A product of independent beta probabilities dose escalation design for dual-agent phase I trials.

Dual-agent trials are now increasingly common in oncology research, and many proposed dose-escalation designs are available in the statistical literature. Despite this, the translation from statistical design to practical application is slow, as has been highlighted in single-agent phase I trials, where a 3 + 3 rule-based design is often still used. To expedite this process, new dose-escalation designs need to be not only scientifically beneficial but also easy to understand and implement by clinicians. In this paper, we propose a curve-free (nonparametric) design for a dual-agent trial in which the model parameters are the probabilities of toxicity at each of the dose combinations. We show that it is relatively trivial for a clinician's prior beliefs or historical information to be incorporated in the model and updating is fast and computationally simple through the use of conjugate Bayesian inference. Monotonicity is ensured by considering only a set of monotonic contours for the distribution of the maximum tolerated contour, which defines the dose-escalation decision process. Varied experimentation around the contour is achievable, and multiple dose combinations can be recommended to take forward to phase II. Code for R, Stata and Excel are available for implementation.We would like to acknowledge funding from the UK Medical Research Council (grant code U1052.00.014) for this work. We would also like to thank the reviewers for providing some excellent suggestions to help improve the manuscript.This is the final published version. It first appeared at http://onlinelibrary.wiley.com/doi/10.1002/sim.6434/abstract

A scoping methodological review of simulation studies comparing statistical and machine learning approaches to risk prediction for time-to-event data

BACKGROUND: There is substantial interest in the adaptation and application of so-called machine learning approaches to prognostic modelling of censored time-to-event data. These methods must be compared and evaluated against existing methods in a variety of scenarios to determine their predictive performance. A scoping review of how machine learning methods have been compared to traditional survival models is important to identify the comparisons that have been made and issues where they are lacking, biased towards one approach or misleading. METHODS: We conducted a scoping review of research articles published between 1 January 2000 and 2 December 2020 using PubMed. Eligible articles were those that used simulation studies to compare statistical and machine learning methods for risk prediction with a time-to-event outcome in a medical/healthcare setting. We focus on data-generating mechanisms (DGMs), the methods that have been compared, the estimands of the simulation studies, and the performance measures used to evaluate them. RESULTS: A total of ten articles were identified as eligible for the review. Six of the articles evaluated a method that was developed by the authors, four of which were machine learning methods, and the results almost always stated that this developed method's performance was equivalent to or better than the other methods compared. Comparisons were often biased towards the novel approach, with the majority only comparing against a basic Cox proportional hazards model, and in scenarios where it is clear it would not perform well. In many of the articles reviewed, key information was unclear, such as the number of simulation repetitions and how performance measures were calculated. CONCLUSION: It is vital that method comparisons are unbiased and comprehensive, and this should be the goal even if realising it is difficult. Fully assessing how newly developed methods perform and how they compare to a variety of traditional statistical methods for prognostic modelling is imperative as these methods are already being applied in clinical contexts. Evaluations of the performance and usefulness of recently developed methods for risk prediction should be continued and reporting standards improved as these methods become increasingly popular

