CONTEXT Tumor necrosis factor (TNF) plays an important role in host defense and tumor growth control. Therefore, anti-TNF antibody therapies may increase the risk of serious infections and ...malignancies. OBJECTIVE To assess the extent to which anti-TNF antibody therapies may increase the risk of serious infections and malignancies in patients with rheumatoid arthritis by performing a meta-analysis to derive estimates of sparse harmful events occurring in randomized trials of anti-TNF therapy. DATA SOURCES A systematic literature search of EMBASE, MEDLINE, Cochrane Library, and electronic abstract databases of the annual scientific meetings of both the European League Against Rheumatism and the American College of Rheumatology was conducted through December 2005. This search was complemented with interviews of the manufacturers of the 2 licensed anti-TNF antibodies. STUDY SELECTION We included randomized, placebo-controlled trials of the 2 licensed anti-TNF antibodies (infliximab and adalimumab) used for 12 weeks or more in patients with rheumatoid arthritis. Nine trials met our inclusion criteria, including 3493 patients who received anti-TNF antibody treatment and 1512 patients who received placebo. DATA EXTRACTION Data on study characteristics to assess study quality and intention-to-treat data for serious infections and malignancies were abstracted. Published information from the trials was supplemented by direct contact between principal investigators and industry sponsors. DATA SYNTHESIS We calculated a pooled odds ratio (Mantel-Haenszel methods with a continuity correction designed for sparse data) for malignancies and serious infections (infection that requires antimicrobial therapy and/or hospitalization) in anti-TNF–treated patients vs placebo patients. We estimated effects for high and low doses separately. The pooled odds ratio for malignancy was 3.3 (95% confidence interval CI, 1.2-9.1) and for serious infection was 2.0 (95% CI, 1.3-3.1). Malignancies were significantly more common in patients treated with higher doses compared with patients who received lower doses of anti-TNF antibodies. For patients treated with anti-TNF antibodies in the included trials, the number needed to harm was 154 (95% CI, 91-500) for 1 additional malignancy within a treatment period of 6 to 12 months. For serious infections, the number needed to harm was 59 (95% CI, 39-125) within a treatment period of 3 to 12 months. CONCLUSIONS There is evidence of an increased risk of serious infections and a dose-dependent increased risk of malignancies in patients with rheumatoid arthritis treated with anti-TNF antibody therapy. The formal meta-analysis with pooled sparse adverse events data from randomized controlled trials serves as a tool to assess harmful drug effects.
A third of deaths in the UK from ruptured abdominal aortic aneurysm (AAA) are in women. In men, national screening programmes reduce deaths from AAA and are cost-effective. The benefits, harms, and ...cost-effectiveness in offering a similar programme to women have not been formally assessed, and this was the aim of this study.
We developed a decision model to assess predefined outcomes of death caused by AAA, life years, quality-adjusted life years, costs, and the incremental cost-effectiveness ratio for a population of women invited to AAA screening versus a population who were not invited to screening. A discrete event simulation model was set up for AAA screening, surveillance, and intervention. Relevant women-specific parameters were obtained from sources including systematic literature reviews, national registry or administrative databases, major AAA surgery trials, and UK National Health Service reference costs.
AAA screening for women, as currently offered to UK men (at age 65 years, with an AAA diagnosis at an aortic diameter of ≥3·0 cm, and elective repair considered at ≥5·5cm) gave, over 30 years, an estimated incremental cost-effectiveness ratio of £30 000 (95% CI 12 000–87 000) per quality-adjusted life year gained, with 3900 invitations to screening required to prevent one AAA-related death and an overdiagnosis rate of 33%. A modified option for women (screening at age 70 years, diagnosis at 2·5 cm and repair at 5·0 cm) was estimated to have an incremental cost-effectiveness ratio of £23 000 (9500–71 000) per quality-adjusted life year and 1800 invitations to screening required to prevent one AAA-death, but an overdiagnosis rate of 55%. There was considerable uncertainty in the cost-effectiveness ratio, largely driven by uncertainty about AAA prevalence, the distribution of aortic sizes for women at different ages, and the effect of screening on quality of life.
By UK standards, an AAA screening programme for women, designed to be similar to that used to screen men, is unlikely to be cost-effective. Further research on the aortic diameter distribution in women and potential quality of life decrements associated with screening are needed to assess the full benefits and harms of modified options.
UK National Institute for Health Research Health Technology Assessment programme.
Abstract
Background
This study investigated whether sex-specific differences in preoperative/perioperative standard of care (SOC) account for disparity in outcomes after elective infrarenal abdominal ...aortic aneurysm repair.
Methods
This was a retrospective cohort study of elective infrarenal abdominal aortic aneurysm repairs (2013–2020) using depersonalized patient-level National Vascular Registry data. SOC was defined for waiting times, preoperative assessment (multidisciplinary/anaesthetic review), cardiovascular risk prevention, and perioperative medication. The primary outcome was major cardiovascular event and/or death (MACED).
