Trastuzumab-associated cardiac events in the Persephone trial.

BACKGROUND: We report cardiac events in the Persephone trial which compares 6-12 months of adjuvant trastuzumab in women with confirmed HER2-positive, early-stage breast cancer. METHODS: Clinical cardiac events were defined as any of the following: symptoms and/or signs of congestive heart failure (CHF) and new or altered CHF medication. In addition, left ventricular ejection fraction (LVEF) was measured at baseline and then 3 monthly for 12 months. RESULTS: A total of 2500 patients, aged 22-82, were included: 1251 randomised to 12 months and 1249 to 6 months of trastuzumab treatment. A total of 93% (2335/2500) received anthracyclines, 49% of these (1136/2335) with taxanes. Cardiotoxicity delayed treatment in 6% of 12-month and 4% of 6-month patients (P=0.01), and stopped treatment early in 8% (96/1214) of 12-month and 4% (45/1216) of 6-month patients (P3 cycles of anthracycline was associated with higher risk of cardiac events only for 12-month patients (OR 1.41 (1.04-1.90)), and not for 6-month patients (OR 1.28 (0.91-1.79)). CONCLUSIONS: We demonstrate significantly fewer cardiac events from 6 months of adjuvant trastuzumab compared with that from 12 months. This cardiac signal adds importance to the question of the optimum duration of adjuvant trastuzumab treatment. If 6 months is proven to have non-inferior outcomes to 12 months treatment, these data would support 6 months as the standard of care.National Institute of Health Research Health Technology Assessment (NIHR HTA) Programme UK. Funding reference number - 06/303/98This is the author accepted manuscript. The final version is available from Nature Publishing Group via https://doi.org/10.1038/bjc.2016.35

Background ozone over the United States in summer: Origin, trend, and contribution to pollution episodes

Observations indicate that ozone (O3) concentrations in surface air over the United States in summer contain a 20–45 ppbv background contribution, presumably reflecting transport from outside the North American boundary layer. We use a three-dimensional global model of tropospheric chemistry driven by assimilated meteorological observations to investigate the origin of this background and to quantify its contribution to total surface O3 on both average and highly polluted summer days. The model simulation is evaluated with a suite of surface and aircraft observations over the United States from the summer of 1995. The model reproduces the principal features in the observed distributions of O3 and its precursors, including frequency distributions of O3 concentrations and the development of regional high-O3 episodes in the eastern United States. Comparison of simulations with 1995 versus 1980 global fossil fuel emissions indicates that the model captures the previously observed decrease in the high end of the O3 probability distribution in surface air over the United States (reflecting reduction of domestic hydrocarbon emissions) and the increase in the low end (reflecting, at least in the model, rising Asian emissions). In the model, background O3 produced outside of the North American boundary layer contributes an average 25–35 ppbv to afternoon O3 concentrations in surface air in the western United States. and 15–30 ppbv in the eastern United States during the summer of 1995. This background generally decays to below 15 ppbv during the stagnation conditions conducive to exceedances of the 8-hour 0.08 ppmv (80 ppbv) National Ambient Air Quality Standard (NAAQS) for O3. A high background contribution of 25–40 ppbv is found during 9% of these exceedances, reflecting convective mixing of free tropospheric O3 from aloft, followed by rapid production within the U.S. boundary layer. Anthropogenic emissions in Asia and Europe are found to increase afternoon O3 concentrations in surface air over the United States by typically 4–7 ppbv, under both average and highly polluted conditions. This enhancement is particularly large (up to 14 ppbv) for O3 concentrations in the 50–70 ppbv range, and would represent a major concern if the NAAQS were to be tightened

DAG-informed regression modelling, agent-based modelling, and microsimulation modelling: A critical comparison of methods for causal inference

The current paradigm for causal inference in epidemiology relies primarily on the evaluation of counterfactual contrasts via statistical regression models informed by graphical causal models (often in the form of directed acyclic graphs, or DAGs) and their underlying mathematical theory. However, there have been growing calls for supplementary methods, and one such method that has been proposed is agent-based modelling due to its potential for simulating counterfactuals. However, within the epidemiological literature there currently exists a general lack of clarity regarding what exactly agent-based modelling is (and is not) and, importantly, how it differs from microsimulation modelling – perhaps its closest methodological comparator. We clarify this distinction by briefly reviewing the history of each method, which provides context for their similarities and differences, and casts light on the types of research questions that they have evolved (and thus are well-suited) to answering; we do the same for DAG-informed regression methods. The distinct historical evolutions of DAG-informed regression modelling, microsimulation modelling, and agent-based modelling have given rise to distinct features of the methods themselves, and provide a foundation for critical comparison. Not only are the three methods well-suited to addressing different types of causal questions, but in doing so they place differing levels of emphasis on fixed and random effects, and also tend to operate on different timescales and in different timeframes

