Pitfalls of using the risk ratio in meta‐analysis

For meta-analysis of studies that report outcomes as binomial proportions, the most popular measure of effect is the odds ratio (OR), usually analyzed as log(OR). Many meta-analyses use the risk ratio (RR) and its logarithm, because of its simpler interpretation. Although log(OR) and log(RR) are both unbounded, use of log(RR) must ensure that estimates are compatible with study-level event rates in the interval (0, 1). These complications pose a particular challenge for random-effects models, both in applications and in generating data for simulations. As background we review the conventional random-effects model and then binomial generalized linear mixed models (GLMMs) with the logit link function, which do not have these complications. We then focus on log-binomial models and explore implications of using them; theoretical calculations and simulation show evidence of biases. The main competitors to the binomial GLMMs use the beta-binomial (BB) distribution, either in BB regression or by maximizing a BB likelihood; a simulation produces mixed results. Two examples and an examination of Cochrane meta-analyses that used RR suggest bias in the results from the conventional inverse-variance-weighted approach. Finally, we comment on other measures of effect that have range restrictions, including risk difference, and outline further research

Seatbelt use and risk of major injuries sustained by vehicle occupants during motor-vehicle crashes: A systematic review and meta-analysis of cohort studies

BackgroundIn 2004, a World Health Report on road safety called for enforcement of measures such as seatbelt use, effective at minimizing morbidity and mortality caused by road traffic accidents. However, injuries caused by seatbelt use have also been described. Over a decade after publication of the World Health Report on road safety, this study sought to investigate the relationship between seatbelt use and major injuries in belted compared to unbelted passengers.MethodsCohort studies published in English language from 2005 to 2018 were retrieved from seven databases. Critical appraisal of studies was carried out using the Scottish Intercollegiate Guidelines Network (SIGN) checklist. Pooled risk of major injuries was assessed using the random effects meta-analytic model. Heterogeneity was quantified using I-squared and Tau-squared statistics. Funnel plots and Egger's test were used to investigate publication bias. This review is registered in PROSPERO (CRD42015020309).ResultsEleven studies, all carried out in developed countries were included. Overall, the risk of any major injury was significantly lower in belted passengers compared to unbelted passengers (RR 0.47; 95%CI, 0.29 to 0.80; I-2=99.7; P=0.000). When analysed by crash types, belt use significantly reduced the risk of any injury (RR 0.35; 95%CI, 0.24 to 0.52). Seatbelt use reduces the risk of facial injuries (RR=0.56, 95% CI=0.37 to 0.84), abdominal injuries (RR=0.87; 95% CI=0.78 to 0.98) and, spinal injuries (RR=0.56, 95% CI=0.37 to 0.84). However, we found no statistically significant difference in risk of head injuries (RR=0.49; 95% CI=0.22 to 1.08), neck injuries (RR=0.69: 95%CI 0.07 to 6.44), thoracic injuries (RR 0.96, 95%CI, 0.74 to 1.24), upper limb injuries (RR=1.05, 95%CI 0.83 to 1.34) and lower limb injuries (RR=0.77, 95%CI 0.58 to 1.04) between belted and non-belted passengers.ConclusionIn sum, the risk of most major road traffic injuries is lower in seatbelt users. Findings were inconclusive regarding seatbelt use and susceptibility to thoracic, head and neck injuries during road traffic accidents. Awareness should be raised about the dangers of inadequate seatbelt use. Future research should aim to assess the effects of seatbelt use on major injuries by crash type

Reduced morbidity by using LigaSure compared to conventional inguinofemoral lymphadenectomy in vulvar cancer patients:A randomized controlled trial

Background: Inguinofemoral lymphadenectomy (IFL) is part of the surgical treatment of different malignancies of the genital tract and/or the lower limb including vulvar carcinoma, penile carcinoma and melanoma. IFL is associated with morbidity in up to 85% of the patients. The aims of this MAMBO-IC study (Morbidity And Measurement of the Body) are to study the feasibility of using LigaSure for IFL and to assess the differences in the incidence of short-term complications using LigaSure versus conventional IFL randomized within each individual patient. Methods: In this multicenter randomized controlled trial (RCT), women diagnosed with squamous cell carcinoma of the vulva with an indication for bilateral IFL were included. It was randomly assigned for which groin the LigaSure was used; the other groin was treated with conventional IFL (sharp/diathermia). We estimated the incidence of >= 1 complication(s) per groin using logistic regression and compared this between the two surgical methods, adjusting for possible confounders. Results: We included 40 groins of 20 patients. The estimated incidence of >= 1 complication(s) was 29% after LigaSure versus 70% after conventional IFL (risk difference 41% (95% CI 19-62), p <0.001). Patients' reported restriction of daily living activities and maximum pain score were equal for both treatment methods. There were no differences in the surgeon reported workload scores. Conclusions: This RCT shows that LigaSure for IFL is feasible and associated with significantly less short-term surgical complications compared to conventional IFL. Further studies with a larger sample size are needed to validate our findings. ISRCTN15057626

