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Preparing Data for Submission to the FDA Its More Than SDTM Bruce W Thompson, PhD, Michael Rippin, Ph.D., Glenn Daughaday M.B.A., Justin Steele, M.B.A. - Clinical Trials and Surveys Corp (C-TASC), Owings Mills, MD; Abstract Introduction Content Analysis SAS Macro Custom Domain Table Cat by TRT by Decod by Occur Write a Series of Oracle and SAS Marcos To Check Incoming SDTM Data Questions Conclusions Using the statistical nature of the domains, it is possible to address some fundamental questions about each domain according to the data that are supposed to be collected: For instance: Are “extra data” appropriately located? Is there statistical reliability associated with the entry of information in the xxdecod entry and the text entry of the actual values recorded by the study staff? Is there temporal consistency with reporting the start and stop times of exposures and onsets and endings of Adverse Events? Is there any evidence that data might not be missing at random? Acknowledgements This work was supported by the Food and Drug Administration Contract Number HHSF223200850024I iiiiiiiiiiiiiiiiiiiiiiiiiiiii Event Reconciliation An event must end before another event of the same type can start. Oracle Procedure: count number of times two AE intervals of the same type overlap. NDA data submissions to the FDA begin with a data check using the OpenCDISC validation tool. The data are further reviewed by FDA staff during a 45- day interval to determine whether the NDA will be permitted to proceed. During this period of time, FDA staff will perform additional levels of data quality checking to ensure that the review will proceed quickly and efficiently. A set of procedures used by the FDA to identify problems of data consistency and completeness can be broken down into five major categories: Content Analysis: Evaluation of supplemental and custom domains for important content and determination of whether the supplemental or custom data can be fit into a standard domain Fuzzy Matching: Validation that original text has been appropriately transformed to standard values Missing Data: Verification that missing data are not treatment- dependant Statistical Consistency: Assessment of data consistency using various statistical methods Event Reconciliation: Confirmation that time-related events occur sequentially In this poster we provide an overview on how these reviews can be performed by the sponsor prior to submission. With the advent of submitting data to the FDA in CDISC SDTM format, it has become possible to develop large programs to check the data as they arrive or are being prepared to be delivered. A current starting point is to use the OpenCDISC checker program to determine the type and severity of errors according to the data that are to be submitted in each domain. Sample output of the SDTM checker are provided below: Fuzzy Matching Oracle Procedure Compare Text to IG list (e.g., MedDRA) Missing Data SAS Survival Analysis Macro Make Withdrawal Code the “event” and the Event Code the censoring variable Statistical Consistency SAS Macro to Review number of times on and off study meds. The standardized format and meanings generated by CDISC SDTM allow the sponsor to generate sophisticated programs to review data before it is submitted to the FDA. The ability to generate and present these types of analyses will allow FDA and the sponsor to effectively communicate problem findings which may reduce the review time. SD0028 Upper limit must be greater than or equal to lower limit 12 SD0073 Referenced Domain not found 144 Total CT0037 Value for MHBODSYS not found in SOC controlled terminology codelist 7529 SD0009 AE is Serious but no qualifiers set to 'Y' 60 SD0027 Missing value although units provided 8 SD0058 Variable appears in dataset but is not in SDTM standard 2 SD0063 SDTM/dataset variable label mismatch 3 Issue Summary Rule ID Message Found Error SD0002 Null value in variable marked as Required 2 SD0028 Upper limit must be greater than or equal to lower limit 12 SD0036 Missing character result when original result provided 131 SD0073 Referenced Domain not found 144 Total 289 Warning CT0037 Value for AEBODSYS not found in SOC controlled terminology codelist 2218 CT0037 Value for MHBODSYS not found in SOC controlled terminology codelist 7529 SD0006 No baseline result in LB for subject 4 SD0009 AE is Serious but no qualifiers set to 'Y' 60 SD0026 Missing units on value 1 SD0027 Missing value although units provided 8 SD0031 Start date expected when end date provided 1 SD0058 Variable appears in dataset but is not in SDTM standard 2 SD0061 Domain referenced in define.xml but dataset is missing 17 SD0063 SDTM/dataset variable label mismatch 3

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Page 1: Preparing Data for Submission to the FDA Its More Than · PDF filePreparing Data for Submission to the FDA ... NDA data submissions to the FDA begin ... With the advent of submitting

Preparing Data for Submission to the FDAIts More Than SDTM

Bruce W Thompson, PhD, Michael Rippin, Ph.D., Glenn Daughaday M.B.A., Justin Steele, M.B.A. - Clinical Trials and Surveys Corp (C-TASC), Owings Mills, MD;

Abstract

Introduction

Content Analysis� SAS Macro Custom Domain� Table Cat by TRT by Decod by Occur

Write a Series of Oracle and SAS MarcosTo Check Incoming SDTM Data

Questions

Conclusions

Using the statistical nature of the domains, itis possible to address some fundamentalquestions about each domain according tothe data that are supposed to be collected:

For instance:� Are “extra data” appropriately located?� Is there statistical reliability associated with

the entry of information in the xxdecodentry and the text entry of the actual valuesrecorded by the study staff?

