A scattered landscape: assessment of the evidence base for 71 patient decision aids developed in a hospital setting

Background Recent publications reveal shortcomings in evidence review and summarization methods for patient decision aids. In the large-scale "Share to Care (S2C)" Shared Decision Making (SDM) project at the University Hospital Kiel, Germany, one of 4 SDM interventions was to develop up to 80 decision aids for patients. Best available evidence on the treatments' impact on patient-relevant outcomes was systematically appraised to feed this information into the decision aids. Aims of this paper were to (1) describe how PtDAs are developed and how S2C evidence reviews for each PtDA are conducted, (2) appraise the quality of the best available evidence identified and (3) identify challenges associated with identified evidence. Methods The quality of the identified evidence was assessed based on GRADE quality criteria and categorized into high-, moderate-, low-, very low-quality evidence. Evidence appraisal was conducted across all outcomes assessed in an evidence review and for specific groups of outcomes, namely mortality, morbidity, quality of life, and treatment harms. Challenges in evidence interpretation and summarization resulting from the characteristics of decision aids and the type and quality of evidence are identified and discussed. Conclusions Evidence reviews in this project were carefully conducted and summarized. However, the evidence identified for our decision aids was indeed a "scattered landscape" and often poor quality. Facing a high prevalence of low-quality, non-directly comparative evidence for treatment alternatives doesn't mean it is not necessary to choose an evidence-based approach to inform patients. While there is an urgent need for high quality comparative trials, best available evidence nevertheless has to be appraised and transparently communicated to patients

Serological profiling of the EBV immune response in Chronic Fatigue Syndrome using a peptide microarray.

Epstein-Barr-Virus (EBV) plays an important role as trigger or cofactor for various autoimmune diseases. In a subset of patients with Chronic Fatigue Syndrome (CFS) disease starts with infectious mononucleosis as late primary EBV-infection, whereby altered levels of EBV-specific antibodies can be observed in another subset of patients.We performed a comprehensive mapping of the IgG response against EBV comparing 50 healthy controls with 92 CFS patients using a microarray platform. Patients with multiple sclerosis (MS), systemic lupus erythematosus (SLE) and cancer-related fatigue served as controls. 3054 overlapping peptides were synthesised as 15-mers from 14 different EBV proteins. Array data was validated by ELISA for selected peptides. Prevalence of EBV serotypes was determined by qPCR from throat washing samples.EBV type 1 infections were found in patients and controls. EBV seroarray profiles between healthy controls and CFS were less divergent than that observed for MS or SLE. We found significantly enhanced IgG responses to several EBNA-6 peptides containing a repeat sequence in CFS patients compared to controls. EBNA-6 peptide IgG responses correlated well with EBNA-6 protein responses. The EBNA-6 repeat region showed sequence homologies to various human proteins.Patients with CFS had a quite similar EBV IgG antibody response pattern as healthy controls. Enhanced IgG reactivity against an EBNA-6 repeat sequence and against EBNA-6 protein is found in CFS patients. Homologous sequences of various human proteins with this EBNA-6 repeat sequence might be potential targets for antigenic mimicry

Primer and probe for EBV load and type PCR.

<p>Primer and probe for EBV load and type PCR.</p

Total IgG responses against EBV, EBNA-1 and enterovirus peptides in the different cohorts.

<p>A) The signal intensity of IgG responses against all EBV peptides (upper row), EBNA-1 peptides (middle row) and enterovirus (lower row) in CFS, healthy controls and MS patients. B) Comparison of patients with SLE and Hodgkin’s lymphoma in disease remission with cancer-related fatigue (HD_NF) or without fatigue (HD_FAT) analysed in another seroarray screening experiment. Statistical analysis by Wilcoxon rank sum test with * p<0.05, *** p <0.001.</p

Seroarray analysis of IgG antibody reactivity against 15-mer EBV peptides which cover 14 EBV proteins with sequences of EBV type I (B-95.8) in 50 healthy donors.

<p>IgG responses of each sample against each peptide are depicted. Responses are defined as a signal intensity above 5,000. In the left graph the % of samples with a response against each single peptide of the indicated proteins are shown. The right graph shows the mean intensity of these IgG responses (defined as a signal intensity above 5,000) against the single peptides. EA- early antigen; PM- polymerase; VCA- viral capsid antigen; gp- glycoprotein.</p