OBJECTIVES: Lack of rigour in PRO data analysis leads to uncertainty around the quality of results impacting the extent to which conclusions can be drawn from the data.  This study sought to provide guidelines for PRO efficacy data analysis for study sponsors in order to ensure confidence in PRO results by stakeholder decision makers. METHODS: A targeted review was undertaken of guidelines for clinical trial and PRO data analysis, and published PRO analysis studies that demonstrated good practice in PRO efficacy analysis.  The evidence was synthesised by a team comprising statistical and PRO experts experienced in the analysis of PRO efficacy data.  An 8-step guideline was developed based on the available evidence. RESULTS: Eight steps that will ensure high quality analysis of PRO trial efficacy data are (1) avoid unplanned or post analysis by developing a PRO specific SAP prior to data base lock, or document comprehensive PRO data analysis in the clinical trial SAP (2) ensure awareness of differing requirements across stakeholders in PRO data analysis/interpretation and adequately address this in the SAP to ensure (3) specify primary and secondary PRO endpoints and/or approaches to correcting for multiplicity (4) develop and specify appropriate approaches to handling missing data including sensitivity analysis (5) include analysis of PRO score change from baseline (6) specify approaches to interpreting change from baseline data including any benchmarks which will be applied during interpretation (7) implement a 100% double programming approach alongside table review by statistically qualified team members (8) interpret PRO results not only in isolation but alongside other clinical outcomes CONCLUSIONS: For PRO data to effectively inform decision making across all stakeholders, high standards of data analysis needs to be mandatory.  This 8-step guideline, if adhered to, will raise the standard of PRO data analysis reducing the likelihood that PRO data is  discounted by decision makers.