Moderators of the effect of therapeutic exercise for knee and hip osteoarthritis: a systematic review and individual participant data meta-analysis.

Background: Many international clinical guidelines recommend therapeutic exercise as a core treatment for knee and hip osteoarthritis. We aimed to identify individual patient-level moderators of the effect of therapeutic exercise for reducing pain and improving physical function in people with knee osteoarthritis, hip osteoarthritis, or both.

Methods: We did a systematic review and individual participant data (IPD) meta-analysis of randomised controlled trials comparing therapeutic exercise with non-exercise controls in people with knee osteoathritis, hip osteoarthritis, or both.

Humanized Patient-derived Xenograft Models of Disseminated Ovarian Cancer Recapitulate Key Aspects of the Tumor Immune Environment within the Peritoneal Cavity.

Unlabelled: The importance of the immune microenvironment in ovarian cancer progression, metastasis, and response to therapies has become increasingly clear, especially with the new emphasis on immunotherapies. To leverage the power of patient-derived xenograft (PDX) models within a humanized immune microenvironment, three ovarian cancer PDXs were grown in humanized NBSGW (huNBSGW) mice engrafted with human CD34 cord blood-derived hematopoietic stem cells. Analysis of cytokine levels in the ascites fluid and identification of infiltrating immune cells in the tumors demonstrated that these humanized PDX (huPDX) established an immune tumor microenvironment similar to what has been reported for patients with ovarian cancer.

Multivariate meta-analysis of multiple outcomes: characteristics and predictors of borrowing of strength from Cochrane reviews.

Objectives: Multivariate meta-analysis allows the joint synthesis of multiple outcomes accounting for their correlation. This enables borrowing of strength (BoS) across outcomes, which may lead to greater efficiency and even different conclusions compared to separate univariate meta-analyses. However, multivariate meta-analysis is complex to apply, so guidance is needed to flag (in advance of analysis) when the approach is most useful.

Determining the Prevalence and Incidence of SARS-CoV-2 Infection in Prisons in England: Protocol for a Repeated Panel Survey and Enhanced Outbreak Study.

Background: There are over 80,000 people imprisoned in England and Wales in 117 prisons. The management of the COVID-19 pandemic presents particular challenges in this setting where confined, crowded, and poorly ventilated conditions facilitate the rapid spread of infectious diseases.

Objective: The COVID-19 in Prison Study aims to examine the epidemiology of SARS-CoV-2 in prisons in England in order to inform public health policy and practice during the pandemic and recovery.

Community-based delivery of intermittent preventive treatment of malaria in pregnancy in Burkina Faso: a qualitative study.

Background: Burkina Faso is among ten countries with the highest rates of malaria cases and deaths in the world. Delivery and coverage of intermittent preventive treatment of malaria in pregnancy (IPTp) is insufficient in Burkina Faso; In a 2016 survey, only 22% of eligible women had received their third dose of IPTp. It is also an extremely rural country and one with an established cadre of community healthcare workers (CHWs).

Factors associated with SARS-CoV-2 infection and outbreaks in long-term care facilities in England: a national cross-sectional survey.

Background: Outbreaks of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection have occurred in long-term care facilities (LTCFs) worldwide, but the reasons why some facilities are particularly vulnerable to outbreaks are poorly understood. We aimed to identify factors associated with SARS-CoV-2 infection and outbreaks among staff and residents in LTCFs.

Methods: We did a national cross-sectional survey of all LTCFs providing dementia care or care to adults aged 65 years or older in England between May 26 and June 19, 2020.

A cluster randomized trial of delivery of intermittent preventive treatment of malaria in pregnancy at the community level in Burkina Faso.

Background: Malaria in pregnancy is responsible for 8-14% of low birth weight and 20% of stillbirths in sub-Saharan Africa. To prevent these adverse consequences, the World Health Organization recommends intermittent preventive treatment of pregnant women (IPTp) with sulfadoxine-pyrimethamine be administered at each ANC visit starting as early as possible in the second trimester. Global IPTp coverage in targeted countries remains unacceptably low.

One-stage individual participant data meta-analysis models for continuous and binary outcomes: Comparison of treatment coding options and estimation methods.

A one-stage individual participant data (IPD) meta-analysis synthesizes IPD from multiple studies using a general or generalized linear mixed model. This produces summary results (eg, about treatment effect) in a single step, whilst accounting for clustering of participants within studies (via a stratified study intercept, or random study intercepts) and between-study heterogeneity (via random treatment effects). We use simulation to evaluate the performance of restricted maximum likelihood (REML) and maximum likelihood (ML) estimation of one-stage IPD meta-analysis models for synthesizing randomized trials with continuous or binary outcomes.

