Systematic review and meta-analysis of the growth and rupture rates of small abdominal aortic aneurysms: implications for surveillance intervals and their cost-effectiveness.

BACKGROUND: Small abdominal aortic aneurysms (AAAs; 3.0-5.4 cm in diameter) are usually asymptomatic and managed by regular ultrasound surveillance until they grow to a diameter threshold (commonly 5.5 cm) at which surgical intervention is considered. The choice of appropriate surveillance intervals is governed by the growth and rupture rates of small AAAs, as well as their relative cost-effectiveness. OBJECTIVES: The aim of this series of studies was to inform the evidence base for small AAA surveillance strategies. This was achieved by literature review, collation and analysis of individual patient data, a focus group and health economic modelling. DATA SOURCES: We undertook systematic literature reviews of growth rates and rupture rates of small AAAs. The databases MEDLINE, EMBASE on OvidSP, Cochrane Central Register of Controlled Trials 2009 Issue 4, ClinicalTrials.gov, and controlled-trials.com were searched from inception up until the end of 2009. We also obtained individual data on 15,475 patients from 18 surveillance studies. REVIEW METHODS: Systematic reviews of publications identified 15 studies providing small AAA growth rates, and 14 studies with small AAA rupture rates, up to December 2009 (later updated to September 2012). We developed statistical methods to analyse individual surveillance data, including the effects of patient characteristics, to inform the choice of surveillance intervals and provide inputs for health economic modelling. We updated an existing health economic model of AAA screening to address the cost-effectiveness of different surveillance intervals. RESULTS: In the literature reviews, the mean growth rate was 2.3 mm/year and the reported rupture rates varied between 0 and 1.6 ruptures per 100 person-years. Growth rates increased markedly with aneurysm diameter, but insufficient detail was available to guide surveillance intervals. Based on individual surveillance data, for each 0.5-cm increase in AAA diameter, growth rates increased by about 0.5 mm/year and rupture rates doubled. To control the risk of exceeding 5.5 cm to below 10% in men, on average a 7-year surveillance interval is sufficient for a 3.0-cm aneurysm, whereas an 8-month interval is necessary for a 5.0-cm aneurysm. To control the risk of rupture to below 1%, the corresponding estimated surveillance intervals are 9 years and 17 months. Average growth rates were higher in smokers (by 0.35 mm/year) and lower in patients with diabetes (by 0.51 mm/year). Rupture rates were almost fourfold higher in women than men, doubled in current smokers and increased with higher blood pressure. Increasing the surveillance interval from 1 to 2 years for the smallest aneurysms (3.0-4.4 cm) decreased costs and led to a positive net benefit. For the larger aneurysms (4.5-5.4 cm), increasing surveillance intervals from 3 to 6 months led to equivalent cost-effectiveness. LIMITATIONS: There were no clear reasons why the growth rates varied substantially between studies. Uniform diagnostic criteria for rupture were not available. The long-term cost-effectiveness results may be susceptible to the modelling assumptions made. CONCLUSIONS: Surveillance intervals of several years are clinically acceptable for men with AAAs in the range 3.0-4.0 cm. Intervals of around 1 year are suitable for 4.0-4.9-cm AAAs, whereas intervals of 6 months would be acceptable for 5.0-5.4-cm AAAs. These intervals are longer than those currently employed in the UK AAA screening programmes. Lengthening surveillance intervals for the smallest aneurysms was also shown to be cost-effective. Future work should focus on optimising surveillance intervals for women, studying whether or not the threshold for surgery should depend on patient characteristics, evaluating the usefulness of surveillance for those with aortic diameters of 2.5-2.9 cm, and developing interventions that may reduce the growth or rupture rates of small AAAs. FUNDING: The National Institute for Health Research Health Technology Assessment programme

Discrete Event Simulation for Decision Modeling in Health Care: Lessons from Abdominal Aortic Aneurysm Screening

Markov models are often used to evaluate the cost-effectiveness of new healthcare interventions but they are sometimes not flexible enough to allow accurate modeling or investigation of alternative scenarios and policies. A Markov model previously demonstrated that a one-off invitation to screening for abdominal aortic aneurysm (AAA) for men aged 65 y in the UK and subsequent follow-up of identified AAAs was likely to be highly cost-effective at thresholds commonly adopted in the UK (£20,000 to £30,000 per quality adjusted life-year). However, new evidence has emerged and the decision problem has evolved to include exploration of the circumstances under which AAA screening may be cost-effective, which the Markov model is not easily able to address. A new model to handle this more complex decision problem was needed, and the case of AAA screening thus provides an illustration of the relative merits of Markov models and discrete event simulation (DES) models. An individual-level DES model was built using the R programming language to reflect possible events and pathways of individuals invited to screening v. those not invited. The model was validated against key events and cost-effectiveness, as observed in a large, randomized trial. Different screening protocol scenarios were investigated to demonstrate the flexibility of the DES. The case of AAA screening highlights the benefits of DES, particularly in the context of screening studies

