Sex differences in cancer outcomes across the range of eGFR.

BACKGROUND AND HYPOTHESIS: People with chronic kidney disease (CKD) have increased incidence and mortality from most cancer types. We hypothesised that odds of presenting with advanced cancer may vary according to differences in eGFR, that this could contribute to increased all-cause mortality and that sex differences may exist. METHODS: Data were from Secure Anonymised Information Linkage Databank, including people with de-novo cancer diagnosis (2011-2017) and two kidney function tests within two years prior to diagnosis to determine baseline eGFR (mL/min/1.73m2). Logistic regression models determined odds of presenting with advanced cancer by baseline eGFR. Cox proportional hazards models tested associations between baseline eGFRcr and all-cause mortality. RESULTS: eGFR < 30 was associated with higher odds of presenting with advanced cancer of prostate, breast and female genital organs, but not other cancer sites. Compared to eGFR > 75-90, eGFR < 30 was associated with greater hazards of all-cause mortality in both sexes, but the association was stronger in females (female: HR 1.71, 95%CI 1.56-1.88; male versus female comparison HR 0.88, 95%CI 0.78-0.90). CONCLUSIONS: Lower or higher eGFR was not associated with substantially higher odds of presenting with advanced cancer across most cancer sites, but was associated with reduced survival. A stronger assocation with all-cause mortality in females compared to males with eGFR < 30 is concerning and warrants further scrutiny.

An observational analysis of frailty in combination with loneliness or social isolation and their association with socioeconomic deprivation, hospitalisation and mortality among UK Biobank participants.

Frailty, social isolation, and loneliness have individually been associated with adverse health outcomes. This study examines how frailty in combination with loneliness or social isolation is associated with socioeconomic deprivation and with all-cause mortality and hospitalisation rate in a middle-aged and older population. Baseline data from 461,047 UK Biobank participants (aged 37-73) were used to assess frailty (frailty phenotype), social isolation, and loneliness. Weibull models assessed the association between frailty in combination with loneliness or social isolation and all-cause mortality adjusted for age/sex/smoking/alcohol/socioeconomic-status and number of long-term conditions. Negative binomial regression models assessed hospitalisation rate. Frailty prevalence was 3.38%, loneliness 4.75% and social isolation 9.04%. Frailty was present across all ages and increased with age. Loneliness and social isolation were more common in younger participants compared to older. Co-occurrence of frailty and loneliness or social isolation was most common in participants with high socioeconomic deprivation. Frailty was associated with increased mortality and hospitalisation regardless of social isolation/loneliness. Hazard ratios for mortality were 2.47 (2.27-2.69) with social isolation and 2.17 (2.05-2.29) without social isolation, 2.14 (1.92-2.38) with loneliness and 2.16 (2.05-2.27) without loneliness. Loneliness and social isolation were associated with mortality and hospitalisation in robust participants, but this was attenuated in the context of frailty. Frailty and loneliness/social isolation affect individuals across a wide age spectrum and disproportionately co-occur in areas of high deprivation. All were associated with adverse outcomes, but the association between loneliness and social isolation and adverse outcomes was attenuated in the context of frailty. Future interventions should target people living with frailty or loneliness/social isolation, regardless of age.

Personalised lung cancer risk stratification and lung cancer screening: do general practice electronic medical records have a role?

BACKGROUND: In the United Kingdom (UK), cancer screening invitations are based on general practice (GP) registrations. We hypothesize that GP electronic medical records (EMR) can be utilised to calculate a lung cancer risk score with good accuracy/clinical utility. METHODS: The development cohort was Secure Anonymised Information Linkage-SAIL (2.3 million GP EMR) and the validation cohort was UK Biobank-UKB (N = 211,597 with GP-EMR availability). Fast backward method was applied for variable selection and area under the curve (AUC) evaluated discrimination. RESULTS: Age 55-75 were included (SAIL: N = 574,196; UKB: N = 137,918). Six-year lung cancer incidence was 1.1% (6430) in SAIL and 0.48% (656) in UKB. The final model included 17/56 variables in SAIL for the EMR-derived score: age, sex, socioeconomic status, smoking status, family history, body mass index (BMI), BMI:smoking interaction, alcohol misuse, chronic obstructive pulmonary disease, coronary heart disease, dementia, hypertension, painful condition, stroke, peripheral vascular disease and history of previous cancer and previous pneumonia. The GP-EMR-derived score had AUC of 80.4% in SAIL and 74.4% in UKB and outperformed ever-smoked criteria (currently the first step in UK lung cancer screening pilots). DISCUSSION: A GP-EMR-derived score may have a role in UK lung cancer screening by accurately targeting high-risk individuals without requiring patient contact.

