Development and comparison of model-integrated evidence approaches for bioequivalence studies with pharmacokinetic end points.

By applying nonlinear mixed-effect (NLME) models, model-integrated evidence (MIE) approaches are able to analyze bioequivalence (BE) data with pharmacokinetic end points that have sparse sampling, which is problematic for non-compartmental analysis (NCA). However, MIE approaches may suffer from inflation of type I error due to underestimation of parameter uncertainty and to the assumption of asymptotic normality. In this study, we developed a MIE BE analysis method that is based on a pre-defined model and consists of several steps including model fitting, uncertainty assessment, simulation, and BE determination. The presented MIE approach has several improvements compared with the previously reported model-integrated methods: (1) treatment, sequence, and period effects are only added to absorption parameters (such as relative bioavailability and rate of absorption) instead of all PK parameters; (2) a simulation step is performed to generate confidence intervals of the pharmacokinetic metrics for BE assessment; and (3) in an effort to maintain type I error, two more advanced parameter uncertainty evaluation approaches are explored, a nonparametric (case resampling) bootstrap, and sampling importance resampling (SIR). To evaluate the developed method and compare the uncertainty assessment methods, simulation experiments were performed for BE studies using a two-way crossover design with different amounts of information (sparse to rich designs) and levels of variability. Based on the simulation results, the method using SIR for parameter uncertainty quantification controls type I error at the nominal level of 0.05 (i.e., the significance level set for BE evaluation) even for studies with small sample size and/or sparse sampling. As expected, our MIE approach for BE assessment exhibited higher power than the NCA-based method, especially as the data becomes sparser and/or more variable.

Heart rate variability biofeedback to reduce anxiety in autism spectrum disorder - a mini review.

There is a reported high prevalence of anxiety in people with autism spectrum disorder. This mini review appraises existing research investigating heart rate variability biofeedback to help manage symptoms of anxiety in people with autism spectrum disorder. A thorough search of electronic databases was conducted to find relevant literature. Consultation with experts and a librarian helped develop search terms following the PICO framework. Five databases were searched, and screening was undertaken using Covidence software, with the process outlined in a PRISMA flowchart. The latest review showed positive short-term effects but there is a need for long-term follow-up. Future investigations should consider device type, training settings, and control interventions. Accurate heart rate variability assessment independent of biofeedback devices is crucial. Additional measures like cortisol assessment and user feedback are recommended for comprehensive evaluation. The findings highlight progress in the evidence base and offer insight to future directions.

Model-based bioequivalence approach for sparse pharmacokinetic bioequivalence studies: Model selection or model averaging?

Conventional pharmacokinetic (PK) bioequivalence (BE) studies aim to compare the rate and extent of drug absorption from a test (T) and reference (R) product using non-compartmental analysis (NCA) and the two one-sided test (TOST). Recently published regulatory guidance recommends alternative model-based (MB) approaches for BE assessment when NCA is challenging, as for long-acting injectables and products which require sparse PK sampling. However, our previous research on MB-TOST approaches showed that model misspecification can lead to inflated type I error. The objective of this research was to compare the performance of model selection (MS) on R product arm data and model averaging (MA) from a pool of candidate structural PK models in MBBE studies with sparse sampling. Our simulation study was inspired by a real case BE study using a two-way crossover design. PK data were simulated using three structural models under the null hypothesis and one model under the alternative hypothesis. MB-TOST was applied either using each of the five candidate models or following MS and MA with or without the simulated model in the pool. Assuming T and R have the same PK model, our simulation shows that following MS and MA, MB-TOST controls type I error rates at or below 0.05 and attains similar or even higher power than when using the simulated model. Thus, we propose to use MS prior to MB-TOST for BE studies with sparse PK sampling and to consider MA when candidate models have similar Akaike information criterion.

Tumour budding as a prognostic biomarker in biopsies and resections of neoadjuvant-treated rectal adenocarcinoma.

