blandaltman: A command to create variants of Bland–Altman plots

Bland–Altman plots can be useful in paired data settings such as measurement-method comparison studies. A Bland–Altman plot has differences, percentage differences, or ratios on the y axis and a mean of the data pairs on the x axis, with 95% limits of agreement indicating the central 95% range of differences, percentage differences, or ratios. This range can vary with the mean. We introduce the community-contributed blandaltman command, which uniquely in Stata can 1) create Bland–Altman plots featuring ratios in addition to differences and percentage differences, 2) allow the limits of agreement for ratios and percentage differences to vary as a function of the mean, and 3) add confidence intervals, prediction intervals, and tolerance intervals to the plots

Climate Variability and Ross River Virus Transmission in Townsville Region, Australia 1985 to 1996

Background How climate variability affects the transmission of infectious diseases at a regional level remains unclear. In this paper, we assessed the impact of climate variation on the Ross River virus (RRv) transmission in the Townsville region, Queensland, north-east Australia. Methods Population-based information was obtained on monthly variations in RRv cases, climatic factors, sea level, and population growth between 1985 and 1996. Cross-correlations were computed for a series of associations between climate variables (rainfall, maximum temperature, minimum temperature, relative humidity and high tide) and the monthly incidence of RRv disease over a range of time lags. The impact of climate variability on RRv transmission was assessed using the seasonal auto-regressive integrated moving average (SARIMA) model. Results There were significant correlations of the monthly incidence of RRv to rainfall, maximum temperature, minimum temperature and relative humidity, all at a lag of 2 months, and high tide in the current month. The results of SARIMA models show that monthly average rainfall (β=0.0012, p=0.04) and high tide (β=0.0262, p=0.01) were significantly associated with RRv transmission, although temperature and relative humidity did not seem to have played an important role in the Townsville region. Conclusions Rainfall, and high tide were likely to be key determinants of RRv transmission in the Townsville region

Suppressor of cytokine signaling (SOCS)5 ameliorates influenza infection via inhibition of EGFR signaling

© Kedzierski et al. Influenza virus infections have a significant impact on global human health. Individuals with suppressed immunity, or suffering from chronic inflammatory conditions such as COPD, are particularly susceptible to influenza. Here we show that suppressor of cytokine signaling (SOCS) five has a pivotal role in restricting influenza A virus in the airway epithelium, through the regulation of epidermal growth factor receptor (EGFR). Socs5-deficient mice exhibit heightened disease severity, with increased viral titres and weight loss. Socs5 levels were differentially regulated in response to distinct influenza viruses (H1N1, H3N2, H5N1 and H11N9) and were reduced in primary epithelial cells from COPD patients, again correlating with increased susceptibility to influenza. Importantly, restoration of SOCS5 levels restricted influenza virus infection, suggesting that manipulating SOCS5 expression and/or SOCS5 targets might be a novel therapeutic approach to influenza

Cryptic multiple hypotheses testing in linear models: overestimated effect sizes and the winner's curse

Fitting generalised linear models (GLMs) with more than one predictor has become the standard method of analysis in evolutionary and behavioural research. Often, GLMs are used for exploratory data analysis, where one starts with a complex full model including interaction terms and then simplifies by removing non-significant terms. While this approach can be useful, it is problematic if significant effects are interpreted as if they arose from a single a priori hypothesis test. This is because model selection involves cryptic multiple hypothesis testing, a fact that has only rarely been acknowledged or quantified. We show that the probability of finding at least one ‘significant’ effect is high, even if all null hypotheses are true (e.g. 40% when starting with four predictors and their two-way interactions). This probability is close to theoretical expectations when the sample size (N) is large relative to the number of predictors including interactions (k). In contrast, type I error rates strongly exceed even those expectations when model simplification is applied to models that are over-fitted before simplification (low N/k ratio). The increase in false-positive results arises primarily from an overestimation of effect sizes among significant predictors, leading to upward-biased effect sizes that often cannot be reproduced in follow-up studies (‘the winner's curse’). Despite having their own problems, full model tests and P value adjustments can be used as a guide to how frequently type I errors arise by sampling variation alone. We favour the presentation of full models, since they best reflect the range of predictors investigated and ensure a balanced representation also of non-significant results