Value of risk scores in the decision to palliate patients withruptured abdominal aortic aneurysm

Background: The aim of this study was to develop a 48‐h mortality risk score, which included morphology data, for patients with ruptured abdominal aortic aneurysm presenting to an emergency department, and to assess its predictive accuracy and clinical effectiveness in triaging patients to immediate aneurysm repair, transfer or palliative care. Methods: Data from patients in the IMPROVE (Immediate Management of the Patient With Ruptured Aneurysm: Open Versus Endovascular Repair) randomized trial were used to develop the risk score. Variables considered included age, sex, haemodynamic markers and aortic morphology. Backwards selection was used to identify relevant predictors. Predictive performance was assessed using calibration plots and the C‐statistic. Validation of the newly developed and other previously published scores was conducted in four external populations. The net benefit of treating patients based on a risk threshold compared with treating none was quantified. Results: Data from 536 patients in the IMPROVE trial were included. The final variables retained were age, sex, haemoglobin level, serum creatinine level, systolic BP, aortic neck length and angle, and acute myocardial ischaemia. The discrimination of the score for 48‐h mortality in the IMPROVE data was reasonable (C‐statistic 0·710, 95 per cent c.i. 0·659 to 0·760), but varied in external populations (from 0·652 to 0·761). The new score outperformed other published risk scores in some, but not all, populations. An 8 (95 per cent c.i. 5 to 11) per cent improvement in the C‐statistic was estimated compared with using age alone. Conclusion: The assessed risk scores did not have sufficient accuracy to enable potentially life‐saving decisions to be made regarding intervention. Focus should therefore shift to offering repair to more patients and reducing non‐intervention rates, while respecting the wishes of the patient and family

Interpreting findings from Mendelian randomization using the MR-Egger method

Mendelian randomization-Egger (MR-Egger) is an analysis method for Mendelian randomization using summarized genetic data. MR-Egger consists of three parts: (1) a test for directional pleiotropy, (2) a test for a causal effect, and (3) an estimate of the causal effect. While conventional analysis methods for Mendelian randomization assume that all genetic variants satisfy the instrumental variable assumptions, the MR-Egger method is able to assess whether genetic variants have pleiotropic effects on the outcome that differ on average from zero (directional pleiotropy), as well as to provide a consistent estimate of the causal effect, under a weaker assumption-the InSIDE (INstrument Strength Independent of Direct Effect) assumption. In this paper, we provide a critical assessment of the MR-Egger method with regard to its implementation and interpretation. While the MR-Egger method is a worthwhile sensitivity analysis for detecting violations of the instrumental variable assumptions, there are several reasons why causal estimates from the MR-Egger method may be biased and have inflated Type 1 error rates in practice, including violations of the InSIDE assumption and the influence of outlying variants. The issues raised in this paper have potentially serious consequences for causal inferences from the MR-Egger approach. We give examples of scenarios in which the estimates from conventional Mendelian randomization methods and MR-Egger differ, and discuss how to interpret findings in such cases.Stephen Burgess is supported by Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (Grant Number 204623/Z/16/Z). Simon G. Thompson is supported by the British Heart Foundation (Grant Number CH/12/2/ 29428)

Making predictions from complex longitudinal data, with application to planning monitoring intervals in a national screening programme.

When biological or physiological variables change over time, we are often interested in making predictions either of future measurements or of the time taken to reach some threshold value. On the basis of longitudinal data for multiple individuals, we develop Bayesian hierarchical models for making these predictions together with their associated uncertainty. Particular aspects addressed, which include some novel components, are handling curvature in individuals' trends over time, making predictions for both underlying and measured levels, making predictions from a single baseline measurement, making predictions from a series of measurements, allowing flexibility in the error and random-effects distributions, and including covariates. In the context of data on the expansion of abdominal aortic aneurysms over time, where reaching a certain threshold leads to referral for surgery, we discuss the practical application of these models to the planning of monitoring intervals in a national screening programme. Prediction of the time to reach a threshold was too imprecise to be practically useful, and we focus instead on limiting the probability of exceeding the threshold after given time intervals. Although more complex models can be shown to fit the data better, we find that relatively simple models seem to be adequate for planning monitoring intervals

Virtual outreach: economic evaluation of joint teleconsultations for patients referred by their general practitioner for a specialist opinion

