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Background Sustaining independence is important for older people, but there is insufficient guidance about which community health and care services to implement. Objectives To synthesise evidence of the effectiveness of community services to sustain independence for older people grouped according to their intervention components, and to examine if frailty moderates the effect. Review design Systematic review and network meta-analysis. Eligibility criteria Studies: Randomised controlled trials or cluster-randomised controlled trials. Participants: Older people (mean age 65+) living at home. Interventions: community-based complex interventions for sustaining independence. Comparators: usual care, placebo or another complex intervention. Main outcomes Living at home, instrumental activities of daily living, personal activities of daily living, care-home placement and service/economic outcomes at 1 year. Data sources We searched MEDLINE (1946–), Embase (1947–), CINAHL (1972–), PsycINFO (1806–), CENTRAL and trial registries from inception to August 2021, without restrictions, and scanned reference lists. Review methods Interventions were coded, summarised and grouped. Study populations were classified by frailty. A random-effects network meta-analysis was used. We assessed trial-result risk of bias (Cochrane RoB 2), network meta-analysis inconsistency and certainty of evidence (Grading of Recommendations Assessment, Development and Evaluation for network meta-analysis). Results We included 129 studies (74,946 participants). Nineteen intervention components, including ‘multifactorial-action’ (multidomain assessment and management/individualised care planning), were identified in 63 combinations. The following results were of low certainty unless otherwise stated. For living at home, compared to no intervention/placebo, evidence favoured: multifactorial-action and review with medication-review (odds ratio 1.22, 95% confidence interval 0.93 to 1.59; moderate certainty) multifactorial-action with medication-review (odds ratio 2.55, 95% confidence interval 0.61 to 10.60) cognitive training, medication-review, nutrition and exercise (odds ratio 1.93, 95% confidence interval 0.79 to 4.77) and activities of daily living training, nutrition and exercise (odds ratio 1.79, 95% confidence interval 0.67 to 4.76). Four intervention combinations may reduce living at home. For instrumental activities of daily living, evidence favoured multifactorial-action and review with medication-review (standardised mean difference 0.11, 95% confidence interval 0.00 to 0.21; moderate certainty). Two interventions may reduce instrumental activities of daily living. For personal activities of daily living, evidence favoured exercise, multifactorial-action and review with medication-review and self-management (standardised mean difference 0.16, 95% confidence interval −0.51 to 0.82). For homecare recipients, evidence favoured the addition of multifactorial-action and review with medication-review (standardised mean difference 0.60, 95% confidence interval 0.32 to 0.88). Care-home placement and service/economic findings were inconclusive. Limitations High risk of bias in most results and imprecise estimates meant that most evidence was low or very low certainty. Few studies contributed to each comparison, impeding evaluation of inconsistency and frailty. Studies were diverse; findings may not apply to all contexts. Conclusions Findings for the many intervention combinations evaluated were largely small and uncertain. However, the combinations most likely to sustain independence include multifactorial-action, medication-review and ongoing review of patients. Some combinations may reduce independence. Future work Further research is required to explore mechanisms of action and interaction with context. Different methods for evidence synthesis may illuminate further. Study registration This study is registered as PROSPERO CRD42019162195. Funding This award was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme (NIHR award ref: NIHR128862) and is published in full in Health Technology Assessment; Vol. 28, No. 48. See the NIHR Funding and Awards website for further award information. Plain language summary Which community services are best for helping older people to be independent? Key messages Due to a lack of robust evidence, the benefits and risks of most types of community services for older people are unclear. Individualised care planning, where medication is adjusted and there are regular follow-ups, probably helps people stay living at home. What are community services for older people? There are many kinds of community services for older people. For example, in some services, everyone is given exercise and dietary advice or an individualised care plan. These often aim to help older people age independently. What was the study about? Maintaining independence is important in later life. We wanted to find out which community services work best: to help people stay living at home, and to do day-to-day activities independently. We reviewed findings from previous studies that have tested different community services for older people. We combined these findings and compared different types of service with one another. We rated our confidence in the evidence. What did we find? We found 129 studies with 74,946 people. We found 63 different kinds of service have been studied. The studies were carried out in diverse populations around the world. Individualised care planning, where medication is adjusted and there are regular follow-ups, may help people age independently. It probably increases the chance of staying at home slightly. It may also help with doing day-to-day activities very slightly. Exercise and dietary advice may also help people stay living at home. However, there was some