Contextual effects: how to, and how not to, quantify them.

The importance of contextual effects and their roles in clinical care controversial. A Cochrane review published in 2010 concluded that placebo interventions lack important clinical effects overall, but that placebo interventions can influence patient-reported outcomes such as pain and nausea. However, systematic reviews published after 2010 estimated greater contextual effects than the Cochrane review, which stems from the inappropriate methods employed to quantify contextual effects. The effects of medical interventions (i.e., the total treatment effect) can be divided into three components: specific, contextual, and non-specific. We propose that the most effective method for quantifying the magnitude of contextual effects is to calculate the difference in outcome measures between a group treated with placebo and a non-treated control group. Here, we show that other methods, such as solely using the placebo control arm or calculation of a 'proportional contextual effect,' are limited and should not be applied. The aim of this study is to provide clear guidance on best practices for estimating contextual effects in clinical research.

Non-optimal apparent temperature and cardiovascular mortality: the association in Puducherry, India between 2011 and 2020.

BACKGROUND: Cardiovascular diseases (CVDs), the leading cause of death worldwide, are sensitive to temperature. In light of the reported climate change trends, it is important to understand the burden of CVDs attributable to temperature, both hot and cold. The association between CVDs and temperature is region-specific, with relatively few studies focusing on low-and middle-income countries. This study investigates this association in Puducherry, a district in southern India lying on the Bay of Bengal, for the first time. METHODS: Using in-hospital CVD mortality data and climate data from the Indian Meteorological Department, we analyzed the association between apparent temperature (Tapp) and in-hospital CVD mortalities in Puducherry between 2011 and 2020. We used a case-crossover model with a binomial likelihood distribution combined with a distributed lag non-linear model to capture the delayed and non-linear trends over a 21-day lag period to identify the optimal temperature range for Puducherry. The results are expressed as the fraction of CVD mortalities attributable to heat and cold, defined relative to the optimal temperature. We also performed stratified analyses to explore the associations between Tapp and age-and-sex, grouped and considered together, and different types of CVDs. Sensitivity analyses were performed, including using a quasi-Poisson time-series approach. RESULTS: We found that the optimal temperature range for Puducherry is between 30°C and 36°C with respect to CVDs. Both cold and hot non-optimal Tapp were associated with an increased risk of overall in-hospital CVD mortalities, resulting in a U-shaped association curve. Cumulatively, up to 17% of the CVD deaths could be attributable to non-optimal temperatures, with a slightly higher burden attributable to heat (9.1%) than cold (8.3%). We also found that males were more vulnerable to colder temperature; females above 60 years were more vulnerable to heat while females below 60 years were affected by both heat and cold. Mortality with cerebrovascular accidents was associated more with heat compared to cold, while ischemic heart diseases did not seem to be affected by temperature. CONCLUSION: Both heat and cold contribute to the burden of CVDs attributable to non-optimal temperatures in the tropical Puducherry. Our study also identified the age-and-sex and CVD type differences in temperature attributable CVD mortalities. Further studies from India could identify regional associations, inform our understanding of the health implications of climate change in India and enhance the development of regional and contextual climate-health action-plans.

Optimal dose and type of physical activity to improve functional capacity and minimise adverse events in acutely hospitalised older adults: a systematic review with dose-response network meta-analysis of randomised controlled trials.

