Using Bayes theorem to estimate positive and negative predictive values for continuously and ordinally scaled diagnostic tests

A review of stakeholder recommendations for defining fit-for-purpose real-world evidence algorithms

Aim: The credibility and value of real-world evidence (RWE) are either supported or undermined by the algorithms (i.e., operational definitions) used. Methods: We conducted a targeted evidence review of key RWE decision makers' published recommendations on RWE algorithms through April 2021. Stakeholders were regulatory bodies, other governmental agencies and payer organizations. Results: Our review identified recommended criteria: relevance, validity, reliability, responsiveness, transparency and replicability, safety, feasibility and quality process. Stakeholders routinely recommended accuracy measures, subgroups evaluation and specific considerations for assessing exposures and covariates and the underlying real-world data (RWD) quality. Conclusion: The importance of stakeholder guidance on fit-for-purpose RWE algorithms is growing. We highlight gaps that future guidance and stakeholder recommendations could address.