How have selection bias and disease misclassification undermined the validity of myalgic encephalomyelitis/chronic fatigue syndrome studies?
How have selection bias and disease misclassification undermined the validity of myalgic encephalomyelitis/chronic fatigue syndrome studies? is a paper that compares the selection criteria of the Oxford criteria (OC) and the Canadian Consensus Criteria (CCC) noting that for every 15 patients selected under the Oxford criteria there are 14 false positives when compared to CCC.
The authors suggest that in a clinical setting SEID criteria from the Institute of Medicine report or the Fukuda criteria (CDC, 1994) can be used to diagnose and then those patients can participate in research.
Authors[edit | edit source]
Citation[edit | edit source]
Nacul, Luis, Eliana M. Lacerda, Caroline C. Kingdon, Hayley Curran, and Erinna W. Bowman. "How have selection bias and disease misclassification undermined the validity of myalgic encephalomyelitis/chronic fatigue syndrome studies?." Journal of health psychology (2017): 1359105317695803.
Abstract[edit | edit source]
Myalgic encephalomyelitis/chronic fatigue syndrome has been a controversial diagnosis, resulting in tensions between patients and professionals providing them with care. A major constraint limiting progress has been the lack of a ‘gold standard’ for diagnosis; with a number of imperfect clinical and research criteria used, each defining different, though overlapping, groups of people with myalgic encephalomyelitis or chronic fatigue syndrome. We review basic epidemiological concepts to illustrate how the use of more specific and restrictive case definitions could improve research validity and drive progress in the field by reducing selection bias caused by diagnostic misclassification.
Summary[edit | edit source]
There are no established biomarkers for ME/CFS, so research studies rely on selecting patients using diagnostic criteria - with over 20 different diagnostic criteria to choose from. Selection bias can be recognized when only the broadcast diagnostic criteria in research - the Oxford criteria or the Australian criteria without identifying or reporting on subgroups - there is a much greater risk of including false positives in clinical trial results (patients incorrectly diagnosed with ME/CFS). In a clinical trial it is possible that this selection bias may result in a null result or adverse effect for patients meeting the Canadian Consensus Criteria going unrecognized, due to a positive outcome for the patients meeting only the broadest Oxford criteria - which identifies 15 times more patients.
Using diabetes as a comparison, failing to distinguish between type 1 diabetes and type 2 diabetes in a clinical trial would allow a drug that is only effective for type 2 diabetes to appear effective for all cases of diabetes, since the greater number of patients with type 2 diabetes would mask any ineffective or harmful result in patients with type 1 diabetes. This over-generalization of results can be seen when psychosocial clinical trial results are assessed by excluding those trials using the Oxford criteria - any positive result for cognitive behavioral therapy or graded exercise therapy treatments totally disappears.
Notable studies using Oxford criteria[edit | edit source]
See also[edit | edit source]
References[edit | edit source]
- Nacul, Luis; Lacerda, Eliana M; Kingdon, Caroline C; Curran, Hayley; Bowman, Erinna W (March 1, 2017). "How have selection bias and disease misclassification undermined the validity of myalgic encephalomyelitis/chronic fatigue syndrome studies?". Journal of Health Psychology: 1359105317695803. doi:10.1177/1359105317695803. ISSN 1359-1053. PMC 5581258. PMID 28810428.