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

The use of repeated blood pressure measures for cardiovascular risk prediction: a comparison of statistical models in the ARIC study.

Many prediction models have been developed for the risk assessment and the prevention of cardiovascular disease in primary care. Recent efforts have focused on improving the accuracy of these prediction models by adding novel biomarkers to a common set of baseline risk predictors. Few have considered incorporating repeated measures of the common risk predictors. Through application to the Atherosclerosis Risk in Communities study and simulations, we compare models that use simple summary measures of the repeat information on systolic blood pressure, such as (i) baseline only; (ii) last observation carried forward; and (iii) cumulative mean, against more complex methods that model the repeat information using (iv) ordinary regression calibration; (v) risk-set regression calibration; and (vi) joint longitudinal and survival models. In comparison with the baseline-only model, we observed modest improvements in discrimination and calibration using the cumulative mean of systolic blood pressure, but little further improvement from any of the complex methods. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.J.K.B. was supported by the Medical Research Council grant numbers G0902100 and MR/K014811/1. This work was funded by the UK Medical Research Council (G0800270), British Heart Foundation (SP/09/002), UK National Institute for Health Research Cambridge Biomedical Research Centre, European Research Council (268834) and European Commission Framework Programme 7 (HEALTH-F2-2012-279233). The ARIC study is carried out as a collaborative study supported by the National Heart, Lung, and Blood Institute contracts (HHSN268201100005C, HHSN268201100006C, HHSN268201100007C, HHSN268201100008C, HHSN268201100009C, HHSN268201100010C, HHSN268201100011C and HHSN268201100012C).This is the final version of the article. It first appeared from Wiley via https://doi.org/10.1002/sim.714

Modelling semi-attributable toxicity in dual-agent phase I trials with non-concurrent drug administration.

In oncology, combinations of drugs are often used to improve treatment efficacy and/or reduce harmful side effects. Dual-agent phase I clinical trials assess drug safety and aim to discover a maximum tolerated dose combination via dose-escalation; cohorts of patients are given set doses of both drugs and monitored to see if toxic reactions occur. Dose-escalation decisions for subsequent cohorts are based on the number and severity of observed toxic reactions, and an escalation rule. In a combination trial, drugs may be administered concurrently or non-concurrently over a treatment cycle. For two drugs given non-concurrently with overlapping toxicities, toxicities occurring after administration of the first drug yet before administration of the second may be attributed directly to the first drug, whereas toxicities occurring after both drugs have been given some present ambiguity; toxicities may be attributable to the first drug only, the second drug only or the synergistic combination of both. We call this mixture of attributable and non-attributable toxicity semi-attributable toxicity. Most published methods assume drugs are given concurrently, which may not be reflective of trials with non-concurrent drug administration. We incorporate semi-attributable toxicity into Bayesian modelling for dual-agent phase I trials with non-concurrent drug administration and compare the operating characteristics to an approach where this detail is not considered. Simulations based on a trial for non-concurrent administration of intravesical Cabazitaxel and Cisplatin in early-stage bladder cancer patients are presented for several scenarios and show that including semi-attributable toxicity data reduces the number of patients given overly toxic combinations. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.G.M. Wheeler and A.P. Mander are supported by the Medical Research Council (grant number G0800860). M.J. Sweeting is supported by a European Research Council Advanced Investigator Award: EPIC-Heart (grant number 268834), the UK Medical Research Council (grant number MR/L003120/1), the British Heart Foundation and the Cambridge National Institute for Health Research Biomedical Research Centre. S.M. Lee is supported by the American Cancer Society (grant number MRSG-13-146-01-CPHPS).This is the final version of the article. It first appeared from Wiley via http://dx.doi.org/10.1002/sim.691

Optimal individualized decision rules from a multi-arm trial: A comparison of methods and an application to tailoring inter-donation intervals among blood donors in the UK.

There is a growing interest in precision medicine where individual heterogeneity is incorporated into decision-making and treatments are tailored to individuals to provide better healthcare. One important aspect of precision medicine is the estimation of the optimal individualized treatment rule (ITR) that optimizes the expected outcome. Most methods developed for this purpose are restricted to the setting with two treatments, while clinical studies with more than two treatments are common in practice. In this work, we summarize methods to estimate the optimal ITR in the multi-arm setting and compare their performance in large-scale clinical trials via simulation studies. We then illustrate their utilities with a case study using the data from the INTERVAL trial, which randomly assigned over 20,000 male blood donors from England to one of the three inter-donation intervals (12-week, 10-week, and eight-week) over two years. We estimate the optimal individualized donation strategies under three different objectives. Our findings are fairly consistent across five different approaches that are applied: when we target the maximization of the total units of blood collected, almost all donors are assigned to the eight-week inter-donation interval, whereas if we aim at minimizing the low hemoglobin deferral rates, almost all donors are assigned to donate every 12 weeks. However, when the goal is to maximize the utility score that "discounts" the total units of blood collected by the incidences of low hemoglobin deferrals, we observe some heterogeneity in the optimal inter-donation interval across donors and the optimal donor assignment strategy is highly dependent on the trade-off parameter in the utility function.Medical Research Council programme MC_UU_00002/

