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Background: Senescent immune cells exhibit altered gene expression and resistance to apoptosis. The prevalence of these cells increases with age and emerging data implicate senescence-associated maladaptive signaling as a potential contributor to sepsis and septic shock. The senolytic drug fisetin promotes clearance of senescent cells and is hypothesized to mitigate septic responses to infection., Methods: We are conducting a multi-center, randomized, double-blinded, adaptive allocation phase 2 clinical trial to assess the efficacy of the senolytic drug fisetin in preventing clinical deterioration of elderly patients diagnosed with sepsis. We intend to enroll and randomize 220 elderly patients (age > 65) with the clinical diagnosis of sepsis to receive either fisetin as a single oral dose of 20 mg/kg, fisetin in two oral doses of 20 mg/kg each spaced 1 day apart, or placebo. The primary outcome will be changed in the composite of cardiovascular, respiratory, and renal sequential organ failure assessment scores at 7 days from enrollment. Secondary outcomes include quantification of senescent CD3 + cells at 7 days, and 28-day assessments of organ failure-free days, days in an intensive care unit, and all-cause mortality., Discussion: This multi-center, randomized, double-blinded trial will assess the efficacy of fisetin in preventing clinical deterioration in elderly patients with sepsis and measure the effects of this drug on the prevalence of senescent immune cells. We intend that the results of this phase 2 trial will inform the design of a larger phase 3 study., Trial Registration: This trial is registered to ClinicalTrials.gov under identifier NCT05758246, first posted on March 7, 2023., (© 2024. The Author(s).)

Randomized trials seek efficient treatment effect estimation within target populations, yet scientific interest often also centers on subpopulations. Although there are typically too few subjects within each subpopulation to efficiently estimate these subpopulation treatment effects, one can gain precision by borrowing strength across subpopulations, as is the case in a basket trial. While dynamic borrowing has been proposed as an efficient approach to estimating subpopulation treatment effects on primary endpoints, additional efficiency could be gained by leveraging the information found in secondary endpoints. We propose a multisource exchangeability model (MEM) that incorporates secondary endpoints to more efficiently assess subpopulation exchangeability. Across simulation studies, our proposed model almost uniformly reduces the mean squared error when compared to the standard MEM that only considers data from the primary endpoint by gaining efficiency when subpopulations respond similarly to the treatment and reducing the magnitude of bias when the subpopulations are heterogeneous. We illustrate our model's feasibility using data from a recently completed trial of very low nicotine content cigarettes to estimate the effect on abstinence from smoking within three priority subpopulations. Our proposed model led to increases in the effective sample size two to four times greater than under the standard MEM., (© The Author(s) 2024. Published by Oxford University Press on behalf of The International Biometric Society.)

Chen et al. (2022) recently proposed a set of estimating equations that incorporate data from secondary endpoints to improve precision in parameter estimates related to a primary endpoint. We were motivated to translate their methodology to the context of randomized controlled trials to gain precision in treatment effect estimation using data from secondary endpoints. Our results suggest that this estimator cannot gain efficiency in this context because of random treatment assignment, especially when there is a treatment effect on secondary endpoints, and that further methodological work in this area is needed., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Introduction: A national nicotine reduction policy could reduce the public health toll of smoking. However, reducing nicotine in cigarettes may lead to changes in the use of other tobacco products such as nicotine vaping devices, particularly among young people. Product use outcomes may depend on characteristics of available nicotine vaping devices. We aimed to determine the impact of cigarette nicotine content, vaping device nicotine concentration, and vaping device flavors on choices to smoke, vape, or abstain., Methods: Early young adults (ages 18-20 inclusive, N=80) who reported smoking daily and vaping nicotine at least twice in their lifetime participated in a laboratory study. Participants received either Very Low Nicotine Content (VLNC; 0.4 mg nicotine/g of tobacco) or Normal Nicotine Content (NNC; 15.8 mg/g) cigarettes. First, participants chose between their assigned cigarette or abstaining. Subsequently, participants chose between 2 cigarette puffs, 2 vape puffs, or abstaining. Vaping device nicotine concentration (3mg vs. 18mg/ml) and flavor (tobacco vs. non-tobacco) were manipulated within-subjects., Results: When only cigarettes were available, there were no differences between the VLNC and NNC groups on cigarette choices. When the nicotine vaping device was concurrently available, the VLNC group made fewer choices to smoke than the NNC group. Non-tobacco flavors and lower vaping device nicotine concentration were associated with fewer choices to smoke., Conclusions: Nicotine vaping device availability reduced choices to smoke VLNC cigarettes, and vaping devices with lower nicotine and non-tobacco flavors led to the fewest choices to smoke. Regulators should consider that the availability and characteristics of alternative tobacco products can moderate the product standard's impact., Implications: The U.S. Food and Drug Administration may enact a reduced nicotine product standard that would affect all commercially-available cigarettes. One important population affected by this policy would be early young adults who smoke. We aimed to determine the impact of cigarette nicotine content, vaping device nicotine concentration, and vaping device flavors on choices to smoke, vape, or abstain. Lower nicotine in cigarettes, along with non-tobacco flavors and lower nicotine concentration in the vaping device, were associated with the fewest choices to smoke. Regulators should consider that the availability and characteristics of alternative tobacco products can moderate the product standard's impact., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

The traditional trial paradigm is often criticized as being slow, inefficient, and costly. Statistical approaches that leverage external trial data have emerged to make trials more efficient by augmenting the sample size. However, these approaches assume that external data are from previously conducted trials, leaving a rich source of untapped real-world data (RWD) that cannot yet be effectively leveraged. We propose a semi-supervised mixture (SS-MIX) multisource exchangeability model (MEM); a flexible, two-step Bayesian approach for incorporating RWD into randomized controlled trial analyses. The first step is a SS-MIX model on a modified propensity score and the second step is a MEM. The first step targets a representative subgroup of individuals from the trial population and the second step avoids borrowing when there are substantial differences in outcomes among the trial sample and the representative observational sample. When comparing the proposed approach to competing borrowing approaches in a simulation study, we find that our approach borrows efficiently when the trial and RWD are consistent, while mitigating bias when the trial and external data differ on either measured or unmeasured covariates. We illustrate the proposed approach with an application to a randomized controlled trial investigating intravenous hyperimmune immunoglobulin in hospitalized patients with influenza, while leveraging data from an external observational study to supplement a subgroup analysis by influenza subtype., (© The Author(s) 2023. Published by Oxford University Press. All rights reserved. [br]For permissions, please e-mail: journals.permissions@oup.com.)

Background: Inpatient telestroke programs have emerged as a solution to provide timely stroke care in underserved areas, but their successful implementation and factors influencing their effectiveness remain underexplored. This study aimed to qualitatively evaluate the perspectives of inpatient clinicians located at spoke hospitals participating in a newly established inpatient telestroke program to identify implementation barriers and facilitators., Methods: This was a formative evaluation relying on semistructured qualitative interviews with 16 inpatient providers (physicians and nurse practitioners) at 5 spoke sites of a hub-and-spoke inpatient telestroke program. The Integrated-Promoting Action on Research Implementation in Health Services framework guided data analysis, focusing on the innovation, recipients, context, and facilitation aspects of implementation. Interviews were transcribed and coded using thematic analysis., Results: Fifteen themes were identified in the data and mapped to the Integrated-Promoting Action on Research Implementation in Health Services framework. Themes related to the innovation (the telestroke program) included easy access to stroke specialists, the benefits of limiting patient transfers, concerns about duplicating tests, and challenges of timing inpatient telestroke visits and notes to align with discharge workflow. Themes pertaining to recipients (care team members and patients) were communication gaps between teams, concern about the supervision of inpatient telestroke advanced practice providers and challenges with nurse empowerment. With regard to the context (hospital and system factors), providers highlighted familiarity with telehealth technologies as a facilitator to implementing inpatient telestroke, yet highlighted resource limitations in smaller facilities. Facilitation (program implementation) was recognized as crucial for education, standardization, and buy-in., Conclusions: Understanding barriers and facilitators to implementation is crucial to determining where programmatic changes may need to be made to ensure the success and sustainment of inpatient telestroke services., Competing Interests: Disclosures Dr Melton is a fiduciary officer for the American College of Medical Informatics, the American Medical Informatics Association, and the President and Chair of the Board of Directors at Fairview Health Services. She is the Chief Analytics and Care Innovation Officer at the University of Minnesota, and she is a consultant at Washington University School of Medicine in St. Louis. She has grants with the Agency for Healthcare Research and Quality, the Food and Drug Administration, the National Institutes of Health, and the US Department of Defense. The other authors report no conflicts.

Current protocols to estimate the number, size, and location of cancerous lesions in the prostate using multiparametric magnetic resonance imaging (mpMRI) are highly dependent on reader experience and expertise. Automatic voxel-wise cancer classifiers do not directly provide estimates of number, location, and size of cancerous lesions that are clinically important. Existing spatial partitioning methods estimate linear or piecewise-linear boundaries separating regions of local stationarity in spatially registered data and are inadequate for the application of lesion detection. Frequentist segmentation and clustering methods often require pre-specification of the number of clusters and do not quantify uncertainty. Previously, we developed a novel Bayesian functional spatial partitioning method to estimate the boundary surrounding a single cancerous lesion using data derived from mpMRI. We propose a Bayesian functional spatial partitioning method for multiple lesion detection with an unknown number of lesions. Our method utilizes functional estimation to model the smooth boundary curves surrounding each cancerous lesion. In a Reversible Jump Markov Chain Monte Carlo (RJ-MCMC) framework, we develop novel jump steps to jointly estimate and quantify uncertainty in the number of lesions, their boundaries, and the spatial parameters in each lesion. Through simulation we show that our method is robust to the shape of the lesions, number of lesions, and region-specific spatial processes. We illustrate our method through the detection of prostate cancer lesions using MRI.

