Background: Loss of skeletal muscle mass (SMM) increases the risk of frailty and, together with excess fat mass (FM), is a risk factor for cardio-metabolic disease. However, use of body composition measurements in nutritional surveillance and routine clinical practice is limited by the lack of reference data. Our aim was to produce age-specific and sex-specific reference values for SMM and FM in the White ethnic adult population in the UK. Secondary objectives were to examine the tracking over time using a subsample of the population with repeated measures of body composition and to assess the validity of these reference values in different ethnic subgroups. Methods: We used data from segmental bioelectrical impedance analysis (BIA) in 390 565 participants, aged 40\u201369 years, in the UK Biobank, and data from dual-energy X-ray absorptiometry from n = 905 participants to validate the BIA measurements. SMM was calculated as the sum of the predicted muscle mass from the limbs. The LMS method was used to produce percentile curves for the SMM index (SMMI = SMM/height2) and the FM index (FMI = FM/height2). We investigated the validity of the White ethnic reference values by plotting z-scores (99.7% confidence interval) from Black and Asian groups to check if their confidence interval included zero. Longitudinal trajectories were predicted based on the baseline z-scores and the correlation between repeated measurements at follow-up. Results: The percentile curves show that SMMI declines in men from the age of 40, whereas in women, SMMI is more stable and decreases only slightly among women in the higher percentiles. FMI increases with age in both men and women. Women have higher FMI and lower SMMI than men in all age groups. The validity of the White-based reference values for non-White ethnic groups is poor. Longitudinal trajectories in body composition in the subsample of participants with a follow-up assessment show regression towards the mean in both men and women, with some evidence of declining SMMI only among men. The predicted 90% limits for the expected 5 year trajectories of SMMI and FMI can be used to identify people with unusual trajectories and in clinical practice to identify and track individuals at risk of excessive loss of SMM. Conclusions: These body composition reference values developed from BIA in a middle/older-aged healthy White ethnic population in the UK could be used as a simple assessment tool for nutritional surveillance and to identify individuals with low SMMI or high FMI who may be at increased risk of disease and/or frailty.
\n \n\n \n \nBackground: Self-regulation for weight loss requires regular self-monitoring of weight, but the frequency of weight tracking commonly declines over time. Objective: This study aimed to investigate whether it is a decline in weight loss or a drop in motivation to lose weight (using physical activity tracking as a proxy) that may be prompting a stop in weight monitoring. Methods: We analyzed weight and physical activity data from 1605 Withings Health Mate app users, who had set a weight loss goal and stopped tracking their weight for at least six weeks after a minimum of 16 weeks of continuous tracking. Mixed effects models compared weight change, average daily steps, and physical activity tracking frequency between a 4-week period of continuous tracking and a 4-week period preceding the stop in weight tracking. Additional mixed effects models investigated subsequent changes in physical activity data during 4 weeks of the 6-week long stop in weight tracking. Results: People lost weight during continuous tracking (mean -0.47 kg, SD 1.73) but gained weight preceding the stop in weight tracking (mean 0.25 kg, SD 1.62; difference 0.71 kg; 95% CI 0.60 to 0.81). Average daily steps (beta=-220 daily steps per time period; 95% CI -320 to -120) and physical activity tracking frequency (beta=-3.4 days per time period; 95% CI -3.8 to -3.1) significantly declined from the continuous tracking to the pre-stop period. From pre-stop to post-stop, physical activity tracking frequency further decreased (beta=-6.6 days per time period; 95% CI -7.12 to -6.16), whereas daily step count on the day's activity was measured increased (beta=110 daily steps per time period; 95% CI 50 to 170). Conclusions: In the weeks before people stop tracking their weight, their physical activity and physical activity monitoring frequency decline. At the same time, weight increases, suggesting that declining motivation for weight control and difficulties with making use of negative weight feedback might explain why people stop tracking their weight. The increase in daily steps but decrease in physical activity tracking frequency post-stop might result from selective measurement of more active days.
