to aid synthesis planning. In an SLR conducted to identify efficacy and safety data of comparator interventions in hereditary angioedema, a new method of study identification was implemented and evaluated.

METHODS: The new method recommends the addition of a preliminary step to separate the identification of studies from identification of reports relating to the studies. To achieve this, clinical trial registers were searched and screened against the PICOS, prior to searching of databases, conferences, and web resources, to map the potential study landscape. The protocol was finalised based on the study mapping results to permit inclusion of trial information in the search strategy.

RESULTS: Double-screening against the pre-defined PICOS of preliminary searches of trial registers identified 68 unique studies. A treatment landscape of 26 RCTs of relevant interventions was mapped three weeks after PICOS finalisation. This early overview of RCTs facilitated search strategy refinement with inclusion of trial information to increase sensitivity and served as early indicator of the need for complex statistical synthesis. Following searching and screening of records from all resources, study reports of previously included trials were identified, in addition to any remaining unregistered studies.

CONCLUSIONS: The new model of study identification which separates out the identification of studies from the identification of reports relating to studies offered multiple benefits to both researchers and Company, the most significant being an early view of the scope for synthesis, indicating the need for advanced statistical comparisons such as network meta-analysis (NMA).