The presence and impact of multimorbidity clusters on adverse outcomes across the spectrum of kidney function.

BACKGROUND: Multimorbidity (the presence of two or more chronic conditions) is common amongst people with chronic kidney disease, but it is unclear which conditions cluster together and if this changes as kidney function declines. We explored which clusters of conditions are associated with different estimated glomerular filtration rates (eGFRs) and studied associations between these clusters and adverse outcomes. METHODS: Two population-based cohort studies were used: the Stockholm Creatinine Measurements project (SCREAM, Sweden, 2006-2018) and the Secure Anonymised Information Linkage Databank (SAIL, Wales, 2006-2021). We studied participants in SCREAM (404,681 adults) and SAIL (533,362) whose eGFR declined lower than thresholds (90, 75, 60, 45, 30 and 15 mL/min/1.73m2). Clusters based on 27 chronic conditions were identified. We described the most common chronic condition(s) in each cluster and studied their association with adverse outcomes using Cox proportional hazards models (all-cause mortality (ACM) and major adverse cardiovascular events (MACE)). RESULTS: Chronic conditions became more common and clustered differently across lower eGFR categories. At eGFR 90, 75, and 60 mL/min/1.73m2, most participants were in large clusters with no prominent conditions. At eGFR 15 and 30 mL/min/1.73m2, clusters involving cardiovascular conditions were larger and were at the highest risk of adverse outcomes. At eGFR 30 mL/min/1.73m2, in the heart failure, peripheral vascular disease and diabetes cluster in SCREAM, ACM hazard ratio (HR) is 2.66 (95% confidence interval (CI) 2.31-3.07) and MACE HR is 4.18 (CI 3.65-4.78); in the heart failure and atrial fibrillation cluster in SAIL, ACM HR is 2.23 (CI 2.04 to 2.44) and MACE HR is 3.43 (CI 3.22-3.64). Chronic pain and depression were common and associated with adverse outcomes when combined with physical conditions. At eGFR 30 mL/min/1.73m2, in the chronic pain, heart failure and myocardial infarction cluster in SCREAM, ACM HR is 2.00 (CI 1.62-2.46) and MACE HR is 4.09 (CI 3.39-4.93); in the depression, chronic pain and stroke cluster in SAIL, ACM HR is 1.38 (CI 1.18-1.61) and MACE HR is 1.58 (CI 1.42-1.76). CONCLUSIONS: Patterns of multimorbidity and corresponding risk of adverse outcomes varied with declining eGFR. While diabetes and cardiovascular disease are known high-risk conditions, chronic pain and depression emerged as important conditions and associated with adverse outcomes when combined with physical conditions.

Frailty in rheumatoidrmdopen-2021-002111 arthritis and its relationship with disease activity, hospitalisation and mortality: a longitudinal analysis of the Scottish Early Rheumatoid Arthritis cohort and UK Biobank.

OBJECTIVE: To assess the prevalence of frailty in rheumatoid arthritis (RA) and its association with baseline and longitudinal disease activity, all-cause mortality and hospitalisation. PARTICIPANTS: People with RA identified from the Scottish Early Rheumatoid Arthritis (SERA) inception cohort (newly diagnosed, mean age 58.2 years) and UK Biobank (established disease identified using diagnostic codes, mean age 59 years). Frailty was quantified using the frailty index (both datasets) and frailty phenotype (UK Biobank only). Disease activity was assessed using Disease Activity Score in 28 joints (DAS28) in SERA. Associations between baseline frailty and all-cause mortality and hospitalisation was estimated after adjusting for age, sex, socioeconomic status, smoking and alcohol, plus DAS28 in SERA. RESULTS: Based on the frailty index, frailty was common in SERA (12% moderate, 0.2% severe) and UK Biobank (20% moderate, 3% severe). In UK Biobank, 23% were frail using frailty phenotype. Frailty index was associated with DAS28 in SERA, as well as age and female sex in both cohorts. In SERA, as DAS28 lessened over time with treatment, mean frailty index also decreased. The frailty index was associated with all-cause mortality (HR moderate/severe frailty vs robust 4.14 (95% CI 1.49 to 11.51) SERA, 1.68 (95% CI 1.26 to 2.13) UK Biobank) and unscheduled hospitalisation (incidence rate ratio 2.27 (95% CI 1.45 to 3.57) SERA 2.74 (95% CI 2.29 to 3.29) UK Biobank). In UK Biobank, frailty phenotype also associated with mortality and hospitalisation. CONCLUSION: Frailty is common in early and established RA and associated with hospitalisation and mortality. Frailty in RA is dynamic and, for some, may be ameliorated through controlling disease activity in early disease.

