Tag: Clinical Trials

0
Forest Plot Add-In for JMP 10

A forest plot (Figure 1) is a convenient way to graphically display several confidence or credible intervals and is often used in meta-analysis. Here, the x-axis represents the treatment effect between two interventions while the y-axis refers to the individual studies from which the intervals are obtained, or to various consensus intervals derived

1
Disproportionality analysis is coming in JMP Clinical 4.0

While randomized clinical trials are the gold standard for evaluating the efficacy of a new intervention, the available sample size is often insufficient to fully understand its safety profile. The risk a new therapy may pose may not be well understood until it has been on the market for many

0
JMP Clinical at CDISC European Interchange

Every year, the Clinical Data Interchange Standards Consortium (CDISC) holds several Interchange events that take place in the US, Europe and Asia. These meetings have several goals: to give CDISC users the opportunity to present solutions to data challenges that arise in the day-to-day use of these standards; to provide new or

0
JMP Clinical present at PhUSE, Brighton 2011

The Pharmaceutical Users Software Exchange (PhUSE) conference in the British seaside resort of Brighton was nearly two months ago, but I am still thinking about it; PhUSE provided an opportunity to learn from experts and share ideas about the application of software in the pharmaceutical industry. The theme for this

0
Accounting for the time at which an adverse event occurs

In a previous post, I described how JMP Clinical allows you to specify time windows within an incidence analysis. Specifying time windows can provide a more informative analysis since it is possible to view how the risk of adverse events (AEs) changes over the course of a clinical trial. However, the

0
Discovering unreported adverse events using your findings data

When designing case report forms (CRFs) for a clinical trial, it is important to minimize or eliminate redundancies in the collected information. Such redundancies can lead to inconsistencies that require a query to the clinical site for resolution. In a poorly designed CRF, data conflicts can be so numerous that

1
Summarizing the incidence of adverse events

The analysis of adverse events (AEs) suffers from the problem of dimensionality. It is impossible to predict what AEs will occur on study, and there are often numerous events by study’s end. Typically, the incidence of adverse events is summarized in tables, with events coded by a medical dictionary, such

0
JMP Clinical 3.1 generates adverse event narratives

In a clinical trial, when a subject has a serious adverse event (SAE) or other significant adverse event (AE), such as those leading to the discontinuation of the study, a narrative is written for the clinical study report. These narratives summarize the details surrounding the event to enable understanding of

0
People Behind JMP Software: Russ Wolfinger

Today, we're releasing the latest version of JMP Clinical and would like to introduce you to someone who is essential to this product (as well as JMP Genomics): Russ Wolfinger. You may know him as a blogger in this space, but Russ' real job at JMP is Director of Scientific

0
JMP Add-Ins: Super Extensibility, Baby!

Congratulations to the Cheeseheads on their Super Bowl victory. As a fan of that pro-sports desolate wasteland known as Cleveland, and despite a conflicting desire to demonstrate league superiority of the AFC North, I found myself pulling for the team in green (plus I love cheese). Nice to see a