Bayesian predictive power for interim adaptation in seamless phase II/III trials where the endpoint is survival up to some specified timepoint

Mobile health tools that enable clinicians and researchers to monitor the type, quantity, and quality of everyday activities of patients and trial participants have long been needed to improve daily care, design more clinically meaningful randomized trials of interventions, and establish cost-effective, evidence-based practices. Inexpensive, unobtrusive wireless sensors, including accelerometers, gyroscopes, and pressure-sensitive textiles, combined with Internet-based communications and machine-learning algorithms trained to recognize upper- and lower-extremity movements, have begun to fulfill this need. Continuous data from ankle triaxial accelerometers, for example, can be transmitted from the home and community via WiFi or a smartphone to a remote data analysis server. Reports can include the walking speed and duration of every bout of ambulation, spatiotemporal symmetries between the legs, and the type, duration, and energy used during exercise. For daily care, this readily accessible flow of real-world information allows clinicians to monitor the amount and quality of exercise for risk factor management and compliance in the practice of skills. Feedback may motivate better self-management as well as serve home-based rehabilitation efforts. Monitoring patients with chronic diseases and after hospitalization or the start of new medications for a decline in daily activity may help detect medical complications before rehospitalization becomes necessary. For clinical trials, repeated laboratory-quality assessments of key activities in the community, rather than by clinic testing, self-report, and ordinal scales, may reduce the cost and burden of travel, improve recruitment and retention, and capture more reliable, valid, and responsive ratio-scaled outcome measures that are not mere surrogates for changes in daily impairment, disability, and functioning.

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“…The availability of repeated measurements, for example, is well suited to adaptive or Bayesian designs. 140 …”

Section: The Solutionsmentioning

confidence: 99%

The Promise of mHealth

Dobkin

Dorsch

2011

Neurorehabil Neural Repair

250

102

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“…Phase II drug trials have been integrated into a phase III study, which shortens development time without compromising the chance of success. 86 Seamless phase II/III trials involve complex adaptations at the interim analysis, such as treatment selection, sample size reassessment, and stopping for futility. Bayesian methods can support these interim adaptations.…”

Section: Solutionsmentioning

confidence: 99%

Progressive Staging of Pilot Studies to Improve Phase III Trials for Motor Interventions

Dobkin

2008

Neurorehabil Neural Repair

180

189

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Based on the suboptimal research pathways that finally led to multicenter randomized clinical trials (MRCTs) of treadmill training with partial body weight support and of robotic assistive devices, strategically planned successive stages are proposed for pilot studies of novel rehabilitation interventions Stage 1, consideration-of-concept studies, drawn from animal experiments, theories, and observations, delineate the experimental intervention in a small convenience sample of participants, so the results must be interpreted with caution. Stage 2, development-of-concept pilots, should optimize the components of the intervention, settle on most appropriate outcome measures, and examine dose-response effects. A well-designed study that reveals no efficacy should be published to counterweight the confirmation bias of positive trials. Stage 3, demonstration-of-concept pilots, can build out from what has been learned to test at least 15 participants in each arm, using random assignment and blinded outcome measures. A control group should receive an active practice intervention aimed at the same primary outcome. A third arm could receive a substantially larger dose of the experimental therapy or a combinational intervention. If only 1 site performed this trial, a different investigative group should aim to reproduce positive outcomes based on the optimal dose of motor training. Stage 3 studies ought to suggest an effect size of 0.4 or higher, so that approximately 50 participants in each arm will be the number required to test for efficacy in a stage 4, proof-of-concept MRCT. By developing a consensus around acceptable and necessary practices for each stage, similar to CONSORT recommendations for the publication of phase III clinical trials, better quality pilot studies may move quickly into better designed and more successful MRCTs of experimental interventions.

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“…[18] Although this type of inference has mostly been used for exploratory trials, [19,20] the use of Bayesian methods has been proposed for trials of a more confirmatory nature with methods to re-evaluate the number of subjects or for phase 2-3 trials. [21,22] 2.4. Pre-specification, operational characteristics and independence of the decision…”

Section: Bayesian Methodsmentioning

confidence: 99%

Adaptive Methods: When and How Should They be Used in Clinical Trials?

2011

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-Adaptive clinical trial designs are defined as designs that use data cumulated during trial to possibly modify certain aspects without compromising the validity and integrity of the said trial. Compared to more traditional trials, in theory, adaptive designs allow the same information to be generated but in a more efficient manner. The advantages and limits of this type of design together with the weight of the constraints, in particular of a logistic nature, that their use implies, differ depending on whether the trial is exploratory or confirmatory with a view to registration. One of the key elements ensuring trial integrity is the involvement of an independent committee to determine adaptations in terms of experimental design during the study. Adaptive methods for clinical trials are appealing and may be accepted by the relevant authorities. However, the constraints that they impose must be determined well in advance.

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Bayesian predictive power for interim adaptation in seamless phase II/III trials where the endpoint is survival up to some specified timepoint

Cited by 44 publications

References 26 publications

The Promise of mHealth

The Promise of mHealth

Progressive Staging of Pilot Studies to Improve Phase III Trials for Motor Interventions

Adaptive Methods: When and How Should They be Used in Clinical Trials?

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