| Adaptive randomisation | Allows modification of the randomisation schedule based on treatment, response, etc. |
| The goal is to assign more patients to a promising test treatment |
| Patient characteristics should be balanced between the groups |
| Not feasible for a large trial with relatively long treatment duration |
| Adaptive group sequential | Classical group sequential design with pre-specified interim analyses |
| Options of additional adaptations include: |
| Sample size re-estimation |
| Modification/deletion/addition of treatment arms |
| Change of study end-points |
| Modification of dose, schedule and treatment duration |
| Flexible sample size re-estimation | Allows for sample size adjustment/re-estimation based on the observed interim data |
| May be biased as the original power analysis for sample size calculation is performed prior to conducting the study |
| The observed interim difference is based on a small number of subjects and: |
| May not be statistically significant (maybe due to chance alone) |
| May not be reproducible |
| Can be either based on overall data or based on criteria such as treatment-effect size, conditional power and/or reproducibility |
| The US Food and Drug Administration recommends re-estimation methods be based on interim analyses on overall data |
| Drop the losers (or picking up the winners) | A multistage design that allows: |
| Dropping the inferior treatment groups |
| Modifying treatment arms |
| Adding additional arms after the review of interim data |
| Risks related to this study design are: |
| Not having enough statistical power at the end of the first stage |
| The investigator may pick up the wrong group |
| Adaptive dose-finding | Used in early phase clinical development to identify the maximum tolerated dose, as it is desirable to achieve it with a limited number of patients |
| The selection of initial dose, dose range and criteria for dose escalation and/or dose de-escalation is important for the success of the trial |
| A recently proposed new method (the continual reassessment method) allows continual reassessment of the dose–response relationship based on the accumulative data collected |
| Biomarker adaptive | Enables adaptations based on the response of biomarkers |
| Involves biomarker qualification, optimal screening design, and model selection and validation |
| It is useful to identify: |
| The patient population most likely to respond |
| The natural course of disease |
| Early disease |
| Adaptive treatment-switching | Allows a patient’s treatment to be switched from one assignment to an alternative if there is evidence of lack of efficacy, disease progression or safety issues |
| Adaptive hypothesis | Permits changes in hypotheses in response to interim analysis results to achieve the desired power |
| Some examples include pre-planned switching: |
| From a single hypothesis to a composite or multiple hypotheses |
| Between the null hypothesis and the alternative hypothesis |
| Between the primary and the secondary end-points |
| Phase I/II (or II/III) adaptive seamless trial | It combines the objectives, traditionally addressed in separate trials, into a single study |
| The most common examples include: |
| Adaptive seamless phase I/II design |
| Adaptive seamless phase II/III design |