\n \n\n \n \nBackground: High exhaled nitric oxide fraction (FENO) levels are associated with greater risk of asthma exacerbation. However, it is not clear how FENO can be used to guide safe reductions in inhaled corticosteroid (ICS) doses in asthma patients. This study assesses the ability of FENO to guide ICS reductions. Methods: Systematic searching of electronic databases identified prospective observational studies and randomised controlled trials which recruited participants with mild-to-moderate asthma aged \u227d12 years and measured FENO before reducing ICS. We performed multilevel mixed-effects logistic regression in relation to acute exacerbations and estimated each participant's exacerbation risk using our logistic regression model. Results: We included data from seven out of eight eligible studies, representing 384 participants. ICS doses were halved in four studies and withdrawn in three studies. A baseline FENO measurement of \u227d50 ppb was associated with increased risk of exacerbations (crude OR 3.14, 95% CI 1.41-7.00, p=0.005; adjusted OR 3.08, 95% CI 1.36-6.98, p=0.007) and corresponded to an estimated exacerbation risk cut-off of 15%. Reducing ICS when estimated exacerbation risk was <15% versus <10% would result in fewer patients remaining on the same ICS dose (40 (10.4%) out of 384 versus 141 (36.7%) out of 384), but similar proportions of patients avoiding exacerbations (222 (91.4%) out of 243, 95% CI 87.1-94.6% versus 311 (90.4%) out of 344, 95% CI 86.8-93.3%). Conclusion: In patients with mild-to-moderate asthma, gradual ICS reduction when FENO is <50 ppb may help decrease ICS use without increasing exacerbations. Future research should aim to validate these findings in larger populations.
\n \n\n \n \nObjective To compare the diagnostic performance of guaiac faecal occult blood (gFOB) testing with faecal immunochemical test (FIT) in a low-risk symptomatic primary care population to provide objective data on which to base local referral guidelines. Design Stool samples from routine primary care practice sent for faecal occult blood testing were analysed by a standard gFOB method and the HM-JACKarc FIT between January and March 2016. Symptoms described on the test request were recorded. Patients were followed up over 21 months for evidence of serious gastrointestinal pathology including colorectal adenocarcinoma. Results In 238 patients, the sensitivity and specificity for colorectal adenocarcinoma detection using gFOB were 85.7% and 65.8%, respectively, compared with 85.7% and 89.2% for FIT. The positive predictive value (PPV) for gFOB was 7.1% and negative predictive value (NPV) was 99.3%. Comparatively, the PPV for FIT was 19.4% and NPV 99.5%. The improved performance of FIT over gFOB was due to a lower false positive rate (10.8 vs 34.2, p\u22640.01) with no increase in the false negatives rate. For any significant colorectal disease, the PPV for FIT increased to 35.5% with a reduction in NPV to 95.7%. Conclusion In this low-risk symptomatic patient group, the proportion of samples considered positive by FIT was considerably lower than gFOB with the same rate of colorectal adenocarcinoma detection. One in three of those with positive FIT had a significant colorectal disease. This supports National Institute of Health and Care Excellence recommendation that FIT can be reliably used as a triage test in primary care without overburdening endoscopy resources.
\n \n\n \n \n\nBACKGROUND\nSelf-regulation for weight loss requires regular self-monitoring of weight, but the frequency of weight tracking commonly declines over time.\n\n\nOBJECTIVE\nThis study aimed to investigate whether it is a decline in weight loss or a drop in motivation to lose weight (using physical activity tracking as a proxy) that may be prompting a stop in weight monitoring.\n\n\nMETHODS\nWe analyzed weight and physical activity data from 1605 Withings Health Mate app users, who had set a weight loss goal and stopped tracking their weight for at least six weeks after a minimum of 16 weeks of continuous tracking. Mixed effects models compared weight change, average daily steps, and physical activity tracking frequency between a 4-week period of continuous tracking and a 4-week period preceding the stop in weight tracking. Additional mixed effects models investigated subsequent changes in physical activity data during 4 weeks of the 6-week long stop in weight tracking.\n\n\nRESULTS\nPeople lost weight during continuous tracking (mean \u22120.47 kg, SD 1.73) but gained weight preceding the stop in weight tracking (mean 0.25 kg, SD 1.62; difference 0.71 kg; 95% CI 0.60 to 0.81). Average daily steps (beta=\u2212220 daily steps per time period; 95% CI \u2212320 to \u2212120) and physical activity tracking frequency (beta=\u22123.4 days per time period; 95% CI \u22123.8 to \u22123.1) significantly declined from the continuous tracking to the pre-stop period. From pre-stop to post-stop, physical activity tracking frequency further decreased (beta=\u22126.6 days per time period; 95% CI \u22127.12 to \u22126.16), whereas daily step count on the day\u2019s activity was measured increased (beta=110 daily steps per time period; 95% CI 50 to 170).