How to stem the tide? Development of three scoping reviews in biomarkers and personalized prevention

Abstract

The “PeRsOnalized Prevention roadmap for the future HEalThcare” (PROPHET) project, seeks to assess the effectiveness, clinical utility and existing gaps in current personalized preventive approaches, and to develop a Strategy Research and Innovation Agenda (SRIA) for the European Union. The first draft of the SRIA concept paper needs to incorporate the state of the art of personalized prevention carried out through scoping reviews. Among them, our work aimed to answer whether there is any biomarker or combination of biomarkers that can help to better identify subgroups of individuals with different risks of developing a particular disease for primary or secondary prevention. These results were needed at early stage of the project; despite covering such a broad topic, it had to be carried out in record time (4 months) by a geographically dispersed team (Granada, Madrid, United Kingdom). Our challenge has been to maintain effective coordination and speed without losing scientific rigor. Between Feb-June 2023, our team conducted three independent scoping reviews (for cardiovascular diseases, neurodegenerative diseases and cancer, respectively) that involved quick and difficult decisions to narrow down the inclusion criteria, study populations, biomarkers included, and types of prevention. To maintain consistency, we created different glossaries and had multiple meetings and constant contact between team members. As a first step, we identified key terms on the topics of interest, helped by expert consultations, identification of significant publications and several specific tools (SR-Accelerator, etc.). A pilot study was conducted to refine the search matrix and to initiate coordination among reviewers. However, in order to shorten timeframes, we limited peer review to 10% of the records in all phases. The protocol, published in OSF, served as a guide for the report. All phases, when possible, overlapped to deliver the report on time. In addition, we made interactive evidence maps to show the results graphically, thanks to the creation of a script, using R and Python, to allow the input of the datasheet extraction file into the mapping application. Despite these challenges, we successfully met the project deadlines.