Stochastic Approximation and Modern Model-Based Designs for Dose-Finding Clinical Trials

In 1951 Robbins and Monro published the seminal article on stochastic approximation and made a specific reference to its application to the "estimation of a quantal using response, nonresponse data." Since the 1990s, statistical methodology for dose-finding studies has grown into an active area of research. The dose-finding problem is at its core a percentile estimation problem and is in line with what the Robbins--Monro method sets out to solve. In this light, it is quite surprising that the dose-finding literature has developed rather independently of the older stochastic approximation literature. The fact that stochastic approximation has seldom been used in actual clinical studies stands in stark contrast with its constant application in engineering and finance. In this article, I explore similarities and differences between the dose-finding and the stochastic approximation literatures. This review also sheds light on the present and future relevance of stochastic approximation to dose-finding clinical trials. Such connections will in turn steer dose-finding methodology on a rigorous course and extend its ability to handle increasingly complex clinical situations.Comment: Published in at http://dx.doi.org/10.1214/10-STS334 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

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

A First Step Towards Behavioral Coaching for Managing Stress: A Case Study on Optimal Policy Estimation with Multi-stage Threshold Q-learning

Psychological stress is a major contributor to the adoption of unhealthy behaviors, which in turn accounts for 41% of global cardiovascular disease burden. While the proliferation of mobile health apps has offered promise to stress management, these apps do not provide micro-level feedback with regard to how to adjust one's behaviors to achieve a desired health outcome. In this paper, we formulate the task of multi-stage stress management as a sequential decision-making problem and explore the application of reinforcement learning to provide micro-level feedback for stress reduction. Specifically, we incorporate a multi-stage threshold selection into Q-learning to derive an interpretable form of a recommendation policy for behavioral coaching. We apply this method on an observational dataset that contains Fitbit ActiGraph measurements and self-reported stress levels. The estimated policy is then used to understand how exercise patterns may affect users' psychological stress levels and to perform coaching more effectively

Dose Transition Pathways::The missing link between complex dose-finding designs and simple decision-making

The ever-increasing pace of development of novel therapies mandates efficient methodologies for assessment of their tolerability and activity. Evidence increasingly support the merits of model-based dose-finding designs in identifying the recommended phase II dose compared with conventional rule-based designs such as the 3 + 3 but despite this, their use remains limited. Here, we propose a useful tool, dose transition pathways (DTP), which helps overcome several commonly faced practical and methodologic challenges in the implementation of model-based designs. DTP projects in advance the doses recommended by a model-based design for subsequent patients (stay, escalate, de-escalate, or stop early), using all the accumulated information. After specifying a model with favorable statistical properties, we utilize the DTP to fine-tune the model to tailor it to the trial's specific requirements that reflect important clinical judgments. In particular, it can help to determine how stringent the stopping rules should be if the investigated therapy is too toxic. Its use to design and implement a modified continual reassessment method is illustrated in an acute myeloid leukemia trial. DTP removes the fears of model-based designs as unknown, complex systems and can serve as a handbook, guiding decision-making for each dose update. In the illustrated trial, the seamless, clear transition for each dose recommendation aided the investigators' understanding of the design and facilitated decision-making to enable finer calibration of a tailored model. We advocate the use of the DTP as an integral procedure in the co-development and successful implementation of practical model-based designs by statisticians and investigators. Clin Cancer Res; 23(24); 7440-7. ©2017 AACR

Cerebral white matter disease and functional decline in older adults from the Northern Manhattan Study: A longitudinal cohort study

Background Cerebral white matter hyperintensities (WMHs) on MRI are common and associated with vascular and functional outcomes. However, the relationship between WMHs and longitudinal trajectories of functional status is not well characterized. We hypothesized that whole brain WMHs are associated with functional decline independently of intervening clinical vascular events and other vascular risk factors. Methods and findings In the Northern Manhattan Study (NOMAS), a population-based racially/ethnically diverse prospective cohort study, 1,290 stroke-free individuals underwent brain MRI and were followed afterwards for a mean 7.3 years with annual functional assessments using the Barthel index (BI) (range 0–100) and vascular event surveillance. Whole brain white matter hyperintensity volume (WMHV) (as percentage of total cranial volume [TCV]) was standardized and treated continuously. Generalized estimating equation (GEE) models tested associations between whole brain WMHV and baseline BI and change in BI, adjusting for sociodemographic, vascular, and cognitive risk factors, as well as stroke and myocardial infarction (MI) occurring during follow-up. Mean age was 70.6 (standard deviation [SD] 9.0) years, 40% of participants were male, 66% Hispanic; mean whole brain WMHV was 0.68% (SD 0.84). In fully adjusted models, annual functional change was −1.04 BI points (−1.20, −0.88), with −0.74 additional points annually per SD whole brain WMHV increase from the mean (−0.99, −0.49). Whole brain WMHV was not associated with baseline BI, and results were similar for mobility and non-mobility BI domains and among those with baseline BI 95–100. A limitation of the study is the possibility of a healthy survivor bias, which would likely have underestimated the associations we found. Conclusions In this large population-based study, greater whole brain WMHV was associated with steeper annual decline in functional status over the long term, independently of risk factors, vascular events, and baseline functional status. Subclinical brain ischemic changes may be an independent marker of long-term functional decline