Case-finding of dementia in general practice and effects of subsequent collaborative care; design of a cluster RCT

<p>Abstract</p> <p>Background</p> <p>In the primary care setting, dementia is often diagnosed relatively late in the disease process. Case finding and proactive collaborative care may have beneficial effects on both patient and informal caregiver by clarifying the cause of cognitive decline and changed behaviour and by enabling support, care planning and access to services.</p> <p>We aim to improve the recognition and diagnosis of individuals with dementia in general practice. In addition to this diagnostic aim, the effects of case finding and subsequent care on the mental health of individuals with dementia and the mental health of their informal carers are explored.</p> <p>Methods and design</p> <p>Design: cluster randomised controlled trial with process evaluation.</p> <p>Participants: 162 individuals ≥ 65 years, in 15 primary care practices, in whom GPs suspect cognitive impairment, but without a dementia diagnosis.</p> <p>Intervention; case finding and collaborative care: 2 trained practice nurses (PNs) invite all patients with suspected cognitive impairment for a brief functional and cognitive screening. If the cognitive tests are supportive of cognitive impairment, individuals are referred to their GP for further evaluation. If dementia is diagnosed, a comprehensive geriatric assessment takes place to identify other relevant geriatric problems that need to be addressed. Furthermore, the team of GP and PN provide information and support.</p> <p>Control: GPs provide care and diagnosis as usual.</p> <p>Main study parameters: after 12 months both groups are compared on: 1) incident dementia (and MCI) diagnoses and 2) patient and caregiver quality of life (QoL-AD; EQ5D) and mental health (MH5; GHQ 12) and caregiver competence to care (SSCQ). The process evaluation concerns facilitating and impeding factors to the implementation of this intervention. These factors are assessed on the care provider level, the care recipient level and on the organisational level.</p> <p>Discussion</p> <p>This study will provide insight into the diagnostic yield and the clinical effects of case finding and collaborative care for individuals with suspected cognitive impairment, compared to usual care. A process evaluation will give insight into the feasibility of this intervention.</p> <p>The first results are expected in the course of 2013.</p> <p>Trial registration</p> <p>NTR3389</p

Attrition and bias in the MRC cognitive function and ageing study: an epidemiological investigation

BACKGROUND: Any hypothesis in longitudinal studies may be affected by attrition and poor response rates. The MRC Cognitive Function and Ageing study (MRC CFAS) is a population based longitudinal study in five centres with identical methodology in England and Wales each recruiting approximately 2,500 individuals. This paper aims to identify potential biases in the two-year follow-up interviews. METHODS: Initial non-response: Those not in the baseline interviews were compared in terms of mortality to those who were in the baseline interviews at the time of the second wave interviews (1993–1996). Longitudinal attrition: Logistic regression analysis was used to examine baseline differences between individuals who took part in the two-year longitudinal wave compared with those who did not. RESULTS: Initial non-response: Individuals who moved away after sampling but before baseline interview were 1.8 times more likely to die by two years (95% Confidence interval(CI) 1.3–2.4) compared to respondents, after adjusting for age. The refusers had a slightly higher, but similar mortality pattern to responders (Odds ratio 1.2, 95%CI 1.1–1.4). Longitudinal attrition: Predictors for drop out due to death were being older, male, having impaired activities of daily living, poor self-perceived health, poor cognitive ability and smoking. Similarly individuals who refused were more likely to have poor cognitive ability, but had less years of full-time education and were more often living in their own home though less likely to be living alone. There was a higher refusal rate in the rural centres. Individuals who moved away or were uncontactable were more likely to be single, smokers, demented or depressed and were less likely to have moved if in warden-controlled accommodation at baseline. CONCLUSIONS: Longitudinal estimation of factors mentioned above could be biased, particularly cognitive ability and estimates of movements from own home to residential homes. However, these differences could also affect other investigations, particularly the estimates of incidence and longitudinal effects of health and psychiatric diseases, where the factors shown here to be associated with attrition are risk factors for the diseases. All longitudinal studies should investigate attrition and this may help with aspects of design and with the analysis of specific hypotheses

