Tournoux-Facon et al. (2011) proposed a new Adaptive Stratified phase II design based on the multiple-stage Fleming design. It is an alternative approach to dealing with stratification in a phase II setting and aims to demonstrate whether an experimental treatment (a control arm is not included, thus it’s about a single arm approach) is beneficial for at least one biomarker-defined subgroup rather than the entire study population.
Alternative names: No alternative names found for this trial design
Adaptations: The number of patients and decision rules are based on the observed response rates during the first stage of the study.
- Decision making and the number of patients used at the second stage of the trial are based on the observed response rates during the first stage of the trial. This approach depends on the identification of heterogeneity between the two biomarker-defined subgroups (positive and negative subgroups).
- Heterogeneity is identified when the observed response rate in one of the biomarker-defined subgroups is less than π0i (defined as the probability of response in one of the biomarker-defined subsets below which the novel treatment is considered to be a low-activity treatment, where i denotes each biomarker-defined subgroup; the value of 0.25 is used for the π0i by Tournoux-Facon et al. (2011)), whereas the other subset has a response rate greater than π0i. The subset for which the observed response rate is less than π0i is considered clinically insignificant, and therefore cannot continue to the second stage of the trial. Only the subgroup with response rate greater than π0i therefore enters the second stage where the study can continue as a randomized Phase III trial comparing the novel treatment which has proved to be effective with the standard of care. More precisely, the identification of heterogeneity of responses is performed by calculating the symmetric interval of probability around π0i at each stage (only a symmetric interval is observed due to binomial calculation).
- When the first stage of the design is terminated, in case that the cumulative number of responses for one of the biomarker-defined subset is less than/greater than the lower/upper boundary of the aforementioned symmetric interval of probability and the cumulative number of responses for the other biomarker-defined subgroup is greater than/less than the upper/lower boundary of the symmetric interval, then the responses between the two subsets are considered heterogeneous; otherwise, the treatment effect is similar in the two subsets, consequently, the trial continues without selecting any biomarker-defined subset. After the identification of heterogeneity of responses, conclusions at the end of the first stage of the trial are made according to decision rules based on specific thresholds which are determined by iterations using a Fleming two-stage approach; a single-arm design which permits early termination of the trial for either efficacy or inefficacy of the treatment.
Note: The adaptive stratified design has a number of differences from the Adaptive Parallel Simon two-stage design proposed by Jones and Holmgren (2007) and the global one-sample test for response rates for stratified phase II clinical trials proposed by London and Chang (2005). First and foremost, the adaptive stratified design permits early stopping for inefficacy or efficacy of the study as it is a strategy based on a Fleming design. On the contrary, the two aforementioned methods are based on the Simon design and do not make the discontinuation of the study possible. Additionally, the stratification approach used in the design provided by Tournoux-Facon et al. (2011) is utilized in order to target the patients who are most likely to respond to a novel treatment, whereas, stratification in the design by London and Chang (2005) aims to ameliorate the power of the overall test.
- Can avoid unethical studies in patients for whom the novel treatment is not effective as it allows for the identification of efficacy which is limited to a particular biomarker-defined subgroup.
- The trial can continue to Phase III only with a subgroup which is proven to benefit from the experimental therapy and not with the entire population.
- Less numbers of individuals for whom the novel treatment is not effective will be tailored to toxic treatments.
- Permits the identification of the actual treatment benefit in at least one biomarker-defined subgroup.
- Avoids the termination of tailoring a novel treatment due to treatment effect dilution in the entire population.
- Permits early stopping of efficacy or inefficacy.
- No information found
No variations found for this trial design