White Papers to Fill the Gaps of Standardization of Tables, Figures, and Listings (Creating Standard Targets)

Analyses and Displays for Vital Signs, ECG, and Laboratory Analyte Measurements

Mary Nilsson, Eli Lilly and Company; Wei Wang, Eli Lilly and Company; Qi Jiang, Amgen

White Paper 2 – Under 1st Round Review!

White Paper 1 – Finalized October 2013

Conclusion:Industry standards have evolved over time for data collection

(CDASH), observed data (SDTM), and analysis datasets (ADaM). Development of standard tables and figures with associated analyses

is the next step! Having an organized process for shared learning of improved

methodologies can lead to earlier safety signal detection and better characterization of the safety profile of our products.

We welcome new members! Contact information on phusewiki.org.

OBJECTIVE

The objective of this poster is to receive feedback on recommended displays for vital signs, electrocardiogram, and laboratory analyte measurements as outlined in PhUSE Computational Science Symposium (CSS) white papers as part of a standardization and code-sharing effort.

The Vision – Development of Standard Scripts for Analysis and Reporting Working Group

Standard Targets and Validated

Scripts

Industry

FDA

Academic

Data Collection Systems

Observed Datasets

Analysis Datasets

Tables, Figures

and Listings

Clinical Data Flow

Trial Design

PRM SDTM ADaM No TFL Stds Exist

IndustryStandardsAlignment

CDASH

Examples of Discussed Topics

Whether to report p-values and confidence intervals

Handling of measures collected in reflex manner, repeated measures, unplanned measures, measurements post drug exposure

Defining baseline

Central versus local laboratories

Choices of lab reference limits

Units and transformations

ECG correction factors

Recommended Tables and Figures

• Allows for visual inspection of changes over time• Can visually assess the potential

impact of outliers on the central tendency summary statistic• Out of range values in red

• Easy to see treatment differences• Summary table compliments box

plot so numbers are available for textual summaries

Two pages per measuremento One for Max. baseline vs. Max.

post-baseline (shown on the left)o Another identical one for Min.

baseline vs. Min. post-baseline

• Scatter ploto Shows patient level informationoAllows quick browsing through a

large amount of information• Shift table

o Shows useful summary level statistics

• Treatment emergent high/low tableo Shows concise summary level

statistics oAllows for easy assessment of

treatment difference

Acknowledgements: Special acknowledgement to members of the PhUSE Computational Science Symposium Standard Scripts for Analysis and Programming Working Group, White Papers Project Team who have contributed to the white papers, and to those who have provided review comments.

• Only has mean and SD - Lacks additional useful summary statistics• Outliers not

displayed• Can be misleading

when data are non-normal

• Lack of information on patient level informationo Lack of magnitude of shift • Difficult to assess overall

treatment differenceo Very popular, however, users

tend to count and create grouped percentages manually for those shifting to high from low/normal (or low from normal/high).

Traditional Tables and Figures

Other White Papers

In Development:Adverse EventsDemographics, Disposition, MedicationsHepatotoxicityNon-compartmental PK Planned: QT Studies

Where to Find Things

PhUSE CSS Final Deliverables: www.phuse.eu, click PublicationsPhUSE CSS Work in Progress:www.phusewiki.org, click CSS Working Groups, then Development of Standard ScriptsScript Repository (reusable code library): https://code.google.com/p/phuse-script