Sunday, December 17, 2017

The future of SDTM

Today, I looked into the newly published SDTM v.1.6 and the new SEND-IG-DART)

This new version is solely meant for SEND-DART (non-clinical sumission datasets: Developmental and Reproductive Toxicology). When going through both new standards, there were quite a number of very disturbing things (at least for me):

  • There are no machine-readable files. The SDTM v.1.6 comes as HTML, the SEND-IG-DART as a PDF. Essentially, this means a lot of frustrating copy-and-paste for those who want to implement these standards into their systems and software.
  • As there is no machine-readable version, all the "rules" and "assumptions" are not machine-readable anyway, thus leaving them open for different interpretations. It is then also foreseeable that a certain company that is working for the FDA will "highjack" the interpretation of the rules and use it for commercial purposes.
  • This version of SDTM is solely meant for SEND-DART. This is very worrying. SDTM which was named "SDS" (Submission Data Standard) in earlier days and has always be meant to be a "universal" model for both SDTM (human trials) as for SEND (non-clinical / preclinical studies). Here is the "big picture" (copied from the CDISC website):

    When starting naming different "flavors" of the "universal" SDTM standard "versions", we are doing something really wrong. "Standards Versions" should be subsequent, a newer version replacing the older one. Unfortunately, this is not the case anymore.
  • We see more and more that some SDTM variables are only allowed/meant to be used in a single domain. Also here, some new veriables have been added which can only be used in one or only a few domains. For me, this evolution demostrates the failure of the SDTM model anyway.
  • The model is again tightly coupled to the outdated SAS-XPT format: variable names and test codes not longer than 8 characters, labels not longer than 40 characters and values not longer than 200 characters. Only US-ASCII is allowed. Such a direct coupling between a model and a transport format is nowadays as an "absolute no-go" in modern informatics.
  • As in prior versions, model and IG contain a lot of derived variables. As SDTM is essentially about "captured data", derived variables should not be in SDTM
  • Also this version of SDTM sticks to "tables" (2-dimensional). Now, there is nothing against tables, but in order to guarantee high quality data, there should be explicit relations between the tables, without any data redundancy. This is what relational databases are based on.
    SDTM however breaks almost every rule of a good relational database, with lots of data redundancy (inevitable leading to reduced data quality), with many unnecessary variables added "for the sake of ease of review" (sic), but essentially ruining the model.
So, what can be done? How should the future of SDTM look like? Let us make a "5-year plan". We can divide this short term, middle term and long term actions.

Short term actions
  • In case FDA and PMDA cannot guarantee that they will accept Dataset-XML very soon, replace SAS-XPT by a simple, easy-to-use, vendor-neutral format that does not overstrain FDA and PMDA.
    It is now clear that FDA and PMDA do not have the capability (or do not want) to switch from XPT to the modern Dataset-XML format. Concerns about file sizes ("a submission might not fit on a memory stick") and inexperience with XML anyway look to be the current "show stoppers".
    As a temporary solution (the "better than nothing solution") but already solving a lot of the limitations of SAS-XPT, a simple "bar-delimited" (also named "pipe-delimited") but UTF-8 encoded simple text files can be used ("HL7-v2 like"). For example (LB dataset):

    Such datasets are very compact, on an average take only 25% of the corresponding SAS-XPT file size, and are easy to import into any software. There is no 8-, 40-, or 200-character limit, and can easily handle non-ASCII characters such as Spanish (USA) and Japanese (Japan) characters.
    The metadata is all in the define.xml, but if also this is a problem for the systems at the regulatroy authorities, the first row can contain the variable names.
    Acceptance for this format could (technically) easily be established in a period of 6 months or less. However, this step can be skipped when FDA and PMDA implement Dataset-XML within a reasonable (<2 years) time.
    Once this done, we are at least freed from the "hostage" of the SAS-XPT format limitations, allowing us to take the next steps (SAS-XPT is currently the "show stopper" for any innovation). The acceptance of XPT should then be stopped within 2-3 years by the FDA and PMDA, to allow sponsors to adapt, this although "bar-delimited" and Dataset-XML files can easily be generated from XPT files.
  • Stop developing controlled terminology for which there is considerably better controlled terminology in the healthcare world. This comprises controlled terminology for LBTESTCD, LBTEST and UNIT. Investigate whether this should also apply to other CDISC controlled terminology (e.g. microorganisms?).
    This step does not mean that the use of the already developed terms is not allowed anymore, but it means that no effort is wasted in developing new terms anymore. Also remark that this may mean that some subteams are put on hold.
Mid term actions