evidence that some services may reduce independence. We do not know what effect most services have. What are the limitations of the evidence? We generally had little confidence in the evidence because studies were small, and information was missing. How current is the evidence? The evidence is up to date to August 2021. Scientific summary Background The number and proportion of older people are growing in the UK and worldwide. Maintaining independence is a goal of community health and care services for older people. The concept of frailty can be used to distinguish between people who remain in robust health in later life and those who are at greater risk of losing independence and needing care. Previous research has suggested that community-based complex interventions are generally effective for supporting independence for older people, but only broad service models have been explored. There is insufficient guidance about which services to implement and the appropriateness of different services for different levels of frailty. We aimed to provide a rigorous, contemporary synthesis of trial evidence to identify how interventions might best be configured to improve outcomes for older people, and inform the commissioning and delivery of evidence-based services. Objectives (list of research questions) Do community-based complex interventions to sustain independence in older people increase living at home, independence and health-related quality of life? Do community-based complex interventions to sustain independence in older people reduce homecare usage, depression, loneliness, falls, hospitalisation, care-home placement, costs and mortality? How should interventions be grouped for network meta-analysis (NMA)? What is the optimal configuration of community-based complex interventions to sustain independence in older people? Do intervention effects differ by a population’s frailty level (robust; pre-frailty; frailty)? Methods Systematic review with NMA of trials evaluating community-based complex interventions to sustain independence in older people (mean age 65 years and over), compared with usual care or another complex intervention meeting our criteria, with follow-up for at least 24 weeks. We followed Cochrane methods, Grading of Recommendations Assessment, Development and Evaluation (GRADE) and Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) NMA guidance. Information sources We searched the following databases and trial registers from inception between 9 and 11 August 2021: Cochrane Central Register of Controlled Trials (CENTRAL) Wiley (1992–); MEDLINE Ovid (1946–); Embase and Embase Classic Ovid (1947–); CINAHL EBSCOhost (1972–); APA PsycINFO Ovid (1806–); US National Institutes of Health Ongoing Trials Register, ClinicalTrials.gov (www.clinicaltrials.gov); World Health Organization, International Clinical Trials Registry Platform (https://trialsearch.who.int). We scanned the reference lists of included studies. Study selection Eligibility criteria Randomised controlled trials (RCTs) or cluster-RCTs. Participants were older people living at home (mean age 65 years or older). Participants living in residential/nursing homes were excluded. With an intervention that: was both initiated and mainly provided in the community included two or more interacting components (intervention practices, structural elements and contextual factors) was targeted at the individual person, with provision of appropriate specialist care focused on sustaining (maintaining or improving) the person’s independence. Usual care, ‘placebo’ or attention control or a different complex intervention which met our criteria were eligible comparators. Outcome data were measured at a minimum 24 weeks (approximately 6 months) time point. Study selection process Two researchers independently evaluated eligibility of records (title and abstract) and reports (full text). Disagreements were resolved by consensus. Data collection process Two researchers independently collected data. Main outcomes Living at home. Activities of daily living (ADL): personal ADL (PADL)/instrumental ADL (IADL). Hospitalisation. Care-home placement. Homecare services (non-healthcare professional) usage. Costs. Cost-effectiveness. Additional outcomes Health status/health-related quality of life. Depression. Loneliness. Falls. Mortality. Data were extracted (including treatment effect estimates) and categorised into three time frames: short term (around 6 months): 24 weeks to 9 months medium term (around 12 months): > 9 months to 18 months long term (around 24 months): > 18 months with the medium term as our main time frame. Intervention grouping We grouped all eligible interventions (including comparators) in preparation for NMA in a three-stage process of coding and summarising based on the Template for Intervention Description and Replication framework, categorisation and grouping. Assessment of frailty Two reviewers with extensive clinical academic frailty expertise (AC and JG) independently categorised study level frailty (robust, pre-frailty, frailty) based on validated measures where available or participant characteristics and study inclusion criteria using the phenotype model as a framework. Risk-of-bias assessment Two reviewers independently assessed risk of bias (RoB) in each result of interest from each included study, using the Revised Cochrane risk-of-bias tool for randomised trials (RoB 2). Data synthesis Meta-analysis was conducted for living at home, PADL, IADL and care-home placement for each of the three time frames separately, and for hospitalisation, health status and depression in the medium term only. Other outcomes were narratively synthesised. Meta-analysis We meta-analysed the extracted effect estimates using modules within Stata. Random-effects meta-analyses were conducted. Initially, for each outcome and time frame, we performed a