OBJECTIVE: To identify the optimal dose and type of physical activity to improve functional capacity and reduce adverse events in acutely hospitalised older adults. DESIGN: Systematic review and Bayesian model-based network meta-analysis. DATA SOURCES: Four databases were searched from inception to 20 June 2022. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Randomised controlled trials that assessed the effectiveness of a physical activity-based intervention on at least one functional outcome in people aged ≥50 years hospitalised due to an acute medical condition were included. Pooled effect estimates (ie, standardised mean differences for functional capacity and the ratio of means for adverse events) were calculated using random treatment effects network meta-analysis models. RESULTS: Nineteen studies (3842 participants) met the inclusion criteria. Approximately 100 Metabolic Equivalents of Task per day (METs-min/day) (~40 min/day of light effort or ~25 min/day of moderate effort activities) was the minimal dose to improve the functional capacity of acute hospitalised older adults (standardised mean difference (SMD)=0.28, 95% credible interval (CrI) 0.01 to 0.55). The optimal dose was estimated at 159 METs-min/day (~70 min/day of light effort or ~40 min/day of moderate effort activities; SMD=0.41, 95% CrI 0.08 to 0.72). Ambulation was deemed the most efficient intervention, and the optimal dose was reached at 143 METs-min/day (~50 min/day of slow-paced walking; SMD=0.76, 95% CrI 0.35 to 1.16), showing a high evidential power (87.68%). The minimal effective ambulation dose was estimated at 74 METs-min/day (~25 min/day of slow-paced walking; SMD=0.25, 95% CrI 0.01 to 0.41). Physical activity interventions resulted in a decrease in the rate of adverse events compared with usual care at discharge (ratio of means=0.96, 95% CrI 0.95 to 0.97; median time 7 days). CONCLUSIONS: This meta-analysis yielded low to moderate evidence supporting the use of in-hospital supervised physical activity programmes in acutely hospitalised older adults. As little as ~25 min/day of slow-paced walking is sufficient to improve functional capacity and minimise adverse events in this population. TRIAL REGISTRATION NUMBER: PROSPERO CRD42021271999.

Methods to assess evidence consistency in dose-response model based network meta-analysis.

Network meta-analysis (NMA) simultaneously estimates multiple relative treatment effects based on evidence that forms a network of treatment comparisons. Heterogeneity in treatment definitions, such as dose, can lead to a violation of the consistency assumption that underpins NMA. Model-based NMA (MBNMA) methods have been proposed that allow functional dose-response relationships to be estimated within an NMA, which avoids lumping different doses together and thereby reduces the likelihood of inconsistency. Dose-response MBNMA relies on appropriate specification of the dose-response relationship as well as consistency of relative effects. In this article we describe methods to check for inconsistency in dose-response MBNMA models. Global and local (node-splitting) tests for inconsistency are described that account for studies with ≥3 arms that are typical in dose-finding trials. We show that consistency needs to be assessed with respect to the choice of dose-response function. We illustrate the methods using a network comparing biologics for moderate-to-severe psoriasis. By comparing results from an Emax and an exponential dose-response function we show that failure to correctly characterise the dose-response can introduce apparent inconsistency. The number of comparisons for which node-splitting is possible is also shown to be dependent on the complexity of the selected dose-response function. We highlight that the nature of dose-finding studies, which typically compare multiple doses of the same agent, provide limited scope to assess inconsistency, but these study designs help guard against inconsistency in the first place. We demonstrate the importance of assessing consistency to obtain robust relative effects to inform drug-development and policy decisions.

Systematic review and meta-analysis of interventions tested in animal models of lacunar stroke.

BACKGROUND AND PURPOSE: A total of 25% of strokes are lacunar, and these are pathophysiologically different from large artery strokes. Despite emerging evidence of a substantial impact on physical disability and dementia, little attention has been paid to the development of specific treatments. The optimal use of the animal models of lacunar stroke used to test candidate interventions is not known. METHODS: We conducted a systematic review and meta-analysis of studies testing candidate interventions in animal models of lacunar stroke. We used random-effects meta-analysis to assess the impact of study characteristics and trim and fill to seek evidence of publication bias. RESULTS: The efficacy of 43 distinct interventions was described in 57 publications. The median number of quality checklist items scored was 3 of 8 (interquartile range, 2-4). Many models reflected mechanisms of limited relevance to lacunar stroke. Meta-analysis of results from 27 studies showed that on average, infarct size and neurobehavioral outcome were improved by 34.2% (24.1-44.2) and 0.82 standardized mean difference (0.51-1.14), respectively. Four interventions improved both infarct size and neurobehavioral outcome but there were insufficient data for this finding to be considered robust. For infarct size, efficacy was lower in studies reporting blinding and higher in studies reporting randomization. For neurobehavior, efficacy was lower in randomized studies. For infarct size there was evidence of publication bias. CONCLUSIONS: No intervention has yet been tested in sufficient range and depth to support translation to clinical trial. There is limited reporting of measures to reduce the risk of bias and evidence for a substantial publications bias.