Multimorbidity and frailty in middle-aged adults with type 2 diabetes mellitus.

Context: Frailty and multimorbidity are common in type 2 diabetes, including in middle-aged people (<65 years). Clinical guidelines recommend adjustment of treatment targets in people with frailty or multimorbidity. However, guidelines do not specify how frailty/multimorbidity should be identified. It is not clear if recommendations should be applied to people with frailty/multimorbidity at younger ages. Objective: Assess prevalence and clinical implications of frailty/multimorbidity in middle- to older-aged people with type 2 diabetes using four different measures. Design: Cohort, baseline 2006-2010, median 8 years follow-up. Setting: Community Participants: UK Biobank participants (n=20,566) with type 2 diabetes aged 40-72 years. Exposures: Four measures of frailty (frailty phenotype and frailty index) and multimorbidity (Charlson Comorbidity index and numerical count of long-term conditions (LTCs)). Outcomes: Mortality (all-cause, cardiovascular- and cancer-related mortality), Major Adverse Cardiovascular Event (MACE), hospitalization with hypoglycaemia, fall or fracture. Results: Frailty and multimorbidity are prevalent in in people with type 2 diabetes from age 40-72. Individuals identified differed depending on which measure was used: 42% frail of multimorbid by at least one scale; 2.2% were identified by all four scales. Each measure was associated with increased risk of mortality (all-cause, cardiovascular, and cancer-related), MACE, hypoglycaemia and falls. The absolute risk of 5-year mortality was higher in older versus younger participants with a given level of frailty (e.g. 1.9%, 4.4%, and 9.9% in men aged, 45, 55, and 65, respectively, using frailty phenotype) or multimorbidity (e.g. 1.3%, 3.7%, and 7.8% in med with 4 long-term conditions aged 45, 55, and 65, respectively). No measure was associated with baseline HbA1c. For the frailty index, Charlson Comorbidity index, and LTC count, the relationship between HbA1c and mortality was consistent across all levels of frailty/multimorbidity. For the frailty phenotype, the relationship between HbA1c and mortality was steeper and more linear in frail compared with pre-frail or robust participants. Conclusion: Assessment of frailty/multimorbidity should be embedded within routine management of middle-aged and older people with type 2 diabetes. Method of identification as well as features such as age impact baseline risk and should influence clinical decisions (eg. glycaemic control).

Association between patterns of alcohol consumption (beverage type, frequency and consumption with food) and risk of adverse health outcomes: a prospective cohort study.

