Understanding ADAPT in the SDTM TS Domain: Adaptive vs Non-Adaptive Trials
The Study Data Tabulation Model (SDTM) plays a critical role in organizing and submitting clinical trial data. One of the parameters that regulatory agencies look for in the Trial Summary (TS) domain is the ADAPT parameter (TSPARMCD=ADAPT), which indicates whether the trial follows an adaptive design. In this blog post, we will explore the meaning of ADAPT and provide examples of adaptive and non-adaptive trials.
What is ADAPT in the TS Domain?
The ADAPT parameter identifies whether the clinical trial is adaptive (ADAPT=Y) or non-adaptive (ADAPT=N). An adaptive trial allows for modifications to the study design based on interim results, making the trial more flexible and often more efficient.
"Adaptive clinical trials allow for changes in design or hypotheses during the study based on accumulating data, without undermining the validity or integrity of the trial."
Example 1: Non-Adaptive Trial (ADAPT = N)
A non-adaptive trial follows a fixed protocol and does not allow for any changes during the study. Most traditional randomized controlled trials (RCTs) fall into this category. For example, a phase III trial that tests a drug against a placebo in a predefined number of patients without any modifications would be classified as non-adaptive.
| STUDYID | TSPARMCD | TSVAL |
|---|---|---|
| ABC123 | ADAPT | N |
In this case, the study ABC123 is a non-adaptive trial with no pre-planned modifications allowed during the course of the trial.
Example 2: Adaptive Trial (ADAPT = Y)
An adaptive trial allows changes to be made during the study based on interim analyses. These changes might include modifying sample size, adjusting dosing regimens, or even dropping treatment arms. Adaptive trials are common in oncology and rare disease studies, where efficient trial design is crucial due to limited patient populations.
For example, a phase II oncology trial might allow for dose adjustments or early termination based on early data. In this case, the trial would be classified as adaptive.
| STUDYID | TSPARMCD | TSVAL |
|---|---|---|
| DEF456 | ADAPT | Y |
The study DEF456 is an adaptive trial where the protocol allows for changes based on interim analysis.
Key Considerations for Adaptive Trials
When implementing an adaptive trial, it's essential to plan for certain regulatory and statistical considerations:
- Pre-Specified Rules: Adaptations must be pre-specified in the protocol and reviewed by regulatory bodies.
- Interim Analyses: Interim analyses require statistical rigor to avoid bias or misleading results.
- Regulatory Approval: Regulatory agencies such as the FDA and EMA provide specific guidelines for adaptive trials, which must be strictly followed.
Conclusion
Understanding whether a trial is adaptive or non-adaptive is crucial for interpreting clinical trial data. Adaptive trials offer flexibility and efficiency but come with additional regulatory and statistical challenges. The ADAPT parameter in the TS domain provides a quick way to identify whether a trial has an adaptive design, allowing for more informed data review and analysis.
References
- CDISC SDTM Documentation - Official documentation for SDTM standards by CDISC.
- FDA Guidance on Adaptive Design - Guidance from the U.S. Food and Drug Administration on adaptive trials.
- EMA Guidelines on Clinical Trial Design - European Medicines Agency resources on adaptive and non-adaptive trial designs.
- SDTM Implementation Guide (SDTM IG) - Official SDTM Implementation Guide from CDISC.