Regularized parametric survival modeling to improve risk prediction models

We propose to combine the benefits of flexible parametric survival modeling and regularization to improve risk prediction modeling in the context of time-to-event data. Thereto, we introduce ridge, lasso, elastic net, and group lasso penalties for both log hazard and log cumulative hazard models. The log (cumulative) hazard in these models is represented by a flexible function of time that may depend on the covariates (i.e., covariate effects may be time-varying). We show that the optimization problem for the proposed models can be formulated as a convex optimization problem and provide a user-friendly R implementation for model fitting and penalty parameter selection based on cross-validation. Simulation study results show the advantage of regularization in terms of increased out-of-sample prediction accuracy and improved calibration and discrimination of predicted survival probabilities, especially when sample size was relatively small with respect to model complexity. An applied example illustrates the proposed methods. In summary, our work provides both a foundation for and an easily accessible implementation of regularized parametric survival modeling and suggests that it improves out-of-sample prediction performance

Inter-individual differences in the responses to pain neuroscience education in adults with chronic musculoskeletal pain: A systematic review and meta-analysis of randomised controlled trials.

Pain neuroscience education (PNE) is an approach used in the management of chronic musculoskeletal pain. Previous reviews on PNE and other pain interventions, have focused on mean treatment effects, but in the context of “precision medicine,” any inter-individual differences in treatment response are also important to quantify. If inter-individual differences are present, and predictors identified, PNE could be tailored to certain people for optimizing effectiveness. Such heterogeneity can be quantified using recently formulated approaches for comparing the response variance between the treatment and control groups. Therefore, we conducted a systematic review and meta-analysis on the extracted standard deviations of baseline-to-follow up change to quantify the inter-individual variation in pain, disability and psychosocial outcomes in response to PNE. Electronic databases were searched between January 1, 2002 and June 14, 2018. The review included 5 randomized controlled trials (n = 428) in which disability outcomes were reported. Using a random effects meta-analysis, the pooled SD (95% confidence interval) for control group-adjusted response heterogeneity to PNE was 7.36 units /100 (95% confidence interval = −3.93 to 11.12). The 95% prediction interval for this response heterogeneity SD was wide (−10.20 to 14.57 units /100). The control group-adjusted proportion of “responders” in the population who would be estimated to exceed a clinically important change of 10/100 ranged from 18 to 45%. Therefore, when baseline-to-follow up random variability in disability is taken into account (informed by the control arm), there is currently insufficient evidence for the notion of clinically important inter-individual differences in disability responses to PNE in people with chronic musculoskeletal pain. The protocol was published on PROSPERO (CRD42017068436). Perspective: We bring a novel method to pain science for calculating inter-individual differences in response to a treatment. This is conductedwithin the context of a systematic review and meta-analysis on PNE. We highlight how using erroneous methods for calculating inter-individual differences can drastically change conclusions when compared to appropriate methods.</p

Evaluation of Perineal Descent Measurements on Pelvic Floor Imaging.

