A prospective cohort and extended comprehensive-cohort design provided insights about the generalizability of a pragmatic trial: the ProtecT prostate cancer trial.

OBJECTIVES: Randomized controlled trials (RCTs) deliver robust internally valid evidence but generalizability is often neglected. Design features built into the Prostate testing for cancer and Treatment (ProtecT) RCT of treatments for localized prostate cancer (PCa) provided insights into its generalizability. STUDY DESIGN AND SETTING: Population-based cluster randomization created a prospective study of prostate-specific antigen (PSA) testing and a comprehensive-cohort study including groups choosing treatment or excluded from the RCT, as well as those randomized. Baseline information assessed selection and response during RCT conduct. RESULTS: The prospective study (82,430 PSA-tested men) represented healthy men likely to respond to a screening invitation. The extended comprehensive cohort comprised 1,643 randomized, 997 choosing treatment, and 557 excluded with advanced cancer/comorbidities. Men choosing treatment were very similar to randomized men except for having more professional/managerial occupations. Excluded men were similar to the randomized socio-demographically but different clinically, representing less healthy men with more advanced PCa. CONCLUSION: The design features of the ProtecT RCT provided data to assess the representativeness of the prospective cohort and generalizability of the findings of the RCT. Greater attention to collecting data at the design stage of pragmatic trials would better support later judgments by clinicians/policy-makers about the generalizability of RCT findings in clinical practice.

Into the valley of death: research to innovation.

The phase between research and successful innovation is known as the valley of death. Increasingly, researchers from the pharmaceutical industry and academia are working together, often encouraged by governments, to cross this 'valley' as they seek to bring basic research to the market. This is consistent with newer models of innovation policy that stress interaction between the different agents across the innovation process. Here, we examine this interaction in the UK, the EU and the USA using several specific examples, suggesting that cooperation is still far from perfect and that the return for academia on its research investment is relatively small. Countries are also beginning to use research as a tool of industrial economic policy.