Variability in meta-analysis estimates of continuous outcomes using different standardization and scale-specific re-expression methods.

OBJECTIVES: To explore the impact of using different data standardization and scale-specific re-expression methods (i.e., processes to convert standardized data into scale-specific units) in meta-analyses using standardized mean differences (SMDs). STUDY DESIGN AND SETTING: We used data assessed by the Short Physical Performance Battery and the Barthel Index from a meta-analysis of randomized controlled trials which synthesized evidence of physical activity effectiveness on the functional capacity of hospitalized older adults. We standardized the data using study-specific pooled standard deviations (SDs), an internal, and an external SD references. Bayesian meta-analyses were performed for each method to compare the posterior distributions of the meta-analysis parameters. Posterior estimates were re-expressed into scale-specific units applying different methods established in the Cochrane guidelines. RESULTS: Meta-analysis estimates depend on the used standardization method. Analyses including data standardized using the largest SD reference presented lower estimates with less uncertainty in both scales. The method applied for re-expressing SMDs into scale-specific units impacted in their posterior clinical interpretation. The most similar results across models were obtained when using the same SD reference to standardize and re-express data. CONCLUSION: Different data standardization methods yielded different meta-analysis estimates on the SMD scale. To avoid the introduction of bias, the use of a single scale-specific SD reference to standardize data is recommended and instead of study-specific pooled sample SDs. Meta-analysis software packages may therefore change their default methods to allow this method by a single scale-specific SD. To re-express the SMDs into scale-specific units, we suggest the application of the same SD reference that was used for data standardization.

Boosting treatment outcomes via the patient-practitioner relationship, treatment-beliefs or therapeutic setting. A systematic review with meta-analysis of contextual effects in chronic musculoskeletal pain.

OBJECTIVE: To ascertain whether manipulating contextual effects (e.g. interaction with patients, or beliefs about treatments) boosted the outcomes of non-pharmacological and non-surgicaltreatments for chronic primary musculoskeletal pain. DESIGN: Systematic review of randomized controlled trials. DATA SOURCES: We searched for trials in six databases, citation tracking, and clinical trials registers. We included trials that compared treatments with enhanced contextual effects with the same treatments without enhancement in adults with chronic primary musculoskeletal pain. DATA SYNTHESIS: The outcomes of interest were pain intensity, physical functioning, global ratings of improvement, quality of life, depression, anxiety, and sleep. We evaluated risk of bias and certainty of the evidence using Cochrane Risk of Bias tool 2.0 and the GRADE approach, respectively. RESULTS: Of 17637 records, we included 10 trials with 990 participants and identified 5 ongoing trials. The treatments were acupuncture, education, exercise training, and physical therapy. The contextual effects that were improved in the enhanced treatments were patient-practitioner relationship, patient beliefs and characteristics, therapeutic setting/environment, and treatment characteristics. Our analysis showed that improving contextual effects in non-pharmacological and non-surgical treatments may not make much difference on pain intensity (mean difference [MD] : -1.77, 95%-CI: [-8.71; 5.16], k = 7 trials, N = 719 participants, Scale: 0-100, GRADE: Low)) or physical functioning (MD: -0.27, 95%-CI: [-1.02; 0.49], 95%-PI: [-2.04; 1.51], k = 6 , N = 567, Scale: 0-10, GRADE: Low) in the short-term and at later follow-ups. Sensitivity analyses revealed similar findings. CONCLUSION: Whilst evidence gaps exist, per current evidence it may not be possible to achieve meaningful benefit for patients with chronic musculoskeletal pain by manipulating the context of non-pharmacological and non-surgical treatments. TRIAL REGISTRATION: This systematic review was prospectively registered in PROSPERO (registration number: CRD42023391601).