BACKGROUND: Alcohol consumption is a leading contributor to death and disability worldwide, but previous research has not examined the effects of different patterns of alcohol consumption. The study objective was to understand the relationship between different alcohol consumption patterns and adverse health outcomes risk, adjusting for average amount consumed among regular drinkers. METHODS: This was a prospective cohort study of UK Biobank (UKB) participants. Abstainers, infrequent alcohol consumers or those with previous cancer, myocardial infarction (MI), stroke or liver cirrhosis were excluded. We used beverage type, consumption with food and consumption frequency as exposures and adjusted for potential confounding. All-cause mortality, major cardiovascular events-MACE (MI/stroke/cardiovascular death), accidents/injuries, liver cirrhosis, all-cause and alcohol-related cancer incidence over 9-year median follow-up period were outcomes of interest. RESULTS: The final sample size for analysis was N = 309,123 (61.5% of UKB sample). Spirit drinking was associated with higher adjusted mortality (hazard ratio (HR) 1.25; 95% confidence intervals (CI) 1.14-1.38), MACE (HR 1.31; 95% CI 1.15-1.50), cirrhosis (HR 1.48; 95% CI 1.08-2.03) and accident/injuries (HR 1.10; 95% CI 1.03-1.19) risk compared to red wine drinking, after adjusting for the average weekly alcohol consumption amounts. Beer/cider drinkers were also at a higher risk of mortality (HR 1.18; 95% CI 1.10-1.27), MACE (HR 1.16; 95% CI 1.05-1.27), cirrhosis (HR 1.36; 95% CI 1.06-1.74) and accidents/injuries (HR 1.11; 95% CI 1.06-1.17). Alcohol consumption without food was associated with higher adjusted mortality (HR 1.10; 95% CI 1.02-1.17) risk, compared to consumption with food. Alcohol consumption over 1-2 times/week had higher adjusted mortality (HR 1.09; 95% CI 1.03-1.16) and MACE (HR 1.14; 95% CI 1.06-1.23) risk, compared to 3-4 times/week, adjusting for the amount of alcohol consumed. CONCLUSION: Red wine drinking, consumption with food and spreading alcohol intake over 3-4 days were associated with lower risk of mortality and vascular events among regular alcohol drinkers, after adjusting for the effects of average amount consumed. Selection bias and residual confounding are important possible limitations. These findings, if replicated and validated, have the potential to influence policy and practice advice on less harmful patterns of alcohol consumption.

Assessing Risks of Polypharmacy Involving Medications With Anticholinergic Properties.

PURPOSE: Anticholinergic burden (ACB), the cumulative effect of anticholinergic medications, is associated with adverse outcomes in older people but is less studied in middle-aged populations. Numerous scales exist to quantify ACB. The aims of this study were to quantify ACB in a large cohort using the 10 most common anticholinergic scales, to assess the association of each scale with adverse outcomes, and to assess overlap in populations identified by each scale. METHODS: We performed a longitudinal analysis of the UK Biobank community cohort (502,538 participants, baseline age: 37-73 years, median years of follow-up: 6.2). The ACB was calculated at baseline using 10 scales. Baseline data were linked to national mortality register records and hospital episode statistics. The primary outcome was a composite of all-cause mortality and major adverse cardiovascular event (MACE). Secondary outcomes were all-cause mortality, MACE, hospital admission for fall/fracture, and hospital admission with dementia/delirium. Cox proportional hazards models (hazard ratio [HR], 95% CI) quantified associations between ACB scales and outcomes adjusted for age, sex, socioeconomic status, body mass index, smoking status, alcohol use, physical activity, and morbidity count. RESULTS: Anticholinergic medication use varied from 8% to 17.6% depending on the scale used. For the primary outcome, ACB was significantly associated with all-cause mortality/MACE for each scale. The Anticholinergic Drug Scale was most strongly associated with mortality/MACE (HR = 1.12; 95% CI, 1.11-1.14 per 1-point increase in score). The ACB was significantly associated with all secondary outcomes. The Anticholinergic Effect on Cognition scale was most strongly associated with dementia/delirium (HR = 1.45; 95% CI, 1.3-1.61 per 1-point increase). CONCLUSIONS: The ACB was associated with adverse outcomes in a middle- to older-aged population. Populations identified and effect size differed between scales. Scale choice influenced the population identified as potentially requiring reduction in ACB in clinical practice or intervention trials.

Relationship between multimorbidity, demographic factors and mortality: findings from the UK Biobank cohort.

