How to bridge the gap between evidence-based and clinical management of endometriosis

• The limitations of EBM and guidelines to take dichotomous decisions, based on multiple variables, are discussed for endometriosis management. • It is suggested to document for clinical decisions on diagnosis, treatment and surgery the collective experience of clinicians, permitting the calculation of the probability and its distribution of the decisions experienced clinicians would make. The collective experience could subsequently be used to update EBM and guidelines. Evidence-based medicine (EBM) rightly intends to use the best available evidence for clinical decisions. The pyramid of evidence reflects the absence of allocation, user, or judgment bias, with on top double-blind, randomised, controlled trials (RCTs) or their meta-analyses having sufficient statistical power. Unfortunately, perfect trials are rare, and the quality of evidence has to be graded. Although important for drug development, the clinical impact of EBM has remained limited in areas such as surgery and endometriosis. The results are limited to the group investigated, and rare events, surgery complications or multimorbidity often require prohibitive large numbers. There is a mismatch between multifactorial clinical and surgical decisions and mono-factorial RCTs. The pitfalls of frequentist statistical inference and cognitive biases are often ignored, and observational medicine, clinical experience and surgical skills are poorly integrated. The EBM guidelines could be updated and expanded with data from collective clinical experience, including rare events, Black Swans, and surgical skills. Clinicians should document their sequential decisions regarding diagnosis, therapy, and surgery, including what should not be done. The agreement between clinicians will be reflected in the range of probabilities, which can then be used to update EBM data. These updated EBM guidelines cover all decisions the clinician has to make, many without trial evidence. These guidelines might vary according to local situations and should be updated when new data become available from trials, documented collective experience, including surgical skills, or models derived from the analysis of observational data.