Power analysis for stepped wedge trials with multiple interventions

Sundin, Phillip; Crespi, Catherine M.

doi:10.1002/sim.9301

Cited by 3 publications

(6 citation statements)

References 40 publications

(54 reference statements)

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“…where t 1k is the calendar time an individual enters the study and N s (t) denotes the number of individuals who entered the study in state s and are study-eligible at time t > t 1k . Individuals who are no longer study-eligible at time t are excluded from numerator and denominator of these percentages presented in equation (7). We obtain a model-based estimate of the effect of a treatment on study population-level initiation and completion percentage outcomes as follows.…”

Section: Intervention Effect On Study Population-level Percentage Out...mentioning

confidence: 99%

“…We fit the multistate cure model using the Bayesian estimation procedure described in the previous section. Initiation and completion percentages were estimated with posterior means using equation (7). Intervention effects were then estimated by setting X tx = 0 and calculating the differences between 𝜁 i − 𝜁 * i and 𝜁 c − 𝜁 * c .…”

Section: Simulationmentioning

confidence: 99%

“…Table 3 shows estimates of study population-level initiation and completion percentages for Simulation 2, calculated using posterior means in equation (7), at three time points, corresponding to the end of Periods 2, 3, and 4. Columns labeled "Observed" initiation and completion are the observed percentage of individuals at time t who are study eligible and have received at least one dose or two doses, respectively, in the simulated data.…”

Section: Simulationmentioning

confidence: 99%

“…To estimate intervention effects on initiation and completion percentages, we fit the model in equation (7) to obtain 𝜁 * i and 𝜁 * c by setting X tx = 0, for Simulation 2. Results are shown in Table 4.…”

Section: Simulationmentioning

confidence: 99%

“…The PCORI-HPV study has a stepped-wedge design (SWD), a type of cluster randomized design in which clusters (and the individuals within them) are randomized to a sequence of intervention conditions. 4 Models for analyzing data from SWDs to estimate intervention effects for continuous outcomes are fairly well developed, [4][5][6][7] but models for other outcomes are less well studied. There has been little work using a multistate model to analyze data from a SWD.…”

Section: Introductionmentioning

confidence: 99%

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A semi-Markov multistate cure model for estimating intervention effects in stepped wedge design trials

Sundin

Aralis

Glenn

et al. 2023

Stat Methods Med Res

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Multistate models are useful for studying exposures that affect transitions among a set of health states. However, they can be challenging to apply when exposures are time-varying. We develop a multistate model and a method of likelihood construction that allows application of the model to data in which interventions or other exposures can be time-varying and an individual may to be exposed to multiple intervention conditions while progressing through states. The model includes cure proportions, reflecting the possibility that some individuals will never leave certain states. We apply the approach to analyze patient vaccination data from a stepped wedge design trial evaluating two interventions to increase uptake of human papillomavirus vaccination. The states are defined as the number of vaccine doses the patient has received. We model state transitions as a semi-Markov process and include cure proportions to account for individuals who will never leave a given state (e.g. never receive their next dose). Multistate models typically quantify intervention effects as hazard ratios contrasting the intensities of transitions between states in intervention versus control conditions. For multistate processes, another clinically meaningful outcome is the change in the percentage of the study population that has achieved a specific state (e.g. completion of all required doses) by a specific point in time due to an intervention. We present a method for quantifying intervention effects in this manner. We apply the model to both simulated and real-world data and also explore some conditions under which such models may give biased results.

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Section: Intervention Effect On Study Population-level Percentage Out...mentioning

confidence: 99%

Section: Simulationmentioning

confidence: 99%

Section: Simulationmentioning

confidence: 99%

Section: Simulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A semi-Markov multistate cure model for estimating intervention effects in stepped wedge design trials

Sundin

Aralis

Glenn

et al. 2023

Stat Methods Med Res

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Enhancing doctor-patient relationships in community health care institutions: the Patient Oriented Four Habits Model (POFHM) trial—a stepped wedge cluster randomized trial protocol

Zhu

Zhang

et al. 2023

BMC Psychiatry

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Background The poor relationship between doctors and patients is a long-standing, global problem. However, current interventions tend to focus on the training of physicians, while patient-targeted interventions still need to be improved. Considering that patients play a significant role in outpatient consultations, we developed a protocol to assess the effectiveness of the Patient Oriented Four Habits Model (POFHM) in improving doctor-patient relationships. Methods A cross-sectional incomplete stepped-wedge cluster randomized trial design will be conducted in 8 primary healthcare institutions (PHCs). Following phase I of “usual care” as control measures for each PHC, either a patient- or doctor-only intervention will be implemented in phase II. In phase III, both patients and doctors will be involved in the intervention. This study will be conducted simultaneously in Nanling County and West Lake District. The primary outcomes will be evaluated after patients complete their visit: (1) patient literacy, (2) sense of control and (3) quality of doctor-patient communication. Finally, a mixed-effects model and subgroup analysis will be used to evaluate the effectiveness of the interventions. Discussion Fostering good consultation habits for the patient is a potentially effective strategy to improve the quality of doctor-patient communication. This study evaluates the implementation process and develops a rigorous quality control manual using a theoretical domain framework under the collective culture of China. The results of this trial will provide substantial evidence of the effectiveness of patient-oriented interventions. The POFHM can benefit the PHCs and provide a reference for countries and regions where medical resources are scarce and collectivist cultures dominate. Trial registration AsPredicted #107,282 on Sep 18, 2022; https://aspredicted.org/QST_MHW

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Advancing the integration of biosignal-based automated pain assessment methods into a comprehensive model for addressing cancer pain

Cascella,

Di Gennaro,

Crispo

et al. 2024

BMC Palliat Care

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Power analysis for stepped wedge trials with multiple interventions

Cited by 3 publications

References 40 publications

A semi-Markov multistate cure model for estimating intervention effects in stepped wedge design trials

A semi-Markov multistate cure model for estimating intervention effects in stepped wedge design trials

Enhancing doctor-patient relationships in community health care institutions: the Patient Oriented Four Habits Model (POFHM) trial—a stepped wedge cluster randomized trial protocol

Advancing the integration of biosignal-based automated pain assessment methods into a comprehensive model for addressing cancer pain

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