Background: Randomized controlled trials include interim monitoring guidelines to stop early for safety, efficacy, or futility. Futility monitoring facilitates re-allocation of limited resources. However, conventional methods for interim futility monitoring require a trial to accrue nearly half of the outcome data to make a reliable early stopping decision, limiting its benefit. As early stopping for futility will not inflate type-I error, these analyses are an appealing venue for incorporating external data to improve efficiency., Methods: We propose a Bayesian approach to futility monitoring leveraging real world data using Semi-Supervised MIXture Multi-source Exchangeability Models, which accounts for both measured and unmeasured differences between data sources. We implement futility monitoring using predictive probabilities and investigate the optimal timing with respect to the expected sample size under the null hypothesis. Because we only incorporate external data during the interim futility analysis the proposed design is not limited by type-I error inflation., Results: When the external and trial data are exchangeable, the proposed method provides a roughly 70 person reduction in expected sample size under the null. Under scenarios where exchangeability does not hold, our approach still provides a 10-20 person reduction in expected sample size under the null with about 80% power., Conclusions: External data borrowing in interim futility monitoring is a promising venue to improve trial efficiency without type-I error inflation. Approaches that are acceptable to regulatory authorities and leverage the complementary strengths of real world and trial data are vital to more efficiently allocate limited resources amongst clinical trials., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: Learning health systems (LHSs) iteratively generate evidence that can be implemented into practice to improve care and produce generalizable knowledge. Pragmatic clinical trials fit well within LHSs as they combine real-world data and experiences with a degree of methodological rigor which supports generalizability., Objectives: We established a pragmatic clinical trial unit ("RapidEval") to support the development of an LHS. To further advance the field of LHS, we sought to further characterize the role of health information technology (HIT), including innovative solutions and challenges that occur, to improve LHS project delivery., Methods: During the period from December 2021 to February 2023, eight projects were selected out of 51 applications to the RapidEval program, of which five were implemented, one is currently in pilot testing, and two are in planning. We evaluated pre-study planning, implementation, analysis, and study closure approaches across all RapidEval initiatives to summarize approaches across studies and identify key innovations and learnings by gathering data from study investigators, quality staff, and IT staff, as well as RapidEval staff and leadership., Implementation Results: Implementation approaches spanned a range of HIT capabilities including interruptive alerts, clinical decision support integrated into order systems, patient navigators, embedded micro-education, targeted outpatient hand-off documentation, and patient communication. Study approaches include pre-post with time-concordant controls (1), randomized stepped-wedge (1), cluster randomized across providers (1) and location (3), and simple patient level randomization (2)., Conclusions: Study selection, design, deployment, data collection, and analysis required close collaboration between data analysts, informaticists, and the RapidEval team., Competing Interests: The authors have no relevant conflicts of interest to report., (© 2024 The Authors. Learning Health Systems published by Wiley Periodicals LLC on behalf of University of Michigan.)

Background: Despite strong and growing interest in ending the ongoing opioid health crisis, there has been limited success in reducing the prevalence of opioid addiction and the number of deaths associated with opioid overdoses. Further, 1 explanation for this is that existing interventions target those who are opiate-dependent but do not prevent opioid-naïve patients from becoming addicted., Objective: Leveraging behavioral economics at the patient level could help patients successfully use, discontinue, and dispose of their opioid medications in an acute pain setting. The primary goal of this project is to evaluate the effect of the 3 versions of the Opioid Management for You (OPY) tool on measures of opioid use relative to the standard of care by leveraging a pragmatic randomized controlled trial (RCT)., Methods: A team of researchers from the Center for Learning Health System Sciences (CLHSS) at the University of Minnesota partnered with M Health Fairview to design, build, and test the 3 versions of the OPY tool: social influence, precommitment, and testimonial version. The tool is being built using the Epic Care Companion (Epic Inc) platform and interacts with the patient through their existing MyChart (Epic Systems Corporation) personal health record account, and Epic patient portal, accessed through a phone app or the MyChart website. We have demonstrated feasibility with pilot data of the social influence version of the OPY app by targeting our pilot to a specific cohort of patients undergoing upper-extremity procedures. This study will use a group sequential RCT design to test the impact of this important health system initiative. Patients who meet OPY inclusion criteria will be stratified into low, intermediate, and high risk of opiate use based on their type of surgery., Results: This study is being funded and supported by the CLHSS Rapid Prospective Evaluation and Digital Technology Innovation Programs, and M Health Fairview. Support and coordination provided by CLHSS include the structure of engagement, survey development, data collection, statistical analysis, and dissemination. The project was initially started in August 2022. The pilot was launched in February 2023 and is still running, with the data last counted in August 2023. The actual RCT is planned to start by early 2024., Conclusions: Through this RCT, we will test our hypothesis that patient opioid use and diverted prescription opioid availability can both be improved by information delivery applied through a behavioral economics lens via sending nudges directly to the opioid users through their personal health record., Trial Registration: ClinicalTrials.gov NCT06124079; https://clinicaltrials.gov/study/NCT06124079., International Registered Report Identifier (irrid): PRR1-10.2196/52882., (©Rubina Fatima Rizvi, Jamee Ann Schoephoerster, Sagar Satish Desphande, Michael Usher, Andy Elaine Oien, Maya Marie Peters, Matthew Scott Loth, Matthew William Bahr, Steffen Ventz, Joseph Stephen Koopmeiners, Genevieve B Melton. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 08.03.2024.)

Osteosarcoma is a devastating bone cancer that disproportionally afflicts children, adolescents, and young adults. Standard therapy includes surgical tumor resection combined with multiagent chemotherapy, but many patients still suffer from metastatic disease progression. Neoadjuvant systemic oncolytic virus (OV) therapy has the potential to improve clinical outcomes by targeting primary and metastatic tumor sites and inducing durable antitumor immune responses. Here we describe the first evaluation of neoadjuvant systemic therapy with a clinical-stage recombinant oncolytic vesicular stomatitis virus (VSV), VSV-IFNβ-NIS, in naturally occurring cancer, specifically appendicular osteosarcoma in companion dogs. Canine osteosarcoma has a similar natural disease history as its human counterpart. VSV-IFNβ-NIS was administered prior to standard of care surgical resection, permitting microscopic and genomic analysis of tumors. Treatment was well-tolerated and a "tail" of long-term survivors (∼35%) was apparent in the VSV-treated group, a greater proportion than observed in two contemporary control cohorts. An increase in tumor inflammation was observed in VSV-treated tumors and RNA-seq analysis showed that all the long-term responders had increased expression of a T cell anchored immune gene cluster. We conclude that neoadjuvant VSV-IFNβ-NIS is safe and may increase long-term survivorship in dogs with naturally occurring osteosarcoma, particularly those that exhibit pre-existing antitumor immunity., Competing Interests: S.N., S.J.R., and Mayo Clinic have a financial conflict of interest related to this research. S.N. and S.J.R. are inventors on patents related to oncolytic vesicular stomatitis virus that has been licensed by Mayo Clinic to Vyriad. S.N. and S.J.R. have equity interests in Vyriad, and S.J.R. is the CEO of Vyriad. The research has been reviewed by the Mayo Clinic Conflict of Interest Review Board and is being conducted in compliance with Mayo Conflict of Interest policies., (© 2023 The Authors.)

Individuals can vary drastically in their response to the same treatment, and this heterogeneity has driven the push for more personalized medicine. Accurate and interpretable methods to identify subgroups that respond to the treatment differently from the population average are necessary to achieving this goal. The Virtual Twins (VT) method is a highly cited and implemented method for subgroup identification because of its intuitive framework. However, since its initial publication, many researchers still rely heavily on the authors' initial modeling suggestions without examining newer and more powerful alternatives. This leaves much of the potential of the method untapped. We comprehensively evaluate the performance of VT with different combinations of methods in each of its component steps, under a collection of linear and nonlinear problem settings. Our simulations show that the method choice for Step 1 of VT, in which dense models with high predictive performance are fit for the potential outcomes, is highly influential in the overall accuracy of the method, and Superlearner is a promising choice. We illustrate our findings by using VT to identify subgroups with heterogeneous treatment effects in a randomized, double-blind trial of very low nicotine content cigarettes.