Once we are "freed" from SAS-XPT, we can take the next steps
  • Decide which controlled terminology should be deprecated. For example, I expect the "COMPONENT" part of LOINC to be a better alternative for LBTESTCD/LBTEST. Databases for these are already available. Remark that "COMPONENT" in LOINC is limited to 255 characters in length, so considerably more than the ridiculous 8 characters in LBTESTCD. But that is not a problem as the transport format has no length limitations for fields at all.
    The "deprecation time" in which the old terminology is faded out can then be agree e.g. to be 5 years. For UCUM, I think the case is clear: we can no longer afford to disconnect from e-healthcare
  • Considerably improve our relationships with other SDOs (HL7, Regenstrief, NLM) in healthcare, not considering them as "the enemy" anymore, but being prepared to learn from them, even deprecating some of our standards in favor of well-established ones in healthcare.
  • As SDTM is not fit for e-Source, develop new Findings domains that are fit for e-Source, probably using LOINC and other modern coding systems as identfiers for tests. As long as not everything is e-Source, these domains will probably be in parallel with the existing domains. This time do it good: do not allow for derived and data-redundant variables.
    This step is not as easy as it looks: it would mean that for these domains, SDTM becomes a real relational database, which also has the consequence that the data-redundant variables that were introduced "for ease of review" will not be present anymore (leading to higher data quality), and that review tools at the regulatory authorities will needed to be adapted, i.e. that they will need to implement "JOINS" between tables (for relational databases, this might mean creating "VIEW" tables).
    This step will require a change in mentality for both CDISC and the regulatory authorities: for CDISC from "we do everything the FDA/PMDA (reviewers) ask us", to a real partnership, where CDISC helps the FDA and PMDA implementing these new, improved domains. This may mean that CDISC's own consultants work at FDA and PMDA for some time to help adapting their systems. This looks more difficult as it is, as it essentially reduces in implementing foreign keys and creating "VIEW"s on tables. Essentially, it would also mean that CDISC and FDA work together on the validation rules and their technical implementation, so that high quality validation rules and implementations of them become available, very probably as "real open source" (the current validation software used by the FDA and PMDA is less than suboptimal and based on the own interpretation of the SDTM-IGs by a commercial company)
  • Switch from a simple transport to a modern transport format (which might, but must not be Dataset-XML), allowing for modern review using RESTful web services, as e.g. delived by the National Library of Medicine and others, allowing "Artificial Intelligence" for considerably higher quality (and speed) of review.
  • Start thinking of the SDTM of the future. Must it be tables (the world is not flat, neither is clinical data - Armando Oliva, 2009)? Execute pilots with submissions of "biomedical concepts", and "linked data" using a transport format that is independent from the model.
Whereas the "short term" can be limited to something like 6 months, the "middle term" will probably take something like 2-3 years. This step will surely require "bye-in" from FDA and PMDA. Within CDISC, there is so much expertise which is currently not used: we do have a good number of brilliant volunteers (some of we lost to other organizations such as Phuse) who can help bring ourselves and the regulatory authorities to the next level of quality in review.

Long term actions
  • SDTM is highly probably not the ideal way to submit information to the regulatory authorities. Even when "cleaned", removing unnecessary and redundant information, a set of tables should not be the "model", it should only be one of the many possible "views" on the data. At this moment, only the "table view" is essentially used, or it must be that some (but not all) reviewers have their own "trick box" (own tools) to get more out of the data.
  • In the "middle term" period, we should already start looking into using "biomedical concepts" for submission, following ideas already developed by some of our volunteers and a number of companies. We might even already do pilots with the regulatory authorities at this point
  • In the "long term" we must come to a better way of submitting information, part of which will be in the form of "biomedical concepts". When looking at HL7-FHIR, I see that their "resources" and "profiles" are extremely successful and very near to what we need in clinical research, also for submissions.
  • Work together with other organizations to come to a single model for care and research in the medical world. With the upcome of wearables, site-less studies, interoperable electronic health records in many countries, we can no longer afford to work in isolation (or even claim that clinical research is "special").
Personally, but who am I, I would not be surprised that we make it happen that e.g. FHIR and CDISC standards evolve into a single standard in 10 years from now.

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