separate meta-analysis for each type of intervention versus control, to provide summary effectiveness results based only on direct evidence. An NMA was then conducted (for each outcome and time frame separately) using a multivariate random-effects meta-analysis framework via the network module in Stata using restricted maximum likelihood estimation. We produced summary (pooled) effect estimates for each pair of treatments in the network, with 95% confidence intervals (CIs). Based on the results, the ranking of intervention groups was calculated using resampling methods. The consistency assumption (that direct and indirect evidence are consistent with each other) was examined for each treatment comparison where possible and across the whole network. The effect of study-level frailty on each intervention group effect was examined where data allowed. Sensitivity analyses were conducted excluding results at the highest RoB, and funnel plots examined for small-study effects. Confidence in cumulative evidence We used the GRADE framework, adapted for NMA, to rate the certainty of the results of our NMA. Summary of economic evidence We followed the brief economic commentary framework to summarise, compare and contrast the principal findings from the included studies. Results We screened 40,112 records and assessed 973 reports for eligibility. We included 129 studies consisting of 496 reports. The studies assigned 74,946 participants (three studies missing data) to 266 eligible intervention arms. They were predominantly conducted in developed countries and most participants were described as white. Nonetheless, the overall population included a broad range of demographic characteristics. Study populations included all frailty levels. We identified 19 separate components of included interventions which were evaluated in 63 combinations including the absence of all of these components, which we termed available care (ac), and homecare (a common control group in populations where all participants were receiving homecare). Homecare involved frequent visits at home by professionals who typically supported domestic and self-care tasks. Five components were primarily about a process of ascertainment or assessment and planning with subsequent action: multifactorial-action from care planning (a process of individualised multidomain assessment and management) with or without routine review (scheduled, regular follow-ups), medication-review, monitoring and routine risk-screening. The 14 other components and their short labels (bold) were ADL training, providing aids and adaptations, alternative medicine, care voucher provision, cognitive training, health education, physical exercise, formal homecare, engagement in meaningful-activities, nutritional support, psychological (mood) therapy (psychology), social skills training, technology for communication and engagement (telecoms), welfare rights advice. Multifactorial-action was further delineated based on the presence or absence of an embedded medication-review and specific self-management strategies. We judged most results to be at high RoB, primarily due to missing outcome data. This led to serious concerns with RoB for many of the GRADE ratings of evidence. Findings Most networks were small and sparse, with few included studies contributing to most networks. We found little evidence of inconsistency but there was usually low power to detect this. All outcomes except mortality needed to be analysed in two separate NMAs as the networks were disconnected: one with ac as the reference comparator (‘available-care network’) and one with homecare as the reference comparator (‘homecare network’). Estimates are reported here only in comparison with the reference comparator. Comparisons with ac can be thought of as the effect of adding the intervention for a population who are not all receiving any particular care; comparisons with homecare are similarly an alternative intervention for a population already in receipt of homecare without associated reablement or multifactorial-action from care planning. Most estimates were low certainty or very low certainty due to RoB, imprecision or their combination, and we do not describe very low-certainty evidence below. Living at home For living at home in the medium term there were 21 studies (n = 16,937) with 14 intervention groups in the available-care network. There was moderate-certainty evidence that multifactorial-action and review with medication-review probably results in a slight increase in the chance of living at home [odds ratio (OR) 1.22, 95% CI 0.93 to 1.59; moderate certainty]. There was low-certainty evidence that multifactorial-action with medication-review [OR 2.55 (large), 95% CI 0.61 to 10.60]; cognitive training, medication-review, nutrition and exercise [OR 1.93 (large), 95% CI 0.79 to 4.77]; and ADL, nutrition and exercise [OR 1.79 (large), 95% CI 0.67 to 4.76] may result in an increase in the chance of living at home, and that risk-screening; education, multifactorial-action and review with medication-review; and education, multifactorial-action and review with medication-review and self-management may each result in some reduction in chance of living at home. Other comparisons with ac were of very low certainty. In the short- and long-term time frames, results were at best low certainty. For multifactorial-action and review with medication-review; and ADL, nutrition and exercise, estimates were similarly of small increases in the long term but of little to no difference in the short term. There were similar results in other time frames for education, multifactorial-action and review with medication-review and self-management; and risk-screening, but contrasting evidence of reduction followed by an increase in living at home for education, multifactorial-action and review with medication-review. The homecare network