Youth vaping and smoking and parental vaping: a panel survey

Background: Concerns remain about potential negative impacts of e-cigarettes including possibilities that: youth e-cigarette use (vaping) increases risk of youth smoking; and vaping by parents may have impacts on their children’s vaping and smoking behaviour. Methods: With panel data from 3291 youth aged 10–15 years from the 7th wave of the UK Understanding Society Survey (2015–2017), we estimated effects of youth vaping on youth smoking (ever, current and past year initiation), and of parental vaping on youth smoking and vaping, and examined whether the latter differed by parental smoking status. Propensity weighting was used to adjust for measured confounders and estimate average effects of vaping for all youth, and among youth who vaped. E-values were calculated to assess the strength of unmeasured confounding influences needed to negate our estimates. Results: Associations between youth vaping and youth smoking were attenuated considerably by adjustment for measured confounders. Estimated average effects of youth vaping on youth smoking were stronger for all youth (e.g. OR for smoking initiation: 32.5; 95% CI: 9.8–107.1) than among youth who vaped (OR: 4.4; 0.6–30.9). Relatively strong unmeasured confounding would be needed to explain these effects. Associations between parental vaping and youth vaping were explained by measured confounders. Estimates indicated effects of parental vaping on youth smoking, especially for youth with ex-smoking parents (e.g. OR for smoking initiation: 11.3; 2.7–46.4) rather than youth with currently smoking parents (OR: 1.0; 0.2–6.4), but these could be explained by relatively weak unmeasured confounding. Conclusions While measured confounding accounted for much of the associations between youth vaping and youth smoking, indicating support for underlying propensities, our estimates suggested residual effects that could only be explained away by considerable unmeasured confounding or by smoking leading to vaping. Estimated effects of youth vaping on youth smoking were stronger among the general youth population than among the small group of youth who actually vaped. Associations of parental vaping with youth smoking and vaping were either explained by measured confounding or could be relatively easily explained by unmeasured confounding

Biases incurred from non-random repeat testing of haemoglobin levels in blood donors

To help prevent anaemia, it is a requisite for blood donors to undergo a haemoglobin test to ensure levels are not too low before donation. It is therefore important to have an accurate testing device and strategy to ensure donors are not being inappropriately bled. A recent study in blood donors used a selective testing strategy where if a donor’s haemoglobin level is below the level required for donation, then another reading is taken and if this occurs again, a third and final reading is used. This strategy can reduce the average number of readings required per donor compared to taking three measurements for all donors. However, the final decision-making measurement will on average be higher than a single measurement. In this paper, a selective testing strategy is compared against other strategies. Individual-level biases are derived for the selective strategy and are shown to depend on how close a donor’s true haemoglobin level is to the donation threshold and the magnitude of error in the testing device. A simulation study was conducted using the distribution of haemoglobin levels from a large donor population to investigate the effects different strategies have on population performance. We consider scenarios based on varying the measurement device bias and error, including differential biases that depend on the underlying haemoglobin level. Discriminatory performance is shown to be affected when using the selective testing strategies, especially when measurement error is large and when differential bias is present in the device. We recommend that the average of a number of readings should be used in preference to selective testing strategies if multiple measurements are available

Potential outcome simulation for efficient head-to-head comparison of adaptive dose-finding designs

Dose-finding trials are a key component of the drug development process and rely on a statistical design to help inform dosing decisions. Triallists wishing to choose a design require knowledge of operating characteristics of competing methods. This is often assessed using a large-scale simulation study with multiple designs and configurations investigated, which can be time-consuming and therefore limits the scope of the simulation. We introduce a new approach to the design of simulation studies of dose-finding trials. The approach simulates all potential outcomes that individuals could experience at each dose level in the trial. Datasets are simulated in advance and then the same datasets are applied to each of the competing methods to enable a more efficient head-to-head comparison. In two case-studies we show sizeable reductions in Monte Carlo error for comparing a performance metric between two competing designs. Efficiency gains depend on the similarity of the designs. Comparing two Phase I/II design variants, with high correlation of recommending the same optimal biologic dose, we show that the new approach requires a simulation study that is approximately 30 times smaller than the conventional approach. Furthermore, advance-simulated trial datasets can be reused to assess the performance of designs across multiple configurations. We recommend researchers consider this more efficient simulation approach in their dose-finding studies and we have updated the R package escalation to help facilitate implementation.Comment: 27 pages, 4 figures, 1 tabl

Alcohol intake in relation to fatal and non-fatal incident coronary heart disease and stroke in the EPIC-CVD study.