Participation of older newly-diagnosed cancer patients in an observational prospective pilot study: an example of recruitment and retention

<p>Abstract</p> <p>Background</p> <p>There have been few prospective observational studies which recruited older newly-diagnosed cancer patients, and of these only some have reported information on the number needed to screen to recruit their study sample, and the number and reasons for refusal and drop-out. This paper reports on strategies to recruit older newly-diagnosed cancer patients prior to treatment into an observational prospective pilot study and to retain them during a six-month period.</p> <p>Methods</p> <p>Medical charts of all patients in the Segal Cancer Centre aged 65 and over were screened and evaluated for inclusion. Several strategies to facilitate recruitment and retention were implemented. Reasons for exclusion, refusal and loss to follow-up were recorded. Descriptive statistics were used to report the reasons for refusal and loss to follow-up. A non-response analysis using chi-square tests and t-tests was conducted to compare respondents to those who refused to participate and to compare those who completed the study to those who were lost to follow-up. A feedback form with open-ended questions was administered following the last interview to obtain patient's opinions on the length of the interviews and conduct of this pilot study.</p> <p>Results</p> <p>3060 medical charts were screened and 156 eligible patients were identified. Of these 112 patients participated for a response rate of 72%. Reasons for refusal were: feeling too anxious (40%), not interested (25%), no time (12.5%), too sick (5%) or too healthy (5%) or other reasons (5%). Ninety-one patients participated in the six-month follow-up (retention 81.3%), seven patients refused follow-up (6.2%) and fourteen patients died (12.5%) during the course of the study. The median time to conduct the baseline interview was 45 minutes and 57% of baseline interviews were conducted at home. Most patients enjoyed participation and only five felt that the interviews were too long.</p> <p>Conclusion</p> <p>It was feasible to recruit newly-diagnosed cancer patients prior to treatment although it required considerable time and effort. Once patients were included, the retention rate was high despite the fact that most were undergoing active cancer treatment.</p

The acceptability and feasibility of using the Adult Social Care Outcomes Toolkit (ASCOT) to inform practice in care homes

Background: The Adult Social Care Outcomes Toolkit (ASCOT) measures social care related quality of life (SCRQoL) and can be used to measure outcomes and demonstrate impact across different social care settings. This exploratory study built on previous work by collecting new inter-rater reliability data on the mixed-methods version of the toolkit and exploring how it might be used to inform practice in four case study homes. Method: We worked with two care home providers to agree an in-depth study collecting SCRQoL data in four case-study homes. Data was collected about residents’ age, ethnicity, cognitive impairment, ability to perform activities of daily living and SCRQoL in the four homes. Feedback sessions with staff and managers were held in the homes two weeks after baseline and follow-up data collected three months later. Interviews with managers explored their views of the feedback and recorded any changes that had been made because of it. Results: Participant recruitment was challenging, despite working in partnership with the homes. Resident response rates ranged from 23 to 54 % with 58 residents from four care homes taking part in the research. 53 % lacked capacity to consent. Inter-rater reliability for the ASCOT ratings of SCRQoL were good at time one (IRR = 0.72) and excellent at time two (IRR = 0.76). During the study, residents’ ability to perform activities of daily living declined significantly (z = -2.67, p < .01), as did their expected needs in the absence of services (z = -2.41, p < .05). Despite these rapid declines in functionings, residents’ current SCRQoL declined slightly but not significantly (Z = -1.49, p = .14). Staff responded positively to the feedback given and managers reported implementing changes in practice because of it. Conclusion: This exploratory study faced many challenges in the recruitment of residents, many of whom were cognitively impaired. Nevertheless, without a mixed-methods approach many of the residents living in the care homes would have been excluded from the research altogether or had their views represented only by a representative or proxy. The value of the mixed-methods toolkit and its potential for use by providers is discussed