Background: Human papillomavirus (HPV) is a common sexually transmitted infection, causing multiple cancers, including cervical, penile, and anal. Infection and subsequent health risks caused by HPV can be diminished by HPV vaccination. Unfortunately, vaccination rates among Hmong Americans are substantially lower than those among other racial and ethnic groups, despite having higher cervical cancer rates than non-Hispanic White women. Such disparities and sparse literature highlight the need for innovative and culturally appropriate educational interventions to improve HPV vaccine rates in Hmong Americans., Objective: We aimed to develop and evaluate the effectiveness and usability of an innovative web-based eHealth educational website, the Hmong Promoting Vaccines website (HmongHPV website), for Hmong-American parents and adolescents to improve their knowledge, self-efficacy, and decision-making capacities to obtain HPV vaccinations., Methods: Through social cognitive theory and community-based participatory action research process, we created a theory-driven and culturally and linguistically appropriate website for Hmong parents and adolescents. We conducted a pre-post intervention pilot study to assess the website's effectiveness and usability. Overall, 30 Hmong-American parent and adolescent dyads responded to questions about HPV and HPV vaccine knowledge, self-efficacy, and decision-making at preintervention, 1 week after intervention, and at the 5-week follow-up. Participants responded to survey questions about website content and processes at 1 and 5 weeks, and a subset of 20 dyad participants participated in telephone interviews 6 weeks later. We used paired t tests (2-tailed) to measure the change in knowledge, self-efficacy, and decision-making processes, and used template analysis to identify a priori themes for website usability., Results: Participants' HPV and HPV vaccine knowledge improved significantly from pre- to postintervention stage and follow-up. Knowledge scores increased from preintervention to 1 week after intervention for both parents (HPV knowledge, P=.01; vaccine knowledge, P=.01) and children (HPV knowledge, P=.01; vaccine knowledge, P<.001), which were sustained at the 5-week follow-up. Parents' average self-efficacy score increased from 21.6 at baseline to 23.9 (P=.007) at post intervention and 23.5 (P=.054) at follow-up. Similar improvements were observed in the teenagers' self-efficacy scores (from 30.3 at baseline to 35.6, P=.009, at post intervention and 35.9, P=.006, at follow-up). Collaborative decision-making between parents and adolescents improved immediately after using the website (P=.002) and at follow-up (P=.02). The interview data also revealed that the website's content was informative and engaging; in particular, participants enjoyed the web-based quizzes and vaccine reminders., Conclusions: This theory-driven, community-based participatory action research-designed and culturally and linguistically appropriate educational website was well received. It improved Hmong parents' and adolescents' knowledge, self-efficacy, and decision-making processes regarding HPV vaccination. Future studies should examine the website's impact on HPV vaccine uptake and its potential for broader use across various settings (eg, clinics and schools)., (©Hee Yun Lee, Serena Xiong, Aparajita Sur, Tounhia Khang, Bai Vue, Kathleen A Culhane-Pera, Shannon Pergament, M Beatriz Torres, Joseph S Koopmeiners, Jay Desai. Originally published in JMIR Formative Research (https://formative.jmir.org), 20.06.2023.)

Spatial partitioning methods correct for nonstationarity in spatially related data by partitioning the space into regions of local stationarity. Existing spatial partitioning methods can only estimate linear partitioning boundaries. This is inadequate for detecting an arbitrarily shaped anomalous spatial region within a larger area. We propose a novel Bayesian functional spatial partitioning (BFSP) algorithm, which estimates closed curves that act as partitioning boundaries around anomalous regions of data with a distinct distribution or spatial process. Our method utilizes transitions between a fixed Cartesian and moving polar coordinate system to model the smooth boundary curves using functional estimation tools. Using adaptive Metropolis-Hastings, the BFSP algorithm simultaneously estimates the partitioning boundary and the parameters of the spatial distributions within each region. Through simulation we show that our method is robust to shape of the target zone and region-specific spatial processes. We illustrate our method through the detection of prostate cancer lesions using magnetic resonance imaging., (© 2021 The International Biometric Society.)

The reinforcing characteristics of e-cigarettes could moderate the impact of reducing cigarette nicotine content. In this study, people who smoke daily were recruited from North Carolina and Pennsylvania (US) in 2018 and 2019. Within a randomized 2 × 2 × 2 factorial design, participants received investigational cigarettes and an e-cigarette for 12 weeks. Cigarette nicotine content was very low (0.4 mg/g of tobacco; VLNC) or normal (15.8 mg/g; NNC). E-liquids were 0.3% ("low") or 1.8% ("moderate") freebase nicotine, and available in tobacco flavors or tobacco, fruit, dessert and mint flavors. Study recruitment concluded before reaching the planned sample size (N = 480). Fifty participants were randomized and 32 completed the study. We found that randomization to VLNC, relative to NNC cigarettes, reduced self-reported cigarettes per day (CPD; mean difference: -12.96; 95% CI: -21.51, -4.41; p = 0.005); whereas e-liquid nicotine content and flavor availability did not have significant effects. The effect of cigarette nicotine content was larger in the moderate vs. low nicotine e-liquid groups and in the all flavors versus tobacco flavors e-liquid groups; tests of the interaction between e-liquid characteristics and cigarette nicotine content were not significant. Biomarkers of smoke exposure at Week 12 did not differ across conditions, which may reflect variability in adherence to only using VLNC cigarettes. In conclusion this study offers preliminary evidence that the extent to which cigarette nicotine reduction decreases smoking may depend on the reinforcing characteristics of alternative products, including the available nicotine contents and flavors of e-cigarettes., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Introduction: In response to reducing cigarette nicotine content, people who smoke could attempt to compensate by using more cigarettes or by puffing on individual cigarettes with greater intensity. Such behaviors may be especially likely under conditions where normal nicotine content (NNC) cigarettes are not readily accessible. The current within-subject, residential study investigated whether puffing intensity increased with very low nicotine content (VLNC) cigarette use, relative to NNC cigarette use, when no other nicotine products were available., Aims and Methods: Sixteen adults who smoke daily completed two four-night hotel stays in Charleston, South Carolina (United States) in 2018 during which only NNC or only VLNC cigarettes were accessible. We collected the filters from all smoked cigarettes and measured the deposited solanesol to estimate mouth-level nicotine delivery per cigarette. These estimates were averaged within and across participants, per each 24-h period. We then compared the ratio of participant-smoked VLNC and NNC cigarette mouth-level nicotine with the ratio yielded by cigarette smoking machines (when puffing intensity is constant)., Results: Average mouth-level nicotine estimates from cigarettes smoked during the hotel stays indicate participants puffed VLNC cigarettes with greater intensity than NNC cigarettes in each respective 24-h period. However, this effect diminished over time (p &lt; .001). Specifically, VLNC puffing intensity was 40.0% (95% CI: 29.9, 53.0) greater than NNC puffing intensity in the first period, and 16.1% (95% CI: 6.9, 26.0) greater in the fourth period., Conclusion: Average puffing intensity per cigarette was elevated with exclusive VLNC cigarette use, but the extent of this effect declined across four days., Implications: In an environment where no other sources of nicotine are available, people who smoke daily may initially attempt to compensate for cigarette nicotine reduction by puffing on individual cigarettes with greater intensity. Ultimately, the compensatory behavior changes required to achieve usual nicotine intake from VLNC cigarettes are drastic and unrealistic. Accordingly, people are unlikely to sustain attempts to compensate for very low cigarette nicotine content., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background/aims: Secondary analyses of randomized clinical trials often seek to identify subgroups with differential treatment effects. These discoveries can help guide individual treatment decisions based on patient characteristics and identify populations for which additional treatments are needed. Traditional analyses require researchers to pre-specify potential subgroups to reduce the risk of reporting spurious results. There is a need for methods that can detect such subgroups without a priori specification while allowing researchers to control the probability of falsely detecting heterogeneous subgroups when treatment effects are uniform across the study population., Methods: We propose a permutation procedure for tuning parameter selection that allows for type I error control when testing for heterogeneous treatment effects framed within the Virtual Twins procedure for subgroup identification. We verify that the type I error rate can be controlled at the nominal rate and investigate the power for detecting heterogeneous effects when present through extensive simulation studies. We apply our method to a secondary analysis of data from a randomized trial of very low nicotine content cigarettes., Results: In the absence of type I error control, the observed type I error rate for Virtual Twins was between 99% and 100%. In contrast, models tuned via the proposed permutation were able to control the type I error rate and detect heterogeneous effects when present. An application of our approach to a recently completed trial of very low nicotine content cigarettes identified several variables with potentially heterogeneous treatment effects., Conclusions: The proposed permutation procedure allows researchers to engage in secondary analyses of clinical trials for treatment effect heterogeneity while maintaining the type I error rate without pre-specifying subgroups.