The importance of context (placebo effects) in conservative interventions for musculoskeletal pain: A systematic review and meta-analysis of randomized controlled trials.

BACKGROUND AND OBJECTIVE: Contextual effects (e.g. patient expectations) may play a role in treatment effectiveness. This study aimed to estimate the magnitude of contextual effects for conservative, non-pharmacological interventions for musculoskeletal pain conditions. A systematic review and meta-analysis of randomized controlled trials (RCTs) that compared placebo conservative non-pharmacological interventions to no treatment for musculoskeletal pain. The outcomes assessed included pain intensity, physical functioning, health-related quality of life, global rating of change, depression, anxiety and sleep at immediate, short-, medium- and/or long-term follow-up. DATABASES AND DATA TREATMENT: MEDLINE, EMBASE, CINAHL, Web of Science Core Collection, CENTRAL and SPORTDiscus were searched from inception to September 2021. Trial registry searches, backward and forward citation tracking and searches for prior systematic reviews were completed. The Cochrane risk of bias 2 tool was implemented. RESULTS: The study included 64 RCTs (N = 4314) out of 8898 records. For pain intensity, a mean difference of (MD: -5.32, 95% confidence interval (CI): -7.20, -3.44, N = 57 studies with 74 outcomes, GRADE: very low) was estimated for placebo interventions. A small effect in favour of the placebo interventions for physical function was estimated (SMD: -0.22, 95% CI: -0.35, -0.09; N = 37 with 48 outcomes, GRADE: very low). Similar results were found for a broad range of patient-reported outcomes. Meta-regression analyses did not explain heterogeneity among analyses. CONCLUSION: The study found that the contextual effect of non-pharmacological conservative interventions for musculoskeletal conditions is likely to be small. However, given the known effect sizes of recommended evidence-based treatments for musculoskeletal conditions, it may still contribute an important component. SIGNIFICANCE: Contextual effects of non-pharmacological conservative interventions for musculoskeletal conditions are likely to be small for a broad range of patient-reported outcomes (pain intensity, physical function, quality of life, global rating of change and depression). Contextual effects are unlikely, in isolation, to offer much clinical care. But these factors do have relevance in an overall treatment context as they provide almost 30% of the minimally clinically important difference.

An evaluation of menopause service delivery during the COVID-19 pandemic.

OBJECTIVE: To investigate the experience of remote outpatient menopause service delivery by clinicians and patients during the COVID-19 pandemic. METHODS: Two surveys explored the experiences of patients and clinicians separately. Patients attending menopause clinics in the UK were directed to an online survey which included questions on demographics and on their experience of their most recent appointment. A clinician survey was shared to members of the British Menopause Society (BMS) via email and was made available on the BMS website. It contained questions on clinic characteristics and clinicians' experience of delivering remote menopause consultations. Surveys were available for completion between 01/12/2020 and 10/02/2021. RESULTS: Of 180 patients who completed the patient survey, 52% felt remote consultations were the same or better than face-to-face consultations, and 90% of patients felt a choice between remote and face-to-face consultations should be offered. Patients overall were satisfied with many aspects of care, though numerous problems were highlighted with appointment administration. Of 76 clinicians who completed the clinician survey, most found remote patient consultations either no different or a bit worse than face-to face consultations but found that they offered more flexibility. In some cases, significant rescheduling was necessary to accommodate for the clinical needs of the consultation. CONCLUSION: A 'one-size-fits-all' approach to managing the delivery of menopause care is not supported by patients or clinicians. There must be a robust process in place to avoid problems with appointment scheduling and associated communications. Lessons learned from the pandemic can help to provide holistic menopause care.

