Blinding and sham control methods in trials of physical, psychological, and self-management interventions for pain (article II): a meta-analysis relating methods to trial results.

ABSTRACT: Sham interventions in randomized clinical trials (RCTs) of physical, psychological, and self-management (PPS) therapies for pain are highly variable in design and believed to contribute to poor internal validity. However, it has not been formally tested whether the extent to which sham controls resemble the treatment under investigation consistently affects trial outcomes, such as effect sizes, differential attrition, participant expectancy, and blinding effectiveness. Placebo- or sham-controlled RCTs of PPS interventions of clinical pain populations were searched in 12 databases. The similarity of control interventions to the experimental treatment was rated across 25 features. Meta-regression analyses assessed putative links between employed control interventions, observed effect sizes in pain-related outcomes, attrition, and blinding success. The sample included 198 unique control interventions, dominated by manual therapy and chronic musculoskeletal pain research. Meta-analyses indicated small-to-moderate benefits of active treatments over control interventions, across subgroups of manual therapies, exercise, and rehabilitation, and psychological intervention trials. Multiple meta-regression modelling demonstrated that similarity between sham control and tested interventions predicted variability in pain-related outcomes, attrition, and blinding effectiveness. Influential variables were differences relating to the extent of intervention exposure, participant experience, and treatment environments. The results support the supposed link between blinding methods and effect sizes, based on a large and systematically sourced overview of methods. However, challenges to effective blinding are complex and often difficult to discern from trial reports. Nonetheless, these insights have the potential to change trial design, conduct, and reporting and will inform guideline development.

Blinding and sham control methods in trials of physical, psychological, and self-management interventions for pain (article I): a systematic review and description of methods.

ABSTRACT: Blinding is challenging in randomised controlled trials of physical, psychological, and self-management therapies for pain, mainly because of their complex and participatory nature. To develop standards for the design, implementation, and reporting of control interventions in efficacy and mechanistic trials, a systematic overview of currently used sham interventions and other blinding methods was required. Twelve databases were searched for placebo or sham-controlled randomised clinical trials of physical, psychological, and self-management treatments in a clinical pain population. Screening and data extraction were performed in duplicate, and trial features, description of control methods, and their similarity to the active intervention under investigation were extracted (protocol registration ID: CRD42020206590). The review included 198 unique control interventions, published between 2008 and December 2021. Most trials studied people with chronic pain, and more than half were manual therapy trials. The described control interventions ranged from clearly modelled based on the active treatment to largely dissimilar control interventions. Similarity between control and active interventions was more frequent for certain aspects (eg, duration and frequency of treatments) than others (eg, physical treatment procedures and patient sensory experiences). We also provide an overview of additional, potentially useful methods to enhance blinding, as well as the reporting of processes involved in developing control interventions. A comprehensive picture of prevalent blinding methods is provided, including a detailed assessment of the resemblance between active and control interventions. These findings can inform future developments of control interventions in efficacy and mechanistic trials and best-practice recommendations.

Tissue volume estimation and age prediction using rapid structural brain scans.

The multicontrast EPImix sequence generates six contrasts, including a T1-weighted scan, in ~1 min. EPImix shows comparable diagnostic performance to conventional scans under qualitative clinical evaluation, and similarities in simple quantitative measures including contrast intensity. However, EPImix scans have not yet been compared to standard MRI scans using established quantitative measures. In this study, we compared conventional and EPImix-derived T1-weighted scans of 64 healthy participants using tissue volume estimates and predicted brain-age. All scans were pre-processed using the SPM12 DARTEL pipeline, generating measures of grey matter, white matter and cerebrospinal fluid volume. Brain-age was predicted using brainageR, a Gaussian Processes Regression model previously trained on a large sample of standard T1-weighted scans. Estimates of both global and voxel-wise tissue volume showed significantly similar results between standard and EPImix-derived T1-weighted scans. Brain-age estimates from both sequences were significantly correlated, although EPImix T1-weighted scans showed a systematic offset in predictions of chronological age. Supplementary analyses suggest that this is likely caused by the reduced field of view of EPImix scans, and the use of a brain-age model trained using conventional T1-weighted scans. However, this systematic error can be corrected using additional regression of T1-predicted brain-age onto EPImix-predicted brain-age. Finally, retest EPImix scans acquired for 10 participants demonstrated high test-retest reliability in all evaluated quantitative measurements. Quantitative analysis of EPImix scans has potential to reduce scanning time, increasing participant comfort and reducing cost, as well as to support automation of scanning, utilising active learning for faster and individually-tailored (neuro)imaging.

Rapid processing and quantitative evaluation of structural brain scans for adaptive multimodal imaging.

Current neuroimaging acquisition and processing approaches tend to be optimised for quality rather than speed. However, rapid acquisition and processing of neuroimaging data can lead to novel neuroimaging paradigms, such as adaptive acquisition, where rapidly processed data is used to inform subsequent image acquisition steps. Here we first evaluate the impact of several processing steps on the processing time and quality of registration of manually labelled T1 -weighted MRI scans. Subsequently, we apply the selected rapid processing pipeline both to rapidly acquired multicontrast EPImix scans of 95 participants (which include T1 -FLAIR, T2 , T2 *, T2 -FLAIR, DWI and ADC contrasts, acquired in ~1 min), as well as to slower, more standard single-contrast T1 -weighted scans of a subset of 66 participants. We quantify the correspondence between EPImix T1 -FLAIR and single-contrast T1 -weighted scans, using correlations between voxels and regions of interest across participants, measures of within- and between-participant identifiability as well as regional structural covariance networks. Furthermore, we explore the use of EPImix for the rapid construction of morphometric similarity networks. Finally, we quantify the reliability of EPImix-derived data using test-retest scans of 10 participants. Our results demonstrate that quantitative information can be derived from a neuroimaging scan acquired and processed within minutes, which could further be used to implement adaptive multimodal imaging and tailor neuroimaging examinations to individual patients.