Well-done cooked red meat consumption is linked to aggressive prostate cancer (PC) risk. Identifying mutation-inducing DNA adducts in the prostate genome can advance our understanding of chemicals in meat that may contribute to PC. 2-Amino-1-methyl-6-phenylimidazo[4,5- b ]pyridine (PhIP), a heterocyclic aromatic amine (HAA) formed in cooked meat, is a potential human prostate carcinogen. PhIP was measured in the hair of PC patients undergoing prostatectomy, bladder cancer patients under treatment for cystoprostatectomy, and patients treated for benign prostatic hyperplasia (BPH). PhIP hair levels were above the quantification limit in 123 of 205 subjects. When dichotomizing prostate pathology biomarkers, the geometric mean PhIP hair levels were higher in patients with intermediate and elevated-risk prostate-specific antigen values than lower-risk values <4 ng/mL ( p = 0.03). PhIP hair levels were also higher in patients with intermediate and high-risk Gleason scores ≥7 compared to lower-risk Gleason score 6 and BPH patients ( p = 0.02). PC patients undergoing prostatectomy had higher PhIP hair levels than cystoprostatectomy or BPH patients ( p = 0.02). PhIP-DNA adducts were detected in 9.4% of the patients assayed; however, DNA adducts of other carcinogenic HAAs, and benzo[ a ]pyrene formed in cooked meat, were not detected. Prostate specimens were also screened for 10 oxidative stress-associated lipid peroxidation (LPO) DNA adducts. Acrolein 1, N 2 -propano-2'-deoxyguanosine adducts were detected in 54.5% of the patients; other LPO adducts were infrequently detected. Acrolein adducts were not associated with prostate pathology biomarkers, although DNA adductomic profiles differed between PC patients with low and high-grade Gleason scores. Many DNA adducts are of unknown origin; however, dG adducts of formaldehyde and a series of purported 4-hydroxy-2-alkenals were detected at higher abundance in a subset of patients with elevated Gleason scores. The PhIP hair biomarker and DNA adductomics data support the paradigm of well-done cooked meat and oxidative stress in aggressive PC risk.

Importance: SARS-CoV-2 viral entry may disrupt angiotensin II (AII) homeostasis, contributing to COVID-19 induced lung injury. AII type 1 receptor blockade mitigates lung injury in preclinical models, although data in humans with COVID-19 remain mixed., Objective: To test the efficacy of losartan to reduce lung injury in hospitalized patients with COVID-19., Design, Setting, and Participants: This blinded, placebo-controlled randomized clinical trial was conducted in 13 hospitals in the United States from April 2020 to February 2021. Hospitalized patients with COVID-19 and a respiratory sequential organ failure assessment score of at least 1 and not already using a renin-angiotensin-aldosterone system (RAAS) inhibitor were eligible for participation. Data were analyzed from April 19 to August 24, 2021., Interventions: Losartan 50 mg orally twice daily vs equivalent placebo for 10 days or until hospital discharge., Main Outcomes and Measures: The primary outcome was the imputed arterial partial pressure of oxygen to fraction of inspired oxygen (Pao2:Fio2) ratio at 7 days. Secondary outcomes included ordinal COVID-19 severity; days without supplemental o2, ventilation, or vasopressors; and mortality. Losartan pharmacokinetics and RAAS components (AII, angiotensin-[1-7] and angiotensin-converting enzymes 1 and 2)] were measured in a subgroup of participants., Results: A total of 205 participants (mean [SD] age, 55.2 [15.7] years; 123 [60.0%] men) were randomized, with 101 participants assigned to losartan and 104 participants assigned to placebo. Compared with placebo, losartan did not significantly affect Pao2:Fio2 ratio at 7 days (difference, -24.8 [95%, -55.6 to 6.1]; P = .12). Compared with placebo, losartan did not improve any secondary clinical outcomes and led to fewer vasopressor-free days than placebo (median [IQR], 9.4 [9.1-9.8] vasopressor-free days vs 8.7 [8.2-9.3] vasopressor-free days)., Conclusions and Relevance: This randomized clinical trial found that initiation of orally administered losartan to hospitalized patients with COVID-19 and acute lung injury did not improve Pao2:Fio2 ratio at 7 days. These data may have implications for ongoing clinical trials., Trial Registration: ClinicalTrials.gov Identifier: NCT04312009.

Definitive clinical trials are resource intensive, often requiring a large number of participants over several years. One approach to improve the efficiency of clinical trials is to incorporate historical information into the primary trial analysis. This approach has tremendous potential in the areas of pediatric or rare disease trials, where achieving reasonable power is difficult. In this article, we introduce a novel Bayesian group-sequential trial design based on Multisource Exchangeability Models, which allows for dynamic borrowing of historical information at the interim analyses. Our approach achieves synergy between group sequential and adaptive borrowing methodology to attain improved power and reduced sample size. We explore the frequentist operating characteristics of our design through simulation and compare our method to a traditional group-sequential design. Our method achieves earlier stopping of the primary study while increasing power under the alternative hypothesis but has a potential for type I error inflation under some null scenarios. We discuss the issues of decision boundary determination, power and sample size calculations, and the issue of information accrual. We present our method for a continuous and binary outcome, as well as in a linear regression setting., (© 2021 John Wiley & Sons Ltd.)

Multi-parametric magnetic resonance imaging (mpMRI) has been playing an increasingly important role in the detection of prostate cancer (PCa). Various computer-aided detection algorithms were proposed for automated PCa detection by combining information in multiple mpMRI parameters. However, there are specific features of mpMRI, including between-voxel correlation within each prostate and heterogeneity across patients, that have not been fully explored but could potentially improve PCa detection if leveraged appropriately. This article proposes novel Bayesian approaches for voxel-wise PCa classification that accounts for spatial correlation and between-patient heterogeneity in the mpMRI data. Modeling the spatial correlation is challenging due to the extreme high dimensionality of the data, and we propose three scalable approaches based on Nearest Neighbor Gaussian Process (NNGP), reduced-rank approximation, and a conditional autoregressive (CAR) model that approximates a Gaussian Process with the Matérn covariance, respectively. Our simulation study shows that properly modeling the spatial correlation and between-patient heterogeneity can substantially improve PCa classification. Application to in vivo data illustrates that classification is improved by all three spatial modeling approaches considered, while modeling the between-patient heterogeneity does not further improve our classifiers. Among the proposed models, the NNGP-based model is recommended given its high classification accuracy and computational efficiency., (© 2021 John Wiley & Sons Ltd.)

Multi-parametric MRI (mpMRI) is a critical tool in prostate cancer (PCa) diagnosis and management. To further advance the use of mpMRI in patient care, computer aided diagnostic methods are under continuous development for supporting/supplanting standard radiological interpretation. While voxel-wise PCa classification models are the gold standard, few if any approaches have incorporated the inherent structure of the mpMRI data, such as spatial heterogeneity and between-voxel correlation, into PCa classification. We propose a machine learning-based method to fill in this gap. Our method uses an ensemble learning approach to capture regional heterogeneity in the data, where classifiers are developed at multiple resolutions and combined using the super learner algorithm, and further account for between-voxel correlation through a Gaussian kernel smoother. It allows any type of classifier to be the base learner and can be extended to further classify PCa sub-categories. We introduce the algorithms for binary PCa classification, as well as for classifying the ordinal clinical significance of PCa for which a weighted likelihood approach is implemented to improve the detection of less prevalent cancer categories. The proposed method has shown important advantages over conventional modeling and machine learning approaches in simulations and application to our motivating patient data., Competing Interests: No potential conflict of interest was reported by the author(s)., (© 2021 Informa UK Limited, trading as Taylor & Francis Group.)

Multisource exchangeability models (MEMs), a BayeTsian approach for dynamically integrating information from multiple clinical trials, are a promising approach for gaining efficiency in randomized controlled trials. When the supplementary trials are considerably larger than the primary trial, care must be taken when integrating supplementary data to avoid overwhelming the primary trial. In this paper, we propose "capping priors," which controls the extent of dynamic borrowing by placing an a priori cap on the effective supplemental sample size. We demonstrate the behavior of this technique via simulation, and apply our method to four randomized trials of very low nicotine content cigarettes.

A simple approach for analyzing longitudinally measured biomarkers is to calculate summary measures such as the area under the curve (AUC) for each individual and then compare the mean AUC between treatment groups using methods such as t test. This two-step approach is difficult to implement when there are missing data since the AUC cannot be directly calculated for individuals with missing measurements. Simple methods for dealing with missing data include the complete case analysis and imputation. A recent study showed that the estimated mean AUC difference between treatment groups based on the linear mixed model (LMM), rather than on individually calculated AUCs by simple imputation, has negligible bias under random missing assumptions and only small bias when missing is not at random. However, this model assumes the outcome to be normally distributed, which is often violated in biomarker data. In this paper, we propose to use a LMM on log-transformed biomarkers, based on which statistical inference for the ratio, rather than difference, of AUC between treatment groups is provided. The proposed method can not only handle the potential baseline imbalance in a randomized trail but also circumvent the estimation of the nuisance variance parameters in the log-normal model. The proposed model is applied to a recently completed large randomized trial studying the effect of nicotine reduction on biomarker exposure of smokers., (© 2021 John Wiley & Sons Ltd.)

The increasing multiplicity of data sources offers exciting possibilities in estimating the effects of a treatment, intervention, or exposure, particularly if observational and experimental sources could be used simultaneously. Borrowing between sources can potentially result in more efficient estimators, but it must be done in a principled manner to mitigate increased bias and Type I error. Furthermore, when the effect of treatment is confounded, as in observational sources or in clinical trials with noncompliance, causal effect estimators are needed to simultaneously adjust for confounding and to estimate effects across data sources. We consider the problem of estimating causal effects from a primary source and borrowing from any number of supplemental sources. We propose using regression-based estimators that borrow based on assuming exchangeability of the regression coefficients and parameters between data sources. Borrowing is accomplished with multisource exchangeability models and Bayesian model averaging. We show via simulation that a Bayesian linear model and Bayesian additive regression trees both have desirable properties and borrow under appropriate circumstances. We apply the estimators to recently completed trials of very low nicotine content cigarettes investigating their impact on smoking behavior., (© 2021 John Wiley & Sons Ltd.)

