PHASTAR staff made multiple contributions to this year's PSI Conference, which was held in London this past May.

Members of our statistical staff presented on Overdispersed Count Data, describing various models available to account for overdispersion, and presented a simulation study comparing their performance when dispersion differs between treatment groups. They concluded that the standard Negative Binomial model is quite robust to violation of the assumption of a single common dispersion parameter. However, in extreme circumstances, fitting a Heterogeneous Negative Binomial model can provide improved standard errors.

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Missing Data at Clinical Trial Level?

Completeness of Clinical Trial Reporting

Professor Sally Hollis, PHASTAR's Head of Statistical Consultancy, was a panellist on an EFSPI/PSI webinar on Data Sharing recently (recording available here: 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 (  

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.

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Managing Missing Data

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.

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New Setting - Old Principles at ACDM 2017

ACDM 2017 - Conference Review

The ACDM Annual Conference 2017 was hosted in Brussels in a move away from the usual UK base, resulting in a truly European audience. The Chair of the ACDM welcomed us all and reminded us that throughout this transition period of new technologies and regulations to stay true to the QPR principles - Quality, Protection and Responsibility.

The two key note speakers brought a diversity of approaches to the meeting, from the impending implementation of regulations set out in ICH E6 (R2) in June 2017 and the move to Risk Based Monitoring (RBM) to the challenges faced by Médecins Sans Frontières (MSF) when delivering emergency aid in exceptionally difficult circumstances.

Aspects of e-data were central throughout the presentations, including it's role and contribution in the setting and monitoring of Tolerance limits, the quality measures required for Clinical Trials based on statistical and medical knowledge. The effect of eSource on EDC and the electronic Trial Master File (eTMF), centralised monitoring, monitoring strategies and Risk Indicators were key focal points for discussion together with how to address data security in a cloud based environment and best practices for implementing such applications.

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Interim Locks and DSMBs

Interim Locks and DSMBs                   

Special consideration needs to be given to providing data for interim locks and DSMBs during the course of a study. It is crucial that the data provided for these milestones is as complete, accurate and up-to-date as possible because the outcome can have serious implications on the review and progress of the study. 

It is essential for data management to plan in advance the identification of key data, the level of cleaning required and agree timelines with the project team.  This strategic planning requires input and commitment from wider study team:

  • For electronic-data-capture studies, site personnel need to commit to entering the key data and responding to queries in a timely manner. For paper studies, CRFs must be completed and sent to the Data Entry department. Phastar work closely with the sponsor, clinical project managers and CRAs to provide assistance if required in database issues and ensure new user accounts are set up promptly.
  • Source document verification of key data must be completed in time for data management review and query resolution.

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