Participant retention in paediatric randomised controlled trials published in six major journals 2015-2019: systematic review and meta-analysis.

BACKGROUND: The factors which influence participant retention in paediatric randomised controlled trials are under-researched. Retention may be more challenging due to child developmental stages, involving additional participants, and proxy-reporting of outcomes. This systematic review and meta-analysis explores the factors which may influence retention in paediatric trials. METHODS: Using the MEDLINE database, paediatric randomised controlled trials published between 2015 and 2019 were identified from six general and specialist high-impact factor medical journals. The review outcome was participant retention for each reviewed trial's primary outcome. Context (e.g. population, disease) and design (e.g. length of trial) factors were extracted. Retention was examined for each context and design factor in turn, with evidence for an association being determined by a univariate random-effects meta-regression analysis. RESULTS: Ninety-four trials were included, and the median total retention was 0.92 (inter-quartile range 0.83 to 0.98). Higher estimates of retention were seen for trials with five or more follow-up assessments before the primary outcome, those less than 6 months between randomisation and primary outcome, and those that used an inactive data collection method. Trials involving children aged 11 and over had the higher estimated retention compared with those involving younger children. Those trials which did not involve other participants also had higher retention, than those where they were involved. There was also evidence that a trial which used an active or placebo control treatment had higher estimated retention, than treatment-as-usual. Retention increased if at least one engagement method was used. Unlike reviews of trials including all ages of participants, we did not find any association between retention and the number of treatment groups, size of trial, or type of treatment. CONCLUSIONS: Published paediatric RCTs rarely report the use of specific modifiable factors that improve retention. Including multiple, regular follow-ups with participants before the primary outcome may reduce attrition. Retention may be highest when the primary outcome is collected up to 6 months after a participant is recruited. Our findings suggest that qualitative research into improving retention when trials involve multiple participants such as young people, and their caregivers or teachers would be worthwhile. Those designing paediatric trials also need to consider the use of appropriate engagement methods. RESEARCH ON RESEARCH (ROR) REGISTRY: https://ror-hub.org/study/2561.

Monotreatment With Conventional Antirheumatic Drugs or Glucocorticoids in Rheumatoid Arthritis: A Network Meta-Analysis.

Importance: This is the first network meta-analysis to assess outcomes associated with multiple conventional synthetic disease-modifying antirheumatic drugs and glucocorticoid. Objective: To analyze clinical outcomes after treatment with conventional synthetic disease-modifying antirheumatic drugs and glucocorticoid among patients with rheumatoid arthritis. Data Sources: With no time restraint, English language articles were searched in MEDLINE, Embase, Cochrane Central, ClinicalTrials.gov, and reference lists of relevant meta-analyses until September 15, 2022. Study Selection: Four reviewers in pairs of 2 independently included controlled studies randomizing patients with rheumatoid arthritis to mono-conventional synthetic disease-modifying antirheumatic drugs, glucocorticoid, placebo, or nonactive treatment that recorded at least 1 outcome of tender joint count, swollen joint count, erythrocyte sedimentation rate, and C-reactive protein level. Of 1098 assessed articles, 130 articles (132 interventions) were included. Data Extraction and Synthesis: The review followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses reporting guideline, and data quality was assessed by the Cochrane risk of bias tool RoB 2. Data were extracted by a single author and checked independently by 2 authors. Data were analyzed using a random effect model, and data analysis was conducted from June 2021 to February 2023. Main Outcomes and Measures: A protocol with hypothesis and study plan was registered before data recording. The most complete of recorded outcomes (tender joint count) was used as primary outcome, with imputations based on other outcomes to obtain a full analysis of all studies. Absolute change adjusted for baseline disease activity was assessed. Results: A total of 29 interventions in 275 treatment groups among 132 randomized clinical trials (mean [range], 71.0% [27.0% to 100%] females in studies; mean [range] of ages in studies, 53 [36 to 70] years) were identified, which included 13 260 patients with rheumatoid arthritis. The mean (range) duration of RA was 79 (2 to 243) months, and the mean (range) disease activity score was 6.3 (4.0 to 8.8). Compared with placebo, oral methotrexate was associated with a reduced tender joint count by 5.18 joints (95% credible interval [CrI], 4.07 to 6.28 joints). Compared with methotrexate, glucocorticoid (-2.54 joints; 95% CrI, -5.16 to 0.08 joints) and remaining drugs except cyclophosphamide (6.08 joints; 95% CrI, 0.44 to 11.66 joints) were associated with similar or lower tender joint counts. Conclusions and Relevance: This study's results support the present role of methotrexate as the primary reference conventional synthetic disease-modifying antirheumatic drug.