A number of statistical approaches have been proposed for incorporating supplemental information in randomized clinical trials. Existing methods often compare the marginal treatment effects to evaluate the degree of consistency between sources. Dissimilar marginal treatment effects would either lead to increased bias or down-weighting of the supplemental data. This represents a limitation in the presence of treatment effect heterogeneity, in which case the marginal treatment effect may differ between the sources solely due to differences between the study populations. We introduce the concept of covariate-adjusted exchangeability, in which differences in the marginal treatment effect can be explained by differences in the distributions of the effect modifiers. The potential outcomes framework is used to conceptualize covariate-adjusted and marginal exchangeability. We utilize a linear model and the existing multisource exchangeability models framework to facilitate borrowing when marginal treatment effects are dissimilar but covariate-adjusted exchangeability holds. We investigate the operating characteristics of our method using simulations. We also illustrate our method using data from two clinical trials of very low nicotine content cigarettes. Our method has the ability to incorporate supplemental information in a wider variety of situations than when only marginal exchangeability is considered., (© The Author 2020. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Introduction: As the FDA works to determine whether a nicotine reduction policy would benefit public health, one key question is whether to mandate an immediate or gradual reduction in nicotine levels in cigarettes. The aim of this study was to determine whether the effects of gradual versus immediate nicotine reduction on cigarettes per day (CPD), total nicotine equivalents, and subjective responses differed in younger adults versus older adults., Methods: Using data from a recent randomized trial conducted in the United States (N = 1250) that switched smokers over a 20-week period to very low nicotine content (VLNC) cigarettes either immediately, gradually (via monthly reductions in nicotine content), or not at all (control condition, normal nicotine content research cigarette), we analyzed the moderating effect of age (age 18-24 or 25+)., Results: For both age groups, CPD in the immediate condition was significantly lower relative to gradual condition (estimated mean difference of 6.3 CPD in young adults, 5.2 CPD in older adults; p's < .05). Younger and older adults in the immediate and gradual reduction conditions had lower total nicotine equivalents at Week 20 (all p's < .05) than those in the control condition; age group did not moderate this effect. Positive subjective responses to cigarettes were lower among young adults relative to older adults in the immediate condition., Conclusions: These results indicate that an immediate reduction in nicotine would result in beneficial effects in both young and older adults. Young adults show less positive subjective effects of smoking following switching to VLNC cigarettes relative to older adults., Implications: As researchers work to understand how a potential reduced-nicotine product standard for cigarettes may affect public health, one question is whether nicotine should be reduced immediately or gradually. This study demonstrates that both young and older adults who were switched immediately to the lowest content of nicotine smoked fewer CPD and had lower nicotine intake than those in the gradual condition. Furthermore, young adults appear to show lower positive subjective effects following switching to VLNC cigarettes relative to older adults. This is consistent with previous work demonstrating that young people appear to show lower abuse liability for VLNC cigarettes., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Lowering nicotine in cigarettes may reduce smoking prevalences; however, it is not known whether an immediate or gradual reduction in nicotine is the optimal approach for all population groups., Objectives: We examined whether the optimal approach to nicotine reduction depended on the education, gender, or race of people who smoke and whether the optimal approach differentially benefited people who smoke based on their education, gender, or race., Methods: Secondary analysis was conducted on a randomized clinical trial (N = 1250) comparing (1) immediate reduction from 15.5 to 0.4 mg of nicotine per gram of tobacco(mg/g);(2) gradual reduction to 0.4 mg/g;(3) control group with normal nicotine cigarettes(15.5 mg/g). Outcomes included cigarettes per day(CPD), carbon monoxide(CO), total nicotine equivalents(TNE), 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol and its glucuronides(NNAL), phenanthrene tetraol(PheT), N-Acetyl-S-(2-cyanoethyl)-l-cysteine(CEMA). Data were analyzed as area under the curve(AUC)., Results: Results were presented by education (High school[HS] or less n = 505, more than HS n = 745), gender (males n = 701, females n = 549), and race (Black participants n = 373,White participants n = 758). Regardless of education, gender, and race, CPD, CO, TNE, NNAL, PheT, and CEMA were lower in immediate versus gradual nicotine reduction. Comparing immediate versus the control, outcomes were lower for all subgroups; however, the magnitude of the effect for TNE varied by race. Specifically, geometric mean of the AUC of TNE in immediate versus gradual was 49 % lower in Black participants and 61 % lower in White participants (p-value = 0.047)., Conclusions: Immediately reducing nicotine in cigarettes has the potential to benefit people who smoke across lower and higher educational attainment, male and female gender, and Black and White race., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Background: The SARS-CoV-2 virus enters cells via Angiotensin-converting enzyme 2 (ACE2), disrupting the renin-angiotensin-aldosterone axis, potentially contributing to lung injury. Treatment with angiotensin receptor blockers (ARBs), such as losartan, may mitigate these effects, though induction of ACE2 could increase viral entry, replication, and worsen disease., Methods: This study represents a placebo-controlled blinded randomized clinical trial (RCT) to test the efficacy of losartan on outpatients with COVID-19 across three hospital systems with numerous community sites in Minnesota, U.S. Participants included symptomatic outpatients with COVID-19 not already taking ACE-inhibitors or ARBs, enrolled within 7 days of symptom onset. Patients were randomized to 1:1 losartan (25 mg orally twice daily unless estimated glomerular filtration rate, eGFR, was reduced, when dosing was reduced to once daily) versus placebo for 10 days, and all patients and outcome assesors were blinded. The primary outcome was all-cause hospitalization within 15 days. Secondary outcomes included functional status, dyspnea, temperature, and viral load. (clinicatrials.gov, NCT04311177, closed to new participants)., Findings: From April to November 2020, 117 participants were randomized 58 to losartan and 59 to placebo, and all were analyzed under intent to treat principles. The primary outcome did not differ significantly between the two arms based on Barnard's test [losartan arm: 3 events (5.2% 95% CI 1.1, 14.4%) versus placebo arm: 1 event (1.7%; 95% CI 0.0, 9.1%)]; proportion difference -3.5% (95% CI -13.2, 4.8%); p  = 0.32]. Viral loads were not statistically different between treatment groups at any time point. Adverse events per 10 patient days did not differ signifcantly [0.33 (95% CI 0.22-0.49) for losartan vs. 0.37 (95% CI 0.25-0.55) for placebo]. Due to a lower than expected hospitalization rate and low likelihood of a clinically important treatment effect, the trial was terminated early., Interpretation: In this multicenter blinded RCT for outpatients with mild symptomatic COVID-19 disease, losartan did not reduce hospitalizations, though assessment was limited by low event rate. Importantly, viral load was not statistically affected by treatment. This study does not support initiation of losartan for low-risk outpatients., Competing Interests: The authors have no financial conflicts of interest to disclose. All the authors report grants from Minnesota Partnership for Biotechnology and Medical Genomics during the conduct of the study. MAP reports also grants from Bill and Melinda Gates Foundation and grants from NHLBI, outside the submitted work., (© 2021 The Author(s).)

Introduction: A nicotine product standard reducing the nicotine content in cigarettes could improve public health by reducing smoking. This study evaluated the potential unintended consequences of a reduced nicotine product standard by examining its effects on (1) smoking behaviors based on drinking history; (2) drinking behavior; and (3) daily associations between smoking and drinking., Methods: Adults who smoke daily (n = 752) in the United States were randomly assigned to smoke very low nicotine content (VLNC) cigarettes versus normal nicotine content (NNC; control) cigarettes for 20 weeks. Linear mixed models determined if baseline drinking moderated the effects of VLNC versus NNC cigarettes on Week 20 smoking outcomes. Time-varying effect models estimated the daily association between smoking VLNC cigarettes and drinking outcomes., Results: Higher baseline alcohol use (vs no use or lower use) was associated with a smaller effect of VLNC on Week 20 urinary total nicotine equivalents (ps < .05). No additional moderation was supported (ps > .05). In the subsample who drank (n = 415), in the VLNC versus NNC condition, daily alcohol use was significantly reduced from Weeks 17 to 20 and odds of binge drinking were significantly reduced from Weeks 9 to 17. By Week 7, in the VLNC cigarette condition (n = 272), smoking no longer predicted alcohol use but remained associated with binge drinking., Conclusions: We did not support negative unintended consequences of a nicotine product standard. Nicotine reduction in cigarettes generally affected smoking behavior for individuals who do not drink or drink light-to-moderate amounts in similar ways. Extended VLNC cigarette use may improve public health by reducing drinking behavior., Implications: There was no evidence that a VLNC product standard would result in unintended consequences based on drinking history or when considering alcohol outcomes. Specifically, we found that a very low nicotine standard in cigarettes generally reduces smoking outcomes for those who do not drink and those who drink light-to-moderate amounts. Furthermore, an added public health benefit of a very low nicotine standard for cigarettes could be a reduction in alcohol use and binge drinking over time. Finally, smoking VLNC cigarettes may result in a decoupling of the daily associations between smoking and drinking., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved.For permissions, please e-mail: journals.permissions@oup.com.)