BACKGROUND: Multimorbidity is associated with higher mortality, but the relationship with cancer and cardiovascular mortality is unclear. The influence of demographics and type of condition on the relationship of multimorbidity with mortality remains unknown. We examine the relationship between multimorbidity (number/type) and cause of mortality and the impact of demographic factors on this relationship. METHODS: Data source: the UK Biobank; 500,769 participants; 37-73 years; 53.7% female. Exposure variables: number and type of long-term conditions (LTCs) (N = 43) at baseline, modelled separately. Cox regression models were used to study the impact of LTCs on all-cause/vascular/cancer mortality during median 7-year follow-up. All-cause mortality regression models were stratified by age/sex/socioeconomic status. RESULTS: All-cause mortality is 2.9% (14,348 participants). Of all deaths, 8350 (58.2%) were cancer deaths and 2985 (20.8%) vascular deaths. Dose-response relationship is observed between the increasing number of LTCs and all-cause/cancer/vascular mortality. A strong association is observed between cardiometabolic multimorbidity and all three clinical outcomes; non-cardiometabolic multimorbidity (excluding cancer) is associated with all-cause/vascular mortality. All-cause mortality risk for those with ≥ 4 LTCs was nearly 3 times higher than those with no LTCs (HR 2.79, CI 2.61-2.98); for ≥ 4 cardiometabolic conditions, it was > 3 times higher (HR 3.20, CI 2.56-4.00); and for ≥ 4 non-cardiometabolic conditions (excluding cancer), it was 50% more (HR 1.50, CI 1.36-1.67). For those with ≥ 4 LTCs, morbidity combinations that included cardiometabolic conditions, chronic kidney disease, cancer, epilepsy, chronic obstructive pulmonary disease, depression, osteoporosis and connective tissue disorders had the greatest impact on all-cause mortality. In the stratified model by age/sex, absolute all-cause mortality was higher among the 60-73 age group with an increasing number of LTCs; however, the relative effect size of the increasing number of LTCs on higher mortality risk was larger among those 37-49 years, especially men. While socioeconomic status was a significant predictor of all-cause mortality, mortality risk with increasing number of LTCs remained constant across different socioeconomic gradients. CONCLUSIONS: Multimorbidity is associated with higher all-cause/cancer/vascular mortality. Type, as opposed to number, of LTCs may have an important role in understanding the relationship between multimorbidity and mortality. Multimorbidity had a greater relative impact on all-cause mortality in middle-aged as opposed to older populations, particularly males, which deserves exploration.

Frailty and pre-frailty in middle-aged and older adults and its association with multimorbidity and mortality: a prospective analysis of 493 737 UK Biobank participants.

BACKGROUND: Frailty is associated with older age and multimorbidity (two or more long-term conditions); however, little is known about its prevalence or effects on mortality in younger populations. This paper aims to examine the association between frailty, multimorbidity, specific long-term conditions, and mortality in a middle-aged and older aged population. METHODS: Data were sourced from the UK Biobank. Frailty phenotype was based on five criteria (weight loss, exhaustion, grip strength, low physical activity, slow walking pace). Participants were deemed frail if they met at least three criteria, pre-frail if they fulfilled one or two criteria, and not frail if no criteria were met. Sociodemographic characteristics and long-term conditions were examined. The outcome was all-cause mortality, which was measured at a median of 7 years follow-up. Multinomial logistic regression compared sociodemographic characteristics and long-term conditions of frail or pre-frail participants with non-frail participants. Cox proportional hazards models examined associations between frailty or pre-frailty and mortality. Results were stratified by age group (37-45, 45-55, 55-65, 65-73 years) and sex, and were adjusted for multimorbidity count, socioeconomic status, body-mass index, smoking status, and alcohol use. FINDINGS: 493 737 participants aged 37-73 years were included in the study, of whom 16 538 (3%) were considered frail, 185 360 (38%) pre-frail, and 291 839 (59%) not frail. Frailty was significantly associated with multimorbidity (prevalence 18% [4435/25 338] in those with four or more long-term conditions; odds ratio [OR] 27·1, 95% CI 25·3-29·1) socioeconomic deprivation, smoking, obesity, and infrequent alcohol consumption. The top five long-term conditions associated with frailty were multiple sclerosis (OR 15·3; 99·75% CI 12·8-18·2); chronic fatigue syndrome (12·9; 11·1-15·0); chronic obstructive pulmonary disease (5·6; 5·2-6·1); connective tissue disease (5·4; 5·0-5·8); and diabetes (5·0; 4·7-5·2). Pre-frailty and frailty were significantly associated with mortality for all age strata in men and women (except in women aged 37-45 years) after adjustment for confounders. INTERPRETATION: Efforts to identify, manage, and prevent frailty should include middle-aged individuals with multimorbidity, in whom frailty is significantly associated with mortality, even after adjustment for number of long-term conditions, sociodemographics, and lifestyle. Research, clinical guidelines, and health-care services must shift focus from single conditions to the requirements of increasingly complex patient populations. FUNDING: CSO Catalyst Grant and National Health Service Research for Scotland Career Research Fellowship.

