Model misspecification in stepped wedge trials: Random effects for time or treatment

Maintaining the validity of inference from linear mixed models in stepped-wedge cluster randomized trials under misspecified random-effects structures

Linear mixed models are commonly used in analyzing stepped-wedge cluster randomized trials. A key consideration for analyzing a stepped-wedge cluster randomized trial is accounting for the potentially complex correlation structure, which can be achieved by specifying random-effects. The simplest random effects structure is random intercept but more complex structures such as random cluster-by-period, discrete-time decay, and more recently, the random intervention structure, have been proposed. Specifying appropriate random effects in practice can be challenging: assuming more complex correlation structures may be reasonable but they are vulnerable to computational challenges. To circumvent these challenges, robust variance estimators may be applied to linear mixed models to provide consistent estimators of standard errors of fixed effect parameters in the presence of random-effects misspecification. However, there has been no empirical investigation of robust variance estimators for stepped-wedge cluster randomized trials. In this article, we review six robust variance estimators (both standard and small-sample bias-corrected robust variance estimators) that are available for linear mixed models in R, and then describe a comprehensive simulation study to examine the performance of these robust variance estimators for stepped-wedge cluster randomized trials with a continuous outcome under different data generators. For each data generator, we investigate whether the use of a robust variance estimator with either the random intercept model or the random cluster-by-period model is sufficient to provide valid statistical inference for fixed effect parameters, when these working models are subject to random-effect misspecification. Our results indicate that the random intercept and random cluster-by-period models with robust variance estimators performed adequately. The CR3 robust variance estimator (approximate jackknife) estimator, coupled with the number of clusters minus two degrees of freedom correction, consistently gave the best coverage results, but could be slightly conservative when the number of clusters was below 16. We summarize the implications of our results for the linear mixed model analysis of stepped-wedge cluster randomized trials and offer some practical recommendations on the choice of the analytic model.

Study protocol for two stepped-wedge interventional trials evaluating the effects of holistic information technology-based patient-oriented management in older multimorbid patients with cancer: The GERONTE trials

INTRODUCTION

Current hospital-based care pathways are generally single-disease centred. As a result, coexisting morbidities are often suboptimally evaluated and managed, a deficiency becoming increasingly apparent among older patients who exhibit heterogeneity in health status, functional abilities, frailty, and other geriatric impairments. To address this issue, our study aims to assess a newly developed patient-centred care pathway for older patients with multimorbidity and cancer. The new care pathway was based on currently available evidence and co-designed by end-users including health care professionals, patients, and informal caregivers. Within this care pathway, all healthcare professionals involved in the care of older patients with multimorbidity and cancer will form a Health Professional Consortium (HPC). The role of the HPC will be to centralise oncologic and non-oncologic treatment recommendations in accordance with the patient's priorities. Moreover, an Advanced Practice Nurse will act as case-manager by being the primary point of contact for the patient, thus improving coordination between specialists, and by organising and leading the consortium. Patient monitoring and the HPC collaboration will be facilitated by digital communication tools designed specifically for this purpose, with the added benefit of being customisable for each patient.

MATERIALS AND METHODS

The GERONTE study is a prospective international, multicentric study consisting of two stepped-wedge trials performed at 16 clinical sites across three European countries. Each trial will include 720 patients aged 70 years and over with a new or progressive cancer (breast, lung, colorectal, prostate) and at least one moderate or severe multimorbidity. The patients in the intervention group will receive the new care pathway whereas patients in the control group will receive usual oncologic care.

DISCUSSION

GERONTE will evaluate whether this kind of holistic, patient-oriented healthcare management can improve quality of life (primary outcome) and other valuable endpoints in older patients with multimorbidity and cancer. An ancillary study will assess in depth the socio-economic impact of the intervention and deliver concrete implementation guidelines for the GERONTE intervention care pathway.

TRIAL REGISTRATION

FRONE: NCT05720910 TWOBE: NCT05423808.

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

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.

Analysis of stepped wedge cluster randomized trials in the presence of a time-varying treatment effect

Stepped wedge cluster randomized controlled trials are typically analyzed using models that assume the full effect of the treatment is achieved instantaneously. We provide an analytical framework for scenarios in which the treatment effect varies as a function of exposure time (time since the start of treatment) and define the "effect curve" as the magnitude of the treatment effect on the linear predictor scale as a function of exposure time. The "time-averaged treatment effect" (TATE) and "long-term treatment effect" (LTE) are summaries of this curve. We analytically derive the expectation of the estimatorδ ^ $$ \hat{\delta} $$ resulting from a model that assumes an immediate treatment effect and show that it can be expressed as a weighted sum of the time-specific treatment effects corresponding to the observed exposure times. Surprisingly, although the weights sum to one, some of the weights can be negative. This implies thatδ ^ $$ \hat{\delta} $$ may be severely misleading and can even converge to a value of the opposite sign of the true TATE or LTE. We describe several models, some of which make assumptions about the shape of the effect curve, that can be used to simultaneously estimate the entire effect curve, the TATE, and the LTE. We evaluate these models in a simulation study to examine the operating characteristics of the resulting estimators and apply them to two real datasets.

Random effect misspecification in stepped wedge designs

Stepped wedge cluster randomized trials are often analysed using linear mixed effects models that may include random effects for cluster, time and/or treatment. We investigate the impact of misspecification of the random effects structure of the model. Specifically, we considered two cases of misspecification of the random effects in a cross-sectional stepped wedge cluster randomized trials model - fit a linear mixed effects model with random time effects but the true model includes random treatment effects (case 1) or fit a linear mixed effects model with random treatment effect but the true model includes random time effects (case 2) - and derived the variance of the estimated treatment effect under misspecification. We defined two measures of the effect of misspecification: validity and efficiency. Validity is the ratio of the model-based variance of the treatment effect from the mis-specified model divided by the true variance of the treatment effect from the mis-specified model (based on a sandwich estimate of the variance). Efficiency is the ratio of the model-based variance of the treatment effect from the correctly specified model divided by the true variance of the treatment effect from the mis-specified model. We found that validity is less than 1.0 (anti-conservative) in almost all situations investigated with the exception of case 1 with two sequences, when validity could be greater than 1.0. Efficiency is less than 1 in all cases and depends on the intracluster correlation coefficient, the relative magnitude of the variance of the misclassified variance component, and the number of sequences. In general, there is no universal recommendation as to the most robust approach except for the case of a classic stepped wedge cluster randomized trial with only 2 sequences, where fitting a random time model is less likely to lead to anti-conservative inference compared with fitting a random intervention model.