The complementary role of expert opinion in science

 by Solomon Christopher

Expert opinions complement systematically collected patient-level data in various ways. They can be based on mechanistic interpretations, for example, a certain viewpoint of the pathophysiology of disease or treatment action. These interpretations would require further functional studies that may not be feasible or limited in scope.

 

Expert opinions are also well founded on personal clinical practice experience. A certain clinical observation may have not yet been rigorously studied. This information from multiple experts is crucial additional information that should add to scientific data and inform the scope of further studies. 

 

Mere patient-level data and their analysis, especially those based on real world evidence (RWE) alone, can be an empirical account of associations at worst. This might be due to unobservability of certain data or lack of experimental evidence. 

 

Bayesian statistical viewpoint has always facilitated subjective information to be included in data analysis. After all, most scientific studies, however rigorous, involve subjectivity at the design and interpretation. Bayesian statistics account for this subjectivity by quantifying the uncertainty of information at various levels. 

 

Together, systematically collected patient-level data, expert opinions and rigorous statistical analysis along with quantified uncertainty at various levels of information are powerful tools to scientific progress.

 

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