Home and Online Management and Evaluation of Blood Pressure (HOME BP) using a digital intervention in poorly controlled hypertension: randomised controlled trial

Objective: The HOME BP (Home and Online Management and Evaluation of Blood Pressure) trial aimed to test a digital intervention for hypertension management in primary care by combining self-monitoring of blood pressure with guided self-management. Design: Unmasked randomised controlled trial with automated ascertainment of primary endpoint. Setting: 76 general practices in the United Kingdom. Participants: 622 people with treated but poorly controlled hypertension (>140/90 mm Hg) and access to the internet. Interventions: Participants were randomised by using a minimisation algorithm to self-monitoring of blood pressure with a digital intervention (305 participants) or usual care (routine hypertension care, with appointments and drug changes made at the discretion of the general practitioner; 317 participants). The digital intervention provided feedback of blood pressure results to patients and professionals with optional lifestyle advice and motivational support. Target blood pressure for hypertension, diabetes, and people aged 80 or older followed UK national guidelines. Main outcome measures: The primary outcome was the difference in systolic blood pressure (mean of second and third readings) after one year, adjusted for baseline blood pressure, blood pressure target, age, and practice, with multiple imputation for missing values. Results: After one year, data were available from 552 participants (88.6%) with imputation for the remaining 70 participants (11.4%). Mean blood pressure dropped from 151.7/86.4 to 138.4/80.2 mm Hg in the intervention group and from 151.6/85.3 to 141.8/79.8 mm Hg in the usual care group, giving a mean difference in systolic blood pressure of −3.4 mm Hg (95% confidence interval −6.1 to −0.8 mm Hg) and a mean difference in diastolic blood pressure of −0.5 mm Hg (−1.9 to 0.9 mm Hg). Results were comparable in the complete case analysis and adverse effects were similar between groups. Within trial costs showed an incremental cost effectiveness ratio of £11 ($15, €12; 95% confidence interval £6 to £29) per mm Hg reduction. Conclusions: The HOME BP digital intervention for the management of hypertension by using self-monitored blood pressure led to better control of systolic blood pressure after one year than usual care, with low incremental costs. Implementation in primary care will require integration into clinical workflows and consideration of people who are digitally excluded. Trial registration: ISRCTN13790648

Living fast, dying when? The link between aging and energetics

The idea that aging should be linked to energy expenditure has a long history that can be traced to the late 1800s and the industrial revolution. Machines that are run fast wear out more quickly, so the notion was born that humans and animals might experience similar fates: the faster they live (expressed as greater energy expenditure), the sooner they die. Evidence supporting the “rate-of-living” theory was gleaned from the scaling of resting metabolism and life span as functions of body mass. The product of these factors yields a mass-invariant term, equivalent to the “amount of living.” There are at least four problems with this evidence, which are summarized and reviewed in this communication: 1) life span is a poor measure of aging, 2) resting metabolism is a poor measure of energy expenditure, 3) the effects are confounded by body mass and 4) the comparisons made are not phylogenetically independent. We demonstrate that there is a poor association between resting metabolic rate (RMR) and daily energy expenditure (DEE) measured using the doubly labeled water (DLW) method at the level of species. Nevertheless, the scaling relation between DEE and body mass still has the same scaling exponent as the RMR and body mass relationship. Thus, if we use DEE rather than RMR in the analysis, the rate-of-living ideas are still supported. Data for 13 species of small mammal were obtained, where energy demands by DLW and longevity were reliably known. In these species, there was a strong negative relationship between residual longevity and residual DEE, both with the effects of body mass removed (r2 = 0.763, F = 32.1, P < 0.001). Hence, the association of energy demands and life span is not attributed to the confounding effects of body size. We subjected these latter data to an analysis that extracts phylogenetically independent contrasts, and the relationship remained significant (r2 = 0.815, F = 39.74, P < 0.001). Small mammals that live fast really do die young. However, there are very large differences between species in the amounts of living that each enjoy and these disparities are even greater when other taxa are included in the comparisons. Such differences are incompatible with the “rate-of-living” theory. However, the link between energetics and aging across species is reconcilable within the framework of the “free-radical damage hypothesis” and the “disposable soma hypothesis.” Within species one might anticipate the rate-of-living model would be more appropriate. We reviewed data generated from three different sources to evaluate whether this were so, studies in which metabolic rate is experimentally increased and impacts on life span followed, studies of caloric restriction and studies where links between natural variation in metabolism and life span are sought. This review reveals that there might be contrasting effects of resting and nonresting energy expenditure on aging, with increases in the former being protective and increases in the latter being harmful