Optimal approaches to data collection and analysis of potential immune mediated disorders in clinical trials of new vaccines VACCINE Da Silva, F. T., De Keyser, F., Lambert, P., Robinson, W. H., Westhovens, R., Sindic, C. 2013; 31 (14): 1870-1876


The potential for development of autoimmune diseases after vaccination with new vaccines containing novel adjuvants is a theoretical concern. Randomised, placebo-controlled trials are the best method for assessing a potential causal relationship between an adverse event and vaccination, but usually have a sample size too small to detect adverse events occurring in <1% of subjects. Incomplete case documentation may hamper definitive diagnoses, preventing accurate causality assessment. To date there are no guidelines for collection, documentation and monitoring of potential immune mediated disorders (pIMD) reported in the course of clinical trials with adjuvanted vaccines.This paper proposes a methodology for collection of pIMDs in clinical vaccine trials, with the objective of obtaining complete and reliable data using standardised methodology for its collection and analysis.The role of the study investigator in prospective, standardised safety data collection is key and can be facilitated by providing a pIMD list in study documents and disease-specific standard questionnaires to assist timely and thorough documentation. External expert review of histopathology samples or other specialised diagnostic data would increase diagnostic accuracy. Centralised case ascertainment using standard case definitions would identify true cases of interest. We propose collection of safety data for at least 6 months and up to one year after the last vaccine dose. Bio-banking as a platform for collecting samples from enrolled patients for future use (e.g., to measure biomarkers of diagnostic, prognostic or predictive utility) could eventually provide valuable information in cases where a pIMD is diagnosed during the study period.Standardised collection of safety data to allow appropriate analyses are optimal approaches for detecting rare events in clinical trials. Appropriate data analysis will then more reliably define potential causal relationships with vaccination.

View details for DOI 10.1016/j.vaccine.2013.01.042

View details for Web of Science ID 000317450200016

View details for PubMedID 23391600