Professor Sally Hollis, PHASTAR's Head of Statistical Consultancy, was a panellist on an EFSPI/PSI webinar on Data Sharing recently (recording available here: https://youtu.be/V8lsPLck5xI). This is an area which has been rapidly evolving over the last decade. The EMA first outlined steps towards proactive disclosure of data in an article published in 2012 (http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001202).
Following a process of consultation, the EMA published a policy on publication of clinical data in October 2014, the first phase of which came into force in January 2015. This provides access (via the EMA website) to documents relating to submissions, including the individual study reports with redaction of personal data, supporting documents such as the protocol and amendments, CRF and analysis plan, and the clinical overview and summary. In a second phase, the EMA are consulting with stakeholders to find the most appropriate way to make Individual Patient Data (IPD) available, in compliance with privacy and data protection laws.
Missing data: Management and Prevention
Data managers strive to produce high quality, reliable and intact data for analysis. Integral to this quality standard is to ensure minimal or no missing data. Missing data may have different sources such as equipment failure, missed visits, death or withdrawal of a subject and is usually dealt with during the analysis by defined handling strategies. Data which are available at the investigational site, but have not been collected and are missing from the eCRF through error or omission can be avoided by good data handling procedures.
The impact of missing data can be many fold from delay in timelines, additional costs and resources associated with retrieving and reconciling the data, and of course, adversely affecting the interpretation of study results through the introduction of bias. Many data items are dependent upon or form dependencies on other data items, therefore the unavailability of a single item of data may affect the integrity of data points elsewhere in the database.
The optimal approach to dealing with missing data is one of prevention. Trial design has a role to play and consideration should be given to practicalities, such as the impact on site and subject, in an effort to avoid missing data due to confusion or errors in study conduct. Effective and efficient data capture processes are essential. Good eCRF (or paper CRF) design with a logical data flow which mimics the sequence of procedures in the clinic and facilitates efficient data collection is important. Skip logic is a feature that changes what question or page a respondent sees based on how they answer another question, thus guiding the user through the eCRF and avoiding data entry into variables that should remain blank. Clear on-screen data entry instructions and readily available eCRF completion guidelines are essential. User Acceptance Testing (UAT) during the database design stage is key to this and developers should ensure that a wide range of user-types test the design to consider ease of use. It goes without saying that user training and support are essential. Along with periodic refresher training demonstrations, vignette style videos are well received.