Correction to: joint models for longitudinal and time-to-event data: a review of reporting quality with a view to meta-analysis

Abstract Following publication of the original article [1] the authors reported that reference 15 (Cella et al.) had been incorrectly replaced with a duplicate of Brombin et al. during publication

What is the evidence for the effectiveness, appropriateness and feasibility of group clinics for patients with chronic conditions? A systematic review

Background Group clinics are a form of delivering specialist-led care in groups rather than in individual consultations. Objective To examine the evidence for the use of group clinics for patients with chronic health conditions. Design A systematic review of evidence from randomised controlled trials (RCTs) supplemented by qualitative studies, cost studies and UK initiatives. Data sources We searched MEDLINE, EMBASE, The Cochrane Library, Web of Science and Cumulative Index to Nursing and Allied Health Literature from 1999 to 2014. Systematic reviews and RCTs were eligible for inclusion. Additional searches were performed to identify qualitative studies, studies reporting costs and evidence specific to UK settings. Review methods Data were extracted for all included systematic reviews, RCTs and qualitative studies using a standardised form. Quality assessment was performed for systematic reviews, RCTs and qualitative studies. UK studies were included regardless of the quality or level of reporting. Tabulation of the extracted data informed a narrative synthesis. We did not attempt to synthesise quantitative data through formal meta-analysis. However, given the predominance of studies of group clinics for diabetes, using common biomedical outcomes, this subset was subject to quantitative analysis. Results Thirteen systematic reviews and 22 RCT studies met the inclusion criteria. These were supplemented by 12 qualitative papers (10 studies), four surveys and eight papers examining costs. Thirteen papers reported on 12 UK initiatives. With 82 papers covering 69 different studies, this constituted the most comprehensive coverage of the evidence base to date. Disease-specific outcomes – the large majority of RCTs examined group clinic approaches to diabetes. Other conditions included hypertension/heart failure and neuromuscular conditions. The most commonly measured outcomes for diabetes were glycated haemoglobin A1c (HbA1c), blood pressure and cholesterol. Group clinic approaches improved HbA1c and improved systolic blood pressure but did not improve low-density lipoprotein cholesterol. A significant effect was found for disease-specific quality of life in a few studies. No other outcome measure showed a consistent effect in favour of group clinics. Recent RCTs largely confirm previous findings. Health services outcomes – the evidence on costs and feasibility was equivocal. No rigorous evaluation of group clinics has been conducted in a UK setting. A good-quality qualitative study from the UK highlighted factors such as the physical space and a flexible appointment system as being important to patients. The views and attitudes of those who dislike group clinic provision are poorly represented. Little attention has been directed at the needs of people from ethnic minorities. The review team identified significant weaknesses in the included research. Potential selection bias limits the generalisability of the results. Many patients who could potentially be included do not consent to the group approach. Attendance is often interpreted liberally. Limitations This telescoped review, conducted within half the time period of a conventional systematic review, sought breadth in covering feasibility, appropriateness and meaningfulness in addition to effectiveness and cost-effectiveness and utilised several rapid-review methods. It focused on the contribution of recently published evidence from RCTs to the existing evidence base. It did not reanalyse trials covered in previous reviews. Following rapid review methods, we did not perform independent double data extraction and quality assessment. Conclusions Although there is consistent and promising evidence for an effect of group clinics for some biomedical measures, this effect does not extend across all outcomes. Much of the evidence was derived from the USA. It is important to engage with UK stakeholders to identify NHS considerations relating to the implementation of group clinic approaches. Future work The review team identified three research priorities: (1) more UK-centred evaluations using rigorous research designs and economic models with robust components; (2) clearer delineation of individual components within different models of group clinic delivery; and (3) clarification of the circumstances under which group clinics present an appropriate alternative to an individual consultation

COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records

BACKGROUND: Updatable estimates of COVID-19 onset, progression, and trajectories underpin pandemic mitigation efforts. To identify and characterise disease trajectories, we aimed to define and validate ten COVID-19 phenotypes from nationwide linked electronic health records (EHR) using an extensible framework. METHODS: In this cohort study, we used eight linked National Health Service (NHS) datasets for people in England alive on Jan 23, 2020. Data on COVID-19 testing, vaccination, primary and secondary care records, and death registrations were collected until Nov 30, 2021. We defined ten COVID-19 phenotypes reflecting clinically relevant stages of disease severity and encompassing five categories: positive SARS-CoV-2 test, primary care diagnosis, hospital admission, ventilation modality (four phenotypes), and death (three phenotypes). We constructed patient trajectories illustrating transition frequency and duration between phenotypes. Analyses were stratified by pandemic waves and vaccination status. FINDINGS: Among 57 032 174 individuals included in the cohort, 13 990 423 COVID-19 events were identified in 7 244 925 individuals, equating to an infection rate of 12·7% during the study period. Of 7 244 925 individuals, 460 737 (6·4%) were admitted to hospital and 158 020 (2·2%) died. Of 460 737 individuals who were admitted to hospital, 48 847 (10·6%) were admitted to the intensive care unit (ICU), 69 090 (15·0%) received non-invasive ventilation, and 25 928 (5·6%) received invasive ventilation. Among 384 135 patients who were admitted to hospital but did not require ventilation, mortality was higher in wave 1 (23 485 [30·4%] of 77 202 patients) than wave 2 (44 220 [23·1%] of 191 528 patients), but remained unchanged for patients admitted to the ICU. Mortality was highest among patients who received ventilatory support outside of the ICU in wave 1 (2569 [50·7%] of 5063 patients). 15 486 (9·8%) of 158 020 COVID-19-related deaths occurred within 28 days of the first COVID-19 event without a COVID-19 diagnoses on the death certificate. 10 884 (6·9%) of 158 020 deaths were identified exclusively from mortality data with no previous COVID-19 phenotype recorded. We observed longer patient trajectories in wave 2 than wave 1. INTERPRETATION: Our analyses illustrate the wide spectrum of disease trajectories as shown by differences in incidence, survival, and clinical pathways. We have provided a modular analytical framework that can be used to monitor the impact of the pandemic and generate evidence of clinical and policy relevance using multiple EHR sources. FUNDING: British Heart Foundation Data Science Centre, led by Health Data Research UK

Investigation of two stage meta-analysis methods for joint longitudinal and time-to-event data through simulation and real data application

Background Joint modelling of longitudinal and time-to-event data is often preferred over separate longitudinal or time-to-event analyses as it can account for study dropout, error in longitudinally measured covariates, and correlation between longitudinal and time-to-event outcomes. The joint modelling literature focuses mainly on the analysis of single studies with no methods currently available for the meta-analysis of joint model estimates from multiple studies. Methods We propose a 2-stage method for meta-analysis of joint model estimates. These methods are applied to the INDANA dataset to combine joint model estimates of systolic blood pressure with time to death, time to myocardial infarction, and time to stroke. Results are compared to meta-analyses of separate longitudinal or time-to-event models. A simulation study is conducted to contrast separate versus joint analyses over a range of scenarios. Results Using the real dataset, similar results were obtained by using the separate and joint analyses. However, the simulation study indicated a benefit of use of joint rather than separate methods in a meta-analytic setting where association exists between the longitudinal and time-to-event outcomes. Conclusions Where evidence of association between longitudinal and time-to-event outcomes exists, results from joint models over standalone analyses should be pooled in 2-stage meta-analyses

Additional file 2: of Joint models for longitudinal and time-to-event data: a review of reporting quality with a view to meta-analysis

This file includes a blank example of the data collection form used to record information from the studies identified by this review. (DOCX 14 kb