for living at home was smaller (five studies, n = 1978 in the medium term). In the short- and medium-term time frames, there was low-certainty evidence that homecare, ADL, multifactorial-action and review with self-management may result in a moderate or large reduction in the chance of living at home compared with homecare alone. Instrumental activities of daily living For the medium-term instrumental activities of daily living (IADL) available-care network there were 16 studies (n = 5309) with 14 intervention groups. Multifactorial-action and review with medication-review was associated with very slightly increased independence in IADL versus ac [standardised mean difference (SMD) 0.11, 95% CI 0.00 to 0.21; moderate-certainty evidence]. Two intervention groups may result in some reduction in IADL: ADL, aids and exercise; and ADL, aids, education, exercise, multifactorial-action and review with medication-review and self-management. There were contrasting findings for multifactorial-action and review with medication-review in the long term, with moderate-certainty evidence of a very slight reduction in IADL (SMD −0.08, 95% CI −0.21 to 0.05). For the homecare network, there was one low certainty finding in the short-term time frame of little to no difference for homecare, ADL, multifactorial-action and review with self-management with all other estimates being very low certainty. Personal activities of daily living For personal activities of daily living (PADL), 20 trials (n = 8583 participants) with 16 intervention groups contributed to the medium-term available-care network. One comparison was judged low certainty. Exercise, multifactorial-action and review with medication-review and self-management may result in a very slight increase in PADL (SMD 0.16, 95% CI −0.51 to 0.82). The homecare network included four trials (n = 632 participants) in the medium term. As for ac, only one comparison with homecare was low certainty: homecare, multifactorial-action and review with medication-review may result in an increase in PADL [SMD 0.60 (moderate), 95% CI 0.32 to 0.88]. Other outcomes For the service outcome of hospitalisation, there were low-certainty estimates of some reductions for education, exercise, multifactorial-action and review with medication-review and self-management; and education, multifactorial-action and review with medication-review; and of an increase for exercise, multifactorial-action and review with medication-review and self-management. For care-home placement, all estimates were rated very low certainty in the medium term. There was some evidence of both increases and decreases in use of homecare services with little pattern (not meta-analysed). For our additional outcomes, there was little evidence of any effect on self-reported health status, only low certainty beneficial findings regarding depression, very little evidence regarding loneliness and more complex interventions were associated with less falling than more falling (12 studies vs. 4 studies). For mortality, there was a large network of 65 studies (n = 38,351) and 41 intervention groups. There was low-certainty evidence of reductions for two, and increases for five, intervention groups. The summary of economic evidence included 39 studies. Based on the conclusions of 22 studies that performed a full economic evaluation, five intervention groups appeared promising compared with a standard intervention or ac from an economic perspective: ADL (medium-term time horizon); homecare, multifactorial-action and review with medication-review and self-management (short-term time horizon); meaningful-activities and education (short- and medium-term time horizon); multifactorial-action and review with medication-review (short- but not medium- or long-term time horizon); and exercise and multifactorial-action with medication-review (long-term time horizon). Summary across outcomes We found evidence that multifactorial-action and review with medication-review probably improves some important outcomes slightly (living at home, IADL), but there was also contradictory evidence for IADL in the long term. For some other intervention groups there was low-certainty evidence that they may improve or worsen particular outcomes but for most intervention groups evidence was either absent or very uncertain. Conclusions Available evidence suggests the community-based complex interventions most likely to sustain independence in older people involve multifactorial-action from multidomain assessment and individualised care planning, routine review and the incorporation of medication-review. There was also some positive evidence for the combination of exercise and nutritional support and multiple other intervention combinations. Decision-makers should be aware that there is plausible evidence that some community-based complex interventions may worsen outcomes such as living at home and ADL independence and that all of these findings are tentative. We recommend the uncertainty in these findings be addressed by: realist synthesis to explore the mechanisms and broader contextual factors relating to individual benefit or harm future robust, large-scale trials which compare alternative interventions with multifactorial-action and review with medication-review future Individual Participant Data meta-analysis (IPDMA) focusing on interventions with multifactorial action to explore factors relating to individual benefit or harm greater reporting of the organisational aspects of intervention implementation in complex intervention research. Study registration This study is registered as PROSPERO CRD42019162195. Funding This award was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme (NIHR award ref: NIHR128862) and is published in full in Health Technology Assessment; Vol. 28, No. 48. See the NIHR Funding and Awards website for further award information.