Objectives: The aim of this study is to validate a uniform method for measuring perineal descent which can be used for different imaging methods, to establish cut-off values for this measurement, and to assess diagnostic test accuracy (DTA) of imaging techniques using these cut-off values. Secondly, the study aims to correlate perineal descent to symptoms, signs and imaging findings in women with obstructed defaecation syndrome (ODS) to assess its clinical relevance. Methods: Cross-sectional study of 131 women with symptoms of ODS. Symptoms and signs were assessed using validated methods. These women underwent evacuation proctography (EP), magnetic resonance imaging (MRI), transperineal ultrasound (TPUS) and endovaginal ultrasound (EVUS). Perineal descent was measured on EP and MRI as the position of anorectal junction (ARJ) with respect to the pubococcygeal line (PCL) at rest (i.e., static descent) and during evacuation (i.e., descent at Valsalva). Dynamic perineal descent was measured on all four imaging techniques as the difference between the position of the ARJ at rest and Valsalva. DTA of dynamic perineal descent was estimated using Latent Class Analysis in the absence of a reference standard. Results: Interobserver agreement of dynamic perineal descent measurements was good for MRI and EVUS (ICC 0.86 and 0.85) and moderate for EP and TPUS (ICC 0.61 and 0.59). The systematic differences in measurements between imaging techniques show the need for individual cut-off values. New established cut-off values for dynamic descent are for EP 20 mm, MRI 35 mm, TPUS 15 mm and EVUS 15 mm. Sensitivity was moderate for EP (0.78) and MRI (0.74), fair for TPUS (0.65) and poor for EVUS (0.58). Specificity was similar for all imaging techniques (0.73-0.77). Static perineal descent correlated with symptoms of pelvic organ prolapse (POP) (r = 0.19), prolapse of all three compartments (r = 0.19-0.36), presence of levator ani muscle avulsion (p = 0.01) and increased hiatal area (r = 0.51). Dynamic perineal descent correlated with excessive straining (r = 0.24) and use of laxatives (r = 0.24). Classic symptoms of ODS (incomplete evacuation and digitation) did not correlate with perineal descent measurements. Static and dynamic perineal descent were associated with presence of rectocele, enterocele, intussusception, and absence of anismus. Conclusions: Dynamic perineal descent is a reliable measurement that can be applied to different imaging techniques to allow standardisation. Static descent is more often present in women with POP and dynamic descent is more often present in women with constipation. Perineal descent does not correlate with typical symptoms of ODS. Specificity of TPUS and EVUS is comparable to EP and MRI, hence ultrasound could be used for the initial assessment of pelvic floor dysfunction

A tutorial on individualized treatment effect prediction from randomized trials with a binary endpoint.

Randomized trials typically estimate average relative treatment effects, but decisions on the benefit of a treatment are possibly better informed by more individualized predictions of the absolute treatment effect. In case of a binary outcome, these predictions of absolute individualized treatment effect require knowledge of the individual's risk without treatment and incorporation of a possibly differential treatment effect (ie, varying with patient characteristics). In this article, we lay out the causal structure of individualized treatment effect in terms of potential outcomes and describe the required assumptions that underlie a causal interpretation of its prediction. Subsequently, we describe regression models and model estimation techniques that can be used to move from average to more individualized treatment effect predictions. We focus mainly on logistic regression-based methods that are both well-known and naturally provide the required probabilistic estimates. We incorporate key components from both causal inference and prediction research to arrive at individualized treatment effect predictions. While the separate components are well known, their successful amalgamation is very much an ongoing field of research. We cut the problem down to its essentials in the setting of a randomized trial, discuss the importance of a clear definition of the estimand of interest, provide insight into the required assumptions, and give guidance with respect to modeling and estimation options. Simulated data illustrate the potential of different modeling options across scenarios that vary both average treatment effect and treatment effect heterogeneity. Two applied examples illustrate individualized treatment effect prediction in randomized trial data

A broadscale analysis of host-symbiont cophylogeny reveals the drivers of phylogenetic congruence

This is the final version. Available on open access from Wiley via the DOI in this recordData availability statement: A copy of the source data and R code used in this study have been deposited at figshare.com: https://doi.org/10.6084/m9.figshare.14393309 This article has earned Open Data and Open Materials badges. Data and materials are available at: https://figshare.com/articles/dataset/Dataset_for_ELE_EV_ELE13757/14393309?file=27503576 and https://figshare.com/articles/dataset/Dataset_for_ELE_EV_ELE13757/14393309?file=27503579Symbioses exert substantial biological influence, with great evolutionary and ecological relevance for disease, major evolutionary transitions, and the structure and function of ecological communities. Yet, much remains unknown about the patterns and processes that characterise symbioses. A major unanswered question is the extent to which symbiont phylogenies mirror those of their hosts and if patterns differ for parasites and mutualists. Addressing this question offers fundamental insights into evolutionary processes, such as whether symbionts typically codiverge with their hosts or if diversity is generated via host switches. Here, we perform a meta-analysis of host-symbiont phylogenetic congruence, encompassing 212 host-symbiont cophylogenetic studies that include ~10,000 species. Our analysis supersedes previous qualitative assessments by utilising a quantitative framework. We show that symbiont phylogeny broadly reflects host phylogeny across biodiversity and life-history, demonstrating a general pattern of phylogenetic congruence in host-symbiont interactions. We reveal two key aspects of symbiont life-history that promote closer ties between hosts and symbionts: vertical transmission and mutualism. Mode of symbiosis and mode of transmission are intimately interlinked, but vertical transmission is the dominant factor. Given the pervasiveness of symbioses, these findings provide important insights into the processes responsible for generating and maintaining the Earth's rich biodiversity.Kungliga Fysiografiska Sällskapet i LundAustralian Research Council (ARC