\n\n\nCONCLUSIONS\nIn the weeks before people stop tracking their weight, their physical activity and physical activity monitoring frequency decline. At the same time, weight increases, suggesting that declining motivation for weight control and difficulties with making use of negative weight feedback might explain why people stop tracking their weight. The increase in daily steps but decrease in physical activity tracking frequency post-stop might result from selective measurement of more active days.\n
\n \n\n \n \nBackground/objectives: To develop age- and sex-specific centile reference curves for fat-free mass (FFM) and fat mass (FM) adjusted for height in an adult Kenyan population and to investigate the association between FM, FFM and blood pressure (BP). Subjects/methods: Measures of body composition from bioimpedance analyses and BP were collected in 1995 participants aged \u226550 years in Nakuru County, Kenya. Reference curves were produced using the LMS method. Multivariable linear regression models were used to test the cross-sectional association between body composition indexes and BP. Results: The age- and sex-specific reference curves for body composition (FMI and FFMI) confirmed that FFMI is lower in both men and women with increasing age. FMI declines with age in women while among men the decline starts after 70 years. FFM was higher in men (47.4 \u00b1 7.2 kg) than in women (38.8 \u00b1 5.5 kg), while FM was lower in men (17.3 \u00b1 8.1 kg) than in women (24.4 \u00b1 10.2 kg). FMI, FFMI and BMI were all positively associated with systolic and diastolic BP, and after adjusting for body weight, FFMI remained positively associated with systolic BP and the FMI remained positively associated with diastolic BP. There was no evidence to suggest that FMI and FFMI were superior to measurement of BMI alone. Conclusions: These body composition reference curves provide normative data on body composition for older adults in Kenya. Further research should consider the prospective associations with health, including frailty-related outcomes.
\n \n\n \n \nTo understand Cancer Antigen 125 (CA125) testing in primary care in relation to a national guideline, we conducted a retrospective observational study including CA125 data from a well-defined region in the UK, from 2003 to 2014. 51,033 CA125 tests from 30,737 women were stratified by month and year of testing, location of test request and patient age. Absolute numbers and rates of testing, rates and proportions of positive and negative tests, and frequencies of single and repeat tests were calculated. Negative binomial and logistic regression were used to test the effect of the guideline's introduction. Primary care testing spiked in the three months following the release of the guideline. However, there was no difference in the increase in testing observed across age groups. The proportion of positive tests decreased over time despite both the rates of positive and negative tests increasing. Retesting and repeat testing were associated with the initial CA125 value with no significant difference between women whose first test was 30\u201335 and >35 IU/L. Large studies using linked data are required to investigate the impact of increasing CA125 testing on onward intervention and patient outcomes. CA125 guidelines should be refined to avoid over-investigation in low risk age-groups.
\n \n\n \n \nINTRODUCTION: Lung cancer is a common cancer, with over 1.3 million cases worldwide each year. Early diagnosis using computed tomography (CT) screening has been shown to reduce mortality but also detect non-malignant nodules that require follow-up scanning or alternative methods of investigation. Practical and accurate tools that can predict the probability that a lung nodule is benign or malignant will help reduce costs and the risk of morbidity and mortality associated with lung cancer. METHODS: Retrospectively collected data from 1500 patients with pulmonary nodule(s) of up to 15 mm detected on routinely performed CT chest scans aged 18 years old or older from three academic centres in the UK will be used to to develop risk stratification models. Radiological, clinical and patient characteristics will be combined in multivariable logistic regression models to predict nodule malignancy. Data from over 1000 participants recruited in a prospective phase of the study will be used to evaluate model performance. Discrimination, calibration and clinical utility measures will be presented.