Results
Some 21 810 patients with an infrarenal abdominal aortic aneurysm were included, 2380 women and 19 430 men. Women less often underwent aneurysm repair within SOC waiting times (51.5 versus 59.3 per cent; P < 0.001), but were equally likely to receive preoperative assessment (72.1 versus 72.5 per cent; P = 0.742). Women were less likely to receive secondary prevention for known cardiac disease (34.9 versus 39.6 per cent; P = 0.015), but more often met overall cardiovascular risk prevention standards (52.1 versus 47.3 per cent; P < 0.001). Women were at greater risk of MACED (open: 12.0 versus 8.9 per cent, P < 0.001; endovascular: 4.9 versus 2.9 per cent, P < 0.001; risk-adjusted OR 1.33, 95 per cent c.i. 1.12 to 1.59). A significant reduction in the odds of MACED was associated with preoperative assessment (OR 0.86, 0.75 to 0.98) and SOC waiting times (OR 0.78, 0.69 to 0.87). There was insufficient evidence to confirm a significant sex-specific difference in the effect of SOC preoperative assessment (women: OR 0.69, 0.50 to 0.97; men: OR 0.89, 0.77 to 1.03; interaction P = 0.170) or SOC waiting times (women: OR 0.84, 0.62 to 1.16; men: OR 0.76, 0.67 to 0.87; interaction P = 0.570) on the risk of MACED.
Conclusion
SOC waiting times and preoperative assessment were not met for both sexes, which was associated with an increased risk of MACED. Sex-specific differences in SOC attenuated but did not fully account for the increased risk of MACED in women.
This study used data from the National Vascular Registry (21 810 patients; 2380 women and 19 430 men) to investigate whether sex-specific differences in preoperative/perioperative standard of care account for disparity in major adverse cardiovascular event and/or death following elective infrarenal abdominal aortic aneurysm repair. The study demonstrated that provision of standard of care within the infrarenal abdominal aortic aneurysm repair pathway was associated with a reduction in the risk of major adverse cardiovascular event and/or death but was below minimum attainment targets for both sexes. Standard of care received was lower for women, and their risk of major adverse cardiovascular event and/or death was greater. Although standard of care did not fully account for the sex-specific disparity in outcomes, a significant risk reduction for women receiving preoperative assessment was observed.
IMPORTANCE Small abdominal aortic aneurysms (AAAs 3.0 cm-5.4 cm in diameter) are monitored by ultrasound surveillance. The intervals between surveillance scans should be chosen to detect an expanding ...aneurysm prior to rupture. OBJECTIVE To limit risk of aneurysm rupture or excessive growth by optimizing ultrasound surveillance intervals. DATA SOURCES AND STUDY SELECTION Individual patient data from studies of small AAA growth and rupture were assessed. Studies were identified for inclusion through a systematic literature search through December 2010. Study authors were contacted, which yielded 18 data sets providing repeated ultrasound measurements of AAA diameter over time in 15 471 patients. DATA EXTRACTION AAA diameters were analyzed using a random-effects model that allowed for between-patient variability in size and growth rate. Rupture rates were analyzed by proportional hazards regression using the modeled AAA diameter as a time-varying covariate. Predictions of the risks of exceeding 5.5-cm diameter and of rupture within given time intervals were estimated and pooled across studies by random effects meta-analysis. RESULTS AAA growth and rupture rates varied considerably across studies. For each 0.5-cm increase in AAA diameter, growth rates increased on average by 0.59 mm per year (95% CI, 0.51-0.66) and rupture rates increased by a factor of 1.91 (95% CI, 1.61-2.25). For example, to control the AAA growth risk in men of exceeding 5.5 cm to below 10%, on average, a 7.4-year surveillance interval (95% CI, 6.7-8.1) is sufficient for a 3.0-cm AAA, while an 8-month interval (95% CI, 7-10) is necessary for a 5.0-cm AAA. To control the risk of rupture in men to below 1%, the corresponding estimated surveillance intervals are 8.5 years (95% CI, 7.0-10.5) and 17 months (95% CI, 14-22). CONCLUSION AND RELEVANCE In contrast to the commonly adopted surveillance intervals in current AAA screening programs, surveillance intervals of several years may be clinically acceptable for the majority of patients with small AAA.
In phase I cancer clinical trials, the maximum tolerated dose of a new drug is often found by a dose-escalation method known as the A + B design. We have developed an interactive web application, ...AplusB, which computes and returns exact operating characteristics of A + B trial designs. The application has a graphical user interface (GUI), requires no programming knowledge and is free to access and use on any device that can open an internet browser. A customised report is available for download for each design that contains tabulated operating characteristics and informative plots, which can then be compared with other dose-escalation methods. We present a step-by-step guide on how to use this application and provide several illustrative examples of its capabilities.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract
The benefits of using electronic health records (EHRs) for disease risk screening and personalized health-care decisions are being increasingly recognized. Here we present a computationally ...feasible statistical approach with which to address the methodological challenges involved in utilizing historical repeat measures of multiple risk factors recorded in EHRs to systematically identify patients at high risk of future disease. The approach is principally based on a 2-stage dynamic landmark model. The first stage estimates current risk factor values from all available historical repeat risk factor measurements via landmark-age–specific multivariate linear mixed-effects models with correlated random intercepts, which account for sporadically recorded repeat measures, unobserved data, and measurement errors. The second stage predicts future disease risk from a sex-stratified Cox proportional hazards model, with estimated current risk factor values from the first stage. We exemplify these methods by developing and validating a dynamic 10-year cardiovascular disease risk prediction model using primary-care EHRs for age, diabetes status, hypertension treatment, smoking status, systolic blood pressure, total cholesterol, and high-density lipoprotein cholesterol in 41,373 persons from 10 primary-care practices in England and Wales contributing to The Health Improvement Network (1997–2016). Using cross-validation, the model was well-calibrated (Brier score = 0.041, 95% confidence interval: 0.039, 0.042) and had good discrimination (C-index = 0.768, 95% confidence interval: 0.759, 0.777).