Pharmacological interventions for prevention of depression in high risk conditions: Systematic review and meta-analysis.

Background: Background Depressive disorders account for almost half of all Disability Adjusted Life Years caused by psychiatric disorders but efficacy of pharmacological interventions to prevent depressive disorders is not known. We aimed to assess efficacy of pharmacological treatments in prevention of depression.

Methods: We searched PubMed, Psych Info, EMBASE, and CINHAL from 1980 to January 2020 and bibliographies of relevant systematic reviews.

Do comorbidities predict pain and function in knee osteoarthritis following an exercise intervention, and do they moderate the effect of exercise? Analyses of data from three randomized controlled trials.

Background: Although exercise is a core treatment for people with knee osteoarthritis (OA), it is currently unknown whether those with additional comorbidities respond differently to exercise than those without. We explored whether comorbidities predict pain and function following an exercise intervention in people with knee OA, and whether they moderate response to: exercise versus no exercise; and enhanced exercise versus usual exercise-based care.

Methods: We undertook analyses of existing data from three randomized controlled trials (RCTs): TOPIK (n = 217), APEX (n = 352) and Benefits of Effective Exercise for knee Pain (BEEP) (n = 514).

Predictors of the effects of treatment for shoulder pain: protocol of an individual participant data meta-analysis.

Background: Shoulder pain is one of the most common presentations of musculoskeletal pain with a 1-month population prevalence of between 7 and 26%. The overall prognosis of shoulder pain is highly variable with 40% of patients reporting persistent pain 1 year after consulting their primary care clinician. Despite evidence for prognostic value of a range of patient and disease characteristics, it is not clear whether these factors also predict (moderate) the effect of specific treatments (such as corticosteroid injection, exercise, or surgery).

Minimum sample size for developing a multivariable prediction model: PART II - binary and time-to-event outcomes.

When designing a study to develop a new prediction model with binary or time-to-event outcomes, researchers should ensure their sample size is adequate in terms of the number of participants (n) and outcome events (E) relative to the number of predictor parameters (p) considered for inclusion. We propose that the minimum values of n and E (and subsequently the minimum number of events per predictor parameter, EPP) should be calculated to meet the following three criteria: (i) small optimism in predictor effect estimates as defined by a global shrinkage factor of ≥0.9, (ii) small absolute difference of ≤ 0.

Minimum sample size for developing a multivariable prediction model: Part I - Continuous outcomes.

In the medical literature, hundreds of prediction models are being developed to predict health outcomes in individuals. For continuous outcomes, typically a linear regression model is developed to predict an individual's outcome value conditional on values of multiple predictors (covariates). To improve model development and reduce the potential for overfitting, a suitable sample size is required in terms of the number of subjects (n) relative to the number of predictor parameters (p) for potential inclusion.

Persistent sex disparities in clinical outcomes with percutaneous coronary intervention: Insights from 6.6 million PCI procedures in the United States.

Background: Prior studies have reported inconsistencies in the baseline risk profile, comorbidity burden and their association with clinical outcomes in women compared to men. More importantly, there is limited data around the sex differences and how these have changed over time in contemporary percutaneous coronary intervention (PCI) practice.

Methods And Results: We used the Nationwide Inpatient Sample to identify all PCI procedures based on ICD-9 procedure codes in the United States between 2004-2014 in adult patients.

Individual participant data meta-analysis of continuous outcomes: A comparison of approaches for specifying and estimating one-stage models.

One-stage individual participant data meta-analysis models should account for within-trial clustering, but it is currently debated how to do this. For continuous outcomes modeled using a linear regression framework, two competing approaches are a stratified intercept or a random intercept. The stratified approach involves estimating a separate intercept term for each trial, whereas the random intercept approach assumes that trial intercepts are drawn from a normal distribution.

Simulation-based power calculations for planning a two-stage individual participant data meta-analysis.

Background: Researchers and funders should consider the statistical power of planned Individual Participant Data (IPD) meta-analysis projects, as they are often time-consuming and costly. We propose simulation-based power calculations utilising a two-stage framework, and illustrate the approach for a planned IPD meta-analysis of randomised trials with continuous outcomes where the aim is to identify treatment-covariate interactions.