ABSTRACT Objective To investigate the association between alcohol consumption (at baseline and over lifetime) and non-fatal and fatal coronary heart disease (CHD) and stroke. Design Multicentre case-cohort study. Setting A study of cardiovascular disease (CVD) aetiology (EPIC-CVD) within the European Prospective Investigation into Cancer and nutrition cohort from 8 European countries. Participants A case-cohort study of 32 549 participants without baseline CVD, comprised of incident CVD cases and a subcohort for comparison. Main outcome measure Non-fatal and fatal CHD and stroke (including ischaemic and haemorrhagic). Results There were 9307 non-fatal CHD, 1699 fatal CHD, 5855 non-fatal stroke and 733 fatal stroke events. Baseline alcohol intake was inversely associated with non-fatal CHD, with a hazard ratio of 0.94 (95% confidence interval 0.92 to 0.96) per 12 g/day higher intake. There was a J-shaped association between baseline alcohol intake and risk of fatal CHD (hazard ratios=0.83 [95% confidence interval 0.70 to 0.98], 0.65 [0.53 to 0.81], and 0.82 [0.65 to 1.03] for categories 5.0-14.9 g/day, 15.0-29.9 g/day, and 30.0-59.9 g/day, respectively, compared with 0.1-4.9 g/day. In contrast, hazard ratios for non-fatal and fatal stroke risk were 1.04 (95% confidence interval 1.02 to 1.07), and 1.05 (0.98 to 1.13) per 12 g/day increase in baseline alcohol intake, respectively, including broadly similar findings for ischaemic and haemorrhagic stroke. Associations with cardiovascular outcomes were broadly similar with average lifetime alcohol consumption as for baseline alcohol intake, and across the eight countries we studied. There was no strong evidence for interactions of alcohol consumption with smoking status on the risk of CVD events. Conclusions Alcohol intake was inversely associated with non-fatal CHD risk but positively associated with risk of different stroke subtypes, highlighting the opposing associations of alcohol intake with different cardiovascular disease types and strengthening the evidence for policies to reduce alcohol consumption.This work was supported by the Direction Générale de la Santé (French Ministry of Health) (grant GR-IARC-2003-09-12-01). EPIC-CVD has been supported by the European Union Framework 7 (HEALTH-F2-2012-279233), the European Research Council (268834), the UK Medical Research Council (G0800270 and MR/L003120/1), the British Heart Foundation (SP/09/002 and RG/08/014 and RG13/13/30194), and the UK National Institute of Health Research. The establishment of the random subcohort was supported by the EU Sixth Framework Programme (FP6) (grant LSHM_CT_2006_037197 to the InterAct project) and the Medical Research Council Epidemiology Unit (grants MC_UU_12015/1 and MC_UU_12015/5)

Landmark models for optimizing the use of repeated measurements of risk factors in electronic health records to predict future disease risk

The benefits of using electronic health records for disease risk screening and personalized heathcare decisions are becoming increasingly recognized. We present a computationally feasible statistical approach to address the methodological challenges in utilizing historical repeat measures of multiple risk factors recorded in electronic health records to systematically identify patients at high risk of future disease. The approach is principally based on a two-stage dynamic landmark model. The first stage estimates current risk factor values from all available historical repeat risk factor measurements by landmark-age-specific multivariate linear mixed-effects models with correlated random-intercepts, which account for sporadically recorded repeat measures, unobserved data and measurements 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. Methods are exemplified by developing and validating a dynamic 10-year cardiovascular disease risk prediction model using electronic primary care records for age, diabetes status, hypertension treatment, smoking status, systolic blood pressure, total and high-density lipoprotein cholesterol from 41,373 individuals in 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%CI: 0.039, 0.042]) and had good discrimination (C-index = 0.768 [95%CI: 0.759, 0.777]).This work was funded by the Medical Research Council (MRC) (grant MR/K014811/1). J.B. was supported by an MRC fellowship (grant G0902100) and the MRC Unit Program (grant MC_UU_00002/5). R.H.K. was supported by an MRC Methodology Fellowship (grant MR/M014827/1)

AplusB: A Web Application for Investigating A + B Designs for Phase I Cancer Clinical Trials.