The Association between Apparent Temperature and Hospital Admissions for Cardiovascular Disease in Limpopo Province, South Africa.

Cardiovascular diseases (CVDs) have a high disease burden both globally and in South Africa. They have also been found to be temperature-sensitive globally. The association between temperature and CVD morbidity has previously been demonstrated, but little is known about it in South Africa. It is important to understand how changes in temperature in South Africa will affect CVD morbidity, especially in rural regions, to inform public health interventions and adaptation strategies. This study aimed to determine the short-term effect of apparent temperature (Tapp) on CVD hospital admissions in Mopani District, Limpopo province, South Africa. A total of 3124 CVD hospital admissions records were obtained from two hospitals from 1 June 2009 to 31 December 2016. Daily Tapp was calculated using nearby weather station measurements. The association was modelled using a distributed lag non-linear model with a negative binomial regression over a 21-day lag period. The fraction of morbidity attributable to non-optimal Tapp, i.e., cold (6-25 °C) and warm (27-32 °C) Tapp was reported. We found an increase in the proportion of admissions due to CVDs for warm and cold Tapp cumulatively over 21 days. Increasing CVD admissions due to warm Tapp appeared immediately and lasted for two to four days, whereas the lag-structure for the cold effect was inconsistent. A proportion of 8.5% (95% Confidence Interval (CI): 3.1%, 13.7%) and 1.1% (95% CI: -1.4%, 3.5%) of the total CVD admissions was attributable to cold and warm temperatures, respectively. Warm and cold Tapp may increase CVD admissions, suggesting that the healthcare system and community need to be prepared in the context of global temperature changes.

Joining the Dots: Linking Disconnected Networks of Evidence Using Dose-Response Model-Based Network Meta-Analysis.

BACKGROUND: Network meta-analysis (NMA) synthesizes direct and indirect evidence on multiple treatments to estimate their relative effectiveness. However, comparisons between disconnected treatments are not possible without making strong assumptions. When studies including multiple doses of the same drug are available, model-based NMA (MBNMA) presents a novel solution to this problem by modeling a parametric dose-response relationship within an NMA framework. In this article, we illustrate several scenarios in which dose-response MBNMA can connect and strengthen evidence networks. METHODS: We created illustrative data sets by removing studies or treatments from an NMA of triptans for migraine relief. We fitted MBNMA models with different dose-response relationships. For connected networks, we compared MBNMA estimates with NMA estimates. For disconnected networks, we compared MBNMA estimates with NMA estimates from an "augmented" network connected by adding studies or treatments back into the data set. RESULTS: In connected networks, relative effect estimates from MBNMA were more precise than those from NMA models (ratio of posterior SDs NMA v. MBNMA: median = 1.13; range = 1.04-1.68). In disconnected networks, MBNMA provided estimates for all treatments where NMA could not and were consistent with NMA estimates from augmented networks for 15 of 18 data sets. In the remaining 3 of 18 data sets, a more complex dose-response relationship was required than could be fitted with the available evidence. CONCLUSIONS: Where information on multiple doses is available, MBNMA can connect disconnected networks and increase precision while making less strong assumptions than alternative approaches. MBNMA relies on correct specification of the dose-response relationship, which requires sufficient data at different doses to allow reliable estimation. We recommend that systematic reviews for NMA search for and include evidence (including phase II trials) on multiple doses of agents where available.

