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Why hasn't the FDA more actively promoted CDISC standards

 

Wondering why the FDA hasn't more actively promoted CDISC standards

Jennifer Price Jennifer Price, CDISC CDASH Registered Service Provider (RSP)
It has always been a mystery to me why the FDA hasn't more enthusiastically embraced and offered incentives for NDA submissions to conform to the CDISC standards (A bit of this mystery was lifted for me at the CDISC INTRAchange in March). The INTRAchange is a meeting of the core CDISC participants and Dr. Theresa Mullin, Director of Planning and Informatics at FDA/CDER, spoke about the data review process at the FDA.

Food and Drug Administration (FDA) The FDA uses their Janus software as a repository to store the data, but they allow the reviewers to use different end-user tools to generate their views or develop their own code for analysis purposes. 

The clinical data are typically presented in SAS files, but represented within these files in many different ways. For example, one study might collect medical history written as a narrative in a large text field, another might have collected medical history using a ‘check all that apply' methodology and only list the history that was checked. Medical History could also be represented by asking the patient to list each event in their medical history with the onset date separated out line by line. Some companies may code the history so that it is listed by body system, organ class, high level term, low level term and preferred term. Since there is no mandate to use standards, the reviewer is stuck with whatever they are presented with.

Astoundingly, less than 15% of the studies submitted to the FDA today follow any type of CDISC standard, although most companies agree that submitting data to the FDA using the CDISC standards will provide reviewers with a more consistent deliverable.

Dr. Mullen brought up several points around the submission of data using standards. Here are two that I found most interesting:

  1. There is no way for a Reviewer to know whether the data they are looking at is presented in a CDISC standard. Other unknowns are:
    • Did the sponsor follow the CDISC standard precisely, or make some modifications or assumptions?
    • Do some datasets follow the standard and others don't?
    • Are some fields in some datasets standard, but not all?
    • Are the field names standard names, but the data contained in the fields not collected in a standardized way?
  2. The FDA reviewers are not required to attend training on the CDISC standards. Those familiar with them know that the relationships and instructions for defining the data are complex and reading the complete documentation may not be feasible for all reviewers. Part of the problem stems from the fact that there is limited funding for training.

Thinking about the issues that the FDA faces brings up some new questions:

  • How can the FDA be expected to receive benefits from receiving data in a standard way if reviewers are not trained on the standard?
  • How can a reviewer sort through data easily if it is submitted in standards that are only partially standard?
  • Where should the funding come for providing tools and training on standards to the FDA?
  • How can the industry benefit from CDISC standards without FDA leadership, or at least participation?

I invite your comments and responses!

Sources:

http://www.cdisc.org/rsp

http://www.cdisc.org/standards

http://www.fda.gov/ForIndustry/DataStandards/StudyDataStandards/default.htm

 

Comments

I think CDISC will be adopted within the agency as the generational shift occurs. I firmly believe that there must be some sort of hidden pride in figuring out some of the obscure data structures submitted to these reviewers.
Posted @ Wednesday, May 19, 2010 11:17 PM by D. Bahr
Is the problem that the SDTM is a container standard with 30+ different data exchange structures (domains) with individual columns? And that the SDTM Controlled Terminologies (derived from the NCI Thesaurus) is a content standard for unconnected terms. 
 
While we lack a standard to describe the pieces that needs to be represented, exchanged and interpret together. That is, to make medical knowledge and clinical practice explicit. For example, the result of a blood pressure measurement should be linked to these different positions of the subject, and to an assessment time, and if required also to the required types of devices. 
 
At the Clinical Interchange conference in November 2009 FDA expressed the need for a more normalized way to submit clinical data separated from the analysis views. (Jay Levin in the FDA panel). Such a normalized structure is provided by RDF, part of the stack of semantic web standards from W3C. Billions of data points describing things like earthquakes, schools, roads and clinical studies, have been made available as RDF triples, see US government data http://data.gov and Linked Open Drug Data http://esw.w3.org/HCLSIG/LODD
Posted @ Tuesday, September 07, 2010 8:38 AM by Kerstin Forsberg
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