Joint models of longitudinal and survival data can be used to predict the risk of a future event occurring based on the evolution of an endogenous biomarker measured repeatedly over time. This has ...led naturally to the use of dynamic predictions that update each time a new longitudinal measurement is provided. In this paper, we show how such predictions can be utilised within a fuller decision modelling framework, in particular to allow planning of future interventions for patients under a ‘watchful waiting’ care pathway. Through the objective of maximising expected life‐years, the predicted risks associated with not intervening (e.g. the occurrence of severe sequelae) are balanced against risks associated with the intervention (e.g. operative risks). Our example involves patients under surveillance in an abdominal aortic aneurysm screening programme where a joint longitudinal and survival model is used to associate longitudinal measurements of aortic diameter with the risk of aneurysm rupture. We illustrate how the decision to intervene, which is currently based on a diameter measurement greater than a certain threshold, could be made more personalised and dynamic through the application of a decision modelling approach.
Abstract
Cardiovascular disease (CVD) risk-prediction models are used to identify high-risk individuals and guide statin initiation. However, these models are usually derived from individuals who ...might initiate statins during follow-up. We present a simple approach to address statin initiation to predict “statin-naive” CVD risk. We analyzed primary care data (2004–2017) from the UK Clinical Practice Research Datalink for 1,678,727 individuals (aged 40–85 years) without CVD or statin treatment history at study entry. We derived age- and sex-specific prediction models including conventional risk factors and a time-dependent effect of statin initiation constrained to 25% risk reduction (from trial results). We compared predictive performance and measures of public-health impact (e.g., number needed to screen to prevent 1 event) against models ignoring statin initiation. During a median follow-up of 8.9 years, 103,163 individuals developed CVD. In models accounting for (versus ignoring) statin initiation, 10-year CVD risk predictions were slightly higher; predictive performance was moderately improved. However, few individuals were reclassified to a high-risk threshold, resulting in negligible improvements in number needed to screen to prevent 1 event. In conclusion, incorporating statin effects from trial results into risk-prediction models enables statin-naive CVD risk estimation and provides moderate gains in predictive ability but had a limited impact on treatment decision-making under current guidelines in this population.
To estimate the prevalence of, and number of unobserved people with opioid dependence by sex and age group in New South Wales (NSW), Australia.
We applied a Bayesian statistical modelling approach to ...opioid agonist treatment records linked to adverse event rate data. We estimated prevalence from three types of adverse event separately: opioid mortality, opioid-poisoning hospitalizations and opioid-related charges. We extended the model and produced prevalence estimates from a 'multi-source' model based on all three types of adverse event data.
This study was conducted in NSW, Australia, 2014-16 using data from the Opioid Agonist Treatment and Safety (OATS) study, which included all people who had received treatment for opioid dependence in NSW. Aggregate data were obtained on numbers of adverse events in NSW. Rates of each adverse event type within the OATS cohort were modelled. Population data were provided by State and Commonwealth agencies.
Prevalence of opioid dependence among those aged 15-64 years in 2016 was estimated to be 0.96% (95% credible interval CrI = 0.82%, 1.12%) from the mortality model, 0.75% (95% CrI = 0.70%, 0.83%) from hospitalizations, 0.95% (95% CrI = 0.90%, 0.99%) from charges and 0.92% (95% CrI = 0.88%, 0.96%) from the multi-source model. Of the estimated 46 460 (95% CrI = 44 680, 48 410) people with opioid dependence in 2016 from the multi-source model, approximately one-third (16 750, 95% CrI = 14 960, 18 690) had no record of opioid agonist treatment within the last 4 years. From the multi-source model, prevalence in 2016 was estimated to be 1.24% (95% CrI = 1.18%, 1.31%) in men aged 15-44, 1.22% (95% CrI = 1.14%, 1.31%) in men 45-64, 0.63% (95% CrI = 0.59%, 0.68%) in women aged 15-44 and 0.56% (95% CrI = 0.50%, 0.63%) in women aged 45-64.
A Bayesian statistical approach to estimate prevalence from multiple adverse event types simultaneously calculates that the estimated prevalence of opioid dependence in NSW, Australia in 2016 was 0.92%, higher than previous estimates.
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