Methods: The simulation approach has four steps: (i) specify an underlying (data generating) statistical model for trials in the IPD meta-analysis; (ii) use readily available information (e.

Subgrouping and TargetEd Exercise pRogrammes for knee and hip OsteoArthritis (STEER OA): a systematic review update and individual participant data meta-analysis protocol.

Introduction: Knee and hip osteoarthritis (OA) is a leading cause of disability worldwide. Therapeutic exercise is a recommended core treatment for people with knee and hip OA, however, the observed effect sizes for reducing pain and improving physical function are small to moderate. This may be due to insufficient targeting of exercise to subgroups of people who are most likely to respond and/or suboptimal content of exercise programmes.

Guidance for deriving and presenting percentage study weights in meta-analysis of test accuracy studies.

Percentage study weights in meta-analysis reveal the contribution of each study toward the overall summary results and are especially important when some studies are considered outliers or at high risk of bias. In meta-analyses of test accuracy reviews, such as a bivariate meta-analysis of sensitivity and specificity, the percentage study weights are not currently derived. Rather, the focus is on representing the precision of study estimates on receiver operating characteristic plots by scaling the points relative to the study sample size or to their standard error.

Multivariate and network meta-analysis of multiple outcomes and multiple treatments: rationale, concepts, and examples.

Organisations such as the National Institute for Health and Care Excellence require the synthesis of evidence from existing studies to inform their decisions—for example, about the best available treatments with respect to multiple efficacy and safety outcomes. However, relevant studies may not provide direct evidence about all the treatments or outcomes of interest. Multivariate and network meta-analysis methods provide a framework to address this, using correlated or indirect evidence from such studies alongside any direct evidence.

Perioperative supplementation with a fruit and vegetable juice powder concentrate and postsurgical morbidity: A double-blind, randomised, placebo-controlled clinical trial.

Background & Aims: Surgical trauma leads to an inflammatory response that causes surgical morbidity. Reduced antioxidant micronutrient (AM) levels and/or excessive levels of Reactive Oxygen Species (ROS) have previously been linked to delayed wound healing and presence of chronic wounds. We aimed to evaluate the effect of pre-operative supplementation with encapsulated fruit and vegetable juice powder concentrate (JuicePlus+) on postoperative morbidity and Quality of Life (QoL).

Association of maternal serum PAPP-A levels, nuchal translucency and crown-rump length in first trimester with adverse pregnancy outcomes: retrospective cohort study.

Objective: Are first trimester serum pregnancy-associated plasma protein-A (PAPP-A), nuchal translucency (NT) and crown-rump length (CRL) prognostic factors for adverse pregnancy outcomes?

Method: Retrospective cohort, women, singleton pregnancies (UK 2011-2015). Unadjusted and multivariable logistic regression.

Outcomes: small for gestational age (SGA), pre-eclampsia (PE), preterm birth (PTB), miscarriage, stillbirth, perinatal mortality and neonatal death (NND).

Deriving percentage study weights in multi-parameter meta-analysis models: with application to meta-regression, network meta-analysis and one-stage individual participant data models.

Many meta-analysis models contain multiple parameters, for example due to multiple outcomes, multiple treatments or multiple regression coefficients. In particular, meta-regression models may contain multiple study-level covariates, and one-stage individual participant data meta-analysis models may contain multiple patient-level covariates and interactions. Here, we propose how to derive percentage study weights for such situations, in order to reveal the (otherwise hidden) contribution of each study toward the parameter estimates of interest.

One-stage individual participant data meta-analysis models: estimation of treatment-covariate interactions must avoid ecological bias by separating out within-trial and across-trial information.

Stratified medicine utilizes individual-level covariates that are associated with a differential treatment effect, also known as treatment-covariate interactions. When multiple trials are available, meta-analysis is used to help detect true treatment-covariate interactions by combining their data. Meta-regression of trial-level information is prone to low power and ecological bias, and therefore, individual participant data (IPD) meta-analyses are preferable to examine interactions utilizing individual-level information.

Meta-analysis using individual participant data: one-stage and two-stage approaches, and why they may differ.

Meta-analysis using individual participant data (IPD) obtains and synthesises the raw, participant-level data from a set of relevant studies. The IPD approach is becoming an increasingly popular tool as an alternative to traditional aggregate data meta-analysis, especially as it avoids reliance on published results and provides an opportunity to investigate individual-level interactions, such as treatment-effect modifiers. There are two statistical approaches for conducting an IPD meta-analysis: one-stage and two-stage.