Abstract Background Whether non-genetic prognostic factors significantly influence the variable prognosis of antipsychotic-induced weight gain (AIWG) has not yet been systematically explored. Methods Searches for both randomized and non-randomized studies were undertaken using four electronic databases, two trial registers, and via supplemental searching methods. Unadjusted and adjusted estimates were extracted. Meta-analyses were undertaken using a random-effects generic inverse model. Risk of bias and quality assessments were undertaken using Quality in Prognosis Studies (QUIPS) and Grading of Recommendations Assessment, Development and Evaluation (GRADE), respectively. Results Seventy-two prognostic factors were assessed across 27 studies involving 4426 participants. Only age, baseline body mass index (BMI), and sex were suitable for meta-analysis. Age (b=−0.044, 95%CI −0.157–0.069), sex (b=0.236, 95%CI −0.086–0.558), and baseline BMI (b=−0.013 95%CI −0.225–0.200) were associated with nonsignificant effects on AIWG prognosis. The highest quality GRADE rating was moderate in support of age, trend of early BMI increase, antipsychotic treatment response, unemployment, and antipsychotic plasma concentration. Trend of early BMI increase was identified as the most clinically significant prognostic factor influencing long-term AIWG prognosis. Conclusions The strong prognostic information provided by BMI trend change within 12 weeks of antipsychotic initiation should be included within AIWG management guidance to highlight those at highest risk of worse long-term prognosis. Antipsychotic switching and resource-intensive lifestyle interventions should be targeted toward this cohort. Our results challenge previous research that several clinical variables significantly influence AIWG prognosis. We provide the first mapping and statistical synthesis of studies examining non-genetic prognostic factors of AIWG and highlight practice, policy, and research implications.

Individual participant data (IPD) meta-analysis projects obtain, harmonise, and synthesise original data from multiple studies. Many IPD meta-analyses of randomised trials are initiated to identify treatment effect modifiers at the individual level, thus requiring statistical modelling of interactions between treatment effect and participant-level covariates. Using a two-stage approach, the interaction is estimated in each trial separately and combined in a meta-analysis. In practice, two complications often arise with continuous outcomes: examining non-linear relationships for continuous covariates and dealing with multiple time-points. We propose a two-stage multivariate IPD meta-analysis approach that summarises non-linear treatment-covariate interaction functions at multiple time-points for continuous outcomes. A set-up phase is required to identify a small set of time-points; relevant knot positions for a spline function, at identical locations in each trial; and a common reference group for each covariate. Crucially, the multivariate approach can include participants or trials with missing outcomes at some time-points. In the first stage, restricted cubic spline functions are fitted and their interaction with each discrete time-point is estimated in each trial separately. In the second stage, the parameter estimates defining these multiple interaction functions are jointly synthesised in a multivariate random-effects meta-analysis model accounting for within-trial and across-trial correlation. These meta-analysis estimates define the summary non-linear interactions at each time-point, which can be displayed graphically alongside confidence intervals. The approach is illustrated using an IPD meta-analysis examining effect modifiers for exercise interventions in osteoarthritis, which shows evidence of non-linear relationships and small gains in precision by analysing all time-points jointly.

