Multilevel network meta-regression: methods and implementation:<i>in workshop </i>Time to implement multilevel network meta-regression rather than matching adjusted indirect comparisons

PURPOSE: Multi-level network meta-regression (ML-NMR) extends the standard network meta-analysis framework to leverage individual patient data and aggregate data when comparing multiple treatments while adjusting for differences in populations between trials. Unlike previous population adjustment approaches, ML-NMR is applicable in networks of any size, avoids aggregation bias and issues with non-collapsible effect measures, and crucially for decision-making produces estimates in any target population.DESCRIPTION: Workshop attendees will obtain a working knowledge of the ML-NMR method, its advantages, and considerations for implementation. Dr. Jansen will chair the session and introduce ML-NMR in the context of the challenges with existing methods (10 min.). Dr. Phillippo will explain the statistical methods for ML-NMR, highlight advantages relative to existing methods, and provide an overview of how to implement the method using the multinma R package in terms of the syntax and features (15 min.). Ms. Cope will illustrate how these methods can be applied in a case study regarding the comparative efficacy of alternative interventions for triple-class exposed relapsed refractory multiple myeloma. This will include audience participation regarding selection of covariates, alternative time-to-event models, conditional vs. marginal estimates, and target populations for prediction (15 min). Mr. Klijn will describe lessons learned and recommendations for implementation of ML-NMR (15 min). Questions from the audience will be addressed (5 min) and this interactive workshop will be valuable to researchers and industry analysts interested in comparative efficacy research for health technology assessments

Assessing the robustness of recommendations made in a guideline on specialist neonatal respiratory care in babies born preterm with threshold analysis

View from Obiri (Ubirr) Rock, Kakadu National Park, shows rocky ourcrops in distance and plains in mid distance.Crawford, Pauline

Using individual participant data to improve network meta-analysis projects.

A network meta-analysis combines the evidence from existing randomised trials about the comparative efficacy of multiple treatments. It allows direct and indirect evidence about each comparison to be included in the same analysis, and provides a coherent framework to compare and rank treatments. A traditional network meta-analysis uses aggregate data (eg, treatment effect estimates and standard errors) obtained from publications or trial investigators. An alternative approach is to obtain, check, harmonise and meta-analyse the individual participant data (IPD) from each trial. In this article, we describe potential advantages of IPD for network meta-analysis projects, emphasising five key benefits: (1) improving the quality and scope of information available for inclusion in the meta-analysis, (2) examining and plotting distributions of covariates across trials (eg, for potential effect modifiers), (3) standardising and improving the analysis of each trial, (4) adjusting for prognostic factors to allow a network meta-analysis of conditional treatment effects and (5) including treatment-covariate interactions (effect modifiers) to allow relative treatment effects to vary by participant-level covariate values (eg, age, baseline depression score). A running theme of all these benefits is that they help examine and reduce heterogeneity (differences in the true treatment effect between trials) and inconsistency (differences in the true treatment effect between direct and indirect evidence) in the network. As a consequence, an IPD network meta-analysis has the potential for more precise, reliable and informative results for clinical practice and even allows treatment comparisons to be made for individual patients and targeted populations conditional on their particular characteristics

A Mixed Method Study of Teachers\u27 Appraisals of Student Wellness Services and Supports During COVID-19

BACKGROUNDUnderstanding teachers\u27 appraisals of student wellness services and supports during COVID-19 is essential to strengthening services and improving student health outcomes. This mixed-method study aimed to examine US PK-12 teachers\u27 appraisals of student wellness services and supports during COVID-19.METHODSThis study focuses on qualitative data from 291 teachers\u27 open-ended responses to the question: “What do you wish your school leaders knew about this (wellness support) aspect of your work?” and whose responses described wellness services and supports. A qualitative content analysis was conducted by an interdisciplinary research team using open- and axial coding.RESULTSThree main themes emerged. (1) insufficient access to mental health professionals and programming at schools, (2) concern about the quality of available services, and (3) a need for teacher professional development and support on student wellness. Statistically significant differences in teacher appraisals of insufficient access to mental health professionals and programming were found based on grade level taught and percentage of immigrant students in the school.CONCLUSIONWith amplified student wellness needs, school personnel, including school leaders, must consider ways to allocate additional resources/staffing, assess the quality of services and supports, and design professional development opportunities to support teachers\u27 involvement in supporting student wellness needs

A Mixed Method Study of Teachers’ Appraisals of Student Wellness Services and Supports During COVID-19

BACKGROUND: Understanding teachers\u27 appraisals of student wellness services and supports during COVID-19 is essential to strengthening services and improving student health outcomes. This mixed-method study aimed to examine US PK-12 teachers\u27 appraisals of student wellness services and supports during COVID-19. METHODS: This study focuses on qualitative data from 291 teachers\u27 open-ended responses to the question: “What do you wish your school leaders knew about this (wellness support) aspect of your work?” and whose responses described wellness services and supports. A qualitative content analysis was conducted by an interdisciplinary research team using open- and axial coding. RESULTS: Three main themes emerged. (1) insufficient access to mental health professionals and programming at schools, (2) concern about the quality of available services, and (3) a need for teacher professional development and support on student wellness. Statistically significant differences in teacher appraisals of insufficient access to mental health professionals and programming were found based on grade level taught and percentage of immigrant students in the school. CONCLUSION: With amplified student wellness needs, school personnel, including school leaders, must consider ways to allocate additional resources/staffing, assess the quality of services and supports, and design professional development opportunities to support teachers\u27 involvement in supporting student wellness needs