BACKGROUND: Tumour budding (TB) is a marker of tumour aggressiveness which, when measured in rectal cancer resection specimens, predicts worse outcomes and response to neoadjuvant therapy. We investigated the utility of TB assessment in the setting of neoadjuvant treatment. METHODS AND RESULTS: A single-centre, retrospective cohort study was conducted. TB was assessed using the hot-spot International Tumour Budding Consortium (ITBCC) method and classified by the revised ITBCC criteria. Haematoxylin and eosin (H&E) and AE1/AE3 cytokeratin (CK) stains for ITB (intratumoural budding) in biopsies with PTB (peritumoural budding) and ITB (intratumoural budding) in resection specimens were compared. Logistic regression assessed budding as predictors of lymph node metastasis (LNM). Cox regression and Kaplan-Meier analyses investigated their utility as a predictor of disease-free (DFS) and overall (OS) survival. A total of 146 patients were included; 91 were male (62.3%). Thirty-seven cases (25.3%) had ITB on H&E and 79 (54.1%) had ITB on CK assessment of biopsy tissue. In univariable analysis, H&E ITB [odds (OR) = 2.709, 95% confidence interval (CI) = 1.261-5.822, P = 0.011] and CK ITB (OR = 2.165, 95% CI = 1.076-4.357, P = 0.030) predicted LNM. Biopsy-assessed H&E ITB (OR = 2.749, 95% CI = 1.258-6.528, P = 0.022) was an independent predictor of LNM. In Kaplan-Meier analysis, ITB identified on biopsy was associated with worse OS (H&E, P = 0.003, CK: P = 0.009) and DFS (H&E, P = 0.012; CK, P = 0.045). In resection specimens, CK PTB was associated with worse OS (P = 0.047), and both CK PTB and ITB with worse DFS (PTB, P = 0.014; ITB: P = 0.019). In multivariable analysis H&E ITB predicted OS (HR = 2.930, 95% CI = 1.261-6.809) and DFS (HR = 2.072, 95% CI = 1.031-4.164). CK PTB grading on resection also independently predicted OS (HR = 3.417, 95% CI = 1.45-8.053, P = 0.005). CONCLUSION: Assessment of TB using H&E and CK may be feasible in rectal cancer biopsy and post-neoadjuvant therapy-treated resection specimens and is associated with LNM and worse survival outcomes. Future management strategies for rectal cancer might be tailored to incorporate these findings.

What works, how and in which contexts when supporting parents to implement intensive speech and language therapy at home for children with speech sound disorder? A protocol for a realist review.

INTRODUCTION: Speech and language therapists (SLTs) worldwide report challenges with providing recommended, evidence-based intervention intensity for children with speech sound disorder (SSD). Challenges such as service constraints and/or family contexts impact on access to optimal therapy intensity. Existing research indicates that empowering and training parents to deliver intervention at home, alongside SLT support, offers one possible solution to increasing the intensity of intervention children with SSD receive. Digital health could increase accessibility to intensive home practice and help sustain engagement with therapy activities. Further exploration is needed around what makes parent-implemented interventions for children with SSD effective, for who and in which situations. This paper outlines the protocol for a realist review which aims to explore the active ingredients and contextual factors of effective digital parent-led interventions. METHODS AND ANALYSIS: A realist review will explore the research question, following six stages. The scope of the review will be determined, and initial programme theories will be developed about what works in digital parent-implemented interventions for SSD, for whom, how, why and in what circumstances. Relevant secondary data, identified through a formal search strategy, will be selected, appraised, analysed and synthesised using realist principles to test and further refine the initial programme theories. This process will develop refined underpinning explanatory theories which capture the interaction between contexts, mechanisms and outcomes of the intervention. An expert steering group will provide insight to inform explanatory theories, searches, and dissemination. ETHICS AND DISSEMINATION: Ethical approval is not required for this review. The refined programme theories from the review will inform the next stages of a wider study. A subsequent realist evaluation will test and further refine theories with key stakeholders. Following this, the underpinning programme theory will be used to coproduce a digital tool, to support parents to deliver home intervention alongside SLT support.