Collecting data for an individual participant data meta-analysis (IPDMA) project can be time consuming and resource intensive and could still have insufficient power to answer the question of interest. Therefore, researchers should consider the power of their planned IPDMA before collecting IPD. Here we propose a method to estimate the power of a planned IPDMA project aiming to synthesise multiple cohort studies to investigate the (unadjusted or adjusted) effects of potential prognostic factors for a binary outcome. We consider both binary and continuous factors and provide a three-step approach to estimating the power in advance of collecting IPD, under an assumption of the true prognostic effect of each factor of interest. The first step uses routinely available (published) aggregate data for each study to approximate Fisher's information matrix and thereby estimate the anticipated variance of the unadjusted prognostic factor effect in each study. These variances are then used in step 2 to estimate the anticipated variance of the summary prognostic effect from the IPDMA. Finally, step 3 uses this variance to estimate the corresponding IPDMA power, based on a two-sided Wald test and the assumed true effect. Extensions are provided to adjust the power calculation for the presence of additional covariates correlated with the prognostic factor of interest (by using a variance inflation factor) and to allow for between-study heterogeneity in prognostic effects. An example is provided for illustration, and Stata code is supplied to enable researchers to implement the method.

Background: There are currently many treatment options for patients with subacromial shoulder conditions (SSCs). Clinical decision-making regarding the best treatment option is often difficult. This study aims to evaluate the comparative effectiveness of treatment options for relieving pain and improving function in patients with SSCs. Methods: Eight databases [including MEDLINE, Embase, CINAHL, AMED, PEDro, Cochrane Database of Systematic Reviews and World Health Organization (WHO) International Clinical Trials Registry] were searched from inception until April 2020. Randomised clinical/controlled trials of adult patients investigating the effects of nonsurgical (e.g. corticosteroid injections, therapeutic exercise, shockwave therapy) and surgical treatment for SSCs, compared with each other, placebo, usual care or no treatment, were retrieved. Pairs of reviewers screened studies independently, quality appraised eligible studies using the Cochrane risk of bias tool, extracted and checked data for accuracy. Primary outcomes were pain and disability in the short term (⩽3 months) and long term (⩾6 months). Direct and indirect evidence of treatment effectiveness was synthesised using random-effects network meta-analysis. Results: The review identified 177 eligible trials. Summary estimates (based on 99 trials providing suitable data, 6764 patients, 20 treatment options) showed small to moderate effects for several treatments, but no significant differences on pain or function between many active treatment comparisons. The primary analysis indicated that exercise and laser therapy may provide comparative benefit in terms of both pain and function at different follow-up time-points, with larger effects found for laser in the short term at 2–6 weeks, although direct evidence was provided by one trial only, and for exercise in the longer term [standardised mean difference (SMD) 0.39, 95% confidence interval (CI) 0.18, 0.59 at 3–6 months] compared with control. Sensitivity analyses excluding studies at increased risk of bias confirmed only the comparative effects of exercise as being robust for both pain and function up until 3-month follow-up. Conclusion: Current evidence shows small to moderate effect sizes for most treatment options for SSCs. Six treatments had a high probability of being most effective, in the short term, for pain and function [acupuncture, manual therapy, exercise, exercise plus manual therapy, laser therapy and Microcurrent (MENS) (TENS)], but with low certainty for most treatment options. After accounting for risk of bias, there is evidence of moderate certainty for the comparative effects of exercise on function in patients with SSCs. Future large, high-quality pragmatic randomised trials or meta-analyses are needed to better understand whether specific subgroups of patients respond better to some treatments than others.

Introduction Maintaining independence is a primary goal of community health and care services for older people, but there is currently insufficient guidance about which services to implement. Therefore, we aim to synthesise evidence on the effectiveness of community-based complex interventions to sustain independence for older people, including the effect of frailty, and group interventions to identify the best configurations.Methods and analysis Systematic review and network meta-analysis (NMA). We will include randomised controlled trials (RCTs) and cluster RCTs of community-based complex interventions to sustain independence for older people living at home (mean age ≥65 years), compared with usual care or another complex intervention. We will search MEDLINE (1946 to September 2020), Embase (1947 to September 2020), CINAHL (1981 to September 2020), PsycINFO (1806 to September 2020), CENTRAL and clinical trial registries from inception to September 2020, without date/language restrictions, and scan included papers’ reference lists. Main outcomes were: living at home, activities of daily living (basic/instrumental), home-care services usage, hospitalisation, care home admission, costs and cost effectiveness. Additional outcomes were: health status, depression, loneliness, falls and mortality. Interventions will be coded, summarised and grouped. An NMA using a multivariate random-effects model for each outcome separately will determine the relative effects of different complex interventions. For each outcome, we will produce summary effect estimates for each pair of treatments in the network, with 95% CI, ranking plots and measures, and the borrowing of strength statistic. Inconsistency will be examined using a ‘design-by-treatment interaction’ model. We will assess risk of bias (Cochrane tool V.2) and certainty of evidence using the Grading of Recommendations Assessment, Development and Evaluation for NMA approach.Ethics and dissemination This research will use aggregated, anonymised, published data. Findings will be reported according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidance. They will be disseminated to policy-makers, commissioners and providers, and via conferences and scientific journals.PROSPERO registration number CRD42019162195.