APOE ϵ4 modifies the relationship between infectious burden and poor cognition

Objective: We investigated whether APOE ϵ4 is an effect modifier of the association between infectious burden (IB) and poor cognition in a multiethnic cohort, the Northern Manhattan Study. Methods: IB was assessed by a quantitative weighted index of exposure to common pathogens associated with vascular risk, infectious burden index (IBI), and by serology for individual infections. Cognition was assessed by completion of the Mini-Mental State Examination at baseline and a full neuropsychological test battery after a median follow-up of approximately 6 years. Adjusted linear and logistic regressions estimated the association between IBI and cognition, with a term included for the interaction between APOE ϵ4 and IBI. Results: Among those with full neuropsychological test results (n = 569), there were interactions between IBI and APOE ϵ4 (p = 0.07) and herpes simplex virus 1 (HSV-1) and APOE ϵ4 (p = 0.02) for processing speed. IBI was associated with slower processing speed among non–ϵ4 carriers (β = −0.08 per SD change in IBI, 95% confidence interval [CI] −0.16 to −0.01), but not among APOE ϵ4 carriers (β = 0.06 per SD change in IBI, 95% CI –0.08 to 0.19). HSV-1 positivity was associated with slower processing speed among non–ϵ4 carriers (β = −0.24, 95% CI −0.45 to −0.03), but not among APOE ϵ4 carriers (β = 0.27, 95% CI −0.09 to 0.64). Conclusions: Potential effect modification by the APOE ϵ4 allele on the relationship of infection, and particularly viral infection, to cognitive processing speed warrants further investigation

Multilevel Interventions Targeting Obesity: Research Recommendations for Vulnerable Populations

The origins of obesity are complex and multifaceted. To be successful, an intervention aiming to prevent or treat obesity may need to address multiple layers of biological, social, and environmental influences

Clinical Usefulness of Bright White Light Therapy for Depressive Symptoms in Cancer Survivors: Results from a Series of Personalized (N-of-1) Trials

Publisher's version (útgefin grein)Purpose: Little is known about the effectiveness of bright white light therapy (BWL) for depressive symptoms in cancer survivors, many of whom prefer non-pharmacological treatments. The purpose of this study was to compare the effectiveness of BWL versus dim red light therapy (DRL) on depressive symptoms within individual cancer survivors using personalized (N-of-1) trials. Methods: Cancer survivors with at least mild depressive symptoms were randomized to one of two treatment sequences consisting of counterbalanced crossover comparisons of three-weeks of lightbox-delivered BWL (intervention) or DRL (sham) for 30 min each morning across 12 weeks. A smartphone application guided cancer survivors through the treatment sequence and facilitated data collection. Cancer survivors tracked end-of-day depressive symptoms (primary outcome) and fatigue using visual analog scales. Within-patient effects of BWL were assessed using an autoregressive model with adjustment for linear time trends. Results: Eight of nine cancer survivors completed the 12-week protocol. Two survivors reported significantly (i.e., p < 0.05) lower depressive symptoms (-1.3 +/- 0.5 and -1.30 +/- 0.9 points on a 10-point scale), five reported no difference in depressive symptoms, and one reported higher depressive symptoms (+1.7 +/- 0.6 points) with BWL versus DRL. Eight of nine cancer survivors recommended personalized trials of BWL to others. Conclusions: There were heterogeneous effects of three-week BWL on self-reported depressive symptoms among cancer survivors, with some finding a benefit but others finding no benefit or even harm. Implications for Cancer Survivors: Personalized trials can help cancer survivors learn if BWL is helpful for improving their depressive symptoms.This research was funded in part with Federal funds from the National Cancer Institute, NIH, under Contract No. HHSN261200800001E. Drs. Kronish, Davidson, and Cheung received additional support from the National Library of Medicine (R01LM012836)."Peer Reviewed

Differential Effect of Left vs. Right White Matter Hyperintensity Burden on Functional Decline: The Northern Manhattan Study

Asymmetry of brain dysfunction may disrupt brain network efficiency. We hypothesized that greater left-right white matter hyperintensity volume (WMHV) asymmetry was associated with functional trajectories.Methods: In the Northern Manhattan Study, participants underwent brain MRI with axial T1, T2, and fluid attenuated inversion recovery sequences, with baseline interview and examination. Volumetric WMHV distribution across 14 brain regions was determined separately by combining bimodal image intensity distribution and atlas based methods. Participants had annual functional assessments with the Barthel index (BI, range 0–100) over a mean of 7.3 years. Generalized estimating equations (GEE) models estimated associations of regional WMHV and regional left-right asymmetry with baseline BI and change over time, adjusted for baseline medical risk factors, sociodemographics, and cognition, and stroke and myocardial infarction during follow-up.Results: Among 1,195 participants, greater WMHV asymmetry in the parietal lobes (−8.46 BI points per unit greater WMHV on the right compared to left, 95% CI −3.07, −13.86) and temporal lobes (−2.48 BI points, 95% CI −1.04, −3.93) was associated with lower overall function. Greater WMHV asymmetry in the parietal lobes (−1.09 additional BI points per year per unit greater WMHV on the left compared to right, 95% CI −1.89, −0.28) was independently associated with accelerated functional decline.Conclusions: In this large population-based study with long-term repeated measures of function, greater regional WMHV asymmetry was associated with lower function and functional decline. In addition to global WMHV, WHMV asymmetry may be an important predictor of long-term functional status