Six Meta-analyses on Treatments for Femoroacetabular Impingement Syndrome in a Year and Readers Are None the Wiser: Methods Advice for Researchers Planning Meta-analysis of Data From Fewer Than 5 Trials.

SYNOPSIS: In 2020, 6 meta-analyses comparing arthroscopic hip surgery to physical therapy were published. All included the same 3 randomized controlled trials, and none used methods suitable for the analysis of fewer than 5 studies. When there are fewer than 5 studies and heterogeneity, a random-effects model with the Hartung-Knapp-Sidik-Jonkman adjustment for a maximally conservative estimate should be employed; if reliable prior information is available, a Bayesian random-effects meta-analysis should be employed. Our re-analysis, which employed the appropriate model, found that there is currently insufficient evidence to conclude that surgery is superior to physical therapy for femoroacetabular impingement (FAI) syndrome. Further randomized controlled trials are required to resolve the clinical question of what the best treatment approach is for FAI syndrome. We provide readers with tools to conduct appropriate meta-analysis of fewer than 5 trials. J Orthop Sports Phys Ther 2021;51(5):201-203. doi:10.2519/jospt.2021.0107.

Lagged Association between Climate Variables and Hospital Admissions for Pneumonia in South Africa.

Pneumonia is a leading cause of hospitalization in South Africa. Climate change could potentially affect its incidence via changes in meteorological conditions. We investigated the delayed effects of temperature and relative humidity on pneumonia hospital admissions at two large public hospitals in Limpopo province, South Africa. Using 4062 pneumonia hospital admission records from 2007 to 2015, a time-varying distributed lag non-linear model was used to estimate temperature-lag and relative humidity-lag pneumonia relationships. Mean temperature, relative humidity and diurnal temperature range were all significantly associated with pneumonia admissions. Cumulatively across the 21-day period, higher mean daily temperature (30 °C relative to 21 °C) was most strongly associated with a decreased rate of hospital admissions (relative rate ratios (RR): 0.34, 95% confidence interval (CI): 0.14-0.82), whereas results were suggestive of lower mean daily temperature (12 °C relative to 21 °C) being associated with an increased rate of admissions (RR: 1.27, 95%CI: 0.75-2.16). Higher relative humidity (>80%) was associated with fewer hospital admissions while low relative humidity (<30%) was associated with increased admissions. A proportion of pneumonia admissions were attributable to changes in meteorological variables, and our results indicate that even small shifts in their distributions (e.g., due to climate change) could lead to substantial changes in their burden. These findings can inform a better understanding of the health implications of climate change and the burden of hospital admissions for pneumonia now and in the future.

Network meta-analysis for comparative effectiveness of treatments for chronic low back pain disorders: systematic review protocol.