\n \n\n \n \nThe incidence of cancer in the United Kingdom has increased significantly over the last four decades. The aim of this study was to examine trends in UK cancer incidence and mortality by cancer site and assess the potential for overdiagnosis. Using Cancer Research UK incidence and mortality data for the period (1971\u20132014) we estimated percentage change in incidence and mortality rates and the incidence-mortality ratio (IMR) for cancers in which incidence had increased >50%. Incidence and mortality trend plots were used to assess the potential for overdiagnosis. Incidence rates increased from 67% (uterine) to 375% (melanoma). Change in mortality rates ranged from \u221269% (cervical) to +239% (liver). The greatest divergences occurred in uterine (IMR = 132), prostate (IMR = 9.6), oral (IMR = 9.8) and thyroid cancer (IMR = 5.3). Only in liver cancer did mortality track incidence (IMR = 1.1). For four cancer sites; uterine, prostate, oral and thyroid, incidence and mortality trends are suggestive of overdiagnosis. Trends in melanoma and kidney cancer suggest potential overdiagnosis and an underlying increase in true risk, whereas for cervical and breast cancer, trends may also reflect improvements in treatments or earlier diagnosis. A more detailed analysis is required to fully understand these patterns.
\n \n\n \n \nBackground Early intervention in psychosis (EIP) services are the dominant service model in the treatment of first-episode psychosis. They are a time-limited intervention and little is known about discharge destinations and outcomes once EIP treatment has concluded.Aims To understand discharge pathways and predictors of relapse in an EIP service.Method We collected data on all patients with an electronic health record treated by EIP services in Oxford Health NHS Foundation Trust in the UK between 12 January 2006 and 7 March 2017 (n = 701). Our primary outcomes were discharge destination at end of treatment and relapse.Results Most patients (83.5%) were discharged to primary care. Transfer to secondary care was associated with previous in-patient admissions (odds ratio (OR) = 1.92, 95% CI 1.54-2.39) and longer EIP treatment (OR = 1.04, 95% CI 1.03-1.06). Relapse rate was highest shortly after leaving EIP services. Relapse was associated with transfer to secondary care (hazard ratio (HR) = 2.75, 95% CI 1.75-4.31), higher deprivation (HR = 1.03, 95% CI, 1.01-1.05), a substance misuse disorder (HR = 1.81, 95% CI 1.01-3.26) and a comorbid diagnosis of a personality disorder (HR = 2.96, 95% CI 1.39-6.29).Conclusions Most patients treated by the EIP service in Oxfordshire did not receive ongoing mental healthcare from secondary mental health services. We identified high deprivation and those with substance misuse problems or personality disorders as EIP populations with a high risk of relapse.
\n \n\n \n \nIntroduction Cancer survival in England lags behind most European countries, due partly to lower rates of early stage diagnosis. We report the protocol for the evaluation of a multidisciplinary diagnostic centre-based pathway for the investigation of 'low-risk but not no-risk' cancer symptoms called the Suspected CANcer (SCAN) pathway. SCAN is a new standard of care being implemented in Oxfordshire; one of a number of pathways implemented during the second wave of the Accelerate, Coordinate, Evaluate (ACE) programme, an initiative which aims to improve England's cancer survival rates through establishing effective routes to early diagnosis. Methods and analysis To evaluate SCAN, we are collating a prospective database of patients referred onto the pathway by their general practitioner (GP). Patients aged over 40 years, with non-specific symptoms such as weight loss or fatigue, who do not meet urgent cancer referral criteria or for whom symptom causation remains unclear after investigation via other existing pathways, can be referred to SCAN. SCAN provides rapid CT scanning, laboratory testing and clinic review within 2 weeks. We will follow all patients in the primary and secondary care record for at least 2 years. The data will be used to understand the diagnostic yield of the SCAN pathway in the short term (28 days) and the long term (2 years). Routinely collected primary and secondary care data from patients not referred to SCAN but with similar symptoms will also be used to evaluate SCAN. We will map the routes to diagnosis for patients referred to SCAN to assess cost-effectiveness. Acceptability will be evaluated using patient and GP surveys. Ethics and dissemination The Oxford Joint Research Office Study Classification Group has judged this to be a service evaluation and so outside of research governance. The results of this project will be disseminated by peer-reviewed publication and presentation at conferences.
\n \n\n \n \n[This corrects the article DOI: 10.1186/s41512-016-0001-y.].
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