Abstract 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.g. from publications) and prior knowledge (e.g. number of studies promising IPD) to specify model parameter values (e.g. control group mean, intervention effect, treatment-covariate interaction); (iii) simulate an IPD meta-analysis dataset of a particular size from the model, and apply a two-stage IPD meta-analysis to obtain the summary estimate of interest (e.g. interaction effect) and its associated p-value; (iv) repeat the previous step (e.g. thousands of times), then estimate the power to detect a genuine effect by the proportion of summary estimates with a significant p-value. Results In a planned IPD meta-analysis of lifestyle interventions to reduce weight gain in pregnancy, 14 trials (1183 patients) promised their IPD to examine a treatment-BMI interaction (i.e. whether baseline BMI modifies intervention effect on weight gain). Using our simulation-based approach, a two-stage IPD meta-analysis has

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. Descriptive statistics were used to describe sex-based differences in baseline characteristics and comorbidity burden of patients. Multivariable logistic regressions were used to investigate the association between these differences and in-hospital mortality, complications, length of stay and total hospital charges. Among 6,601,526 patients, 66% were men and 33% were women. Women were more likely to be admitted with diagnosis of NSTEMI (non-ST elevation acute myocardial infarction), were on average 5 years older (median age 68 compared to 63) and had higher burden of comorbidity defined by Charlson score ≥3. Women also had higher in-hospital crude mortality (2.0% vs 1.4%) and any complications compared to men (11.1% vs 7.0%). These trends persisted in our adjusted analyses where women had a significant increase in the odds of in-hospital mortality men (OR 1.20 (95% CI 1.16,1.23) and major bleeding (OR 1.81 (95% CI 1.77,1.86). CONCLUSION:In this national unselected contemporary PCI cohort, there are significant sex-based differences in presentation, baseline characteristics and comorbidity burden. These differences do not fully account for the higher in-hospital mortality and procedural complications observed in women.

Background: Unprovoked first venous thromboembolism (VTE) is defined as VTE in the absence of a temporary provoking factor such as surgery, immobility and other temporary factors. Recurrent VTE in unprovoked patients is highly prevalent, but easily preventable with oral anticoagulant (OAC) therapy. The unprovoked population is highly heterogeneous in terms of risk of recurrent VTE. Objectives: The first aim of the project is to review existing prognostic models which stratify individuals by their recurrence risk, therefore potentially allowing tailored treatment strategies. The second aim is to enhance the existing research in this field, by developing and externally validating a new prognostic model for individual risk prediction, using a pooled database containing individual patient data (IPD) from several studies. The final aim is to assess the economic cost-effectiveness of the proposed prognostic model if it is used as a decision rule for resuming OAC therapy, compared with current standard treatment strategies. Methods: Standard systematic review methodology was used to identify relevant prognostic model development, validation and cost-effectiveness studies. Bibliographic databases (including MEDLINE, EMBASE and The Cochrane Library) were searched using terms relating to the clinical area and prognosis. Reviewing was undertaken by two reviewers independently using pre-defined criteria. Included full-text articles were data extracted and quality assessed. Critical appraisal of included full texts was undertaken and comparisons made of model performance. A prognostic model was developed using IPD from the pooled database of seven trials. A novel internal–external cross-validation (IECV) approach was used to develop and validate a prognostic model, with external validation undertaken in each of the trials iteratively. Given good performance in the IECV approach, a final model was developed using all trials data. A Markov patient-level simulation was used to consider the economic cost-effectiveness of using a decision rule (based on the prognostic model) to decide on resumption of OAC therapy (or not). Results: Three full-text articles were identified by the systematic review. Critical appraisal identified methodological and applicability issues; in particular, all three existing models did not have external validation. To address this, new prognostic models were sought with external validation. Two potential models were considered: one for use at cessation of therapy (pre D-dimer), and one for use after cessation of therapy (post D-dimer). Model performance measured in the external validation trials showed strong calibration performance for both models. The post D-dimer model performed substantially better in terms of discrimination (c = 0.69), better separating high- and low-risk patients. The economic evaluation identified that a decision rule based on the final post D-dimer model may be cost-effective for patients with predicted risk of recurrence of over 8% annually; this suggests continued therapy for patients with predicted risks ≥ 8% and cessation of therapy otherwise. Conclusions: The post D-dimer model performed strongly and could be useful to predict individuals’ risk of recurrence at any time up to 2–3 years, thereby aiding patient counselling and treatment decisions. A decision rule using this model may be cost-effective for informing clinical judgement and patient opinion in treatment decisions. Further research may investigate new predictors to enhance model performance and aim to further externally validate to confirm performance in new, non-trial populations. Finally, it is essential that further research is conducted to develop a model predicting bleeding risk on therapy, to manage the balance between the risks of recurrence and bleeding. Study registration: This study is registered as PROSPERO CRD42013003494. Funding: The National Institute for Health Research Health Technology Assessment programme.