INTRODUCTION: Chronic low back pain disorders (CLBDs) present a substantial societal burden; however, optimal treatment remains debated. To date, pairwise and network meta-analyses have evaluated individual treatment modes, yet a comparison of a wide range of common treatments is required to evaluate their relative effectiveness. Using network meta-analysis, we aim to evaluate the effectiveness of treatments (acupuncture, education or advice, electrophysical agents, exercise, manual therapies/manipulation, massage, the McKenzie method, pharmacotherapy, psychological therapies, surgery, epidural injections, percutaneous treatments, traction, physical therapy, multidisciplinary pain management, placebo, 'usual care' and/or no treatment) on pain intensity, disability and/or mental health in patients with CLBDs. METHODS AND ANALYSIS: Six electronic databases and reference lists of 285 prior systematic reviews were searched. Eligible studies will be randomised controlled/clinical trials (including cross-over and cluster designs) that examine individual treatments or treatment combinations in adult patients with CLBDs. Studies must be published in English, German or Chinese as a full-journal publication in a peer-reviewed journal. A narrative approach will be used to synthesise and report qualitative and quantitative data, and, where feasible, network meta-analyses will be performed. Reporting of the review will be informed by Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidance, including the network meta-analysis extension (PRISMA-NMA). The Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach for network meta-analysis will be implemented for assessing the quality of the findings. ETHICS AND DISSEMINATION: Ethical approval is not required for this systematic review of the published data. Findings will be disseminated via peer-reviewed publication. PROSPERO REGISTRATION NUMBER: PROSPERO registration number CRD42020182039.

Performance of model-based network meta-analysis (MBNMA) of time-course relationships: A simulation study.

Time-course model-based network meta-analysis (MBNMA) has been proposed as a framework to combine treatment comparisons from a network of randomized controlled trials reporting outcomes at multiple time-points. This can explain heterogeneity/inconsistency that arises by pooling studies with different follow-up times and allow inclusion of studies from earlier in drug development. The aim of this study is to explore using simulation: (a) how MBNMA model parameters are affected by the quantity/location of observed time-points across studies/comparisons, (b) how reliably an appropriate MBNMA model can be identified, (c) the robustness of model estimates and predictions under different dataset characteristics. Our results indicate that model parameters for a given treatment comparison are estimated with low mean bias even when no direct evidence was available, provided there was sufficient indirect evidence to estimate the time-course. A staged model selection strategy that selects time-course function, then heterogeneity, then covariance structure, identified the true model most reliably and efficiently. Predictions and parameter estimates from selected models had low mean bias even in the presence of high heterogeneity/correlation between time-points. However, failure to properly account for heterogeneity/correlation could lead to high error in precision of the estimates. Time-course MBNMA provides a statistically robust framework for synthesizing direct and indirect evidence to estimate relative effects and predicted mean responses whilst accounting for time-course and incorporating correlation and heterogeneity. This supports the use of MBNMA in evidence synthesis, particularly when additional studies are available with follow-up times that would otherwise prohibit their inclusion by conventional meta-analysis.

Modelling time-course relationships with multiple treatments: Model-based network meta-analysis for continuous summary outcomes.

BACKGROUND: Model-based meta-analysis (MBMA) is increasingly used to inform drug-development decisions by synthesising results from multiple studies to estimate treatment, dose-response, and time-course characteristics. Network meta-analysis (NMA) is used in Health Technology Appraisals for simultaneously comparing effects of multiple treatments, to inform reimbursement decisions. Recently, a framework for dose-response model-based network meta-analysis (MBNMA) has been proposed that combines, often nonlinear, MBMA modelling with the statistically robust properties of NMA. Here, we aim to extend this framework to time-course models. METHODS: We propose a Bayesian time-course MBNMA modelling framework for continuous summary outcomes that allows for nonlinear modelling of multiparameter time-course functions, accounts for residual correlation between observations, preserves randomisation by modelling relative effects, and allows for testing of inconsistency between direct and indirect evidence on the time-course parameters. We demonstrate our modelling framework using an illustrative dataset of 23 trials investigating treatments for pain in osteoarthritis. RESULTS: Of the time-course functions that we explored, the Emax model gave the best fit to the data and has biological plausibility. Some simplifying assumptions were needed to identify the ET50 , due to few observations at early follow-up times. Treatment estimates were robust to the inclusion of correlations in the likelihood. CONCLUSIONS: Time-course MBNMA provides a statistically robust framework for synthesising evidence on multiple treatments at multiple time points. The use of placebo-controlled studies in drug-development means there is limited potential for inconsistency. The methods can inform drug-development decisions and provide the rigour needed in the reimbursement decision-making process.