Objectives To test the hypotheses that, compared with conventional outpatient consultations, joint teleconsultation (virtual outreach) would incur no increased costs to the NHS, reduce costs to patients, and reduce absences from work by patients and their carers.Design Cost consequences study alongside randomised controlled trial.Setting Two hospitals in London and Shrewsbury and 29 general practices in inner London and Wales.Participants 3170 patients identified; 2094 eligible for inclusion and willing to participate. 1051 randomised to virtual outreach and 1043 to standard outpatient appointments.Main outcome measures NHS costs, patient costs, health status (SF-12), time spent attending index consultation, patient satisfaction.Results Overall six month costs were greater for the virtual outreach consultations (pound724 per patient) than for conventional outpatient appointments (pound625): difference in means pound99 ($162; is not an element of138) (95% confidence interval pound10 to pound187, P=0.03). if the analysis is restricted to resource items deemed "attributable" to the index consultation, six month costs were still greater for virtual outreach: difference in means pound108 (pound73 to pound142, P < 0.0001). In both analyses the index consultation accounted for the excess cost. Savings to patients in terms of costs and time occurred in both centres: difference in mean total patient cost 8 pound (5 pound to 10 pound, P < 0.0001). Loss of productive time was less in the virtual outreach group: difference in mean cost pound11 (pound10 to pound12, P < 0.0001).Condusion The main hypothesis that virtual outreach would be cost neutral is rejected, but the hypotheses that costs to patients and losses in productivity would be lower are supported

Evaluating heterogeneity in cumulative meta-analyses

BACKGROUND: Recently developed measures such as I(2 )and H allow the evaluation of the impact of heterogeneity in conventional meta-analyses. There has been no examination of the development of heterogeneity in the context of a cumulative meta-analysis. METHODS: Cumulative meta-analyses of five smoking cessation interventions (clonidine, nicotine replacement therapy using gum and patch, physician advice and acupuncture) were used to calculate I(2 )and H. These values were plotted by year of publication, control event rate and sample size to trace the development of heterogeneity over these covariates. RESULTS: The cumulative evaluation of heterogeneity varied according to the measure of heterogeneity used and the basis of cumulation. Plots produced from the calculations revealed areas of heterogeneity useful in the consideration of potential sources for further study. CONCLUSION: The examination of heterogeneity in conjunction with summary effect estimates in a cumulative meta-analysis offered valuable insight into the evolution of variation. Such information is not available in the context of conventional meta-analysis and has the potential to lead to the development of a richer picture of the effectiveness of interventions

Identification of hydroxyapatite spherules provides new insight into subretinal pigment epithelial deposit formation in the aging eye.

Accumulation of protein- and lipid-containing deposits external to the retinal pigment epithelium (RPE) is common in the aging eye, and has long been viewed as the hallmark of age-related macular degeneration (AMD). The cause for the accumulation and retention of molecules in the sub-RPE space, however, remains an enigma. Here, we present fluorescence microscopy and X-ray diffraction evidence for the formation of small (0.5-20 μm in diameter), hollow, hydroxyapatite (HAP) spherules in Bruch's membrane in human eyes. These spherules are distinct in form, placement, and staining from the well-known calcification of the elastin layer of the aging Bruch's membrane. Secondary ion mass spectrometry (SIMS) imaging confirmed the presence of calcium phosphate in the spherules and identified cholesterol enrichment in their core. Using HAP-selective fluorescent dyes, we show that all types of sub-RPE deposits in the macula, as well as in the periphery, contain numerous HAP spherules. Immunohistochemical labeling for proteins characteristic of sub-RPE deposits, such as complement factor H, vitronectin, and amyloid beta, revealed that HAP spherules were coated with these proteins. HAP spherules were also found outside the sub-RPE deposits, ready to bind proteins at the RPE/choroid interface. Based on these results, we propose a novel mechanism for the growth, and possibly even the formation, of sub-RPE deposits, namely, that the deposit growth and formation begin with the deposition of insoluble HAP shells around naturally occurring, cholesterol-containing extracellular lipid droplets at the RPE/choroid interface; proteins and lipids then attach to these shells, initiating or supporting the growth of sub-RPE deposits

Determining Sex in Golden Eagle (AQUILA CHRYSAETOS) Nestling

Incorporating sex ratios of nestlings into population viability studies increases knowledge of overall health of endangered populations. Currently, a reliable non-invasive method to identify the sex of golden eagle nestlings is not available; however, claims are commonly made based on morphology. Ten biometric measurements from 43 Scottish golden eagles aged 2–7.5 weeks were assessed to see if sex could actually be determined using this non-invasive methodology. Sex was confirmed via molecular analysis of blood samples. Discrete and principal component analyses of the different biometrics could not correctly determine individual nestling sex. Therefore, despite being more invasive, molecular sexing remains the recommended tool of choice for accurate sex identification of Scottish golden eagle nestlings younger than 7.5 weeks of age. This has important implications for golden eagle field studies where empirical morphological measurements are frequently and typically taken, but we have shown are not reliable in determining the sex of such young nestlings