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.GMW and APM are supported by the UK Medical Research Council (www.mrc.ac.uk; grant number G0800860). MJS is supported by a European Research Council Advanced Investigator Award: EPIC-Heart (https://erc.europa.eu; grant number 268834), the UK Medical Research Council (grant number MR/L003120/1), the British Heart Foundation (www.bhf.org.uk), and the Cambridge National Institute for Health Research Biomedical Research Centre (http://www.cambridge-brc.org.uk). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.This is the final version of the article. It first appeared from PLOS at http://dx.doi.org/10.1371/journal.pone.0159026

Causal effects of transitions to adult roles on early adult smoking and drinking: Evidence from three cohorts

Transitions into work and family roles have become increasingly delayed as participation in tertiary education widens. Such transitions may have adverse or beneficial effects on health behaviours such as smoking and drinking (alcohol). Role socialisation effects may reduce smoking or drinking, but clustering of transitions may lead to role overload, weakening or reversing any role socialisation effects. Effects of transitions were examined in three UK cohorts: the 1958 National Child Development Study, the 1970 British Birth Cohort Study, and the West of Scotland: Twenty-07 Youth Cohort (from around Glasgow, growing up in the same time period as the 1970 cohort). Latent class analysis was employed to identify heterogeneous patterns of transition timing for leaving education, entering employment, starting cohabitation, having a first child, and leaving the parental home. Propensity weighting was then used to estimate causal effects of transition patterns (relative to tertiary education) on smoking and heavy drinking in early adulthood (ages 22–26), adjusting for background confounders (gender, parental socioeconomic position, family structure, parental and adolescent health behaviours, adolescent distress and school performance). Three groups made early (age 16) transitions from education to employment and then either delayed other transitions, made other transitions quickly, or staggered transitions with cohabitation beginning around ages 19–21; a fourth group transitioned from education to employment around ages 17–18. Compared to those in tertiary education with similar background characteristics, those in these groups generally had higher levels of smoking, especially where transitions were more clustered, but less heavy drinking (except those who delayed other transitions after moving into employment). Results partially supported role socialisation effects for drinking, and role overload effects for smoking. Wider participation in tertiary education could have helped reduce smoking levels in these cohorts, but might also have increased risk for heavy drinking

Patterns of initiation in the poetry of Ted Hughes from 1970 to 1980

This study seeks to give a close reading of the poems in the major sequences by Ted Hughes published since 1970. The consideration of the poems centres upon the influence of initiatory religious patterns and their mythologies upon the poet's work. A key to such initiatory patterns is the primitive religious phenomenon known as shamanism. The first chapter of the thesis charts evidence of Hughes's fascination with shamanic practice and shows its pervasive and central influence from early poems such as 'Jaguar' right up to the pivotal work of Caudate. In chapters on each of the three volumes preceding Gaudete Hughes is shown as being preoccupied with shamanic questions rather than with the answers that a fully initiated shaman is able to give. Crow takes its protagonist to the very threshold of initiation, as does Prometheus on his Crag, but the need for the contextualization of the abstract experiences in the poems becomes very clear. Cave Birds is an attempt to introduce a coda of the realities of common human experience, but it is not until Gaudete that the strong mythological element in Hughes's work is disciplined into a greater, though flawed, whole. More and more Hughes seeks to transform the profane experience of our present life into a perception of the sacred. In Gaudete Lumb fails to do this with the rituals of his personal fertility cult and those around him are killed or emotionally damaged. But he himself is radically changed. The Epilogue Poems of Gaudete reflect this change and point the way away from a poetic reliance on the mechanisms of mythology to a living out of ritual in the poetry itself. Both 'Moortown' and Remains of Elmet exemplify this development in their perception of the sacredness of Nature. By Adam and the Sacred Nine the mythological element can now be presented yoked in a balanced way to the sensitivity of the poetry