Introduction: The Food and Drug Administration is considering a policy to drastically reduce the allowable nicotine content of cigarettes. The current study examined whether the policy implementation approach, i.e., either immediately reducing nicotine content to very low levels or gradually reducing nicotine content over an extended period, influences policy support among people who smoke cigarettes., Methods: Adults who smoked daily were randomly assigned (double-blind) to an immediate nicotine reduction condition (0.4 mg/g nicotine cigarettes), a gradual nicotine reduction condition (15.5 to 0.4 mg/g), or a control condition (15.5 mg/g) for 20 weeks. Participants were asked if they would "support or oppose a law that reduced the amount of nicotine in cigarettes, to make cigarettes less addictive." Logistic regression analyses assessed if policy support was affected by treatment condition, demographic covariates, interest in quitting, and subjective cigarette effects., Results: At Week 20 (N = 957 completers), 60.4% of participants supported the policy, 17.4% opposed, and 22.2% responded "Don't know." Policy support did not differ by treatment condition. Support was greater among those interested in quitting (OR = 3.37, 95% CI = 2.49, 4.55). Support was lower among males (OR = 0.49, 95% CI = 0.37, 0.67), those with greater dependence scores (OR = 0.92, 95% CI = 0.86, 0.99) and participants aged 18-24 (OR = 0.53, 95% CI = 0.28, 0.99). No other covariates were associated with policy support., Conclusions: The majority of participants supported a nicotine reduction policy. The implementation approach, immediate or gradual reduction, did not affect policy support. Participants interested in quitting smoking were more likely to support a nicotine reduction policy., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Breakthroughs in cancer biology have defined new research programs emphasizing the development of therapies that target specific pathways in tumor cells. Innovations in clinical trial design have followed with master protocols defined by inclusive eligibility criteria and evaluations of multiple therapies and/or histologies. Consequently, characterization of subpopulation heterogeneity has become central to the formulation and selection of a study design. However, this transition to master protocols has led to challenges in identifying the optimal trial design and proper calibration of hyperparameters. We often evaluate a range of null and alternative scenarios; however, there has been little guidance on how to synthesize the potentially disparate recommendations for what may be optimal. This may lead to the selection of suboptimal designs and statistical methods that do not fully accommodate the subpopulation heterogeneity. This article proposes novel optimization criteria for calibrating and evaluating candidate statistical designs of master protocols in the presence of the potential for treatment effect heterogeneity among enrolled patient subpopulations. The framework is applied to demonstrate the statistical properties of conventional study designs when treatments offer heterogeneous benefit as well as identify optimal designs devised to monitor the potential for heterogeneity among patients with differing clinical indications using Bayesian modeling.

Introduction: Participant noncompliance, in which participants do not follow their assigned treatment protocol, has long complicated the interpretation of randomized clinical trials. No gold standard has been identified for detecting noncompliance, but in some trials participants' biomarkers can provide objective information that suggests exposure to non-study treatments. However, existing methods are limited to retrospectively detecting noncompliance at a single time point based on a single biomarker measurement. We propose a novel method that can leverage participants' full biomarker history to detect noncompliance across multiple time points. Conditional on longitudinal biomarker data, our method can estimate the probability of compliance at (1) a single time point of the trial, (2) all time points, and (3) a future time point., Methods: Across time points, we model the biomarker as a mixture density with (latent) components corresponding to longitudinal patterns of compliance. To estimate the mixture density, we fit mixed effects models for both compliance and the biomarker. We use the mixture density to derive compliance probabilities that condition on the longitudinal biomarker data. We evaluate our compliance probabilities by simulation and apply them to a trial in which current smokers were asked to only smoke low nicotine study cigarettes (Center for the Evaluation of Nicotine in Cigarettes Project 1 Study 2). In the simulation, we investigated three different effects of compliance on the biomarker, as well as the effect of misspecification of the covariance structures. We compared probability estimators (1) and (2) to those that ignore the longitudinal correlation in the data according to area under the receiver operating characteristic curve. We evaluated estimator (3) by plotting its calibration lines. For Center for the Evaluation of Nicotine in Cigarettes Project 1 Study 2, we compared estimators (1) and (3) to a probability estimator of compliance at the last time point that ignores the longitudinal correlation., Results: In the simulation, for both compliance at the last time point and at all time points, conditioning on the longitudinal biomarker data uniformly raised area under the receiver operating characteristic curve across all three compliance effect scenarios. The gains in area under the receiver operating characteristic curve were smaller under misspecification. The calibration lines for the prediction of compliance closely followed 45°, though with additional variability under misspecification. For compliance at the last time point of Center for the Evaluation of Nicotine in Cigarettes Project 1 Study 2, conditioning on participants' full biomarker history boosted area under the receiver operating characteristic curve by three percentage points. The prediction probabilities somewhat accurately approximated the non-longitudinal compliance probabilities., Discussion: Compared to existing methods that only use a single biomarker measurement, our method can account for the longitudinal correlation in the biomarker and compliance to more accurately identify noncompliant participants. Our method can also use participants' biomarker history to predict compliance at a future time point.

We previously reported that eBAT, an EGF-targeted angiotoxin, was safe and it improved the overall survival for dogs with splenic haemangiosarcoma when added to the standard of care in a single cycle of three administrations in the minimal residual disease setting. Our objective for the SRCBST-2 trial was to assess whether increased dosing through multiple cycles of eBAT would be well tolerated and would further enhance the benefits of eBAT. Eligibility was expanded to dogs with stage 3 haemangiosarcoma, provided that gross lesions could be surgically excised. The interval between eBAT and the start of chemotherapy was reduced, and the experimental therapy was expanded to three cycles, each administered at the biologically active dose (50 μg/kg) on a Monday/Wednesday/Friday schedule following splenectomy, and scheduled 1 week prior to the first, second and fifth doxorubicin chemotherapy. Twenty-five dogs were enrolled; six experienced acute hypotension with two requiring hospitalization. Self-limiting elevation of ALT was observed in one dog. A statistically significant survival benefit was not seen in this study in eBAT-treated dogs compared with a Contemporary comparison group of dogs with stages 1-3 haemangiosarcoma treated with standard of care alone. Our results indicate that repeated dosing cycles of eBAT starting 1 week prior to doxorubicin chemotherapy led to greater toxicity and reduced efficacy compared with a single cycle given between surgery and a delayed start of chemotherapy. Further work is needed to understand the precise mechanisms of action of eBAT in order to optimize its clinical benefits in the treatment of canine haemangiosarcoma and other tumours. IACUC Protocols 1110A06186 and 1507-32804A., (© 2020 John Wiley & Sons Ltd.)

Background: Cotinine is the most widely used biomarker of tobacco exposure. At similar smoking levels, African Americans have higher serum cotinine than Whites. UGT2B10-catalyzed cotinine glucuronidation impacts these levels, and African Americans often have low UGT2B10 activity due to a high prevalence of a UGT2B10 splice variant (rs2942857)., Methods: Two UGT2B10 SNPs (rs6175900 and rs2942857) were genotyped in 289 African Americans and 627 White smokers. Each smoker was assigned a genetic score of 0, 1, or 2 based on the number of variant alleles. Total nicotine equivalents (TNE), the sum of nicotine and six metabolites, and serum cotinine and 3'-hydroxycotinine were quantified. The contribution of UGT2B10 genetic score to cotinine concentration was determined., Results: Serum cotinine was significantly higher in smokers with UGT2B10 genetic scores of 2 versus 0 (327 ng/mL vs. 221 ng/mL; P < 0.001); TNEs were not different. In a linear regression model adjusted for age, gender, cigarettes per day, TNE, race, and CYP2A6 activity, geometric mean cotinine increased 43% between genetic score 2 versus 0 ( P < 0.001). A 0.1 increase in the CYP2A6 activity ratio, 3'-hydroxycotinine/cotinine, resulted in a 6% decrease in cotinine. After adjustment for UGT2B10 genotype and the other covariants, there was no significant difference in serum cotinine by race., Conclusions: UGT2B10 genotype is a major contributor to cotinine levels and explains the majority of high serum cotinine in African American smokers., Impact: Cotinine levels in smokers may greatly overestimate tobacco exposure and potentially misinform our understanding of ethnic/racial difference in tobacco-related disease if UGT2B10 genotype is not taken into account., (©2020 American Association for Cancer Research.)

Identifying noncompliance in a randomized trial is challenging, but could be improved by leveraging biomarker data to identify participants that did not comply with their assigned treatment. For randomized trials of very low nicotine content (VLNC) cigarettes, the biomarker of total nicotine equivalents (TNE) could be used to identify noncompliance. Compliant participants should have lower levels of TNEs than participants that did not comply and smoked normal nicotine content cigarettes, resulting in a mixture of compliant and noncompliant participants at each dose level. Thresholds of TNE could then be identified from the compliant groups at each dose level and used to determine which study participants were compliant. Furthermore, proposed biological relationships of TNE with nicotine dose could be incorporated into improve the efficiency of estimation, but may introduce bias if misspecified. To account for multiple modeling assumptions across dose levels, we explore model averaging via reversible jump markov chain monte carlo (MCMC) within each dose level to take advantage of improvements in efficiency when the proposed relationship is true and to downweight the biological model when it is misspecified. In simulation studies, we demonstrate that model averaging in the presence of a correct biological relationship results in a decrease in the mean square error (MSE) of up to 85%, but downweights the model in dose levels where the relationship is not appropriate. We apply our approach to data from a randomized trial of VLNC cigarettes to estimate TNE thresholds and probability of compliance curves as a function of TNEs for each nicotine dose used in the trial., (© 2020 John Wiley & Sons, Ltd.)