Optimising surveillance and re-intervention strategy following elective endovascular repair of abdominal aortic aneurysms

Background Elective endovascular aneurysm repair (EVAR) for abdominal aortic aneurysm has an initial survival advantage over open repair (OR), but more frequent complications increase costs and long-term aneurysm-related mortality. Randomised controlled trials of EVAR versus OR have shown EVAR is not cost-effective over a patient’s lifetime. However, in the EVAR-1 trial, post-operative surveillance may have been sub-optimal, as the importance of sac growth as a predictor of graft failure was overlooked. Methods Real-world data informed a discrete event simulation model of post-operative outcomes following EVAR. Outcomes observed EVAR-1 were compared with those from five alternative post-operative surveillance and re-intervention strategies. Key events, quality-adjusted life years and costs were predicted. The impact of using complication and rupture rates from more recent devices, imaging and re-intervention methods was also explored. Results Compared with observed EVAR-1 outcomes, modelling full adherence to the EVAR-1 scan protocol reduced AAA deaths by 3% and increased elective re-interventions by 44%. European Society re-intervention guidelines provided the most clinically effective strategy, with an 8% reduction in AAA deaths, but a 52% increase in elective re-interventions. The cheapest and most cost-effective strategy used lifetime annual ultrasound in primary care with confirmatory CT if necessary, and reduced AAA-related deaths by 5%. Using contemporary rates for complications and rupture did not alter these conclusions. Conclusions All alternative strategies improved clinical benefits compared with the EVAR-1 trial. Further work is needed regarding the cost and accuracy of primary care ultrasound, and the potential impact of these strategies in the comparison with OR.Financial support from National Institute of Health Research and Camelia Botnar Arterial Foundation. The National Institute of Health Research (NIHR) had no role in study design, data collection, data analysis, data interpretation, in the writing of the report or in the decision to submit the article for publication. The views and opinions expressed herein are those of the authors and do not necessarily reflect those of the NIHR, UK NHS, or Department of Health. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication

Optimizing Surveillance and Re-intervention Strategy Following Elective Endovascular Repair of Abdominal Aortic Aneurysms

Background: EVAR for abdominal aortic aneurysm has an initial survival advantage over OR, but more frequent complications increase costs and long-term aneurysm-related mortality. Randomized controlled trials of EVAR versus OR have shown EVAR is not cost-effective over a patient's lifetime. However, in the EVAR-1 trial, postoperative surveillance may have been sub-optimal, as the importance of sac growth as a predictor of graft failure was overlooked. Methods: Real-world data informed a discrete event simulation model of postoperative outcomes following EVAR. Outcomes observed EVAR-1 were compared with those from 5 alternative postoperative surveillance and reintervention strategies. Key events, quality-adjusted life years and costs were predicted. The impact of using complication and rupture rates from more recent devices, imaging and re-intervention methods was also explored. Results: Compared with observed EVAR-1 outcomes, modeling full adherence to the EVAR-1 scan protocol reduced abdominal aortic aneurysm (AAA) deaths by 3% and increased elective re-interventions by 44%. European Society re-intervention guidelines provided the most clinically effective strategy, with an 8% reduction in AAA deaths, but a 52% increase in elective re-interventions. The cheapest and most cost-effective strategy used lifetime annual ultrasound in primary care with confirmatory computed tomography if necessary, and reduced AAA-related deaths by 5%. Using contemporary rates for complications and rupture did not alter these conclusions. Conclusions: All alternative strategies improved clinical benefits compared with the EVAR-1 trial. Further work is needed regarding the cost and accuracy of primary care ultrasound, and the potential impact of these strategies in the comparison with OR.Peer reviewe

Editor's Choice - Re-interventions After Repair of Ruptured Abdominal Aortic Aneurysm: A Report From the IMPROVE Randomised Trial.