� Is there temporal consistency withreporting the start and stop times ofexposures and onsets and endings ofAdverse Events?

� Is there any evidence that data might notbe missing at random?

Acknowledgements

This work was supported by the Food and Drug Administration

Contract Number HHSF223200850024I

i i i i i i i i i i i i i i i i i i i i i i i i i i i i i

Event Reconciliation

� An event must end beforeanother event of the same typecan start.

�Oracle Procedure: count numberof times two AE intervals of thesame type overlap.

NDA data submissions to the FDA begin with a datacheck using the OpenCDISC validation tool. Thedata are further reviewed by FDA staff during a 45-day interval to determine whether the NDA will bepermitted to proceed. During this period of time,FDA staff will perform additional levels of dataquality checking to ensure that the review willproceed quickly and efficiently. A set of proceduresused by the FDA to identify problems of dataconsistency and completeness can be broken downinto five major categories:

Content Analysis:Evaluation of supplemental and custom domainsfor important content and determination ofwhether the supplemental or custom data can befit into a standard domain

Fuzzy Matching:Validation that original text has beenappropriately transformed to standard values

Missing Data:Verification that missing data are not treatment-dependant

Statistical Consistency:Assessment of data consistency using variousstatistical methods

Event Reconciliation:Confirmation that time-related events occursequentially

In this poster we provide an overview on how thesereviews can be performed by the sponsor prior tosubmission.

With the advent of submitting data to the FDA inCDISC SDTM format, it has become possible todevelop large programs to check the data as theyarrive or are being prepared to be delivered.

A current starting point is to use the OpenCDISCchecker program to determine the type and severityof errors according to the data that are to besubmitted in each domain. Sample output of theSDTM checker are provided below:

Fuzzy Matching�Oracle Procedure�Compare Text to IG list(e.g., MedDRA)

Missing Data�SAS Survival Analysis Macro�Make Withdrawal Code the “event” and the Event Code the censoring variable

Statistical ConsistencySAS Macro to Review number of

times on and off study meds.

The standardized format andmeanings generated by CDISCSDTM allow the sponsor togenerate sophisticated programsto review data before it issubmitted to the FDA. The abilityto generate and present thesetypes of analyses will allow FDAand the sponsor to effectivelycommunicate problem findingswhich may reduce the reviewtime.

Issue Summary

Rule ID Message Found

Error

SD0002 Null value in variable marked as Required 2

SD0028 Upper limit must be greater than or equal to lower limit 12

SD0036 Missing character result when original result provided 131

SD0073 Referenced Domain not found 144

Total 289

Warning

CT0037 Value for AEBODSYS not found in SOC controlled terminology codelist 2218

CT0037 Value for MHBODSYS not found in SOC controlled terminology codelist 7529

SD0006 No baseline result in LB for subject 4

SD0009 AE is Serious but no qualifiers set to 'Y' 60

SD0026 Missing units on value 1

SD0027 Missing value although units provided 8

SD0031 Start date expected when end date provided 1

SD0058 Variable appears in dataset but is not in SDTM standard 2

SD0061 Domain referenced in define.xml but dataset is missing 17

SD0063 SDTM/dataset variable label mismatch 3

Issue Summary

Rule ID Message Found

Error

SD0002 Null value in variable marked as Required 2

SD0028 Upper limit must be greater than or equal to lower limit 12

SD0036 Missing character result when original result provided 131

SD0073 Referenced Domain not found 144

Total 289

Warning

CT0037 Value for AEBODSYS not found in SOC controlled terminology codelist 2218

CT0037 Value for MHBODSYS not found in SOC controlled terminology codelist 7529

SD0006 No baseline result in LB for subject 4

SD0009 AE is Serious but no qualifiers set to 'Y' 60

SD0026 Missing units on value 1

SD0027 Missing value although units provided 8

SD0031 Start date expected when end date provided 1

SD0058 Variable appears in dataset but is not in SDTM standard 2

SD0061 Domain referenced in define.xml but dataset is missing 17

SD0063 SDTM/dataset variable label mismatch 3

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