Background: The FDA is considering a mandated reduction in the nicotine content of cigarettes. Clinical trials have been limited by non-study cigarette use (noncompliance), which could mask compensation. The goal of this study was to assess whether compensation occurs when smokers provided with very low nicotine cigarettes cannot access normal nicotine cigarettes., Methods: In a within-subjects, crossover design, current smokers ( n = 16) were confined to a hotel for two 4-night hotel stays during which they were only able to access the research cigarettes provided. The hotel stays offered normal nicotine cigarettes or very low nicotine content (VLNC) cigarettes, in an unblinded design, available for "purchase" via a study bank., Results: In the context of complete compliance with the study cigarettes ( n = 16), there was not a significant increase during the VLNC condition for cigarettes smoked per day, expired carbon monoxide, or N-acetyl-S-(cyanoethyl)-l-cysteine (cyanoethyl-MA, metabolite of acrylonitrile). There was a significant nicotine × time interaction on urine N-acetyl-S-(3-hydroxypropyl)-l-cysteine (hydroxypropyl-MA, metabolite of acrolein), driven by an increase in the VLNC condition during the first 24 hours. By the end of the VLNC condition, there was no evidence of compensation across any measure of smoking or smoke exposure., Conclusions: Among current smokers who exclusively used VLNC cigarettes for 4 days, there was no significant compensatory smoking behavior., Impact: These data, combined with the larger body of work, suggest that a mandated reduction in nicotine content is unlikely to result in an increase in smoking behavior to obtain more nicotine., (©2020 American Association for Cancer Research.)

Background: A mandated reduction in the nicotine content of cigarettes could reduce smoking rate and prevalence. However, one concern is that smokers may compensate by increasing the intensity with which they smoke each cigarette to obtain more nicotine. This study assessed whether smokers engage in compensatory smoking by estimating the mouth-level nicotine intake of low nicotine cigarettes smoked during a clinical trial., Methods: Smokers were randomly assigned to receive cigarettes with one of five nicotine contents for 6 weeks. An additional group received a cigarette with the lowest nicotine content, but an increased tar yield. The obtained mouth-level nicotine intake from discarded cigarette butts for a subset of participants (51-70/group) was estimated using solanesol as described previously. A compensation index was calculated for each group to estimate the proportion of nicotine per cigarette recovered through changes in smoking intensity., Results: There was no significant increase in smoking intensity for any of the reduced nicotine cigarettes as measured by the compensation index (an estimated 0.4% of the nicotine lost was recovered in the lowest nicotine group; 95% confidence interval, -0.1 to 1.2). There was a significant decrease in smoking intensity for very low nicotine content cigarettes with increased tar yield., Conclusions: Reductions in nicotine content did not result in compensatory changes in how intensively participants smoked research cigarettes., Impact: Combined with data from clinical trials showing a reduction in cigarettes smoked per day, these data suggest that a reduction in nicotine content is unlikely to result in increased smoke exposure., (©2020 American Association for Cancer Research.)

Background: A recent clinical trial showed that an immediate transition to very low nicotine content (VLNC) cigarettes, compared with a gradual transition, produced greater reductions in smoking behavior, smoke exposure, and dependence. However, there was less compliance with the instruction to smoke only VLNC cigarettes in the immediate versus gradual reduction condition. The goal of this study was to test whether nicotine reduction method alters subjective ratings of VLNC cigarettes, and whether subjective ratings mediate effects of nicotine reduction method on smoking behavior, smoke exposure, dependence, and compliance., Methods: This is a secondary analysis of a randomized trial conducted across 10 sites in the United States. Smokers (n = 1250) were randomized to either a control condition, or to have the nicotine content of their cigarettes reduced immediately or gradually to 0.04 mg nicotine/g of tobacco during a 20-week study period. Participants completed the modified Cigarette Evaluation Questionnaire (mCEQ)., Results: After Week 20, the immediate reduction group scored significantly lower than the gradual reduction group on multiple subscales of the mCEQ (ps < .001). The Satisfaction subscale of the mCEQ mediated the impact of nicotine reduction method on smoke exposure, smoking behavior, dependence, compliance, and abstinence. Other subscales also mediated a subset of these outcomes., Conclusions: An immediate reduction in nicotine content resulted in lower product satisfaction than a gradual reduction, suggesting that immediate reduction further reduces cigarette reward value. This study will provide the Food and Drug Administration with information about the impact of nicotine reduction method on cigarette reward value., Implications: These data suggest that an immediate reduction in nicotine content will result in greater reductions in cigarette satisfaction than a gradual reduction, and this reduction in satisfaction is related to changes in smoking behavior and dependence., (© The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco.)

Recent evidence from randomized clinical trials (RCTs) of very low nicotine content (VLNC) cigarettes indicates that smokers randomized to VLNC cigarettes had significantly lower cigarette use, dependence, and biomarkers of exposure than smokers randomized to normal nicotine content control cigarettes. In these trials, a substantial number of participants did not adhere to their randomized treatment assignment, i.e., they used commercial cigarettes not provided by the trial in place of or in addition to the VLNC cigarettes provided by the trial. As with most RCTs, the analysis of these trials followed the intention-to-treat principle, where participants are analyzed according to their randomized treatment assignment regardless of adherence. Alternately, the analysis of an RCT could focus on the estimation and testing of the causal effect of the intervention, which is the treatment effect if all subjects were to adhere to their randomized treatment assignment. In this commentary, we compare these two approaches, highlighting the important role of causal estimation and inference for evaluating the regulatory effect of a nicotine standard for cigarettes. Additionally, we review the results of the secondary analyses of randomized trials of VLNC cigarettes using causal inference methodology to account for non-adherence to the assigned treatment and discuss the implications for a nicotine standard for cigarettes., (© The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco.)

Introduction: Because 30% of cigarettes sold in the United States are characterized as menthol cigarettes, it is important to understand how menthol preference may affect the impact of a nicotine reduction policy., Methods: In a recent trial, non-treatment-seeking smokers were randomly assigned to receive very low nicotine cigarettes (VLNC; 0.4 mg nicotine/g tobacco) or normal nicotine cigarettes (NNC; 15.5 mg/g) for 20 weeks. On the basis of preference, participants received menthol or non-menthol cigarettes. We conducted multivariable regression analyses to examine whether menthol preference moderated the effects of nicotine content on cigarettes per day (CPD), breath carbon monoxide (CO), urinary total nicotine equivalents (TNE), urinary 2-cyanoethylmercapturic acid (CEMA), and abstinence., Results: At baseline, menthol smokers (n = 346) reported smoking fewer CPD (14.9 vs. 19.2) and had lower TNE (52.8 vs. 71.6 nmol/mg) and CO (17.7 vs. 20.5 ppm) levels than non-menthol smokers (n = 406; ps < .05). At week 20, significant interactions indicated that menthol smokers had smaller treatment effects than non-menthol smokers for CPD (-6.4 vs. -9.3), TNE (ratio of geometric means, 0.22 vs. 0.10) and CEMA (ratio, 0.56 vs. 0.37; ps < .05), and trended toward a smaller treatment effect for CO (-4.5 vs. -7.3 ppm; p = .06). Odds ratios for abstinence at week 20 were 1.88 (95% confidence interval [CI] = 0.8 to 4.4) for menthol and 9.11 (95% CI = 3.3 to 25.2) for non-menthol VLNC smokers (p = .02) relative to the NNC condition., Conclusions: Although menthol smokers experienced reductions in smoking, toxicant exposure, and increases in quitting when using VLNC cigarettes, the magnitude of change was smaller than that observed for non-menthol smokers., Implications: Results of this analysis suggest that smokers of menthol cigarettes may respond to a nicotine reduction policy with smaller reductions in smoking rates and toxicant exposure than would smokers of non-menthol cigarettes., (© The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco.)

Progress in the areas of genomics, disease pathways, and drug discovery has advanced into clinical and translational cancer research. The latest innovations in clinical trials have followed with master protocols, which are defined by inclusive eligibility criteria and devised to interrogate multiple therapies for a given tumor histology and/or multiple histologies for a given therapy under one protocol. The use of master protocols for oncology has become more common with the desire to improve the efficiency of clinical research and accelerate overall drug development. Basket trials have been devised to ascertain the extent to which a treatment strategy offers benefit to various patient subpopulations defined by a common molecular target. Conventionally conducted within the phase II setting, basket designs have become popular as drug developers seek to effectively evaluate and identify preliminary efficacy signals among clinical indications identified as promising in preclinical study. This article reviews basket trial designs in oncology settings and discusses several issues that arise with their design and analysis.