OBJECTIVE/BACKGROUND: The aim was to describe the re-interventions after endovascular and open repair of rupture, and investigate whether these were associated with aortic morphology. METHODS: In total, 502 patients from the IMPROVE randomised trial (ISRCTN48334791) with repair of rupture were followed-up for re-interventions for at least 3 years. Pre-operative aortic morphology was assessed in a core laboratory. Re-interventions were described by time (0-90 days, 3 months-3 years) as arterial or laparotomy related, respectively, and ranked for severity by surgeons and patients separately. Rare re-interventions to 1 year, were summarised across three ruptured abdominal aortic aneurysm trials (IMPROVE, AJAX, and ECAR) and odds ratios (OR) describing differences were pooled via meta-analysis. RESULTS: Re-interventions were most common in the first 90 days. Overall rates were 186 and 226 per 100 person years for the endovascular strategy and open repair groups, respectively (p = .20) but between 3 months and 3 years (mid-term) the rates had slowed to 9.5 and 6.0 re-interventions per 100 person years, respectively (p = .090) and about one third of these were for a life threatening condition. In this latter, mid-term period, 42 of 313 remaining patients (13%) required at least one re-intervention, most commonly for endoleak or other endograft complication after treatment by endovascular aneurysm repair (EVAR) (21 of 38 re-interventions), whereas distal aneurysms were the commonest reason (four of 23) for re-interventions after treatment by open repair. Arterial re-interventions within 3 years were associated with increasing common iliac artery diameter (OR 1.48, 95% confidence interval [CI] 0.13-0.93; p = .004). Amputation, rare but ranked as the worst re-intervention by patients, was less common in the first year after treatment with EVAR (OR 0.2, 95% CI 0.05-0.88) from meta-analysis of three trials. CONCLUSION: The rate of mid-term re-interventions after rupture is high, more than double that after elective EVAR and open repair, suggesting the need for bespoke surveillance protocols. Amputations are much less common in patients treated by EVAR than in those treated by open repair

A Bayesian model‐free approach to combination therapy phase I trials using censored time‐to‐toxicity data

The product of independent beta probabilities escalation design for dual agent phase I dose escalation trials is a Bayesian model‐free approach for identifying multiple maximum tolerated dose combinations of novel combination therapies. Despite only being published in 2015, the design has been implemented in at least two oncology trials. However, these trials require patients to have completed follow‐up before clinicians can make dose escalation decisions. For trials of radiotherapy or advanced therapeutics, this may lead to impractically long trial durations due to late‐onset treatment‐related toxicities. We extend the product of independent probabilities escalation design to use censored time‐to‐event toxicity outcomes for making dose escalation decisions. We show via comprehensive simulation studies and sensitivity analyses that trial duration can be reduced by up to 35%, particularly when recruitment is faster than expected, without compromising on other operating characteristics

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 (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)

Endovascular or open repair strategy for ruptured abdominal aortic aneurysm: 30 day outcomes from IMPROVE randomised trial.

OBJECTIVE: To assess whether a strategy of endovascular repair (if aortic morphology is suitable, open repair if not) versus open repair reduces early mortality for patients with suspected ruptured abdominal aortic aneurysm. DESIGN: Randomised controlled trial. SETTING: 30 vascular centres (29 UK, 1 Canadian), 2009-13. PARTICIPANTS: 613 eligible patients (480 men) with a clinical diagnosis of ruptured aneurysm. INTERVENTIONS: 316 patients were randomised to the endovascular strategy (275 confirmed ruptures, 174 anatomically suitable for endovascular repair) and 297 to open repair (261 confirmed ruptures). MAIN OUTCOME MEASURES: 30 day mortality, with 24 hour and in-hospital mortality, costs, and time and place of discharge as secondary outcomes. RESULTS: 30 day mortality was 35.4% (112/316) in the endovascular strategy group and 37.4% (111/297) in the open repair group: odds ratio 0.92 (95% confidence interval 0.66 to 1.28; P=0.62); odds ratio after adjustment for age, sex, and Hardman index 0.94 (0.67 to 1.33). Women may benefit more than men (interaction test P=0.02) from the endovascular strategy: odds ratio 0.44 (0.22 to 0.91) versus 1.18 (0.80 to 1.75). 30 day mortality for patients with confirmed rupture was 36.4% (100/275) in the endovascular strategy group and 40.6% (106/261) in the open repair group (P=0.31). More patients in the endovascular strategy than in the open repair group were discharged directly to home (189/201 (94%) v 141/183 (77%); P<0.001). Average 30 day costs were similar between the randomised groups, with an incremental cost saving for the endovascular strategy versus open repair of £1186 (€1420; $1939) (95% confidence interval -£625 to £2997). CONCLUSIONS: A strategy of endovascular repair was not associated with significant reduction in either 30 day mortality or cost. Longer term cost effectiveness evaluations are needed to assess the full effects of the endovascular strategy in both men and women. TRIAL REGISTRATION: Current Controlled Trials ISRCTN48334791