Examining patterns of multimorbidity, polypharmacy and risk of adverse drug reactions in chronic obstructive pulmonary disease: a cross-sectional UK Biobank study.

OBJECTIVE: This study aims: (1) to describe the pattern and extent of multimorbidity and polypharmacy in UK Biobank participants with chronic obstructive pulmonary disease (COPD) and (2) to identify which comorbidities are associated with increased risk of adverse drug reactions (ADRs) resulting from polypharmacy. DESIGN: Cross-sectional. SETTING: Community cohort. PARTICIPANTS: UK Biobank participants comparing self-reported COPD (n=8317) with no COPD (n=494 323). OUTCOMES: Multimorbidity (≥4 conditions) and polypharmacy (≥5 medications) in participants with COPD versus those without. Risk of ADRs (taking ≥3 medications associated with falls, constipation, urinary retention, central nervous system (CNS) depression, bleeding or renal injury) in relation to the presence of COPD and individual comorbidities. RESULTS: Multimorbidity was more common in participants with COPD than those without (17% vs 4%). Polypharmacy was highly prevalent (52% with COPD taking ≥5 medications vs 18% in those without COPD). Adjusting for age, sex and socioeconomic status, those with COPD were significantly more likely than those without to be prescribed ≥3 medications contributing to falls (OR 2.27, 95% CI 2.13 to 2.42), constipation (OR 3.42, 95% CI 3.10 to 3.77), urinary retention (OR 3.38, 95% CI 2.94 to 3.87), CNS depression (OR 3.75, 95% CI 3.31 to 4.25), bleeding (OR 4.61, 95% CI 3.35 to 6.19) and renal injury (OR 2.22, 95% CI 1.86 to 2.62). Concomitant cardiovascular disease was associated with the greatest risk of taking ≥3 medications associated with falls/renal injury. Concomitant mental health conditions were most strongly associated with medications linked with CNS depression/urinary retention/bleeding. CONCLUSIONS: Multimorbidity is common in COPD and associated with high levels of polypharmacy. Co-prescription of drugs with various ADRs is common. Future research should examine the effects on healthcare outcomes of co-prescribing multiple drugs with similar potential ADRs. Clinical guidelines should emphasise assessment of multimorbidity and ADR risk.

Multimorbidity and co-morbidity in atrial fibrillation and effects on survival: findings from UK Biobank cohort.

Aims: To examine the number and type of co-morbid long-term health conditions (LTCs) and their associations with all-cause mortality in an atrial fibrillation (AF) population. Methods and results: Community cohort participants (UK Biobank n = 502 637) aged 37-73 years were recruited between 2006 and 2010. Self-reported LTCs (n = 42) identified in people with AF at baseline. All-cause mortality was available for a median follow-up of 7 years (interquartile range 76-93 months). Hazard ratios (HRs) examined associations between number and type of co-morbid LTC and all-cause mortality, adjusting for age, sex, socio-economic status, smoking, and anticoagulation status. Three thousand six hundred fifty-one participants (0.7% of the study population) reported AF; mean age was 61.9 years. The all-cause mortality rate was 6.7% (248 participants) at 7 years. Atrial fibrillation participants with ≥4 co-morbidities had a six-fold higher risk of mortality compared to participants without any LTC. Co-morbid heart failure was associated with higher risk of mortality [HR 2.96, 95% confidence interval (CI) 1.83-4.80], whereas the presence of co-morbid stroke did not have a significant association. Among non-cardiometabolic conditions, presence of chronic obstructive pulmonary disease (HR 3.31, 95% CI 2.14-5.11) and osteoporosis (HR 3.13, 95% CI 1.63-6.01) was associated with a higher risk of mortality. Conclusion: Survival in middle-aged to older individuals with self-reported AF is strongly correlated with level of multimorbidity. This group should be targeted for interventions to optimize their management, which in turn may potentially reduce the impact of their co-morbidities on survival. Future AF clinical guidelines need to place greater emphasis on the issue of co-morbidity.

Telehealth Interventions to Support Self-Management of Long-Term Conditions: A Systematic Metareview of Diabetes, Heart Failure, Asthma, Chronic Obstructive Pulmonary Disease, and Cancer.

