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Oh, the places you’ll go with findings data in JMP Clinical

A recent post by Richard Zink highlighted the Shift plots process in JMP Clinical software. Shift plots (and shift tables, a recent enhancement to JMP Clinical 4.1) are a key analysis for data from SDTM findings domains (e.g., laboratory, vital signs, etc.), according the FDA ICH E3 guidance. JMP Clinical offers several additional visualization and analysis options for SDTM Findings domains.

I am a new mother to an extremely active 7-month-old who is crawling and climbing her way EVERYWHERE. So forgive me that my inspiration for this blog post is not only the FDA guidance, but also another common document resource: Dr. Seuss. When my daughter started crawling, a new world suddenly opened up for her. And in a few weeks, she gained several new skills, thanks to her newfound mobility. I could see her thinking:

“Oh, the places you'll go! There is fun to be done!”*

Data analysis is a lot like that. When given the right set of tools, you can learn a lot quickly -- finding results you expect as well as unexpected findings that can drive your analysis.

The more that you learn, the more places you’ll go.”

JMP Clinical offers several tools for clinical findings data, all of which were developed with consideration of FDA guidelines. The ICH E3 guidance specifies evaluation of laboratory values be analyses of values over time (time trends and distributions of abnormal counts across visits), individual patient changes (shift tables and plots) and individual clinically significant abnormalities (patient narratives and profiles). Here’s a summary of JMP Clinical tools to get you to where you want to go with findings analysis:

Histograms, bar charts, analysis of variance (or contingency analysis for character findings) and tables in the distribution process quickly summarize the frequency of laboratory tests, abnormalities, treatment differences and missing results. Count plots shown in Figure 2 are a new feature in JMP Clinical 4.1. Notice the trend of more subjects on treatment (NIC .15) with abnormally high blood urea nitrogen (BUN) levels across visits.

Box plots, time trends and bubble plots produce a variety of views to evaluate findings values over time. You can create box plots summarized across the trial or at timed trial intervals, display mean and individual time trends across visits and time points, and follow the bivariate distribution of two findings tests through the dynamic bubble plot across study day. Calculations can be performed for observed or baseline-relative measurements. Analysis results are at the individual level and offer one-click patient profiles (and one-more-click patient event narratives).

With many ways to view the data, it can be daunting to review each of the potentially dozens of laboratory tests taken during a clinical trial.

“You can get so confused that you'll start in to race down long wiggled roads at a break-necking pace and grind on for miles across weirdish wild space, headed, I fear, toward a most useless place.”

For the statistically minded, Baseline ANOVA fits a repeated measures mixed model to test for treatment differences in baseline-adjusted findings measurements. A space-constrained volcano plot view immediately shows tests with treatment differences that may merit further analysis. Drilling down to shift plots, box plots and trend plots gets you to the subject-level view of values across time for selected tests of interest to help streamline the clinical review. Findings Time to Event provides further targeted analysis to track differences in occurrence of specific finding measurement “events.”

Last but certainly not least, Hy’s Law Screening provides a rich set of tools for liver enzyme analysis to detect potential drug-induced liver injury. This process was developed directly based on the FDA Guidance for Industry Drug-Induced Liver Injury and vetted by industry experts. New features in JMP Clinical 4.1 include a summary view inspired by the FDA eDISH tool, plots of liver test peaks across study day, counts and percent tables of elevations and Hy’s Law Case detection, and new time profile and liver shift plot drill downs. There is so much to this process that it might just require another blog post! Stay tuned, and in the meantime…

“You have brains in your head. You have feet in your shoes. You can steer yourself any direction you choose.”

* Dr. Seuss. (1990). Oh, the Places You'll Go!  New York: Random House Children’s Books.

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