Digital biomarkers: 3PM approach revolutionizing chronic disease management - EPMA 2024 position.

Non-communicable chronic diseases (NCDs) have become a major global health concern. They constitute the leading cause of disabilities, increased morbidity, mortality, and socio-economic disasters worldwide. Medical condition-specific digital biomarker (DB) panels have emerged as valuable tools to manage NCDs. DBs refer to the measurable and quantifiable physiological, behavioral, and environmental parameters collected for an individual through innovative digital health technologies, including wearables, smart devices, and medical sensors. By leveraging digital technologies, healthcare providers can gather real-time data and insights, enabling them to deliver more proactive and tailored interventions to individuals at risk and patients diagnosed with NCDs. Continuous monitoring of relevant health parameters through wearable devices or smartphone applications allows patients and clinicians to track the progression of NCDs in real time. With the introduction of digital biomarker monitoring (DBM), a new quality of primary and secondary healthcare is being offered with promising opportunities for health risk assessment and protection against health-to-disease transitions in vulnerable sub-populations. DBM enables healthcare providers to take the most cost-effective targeted preventive measures, to detect disease developments early, and to introduce personalized interventions. Consequently, they benefit the quality of life (QoL) of affected individuals, healthcare economy, and society at large. DBM is instrumental for the paradigm shift from reactive medical services to 3PM approach promoted by the European Association for Predictive, Preventive, and Personalized Medicine (EPMA) involving 3PM experts from 55 countries worldwide. This position manuscript consolidates multi-professional expertise in the area, demonstrating clinically relevant examples and providing the roadmap for implementing 3PM concepts facilitated through DBs.

Panel stacking is a threat to consensus statement validity.

Consensus statements can be very influential in medicine and public health. Some of these statements use systematic evidence synthesis but others fail on this front. Many consensus statements use panels of experts to deduce perceived consensus through Delphi processes. We argue that stacking of panel members towards one particular position or narrative is a major threat, especially in absence of systematic evidence review. Stacking may involve financial conflicts of interest, but non-financial conflicts of strong advocacy can also cause major bias. Given their emerging importance, we describe here how such consensus statements may be misleading, by analysing in depth a recent high-impact Delphi consensus statement on COVID-19 recommendations as a case example. We demonstrate that many of the selected panel members and at least 35% of the core panel members had advocated towards COVID-19 elimination (zero-COVID) during the pandemic and were leading members of aggressive advocacy groups. These advocacy conflicts were not declared in the Delphi consensus publication, with rare exceptions. Therefore, we propose that consensus statements should always require rigorous evidence synthesis and maximal transparency on potential biases towards advocacy or lobbyist groups to be valid. While advocacy can have many important functions, its biased impact on consensus panels should be carefully avoided.

Use of artificial intelligence and the future of peer review.

Conducting high-quality peer review of scientific manuscripts has become increasingly challenging. The substantial increase in the number of manuscripts, lack of a sufficient number of peer-reviewers, and questions related to effectiveness, fairness, and efficiency, require a different approach. Large-language models, 1 form of artificial intelligence (AI), have emerged as a new approach to help resolve many of the issues facing contemporary medicine and science. We believe AI should be used to assist in the triaging of manuscripts submitted for peer-review publication.

The Subjective Interpretation of the Medical Evidence.

This Viewpoint discusses whether commonly occuring, sometimes divergent interpretations of new evidence's validity and usefulness should be explained when experts and guideline committees provide recommendations for screening or treatment.

Ensuring an Accurate Scientific Record in an Era of Pre-print Servers.

BACKGROUND: Pre-prints have become an increasing part of the biomedical landscape. For example, during the first month of operation, July 2019, medRxiv received 176 submissions, one year later, in June 2020, including the first few months of COVID-19, it received 1866 submissions. The current relevant question is how to ensure an accurate scientific record given that there may be important differences between a pre-print and the peer-reviewed publication. METHODS: Based upon the experience of the authors, conversations with editors, and a focused selective review of the literature, including the recommendations of some professional groups, a limited number of practical recommendations were formulated. RESULTS: Peer-reviewed journals should request that authors indicate if the submitted manuscript has been posted on a pre-print server; ensure this is noted in the article if it is published by including the digital object identifier (DOI); and detail any major differences in the conclusions between the pre-print and the article. Pre-print servers should ensure that all content is marked as not peer-reviewed and be prepared to retract any pre-print that is fundamentally flawed within days that could influence clinical or public health recommendations that have therapeutic implications. CONCLUSION: Authors, those responsible for pre-print servers, and editors of peer- reviewed journals are responsible for ensuring an accurate scientific record.