DSMBs and clinical trial safety
by Global PharmacovigilanceThe Data Safety and Monitoring Board (DSMB) or Data Monitoring Committee (DMC – these are synonymous terms) is a group of individuals put together by the sponsor or CRO (if contracted out) with relevant expertise to carry out the important role of monitoring the safety of a clinical trial study.
Epidemic curves are an important component of the public health and global health toolbox. Learn more about creating and interpretting them.
Become a Cochrane citizen scientist. Anyone can join their collaborative volunteer effort.
Around half of the clinical trials done on medicines we use today are not published; a tragic truth that needs to be changed.
INTERGROWTH-21st Postnatal Growth Standards and z-scores for Preterm Infants
by INTERGROWTH-21stHealthcare associated infections (HAI) are of important concern in patient care. This talk discusses Visual Analytics techniques which have been developed to help detect, monitor, analyse and understand trends, clusters and outbreaks of HAI.
In celebration of Global Health Trials' fifth birthday (May 11th 2015) Professor Trudie Lang, Principal Investigator of the programme, talks to us about why Global Health Trials was started, why people should share their experience, and what the future holds.
Technology issues for research in remote areas/developing regions
by Mike Workman - Senior ContributorResearchers can often be tripped up by issues they encounter in developing regions and remote areas. Although no definitive answers are provided (there are just too many options and unknowns), the following issues should be considered when planning such a trial.
Research misconduct is a global problem as research is a global activity. Wherever there is human activity there is misconduct, but we lack reliable data on the extent and distribution of research misconduct. This PLoS paper seeks to illustrate some examples of researsch misconduct in LMICs.
In this article, the authors illustrate five basic statistical concepts that can significantly impact the interpretation of the medical literature and its application to the care of patients, drawing examples from the vaccine literature: (i) consider clinical and statistical significance separately, (ii) evaluate absolute risks rather than relative risks, (iii) examine confidence intervals rather than p values, (iv) use caution when considering isolated significant p values in the setting of multiple testing, and (v) keep in mind that statistically nonsignificant results may not exclude clinically important benefits or harms.
Transnational Working Group on Data management of the ECRIN, the European Clinical Research Infrastructures Network, present recommendations for quality and harmonisation for data management. In addition good data management practices in general are identified.
Clinical Data Management: Current status, challenges and future directions from industry perspectives.
by Harry van LoenA range of downloadable templates and tools for Clinical Research, including monitoring checklists, budget spreadsheets, informed consent forms, SOPs and so on.
An example of a academic research centre resolving the issue of clinical trial data management Peer reviewed by members of the data management expert committee for this programme.
Good data management practices are essential to the success of a trial because they help to ensure that the data collected is complete and accurate. This article contains some tips to help you get started with data management.