Background: The use of aspirin is well established for secondary prevention of cardiovascular disease. However, a proportion of patients suffer repeat cardiovascular events despite being prescribed aspirin treatment. It is uncertain whether or not this is due to an inherent inability of aspirin to sufficiently modify platelet activity. This report aims to investigate whether or not insufficient platelet function inhibition by aspirin (‘aspirin resistance‘), as defined using platelet function tests (PFTs), is linked to the occurrence of adverse clinical outcomes, and further, whether or not patients at risk of future adverse clinical events can be identified through PFTs. Objectives: To review systematically the clinical effectiveness and cost-effectiveness evidence regarding the association between PFT designation of ‘aspirin resistance’ and the risk of adverse clinical outcome(s) in patients prescribed aspirin therapy. To undertake exploratory model-based cost-effectiveness analysis on the use of PFTs. Data sources: Bibliographic databases (e.g. MEDLINE from inception and EMBASE from 1980), conference proceedings and ongoing trial registries up to April 2012. Methods: Standard systematic review methods were used for identifying clinical and cost studies. A risk-of-bias assessment tool was adapted from checklists for prognostic and diagnostic studies. (Un)adjusted odds and hazard ratios for the association between ‘aspirin resistance’, for different PFTs, and clinical outcomes are presented; however, heterogeneity between studies precluded pooling of results. A speculative economic model of a PFT and change of therapy strategy was developed. Results: One hundred and eight relevant studies using a variety of PFTs, 58 in patients on aspirin monotherapy, were analysed in detail. Results indicated that some PFTs may have some prognostic utility, i.e. a trend for more clinical events to be associated with groups classified as ‘aspirin resistant’. Methodological and clinical heterogeneity prevented a quantitative summary of prognostic effect. Study-level effect sizes were generally small and absolute outcome risk was not substantially different between ‘aspirin resistant’ and ‘aspirin sensitive’ designations.: No studies on the cost-effectiveness of PFTs for ‘aspirin resistance’ were identified. Based on assumptions of PFTs being able to accurately identify patients at high risk of clinical events and such patients benefiting from treatment modification, the economic model found that a test–treat strategy was likely to be cost-effective. However, neither assumption is currently evidence based. Limitations: Poor or incomplete reporting of studies suggests a potentially large volume of inaccessible data. Analyses were confined to studies on patients prescribed aspirin as sole antiplatelet therapy at the time of PFT. Clinical and methodological heterogeneity across studies precluded meta-analysis. Given the lack of robust data the economic modelling was speculative. Conclusions: Although evidence indicates that some PFTs may have some prognostic value, methodological and clinical heterogeneity between studies and different approaches to analyses create confusion and inconsistency in prognostic results, and prevented a quantitative summary of their prognostic effect. Protocol-driven and adequately powered primary studies are needed, using standardised methods of measurements to evaluate the prognostic ability of each test in the same population(s), and ideally presenting individual patient data. For any PFT to inform individual risk prediction, it will likely need to be considered in combination with other prognostic factors, within a prognostic model. Study registration: This study is registered as PROSPERO 2012:CRD42012002151. Funding: The National Institute for Health Research Health Technology Assessment programme.