Introduction: A mandated reduction in the nicotine content of cigarettes may decrease smoking, but also increase demand for other nicotine products. The present study tested the impact of smoking cigarettes with very low nicotine content and concurrent use of a transdermal nicotine patch., Study Design: A balanced 2 × 2 factorial randomized clinical trial investigating the impact of cigarette nicotine content (double-blind, very low nicotine content versus normal nicotine content) and use of a transdermal nicotine patch (open label, patch versus no patch)., Setting/participants: Adult daily smokers (n=240) in the Pittsburgh, PA area., Intervention: Participants were provided with research cigarettes and transdermal nicotine patches (if assigned to patch condition) for 7 weeks. Cigarettes were Spectrum brand (National Institute on Drug Abuse) and either 15.8 mg nicotine/g tobacco (normal nicotine content) or 0.4 mg nicotine/g tobacco (very low nicotine content). In the 7th week, participants were monetarily incentivized to abstain from smoking., Main Outcome Measures: Participants reported daily cigarette use throughout the trial and the primary outcome was average number of cigarettes smoked per day (study + nonstudy) during Week 6. Participants were recruited from 2015 to 2017 and data were analyzed between 2017 and 2018., Results: Assignment to very low nicotine content cigarettes and assignment to wear a nicotine patch both reduced the number of cigarettes smoked per day during Week 6 (p=0.001 and 0.04, respectively). However, assignment to the patch along with very low nicotine content cigarettes did not significantly reduce cigarette smoking compared with assignment to very low nicotine content cigarettes alone., Conclusions: A mandated reduction in the nicotine content of cigarettes is likely to reduce the number of cigarettes smoked per day, but the added benefit of concurrent transdermal nicotine is unclear. Future studies should investigate whether alternative sources of noncombusted tobacco, such as e-cigarettes, enhance the effects of very low nicotine content cigarettes on smoking., Trial Registration: This study is registered at www.clinicaltrials.gov NCT02301325., (Copyright © 2019 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.)

Introduction: Reducing the level of nicotine in cigarettes is a regulatory strategy that has the potential to greatly improve public health. If nicotine levels are reduced in all commercially available cigarettes, current smokers might find it easier to quit and young people might be less likely to become dependent. However, it is not yet known whether age moderates subjective or behavioral responses to low-nicotine cigarettes., Methods: Recently, a large, multisite randomized clinical trial was conducted to compare the effects of cigarettes differing in nicotine content (either usual-brand or research cigarettes containing 15.8, 5.2, 2.4, 1.3, or 0.4 mg nicotine/g tobacco) across 6 weeks of exposure. In this secondary analysis, we tested whether age moderated smokers' subjective (measures of psychological reward, smoking satisfaction) and behavioral (cigarettes smoked per day, smoking topography, and nicotine exposure) responses to cigarettes varying in nicotine content after 2 and 6 weeks of use, while controlling for baseline dependence and demographic factors., Results: Results indicated that younger adults (age 18-24) who smoked cigarettes with 2.4-0.4 mg/g nicotine reported significantly less smoking satisfaction and psychological reward, and smoked fewer cigarettes per day, than older adults (25+ years) after 2 weeks of use. No differences in topography were observed at either time point. After 6 weeks of use, differences had diminished on all measures., Conclusions: The reduced positive effects of reduced-nicotine content cigarettes in young adults suggests that this regulatory policy may reduce smoking reinforcement in this vulnerable population., Implications: As the FDA considers reducing the level of nicotine in cigarettes to make them less addictive, understanding the potential impact of this policy on young people is of crucial importance. We found that young adults had significantly lower positive subjective effects to very-low nicotine content (VLNC) cigarettes and smoked fewer VLNC cigarettes than older adults after 2 weeks of use, indicating that this policy may reduce smoking reinforcement more quickly in young adults. These data add to the growing body of evidence on the potential for this policy to positively affect public health., (© The Author(s) 2018. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Prostate cancer (PCa) is a major cause of cancer death among men. The histopathological examination of post-surgical prostate specimens and manual annotation of PCa not only allow for detailed assessment of disease characteristics and extent, but also supply the ground truth for developing of computer-aided diagnosis (CAD) systems for PCa detection before definitive treatment. As manual cancer annotation is tedious and subjective, there have been a number of publications describing methods for automating the procedure via the analysis of digitized whole-slide images (WSIs). However, these studies have focused only on the analysis of WSIs stained with hematoxylin and eosin (H&E), even though there is additional information that could be obtained from immunohistochemical (IHC) staining. In this work, we propose a framework for automating the annotation of PCa that is based on automated colorimetric analysis of both H&E and IHC WSIs stained with a triple-antibody cocktail against high-molecular weight cytokeratin (HMWCK), p63, and α-methylacyl CoA racemase (AMACR). The analysis outputs were then used to train a regression model to estimate the distribution of cancerous epithelium within slides. The approach yielded an AUC of 0.951, sensitivity of 87.1%, and specificity of 90.7% as compared to slide-level annotations, and generalized well to cancers of all grades.

Objectives: Evaluate the classification accuracy of biomarkers of nicotine exposure for identifying noncompliance in randomized controlled trials (RCTs) of very low nicotine content (VLNC) cigarettes., Methods: We combined data from 2 studies to evaluate the classification accuracy of biomarkers of nicotine exposure for identifying noncompliance in RCTs of VLNC cigarettes. Using a novel approach that did not require knowledge of each participant's compliance status, we modeled the distributions of total nicotine equivalents (TNE), total cotinine, and anatabine in compliant and noncompliant participants using a mixture model. Estimates of the classification accuracy were derived from the estimated densities., Results: TNE and total cotinine had near-perfect classification accuracy, but TNE had better classification accuracy than total cotinine (p = 0.03) and anatabine (p = 0.014). The classification accuracy of TNE and total cotinine decreased as self-reported study cigarettes increased; anatabine was similar, but the results were more statistically variable., Conclusions: TNE and total cotinine are better classifiers of compliance than anatabine. These results will be useful in determining biomarker thresholds for identifying noncompliance and will aid in the interpretation of future RCTs of VLNC cigarettes., Competing Interests: Conflict of Interest Disclosure Statement The authors have no conflicts of interest to report.

Background: The US Food and Drug Administration recently issued an advanced notice of proposed rule-making for reducing the nicotine content in cigarettes to a minimally addictive level. Very little is known about whether use of very low nicotine content (VLNC) cigarettes affects support for a nicotine reduction policy., Objective: This study examined the effects of using VLNC versus usual brand (UB) cigarettes on support for a nicotine reduction policy and determined whether participant characteristics and responses to VLNC cigarettes were associated with policy support., Methods: Participants from a cigarette trial who were assigned to either 0.4 mg nicotine/g tobacco research cigarettes or their UB for 6 weeks were asked about their support for the policy. χ 2 tests were used to compare support for the policy between cigarette conditions and logistic regression analyses were conducted to assess covariates associated with policy support., Findings: Policy support did not differ by condition. After 6 weeks of using VLNC cigarettes, 50% of participants supported the policy, 26% opposed and 24% responded 'Don't Know'. Support was higher among those adherent to smoking only VLNC cigarettes (65%) compared with those who were non-adherent (44%). Older participants and those interested in quitting had increased odds of support. Cigarette satisfaction, perceived harm and perceived nicotine content were not significantly associated with support., Conclusions: Smoking VLNC cigarettes did not affect support for a nicotine reduction policy. Understanding predictors of policy support and opposition will help public health officials to maximise the public health acceptance and impact of this policy (ClinicalTrials.gov Identifier: NCT01681875 Post-Results)., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ.)

The best known ovarian cancer biomarker, CA125, is neither adequately sensitive nor specific for screening the general population. By using a combination of proteins for screening, it may be possible to increase the sensitivity and specificity over CA125 alone. In this study, we used Proseek Multiplex Oncology II plates to simultaneously measure the expression of 92 cancer-related proteins in serum using proximity extension assays. This technology combines the sensitivity of the PCR with the specificity of antibody-based detection methods, allowing multiplex biomarker detection and high-throughput quantification. We analyzed 1 μL of sera from each of 61 women with ovarian cancer and compared the values obtained with those from 88 age-matched healthy women. Principle component analysis and unsupervised hierarchical clustering separated the ovarian cancer patients from the healthy, with minimal misclassification. Data from the Proseek plates for CA125 levels exhibited a strong correlation with clinical values for CA125. We identified 52 proteins that differed significantly ( P < 0.006) between ovarian cancer and healthy samples, several of which are novel serum biomarkers for ovarian cancer. In total, 40 proteins had an estimated area under the ROC curve of 0.70 or greater, suggesting their potential to serve as biomarkers for ovarian cancer. CA125 alone achieved a sensitivity of 93.4% at a specificity of 98%. By adding the Oncology II values for five proteins to CA125 in a multiprotein classifier, we increased the assay sensitivity to 98.4% at a specificity of 98%, thereby improving the sensitivity and specificity of CA125 alone., (©2019 American Association for Cancer Research.)

Estimating causal effects from randomized controlled trials is often complicated due to participant noncompliance to randomized treatment. Although there are a variety of methods to estimate causal effects in the presence of noncompliance, they generally make the assumption that noncompliance is measured without error. This is frequently an untenable assumption, particularly when noncompliance is based on participant self-report. To overcome this issue, we treat compliance as an unobserved variable and show how to estimate the probability of compliance given a biomarker of treatment and the other observed data. We present inverse probability weighted estimators, regression-based estimators, and a doubly-robust augmented estimator that rely on the estimated probability of compliance rather than an indicator of compliance. We investigate the finite-sample properties of the estimators and their efficiency and robustness under correctly specified or misspecified models, and we apply the estimators to a recently completed trial of very low nicotine content cigarettes., (© 2018 John Wiley & Sons, Ltd.)