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The Stroke Hyperglycemia Insulin Network Effort (SHINE) trial: an adaptive trial design case study.

Connor JT, Broglio KR, Durkalski V, Meurer WJ, Johnston KC - Trials (2015)

Bottom Line: Two designs were brought forward, and both were evaluated, revised, and improved based on the input of all parties involved in the ADAPT-IT process.However, the SHINE investigators were tasked with choosing only a single design to implement and ultimately elected not to implement the Goldilocks design.The Goldilocks design will be retrospectively executed upon completion of SHINE to later compare the designs based on their use of patient resources, time, and conclusions in a real world setting.

View Article: PubMed Central - PubMed

Affiliation: Berry Consultants, LLC, 4301 Westbank Dr Bldg B Suite 140, Austin, TX, 78746, USA. jason@berryconsultants.com.

ABSTRACT

Background: The 'Adaptive Designs Accelerating Promising Trials into Treatments (ADAPT-IT)' project is a collaborative effort supported by the National Institutes of Health (NIH) and United States Food & Drug Administration (FDA) to explore how adaptive clinical trial design might improve the evaluation of drugs and medical devices. ADAPT-IT uses the National Institute of Neurologic Disorders & Stroke-supported Neurological Emergencies Treatment Trials (NETT) network as a 'laboratory' in which to study the development of adaptive clinical trial designs in the confirmatory setting. The Stroke Hyperglycemia Insulin Network Effort (SHINE) trial was selected for funding by the NIH-NINDS at the start of ADAPT-IT and is currently an ongoing phase III trial of tight glucose control in hyperglycemic acute ischemic stroke patients. Within ADAPT-IT, a Bayesian adaptive Goldilocks trial design alternative was developed.

Methods: The SHINE design includes response adaptive randomization, a sample size re-estimation, and monitoring for early efficacy and futility according to a group sequential design. The Goldilocks design includes more frequent monitoring for predicted success or futility and a longitudinal model of the primary endpoint. Both trial designs were simulated and compared in terms of their mean sample size and power across a range of treatment effects and success rates for the control group.

Results: As simulated, the SHINE design tends to have slightly higher power and the Goldilocks design has a lower mean sample size. Both designs were tuned to have approximately 80% power to detect a difference of 25% versus 32% between control and treatment, respectively. In this scenario, mean sample sizes are 1,114 and 979 for the SHINE and Goldilocks designs, respectively.

Conclusions: Two designs were brought forward, and both were evaluated, revised, and improved based on the input of all parties involved in the ADAPT-IT process. However, the SHINE investigators were tasked with choosing only a single design to implement and ultimately elected not to implement the Goldilocks design. The Goldilocks design will be retrospectively executed upon completion of SHINE to later compare the designs based on their use of patient resources, time, and conclusions in a real world setting.

Trial registration: ClinicalTrials.gov NCT01369069 June 2011.

No MeSH data available.


Related in: MedlinePlus

Mean total sample size enrolled (left panel) and probability of trial success (right panel). SHINE is plotted with a circle and the Goldilocks is plotted with an x. Heavy line represents a control success rate of 25%, medium line represents a control success rate of 30%, and light line represents a control rate of 35%. Dashed line on the right panel shows 80% power for reference.
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Fig1: Mean total sample size enrolled (left panel) and probability of trial success (right panel). SHINE is plotted with a circle and the Goldilocks is plotted with an x. Heavy line represents a control success rate of 25%, medium line represents a control success rate of 30%, and light line represents a control rate of 35%. Dashed line on the right panel shows 80% power for reference.

Mentions: The left panel of FigureĀ 1 shows the total mean number of patients enrolled for the two designs. Generally, when the treatment effects are or small, both designs stop early for futility and when the treatment effects are large, both designs stop early for success. Thus, sample sizes are smaller at each end of the treatment effect range than in the middle.Figure 1


The Stroke Hyperglycemia Insulin Network Effort (SHINE) trial: an adaptive trial design case study.

Connor JT, Broglio KR, Durkalski V, Meurer WJ, Johnston KC - Trials (2015)

Mean total sample size enrolled (left panel) and probability of trial success (right panel). SHINE is plotted with a circle and the Goldilocks is plotted with an x. Heavy line represents a control success rate of 25%, medium line represents a control success rate of 30%, and light line represents a control rate of 35%. Dashed line on the right panel shows 80% power for reference.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4352277&req=5

Fig1: Mean total sample size enrolled (left panel) and probability of trial success (right panel). SHINE is plotted with a circle and the Goldilocks is plotted with an x. Heavy line represents a control success rate of 25%, medium line represents a control success rate of 30%, and light line represents a control rate of 35%. Dashed line on the right panel shows 80% power for reference.
Mentions: The left panel of FigureĀ 1 shows the total mean number of patients enrolled for the two designs. Generally, when the treatment effects are or small, both designs stop early for futility and when the treatment effects are large, both designs stop early for success. Thus, sample sizes are smaller at each end of the treatment effect range than in the middle.Figure 1

Bottom Line: Two designs were brought forward, and both were evaluated, revised, and improved based on the input of all parties involved in the ADAPT-IT process.However, the SHINE investigators were tasked with choosing only a single design to implement and ultimately elected not to implement the Goldilocks design.The Goldilocks design will be retrospectively executed upon completion of SHINE to later compare the designs based on their use of patient resources, time, and conclusions in a real world setting.

View Article: PubMed Central - PubMed

Affiliation: Berry Consultants, LLC, 4301 Westbank Dr Bldg B Suite 140, Austin, TX, 78746, USA. jason@berryconsultants.com.

ABSTRACT

Background: The 'Adaptive Designs Accelerating Promising Trials into Treatments (ADAPT-IT)' project is a collaborative effort supported by the National Institutes of Health (NIH) and United States Food & Drug Administration (FDA) to explore how adaptive clinical trial design might improve the evaluation of drugs and medical devices. ADAPT-IT uses the National Institute of Neurologic Disorders & Stroke-supported Neurological Emergencies Treatment Trials (NETT) network as a 'laboratory' in which to study the development of adaptive clinical trial designs in the confirmatory setting. The Stroke Hyperglycemia Insulin Network Effort (SHINE) trial was selected for funding by the NIH-NINDS at the start of ADAPT-IT and is currently an ongoing phase III trial of tight glucose control in hyperglycemic acute ischemic stroke patients. Within ADAPT-IT, a Bayesian adaptive Goldilocks trial design alternative was developed.

Methods: The SHINE design includes response adaptive randomization, a sample size re-estimation, and monitoring for early efficacy and futility according to a group sequential design. The Goldilocks design includes more frequent monitoring for predicted success or futility and a longitudinal model of the primary endpoint. Both trial designs were simulated and compared in terms of their mean sample size and power across a range of treatment effects and success rates for the control group.

Results: As simulated, the SHINE design tends to have slightly higher power and the Goldilocks design has a lower mean sample size. Both designs were tuned to have approximately 80% power to detect a difference of 25% versus 32% between control and treatment, respectively. In this scenario, mean sample sizes are 1,114 and 979 for the SHINE and Goldilocks designs, respectively.

Conclusions: Two designs were brought forward, and both were evaluated, revised, and improved based on the input of all parties involved in the ADAPT-IT process. However, the SHINE investigators were tasked with choosing only a single design to implement and ultimately elected not to implement the Goldilocks design. The Goldilocks design will be retrospectively executed upon completion of SHINE to later compare the designs based on their use of patient resources, time, and conclusions in a real world setting.

Trial registration: ClinicalTrials.gov NCT01369069 June 2011.

No MeSH data available.


Related in: MedlinePlus