14.Randomization01.Adaptive enrichment design - sporedata/researchdesigneR GitHub Wiki

1. Use cases: in which situations should I use this method?

  • These are trials where the eligibility criteria can be adaptively updated during the trial, progressively restricting the inclusion to patients who are more likely to benefit from the intervention [1].

2. Input: what kind of data does the method require?

  • Patients willing to be randomized

3. Algorithm: how does the method work?

Model mechanics

Reporting guidelines

  • Guidelines for the Content of Statistical Analysis Plans in Clinical Trials [2].

Data science packages

Suggested companion methods

Learning materials

  1. Books
    *
  2. Articles

4. Output: how do I interpret this method's results?

Mock conclusions or most frequent format for conclusions reached at the end of a typical analysis.

Tables, plots, and their interpretation

5. SporeData-specific

Templates

Data science functions

References

[1] Simon N and Simon R. Adaptive enrichment designs for clinical trials. Biostatistics. 2013 Sep;14(4):613-625.

[2] Gamble C, Krishan A, Stocken D, Lewis S, Juszczak E, Doré C, Williamson PR, Altman DG, Montgomery A, Lim P, and others. Guidelines for the Content of Statistical Analysis Plans in Clinical Trials. Jama. 2017 Dec 19;318(23):2337-2343.

[3] Senn SJ, Lewis RJ. Treatment effects in multicenter randomized clinical trials. Jama. 2019 Mar 26;321(12):1211-2.

⚠️ **GitHub.com Fallback** ⚠️