BACKGROUND: Self-management support is one mechanism by which telehealth interventions have been proposed to facilitate management of long-term conditions. OBJECTIVE: The objectives of this metareview were to (1) assess the impact of telehealth interventions to support self-management on disease control and health care utilization, and (2) identify components of telehealth support and their impact on disease control and the process of self-management. Our goal was to synthesise evidence for telehealth-supported self-management of diabetes (types 1 and 2), heart failure, asthma, chronic obstructive pulmonary disease (COPD) and cancer to identify components of effective self-management support. METHODS: We performed a metareview (a systematic review of systematic reviews) of randomized controlled trials (RCTs) of telehealth interventions to support self-management in 6 exemplar long-term conditions. We searched 7 databases for reviews published from January 2000 to May 2016 and screened identified studies against eligibility criteria. We weighted reviews by quality (revised A Measurement Tool to Assess Systematic Reviews), size, and relevance. We then combined our results in a narrative synthesis and using harvest plots. RESULTS: We included 53 systematic reviews, comprising 232 unique RCTs. Reviews concerned diabetes (type 1: n=6; type 2, n=11; mixed, n=19), heart failure (n=9), asthma (n=8), COPD (n=8), and cancer (n=3). Findings varied between and within disease areas. The highest-weighted reviews showed that blood glucose telemonitoring with feedback and some educational and lifestyle interventions improved glycemic control in type 2, but not type 1, diabetes, and that telemonitoring and telephone interventions reduced mortality and hospital admissions in heart failure, but these findings were not consistent in all reviews. Results for the other conditions were mixed, although no reviews showed evidence of harm. Analysis of the mediating role of self-management, and of components of successful interventions, was limited and inconclusive. More intensive and multifaceted interventions were associated with greater improvements in diabetes, heart failure, and asthma. CONCLUSIONS: While telehealth-mediated self-management was not consistently superior to usual care, none of the reviews reported any negative effects, suggesting that telehealth is a safe option for delivery of self-management support, particularly in conditions such as heart failure and type 2 diabetes, where the evidence base is more developed. Larger-scale trials of telehealth-supported self-management, based on explicit self-management theory, are needed before the extent to which telehealth technologies may be harnessed to support self-management can be established.

Systematic review and meta-analysis of the sero-epidemiological association between Epstein-Barr virus and rheumatoid arthritis.

INTRODUCTION: Infection with Epstein-Barr virus (EBV) has been suggested to contribute to the pathogenesis of autoimmune diseases, including rheumatoid arthritis (RA). We sought to determine whether prior infection with the virus occurs more frequently in patients with RA compared to controls. METHODS: We performed a systematic review and meta-analyses of studies that reported the prevalence of anti-EBV antibodies in the sera of cases with RA and controls by searching Medline and Embase databases from 1946 to 2014, with no language restriction. Mantel-Haenszel odds ratios for the detection of anti-EBV antibodies were calculated, and meta-analyses conducted. Quality assessments were performed using a modified version of the Newcastle-Ottawa scale. RESULTS: Twenty-three studies were included. Quality assessment found most studies reported acceptable selection criteria but poor descriptions of how cases and controls were recruited. When all studies were included, there was a statistically significant higher seroprevalence of anti-VCA IgG in patients with RA compared to controls with an odds ratio (OR) of 1.61 (95 % confidence interval (CI) 1.05-2.46, p = 0.03), which is a similar-sized summary OR to that reported for systemic lupus erythematosus (SLE). However, when studies were restricted to those reporting more plausible levels of exposure to EBV in the control groups, no significant association was apparent, OR 1.47 (95 % CI 0.88-2.46, p = 0.14). Using anti-EBNA 1 or anti-EA IgG as markers of previous infection also did not yield significant associations (OR 1.05, 95 % CI 0.68-1.61, p = 0.82; OR 2.2, 95 % CI 0.86-5.65, p = 0.10 respectively). CONCLUSIONS: Overall, these findings do not demonstrate an association between EBV seroprevalence and RA and therefore do not support the hypothesis that prior infection with EBV predisposes to the development of RA. This contrasts with meta-analyses that indicate EBV infection is associated with multiple sclerosis and SLE.