BACKGROUND: Patient reported outcomes (PROs) are increasingly assessed in clinical trials, and guidelines are available to inform the design and reporting of such trials. However, researchers involved in PRO data collection report that specific guidance on 'in-trial' activity (recruitment, data collection and data inputting) and the management of 'concerning' PRO data (i.e., data which raises concern for the well-being of the trial participant) appears to be lacking. The purpose of this review was to determine the extent and nature of published guidelines addressing these areas.
METHODS AND FINDINGS: Systematic review of 1,362 articles identified 18 eligible papers containing 'in-trial' guidelines. Two independent authors undertook a qualitative content analysis of the selected papers. Guidelines presented in each of the articles were coded according to an a priori defined coding frame, which demonstrated reliability (pooled Kappa 0.86-0.97), and validity (<2% residual category coding). The majority of guidelines present were concerned with 'pre-trial' activities (72%), for example, outcome measure selection and study design issues, or 'post-trial' activities (16%) such as data analysis, reporting and interpretation. 'In-trial' guidelines represented 9.2% of all guidance across the papers reviewed, with content primarily focused on compliance, quality control, proxy assessment and reporting of data collection. There were no guidelines surrounding the management of concerning PRO data.
CONCLUSIONS: The findings highlight there are minimal in-trial guidelines in publication regarding PRO data collection and management in clinical trials. No guidance appears to exist for researchers involved with the handling of concerning PRO data. Guidelines are needed, which support researchers to manage all PRO data appropriately and which facilitate unbiased data collection.
- Clinical Trials as Topic
- Data Collection
- Databases, Bibliographic
- Diagnostic Self Evaluation
- Outcome Assessment (Health Care)
- Practice Guidelines as Topic
- Reproducibility of Results
- Research Design