A multifaceted graphical display, including treatment ranking, was developed to aid interpretation of network meta-analysis.

OBJECTIVES: Network meta-analysis (NMA) is becoming a popular statistical tool for analyzing a network of evidence comparing more than two interventions. A particular advantage of NMA over pairwise meta-analysis is its ability to simultaneously compare multiple interventions including comparisons not previously trialed together, permitting intervention hierarchies to be created. Our aim was to develop a novel graphical display to aid interpretation of NMA to clinicians and decision-makers that incorporates ranking of interventions. STUDY DESIGN AND SETTING: Current literature was searched, scrutinized, and provided direction for developing the novel graphical display. Ranking results were often found to be misinterpreted when presented alone and, to aid interpretation and effective communication to inform optimal decision-making, need to be displayed alongside other important aspects of the analysis including the evidence networks and relative intervention effect estimates. RESULTS: Two new ranking visualizations were developed-the 'Litmus Rank-O-Gram' and the 'Radial SUCRA' plot-and embedded within a novel multipanel graphical display programmed within the MetaInsight application, with user feedback gained. CONCLUSION: This display was designed to improve the reporting, and facilitate a holistic understanding, of NMA results. We believe uptake of the display would lead to better understanding of complex results and improve future decision-making.

Measuring quality of life in trials including patients on haemodialysis: methodological issues surrounding the use of the Kidney Disease Quality of Life Questionnaire.

BACKGROUND: Haemodialysis (HD) treatment causes a significant decrease in quality of life (QoL). When enrolled in a clinical trial, some patients are lost prior to follow-up because they die or they receive a kidney transplant. It is unclear how these patients are dealt with in the analysis of QoL data. There are questions surrounding the consistency of how QoL measures are used, reported and analysed. METHODS: A systematic search of electronic databases for trials measuring QoL in HD patients using any variation of the Kidney Disease Quality of Life (KDQoL) Questionnaire was conducted. The review was conducted in Covidence version 2. Quantitative analysis was conducted in Stata version 16. RESULTS: We included 61 trials in the review, of which 82% reported dropouts. The methods to account for missing data due to dropouts include imputation (7%) and complete case analysis (72%). Few trials (7%) conducted a sensitivity analysis to assess the impact of missing data on the study results. Single imputation techniques were used, but are only valid under strong assumptions regarding the type and pattern of missingness. There was inconsistency in the reporting of the KDQoL, with many articles (70%) amending the validated questionnaires or reporting only statistically significant results. CONCLUSIONS: Missing data are not dealt with according to the missing data mechanism, which may lead to biased results. Inconsistency in the use of patient-reported outcome measures raises questions about the validity of these trials. Methodological issues in nephrology trials could be a contributing factor to why there are limited effective interventions to improve QoL in this patient group. PROSPERO REGISTRATION: CRD42020223869.

Feasibility study for interactive reporting of network meta-analysis: experiences from the development of the MetaInsight COVID-19 app for stakeholder exploration, re-analysis and sensitivity analysis from living systematic reviews.

BACKGROUND: Network meta-analysis (NMA) has been increasingly adopted worldwide by Cochrane reviews, guideline developers and decision-making bodies to identify optimal treatment choices. However, NMA results are often produced statically, not allowing stakeholders to 'dig deeper' and interrogate with their own judgement. Additionally, amid the COVID-19 pandemic, unnecessary or duplicated reviews have been proposed which analyse from the same pool of evidence. We developed the 'MetaInsight COVID-19' app as a prototype for an interactive platform to eliminate such duplicated efforts, by empowering users to freely analyse the data and improve scientific transparency. METHODS: MetaInsight COVID-19 ( https://crsu.shinyapps.io/metainsightcovid/ ) was developed to conduct NMA with the evolving evidence on treatments for COVID-19. It was updated weekly between 19th May - 19th Oct 2020, incorporating new evidence identified from a living systematic review. RESULTS: The app includes embedded functions to facilitate study selection based on study characteristics, and displays the synthesised results in real time. It allows both frequentist and Bayesian NMA to be conducted as well as consistency and heterogeneity assessments. A demonstration of the app is provided and experiences of building such a platform are discussed. CONCLUSIONS: MetaInsight COVID-19 allows users to take control of the evidence synthesis using the analytic approach they deem appropriate to ascertain how robust findings are to alternative analysis strategies and study inclusion criteria. It is hoped that this app will help avoid many of the duplicated efforts when reviewing and synthesising the COVID-19 evidence, and, in addition, establish the desirability of an open platform format such as this for interactive data interrogation, visualisation, and reporting for any traditional or 'living' NMA.

Impact of Covid-19 on health-related quality of life of patients: A structured review.

INTRODUCTION: Coronavirus disease (Covid-19) has led to a global pandemic since its emergence in December 2019. The majority of research into Covid-19 has focused on transmission, and mortality and morbidity associated with the virus. However, less attention has been given to its impact on health-related quality of life (HRQoL) of patients with Covid-19. METHODS: We searched for original studies published between December 2019 and Jan 2021 in PubMed, Scopus and Medline databases using a specific search strategy. We also explored literature on websites of distinguished public health organisations and hand-searched reference lists of eligible studies. The studies were screened by two reviewers according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) flowchart using pre-determined eligibility criteria. Data were synthesised, analysed descriptively and reported in line with PRISMA guidelines. RESULTS: In total, 1276 studies were identified through the search strategy. Of these, 77 studies were selected for full-text reading after screening the studies. After reading full-text, 12 eligible studies were included in this review. The majority of the studies used a generic HRQoL assessment tool; five studies used SF-36, five studies used EQ-5D-5L, and three used pulmonary disease-specific HRQoL tools (two studies used two tools each). The impact of Covid-19 on HRQoL was found to be considerable in both Acute Covid and Long Covid patients. Higher impact on HRQoL was reported in Acute Covid, females, older ages, patients with more severe disease and patients from low-income countries. CONCLUSION: The impact of Covid-19 on HRQoL of Acute and Long Covid patients is substantial. There was disproportional impact on patients by gender, age, severity of illness and study country. The long-term impact of Covid-19 is still in its initial stage. The findings of the review may be useful to researchers, policymakers, and clinicians caring for people following Covid-19 infection.

Following the science? Comparison of methodological and reporting quality of covid-19 and other research from the first wave of the pandemic.

BACKGROUND: Following the initial identification of the 2019 coronavirus disease (covid-19), the subsequent months saw substantial increases in published biomedical research. Concerns have been raised in both scientific and lay press around the quality of some of this research. We assessed clinical research from major clinical journals, comparing methodological and reporting quality of covid-19 papers published in the first wave (here defined as December 2019 to May 2020 inclusive) of the viral pandemic with non-covid papers published at the same time. METHODS: We reviewed research publications (print and online) from The BMJ, Journal of the American Medical Association (JAMA), The Lancet, and New England Journal of Medicine, from first publication of a covid-19 research paper (February 2020) to May 2020 inclusive. Paired reviewers were randomly allocated to extract data on methodological quality (risk of bias) and reporting quality (adherence to reporting guidance) from each paper using validated assessment tools. A random 10% of papers were assessed by a third, independent rater. Overall methodological quality for each paper was rated high, low or unclear. Reporting quality was described as percentage of total items reported. RESULTS: From 168 research papers, 165 were eligible, including 54 (33%) papers with a covid-19 focus. For methodological quality, 18 (33%) covid-19 papers and 83 (73%) non-covid papers were rated as low risk of bias, OR 6.32 (95%CI 2.85 to 14.00). The difference in quality was maintained after adjusting for publication date, results, funding, study design, journal and raters (OR 6.09 (95%CI 2.09 to 17.72)). For reporting quality, adherence to reporting guidelines was poorer for covid-19 papers, mean percentage of total items reported 72% (95%CI:66 to 77) for covid-19 papers and 84% (95%CI:81 to 87) for non-covid. CONCLUSIONS: Across various measures, we have demonstrated that covid-19 research from the first wave of the pandemic was potentially of lower quality than contemporaneous non-covid research. While some differences may be an inevitable consequence of conducting research during a viral pandemic, poor reporting should not be accepted.