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Background: The combination of bazedoxifene 20 mg (BZA) and conjugated estrogens 0.45 mg (CE) marketed as Duavee® is approved for vasomotor symptom relief and osteoporosis prevention. Our pilot study suggested it had potential breast cancer risk reduction, and we proposed a multisite Phase IIB primary prevention trial assessing change in breast imaging and tissue risk biomarkers. By the time funding was acquired in February 2021, Duavee® was unavailable with an uncertain return date. A redesign was needed to salvage the study., Methods: The basic trial design was minimally altered. Women age 45-64 at elevated risk for breast cancer with vasomotor symptoms and no menses for at least 2 months have mammography, phlebotomy, and benign breast tissue sampling before and after 6 months of intervention. However, instead of Duavee® (single pill) vs placebo, women are randomized to 6 months of BZA + CE vs Waitlist. Those initially randomized to Waitlist can receive BZA + CE after 6 months. The primary endpoint is between arm difference in change in a fully automated measure of mammographic density with blood and tissue-based secondary endpoints., Outcomes: Accrual initiation was delayed due to contractual difficulties surrounding BZA importation during COVID-19 and deploying a fully automated method (Volpara®) to assess the primary endpoint. To accommodate this delay, a mid-grant no cost extension along with amended eligibility requirements were employed. 61/120 participants needed were entered in the initial 27 months of accrual and 37 months of funding. Despite a late start, accrual is likely to be completed within the funding period., 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 The Authors. Published by Elsevier Inc. All rights reserved.)

Background and Purpose: Cerebral infarction remains an important cause of death or disability in patients with aneurysmal subarachnoid hemorrhage (SAH). The prevalence, trends, and outcomes of cerebral infarction in patients with aneurysmal SAH at a national level are not known., Methods: We identified the proportion of patients who develop cerebral infarction (ascertained using validated methodology) among patients with aneurysmal SAH and annual trends using the Nationwide Inpatient Sample (NIS) from 2016 to 2021. We analyzed the effect of cerebral infarction on in-hospital mortality, routine discharge without palliative care (based on discharge disposition), poor outcome defined by the NIS SAH outcome measure, and length and costs of hospitalization after adjusting for potential confounders., Results: A total of 35,305 (53.6%) patients developed cerebral infarction among 65,840 patients with aneurysmal SAH over a 6-year period. There was a trend toward an increase in the proportion of patients who developed cerebral infarction from 51.5% in 2016 to 56.1% in 2021 (p trend p<.001). Routine discharge was significantly lower (30.5% vs. 37.8%, odds ratio [OR] 0.82, 95% confidence interval [CI] 0.75-0.89, p<.001), and poor outcome defined by NIS-SAH outcome measure was significantly higher among patients with cerebral infarction compared with those without cerebral infarction (67.4% vs. 59.3%, OR 1.29, 95% CI 1.18-1.40, p<.001). There was no difference in in-hospital mortality (13.0% vs. 13.6%, OR 0.94, 95% CI 0.85-1.05, p = .30). The length of stay (median 18 days [interquartile range [IQR] 13-25] vs. 14 days [IQR 9-20]), coefficient 3.04, 95% CI 2.44-3.52 and hospitalization cost (median $96,823 vs. $71,311, coefficient 22,320, 95% CI 20,053-24,587) were significantly higher among patients who developed cerebral infarction compared with those who did not develop cerebral infarction., Conclusions: Cerebral infarction was seen in 54% of the patients with a trend toward an increase in the affected proportion of patients with aneurysmal SAH. Patients with cerebral infarction had higher rates of adverse outcomes and required higher resources during hospitalization., (© 2024 American Society of Neuroimaging.)

Background: Clinical practice recommendations guide healthcare decisions. This study aims to evaluate the strength and quality of evidence supporting the American Heart Association (AHA)/American Stroke Association (ASA) guidelines for aneurysmal subarachnoid hemorrhage (aSAH) and spontaneous intracerebral hemorrhage (ICH)., Methods: We reviewed the current AHA/ASA guidelines for aSAH and spontaneous ICH and compared with previous guidelines. Guidelines were classified based on the Class of recommendation (COR) and Level of evidence (LOE). COR signifies recommendation strength (COR 1: Strong; COR 2a: Moderate; COR 2b: Weak; COR 3: No Benefit/Harm), while LOE denotes evidence quality (LOE A: High-Quality; LOE B-NR: Moderate-Quality, Not Randomized; LOE B-R: Moderate-Quality, Randomized; LOE C-EO: Expert Opinion; LOE C-LD: Limited Data)., Results: For aSAH, we identified 84 recommendations across 15 guideline categories. Of these, 31% were classified as COR I, 30% as COR 2a, 17% as COR 2b, and 18% as COR 3. In terms of LOE, 7% were based on LOE A, 10% on LOE B-R, 65% on LOE B-NR, 14% on LOE C-LD, and 5% on LOE C-EO. Compared to previous guidelines, there was a 46% decrease in LOE A, a 45% increase in LOE B, and an 11% decrease in LOE C. For spontaneous ICH, 124 guidelines were identified across 31 guideline categories. Of these, 28% were COR I, 32% COR 2b, and 9% COR 3. For LOE, 4% were based on LOE A, 35% on LOE B-NR, and 42% on LOE C-LD. Compared to previous guidelines, there was a 78% decrease in LOE A, an 82% increase in LOE B, and a 14% increase in LOE C. This analysis highlights that less than a third of AHA/ASA guidelines are classified as the highest class of recommendation, with less than 10% based on the highest LOE., Conclusion: Less than a third of AHA/ASA guidelines on aSAH and spontaneous ICH are classified as the highest class of recommendation with less than 10% based on highest LOE. There appears to be a decrease in proportion of guidelines based on highest LOE in most recent guidelines., Competing Interests: Declaration of competing interest The authors declare no conflict of interest., (Copyright © 2024. Published by Elsevier Inc.)

Patient Reported Outcomes (PROs) are widely used in quality of life (QOL) studies, health outcomes research, and clinical trials. The importance of PRO has been advocated by health authorities. We propose this R shiny web application, PROpwr, that estimates power for two-arm clinical trials with PRO measures as endpoints using Item Response Theory (GRM: Graded Response Model) and simulations. PROpwr also supports the analysis of PRO data for convenience of estimating the effect size. There are seven function tabs in PROpwr: Frequentist Analysis, Bayesian Analysis, GRM power, T-test Power Given Sample Size, T-test Sample Size Given Power, Download, and References. PROpwr is user-friendly with point-and-click functions. PROpwr can assist researchers to analyze and calculate power and sample size for PRO endpoints in clinical trials without prior programming knowledge.

Background: Excessive gestational weight gain (GWG) is related to increased offspring fat accrual, and increased fat mass (FM) is related to obesity development. Prenatal DHA supplementation has been linked to lower levels of offspring FM; however, conflicting data exist., Objectives: This study aimed to determine if there is a protective effect of prenatal DHA supplementation on offspring fat accrual and adipose tissue deposition at 24 mo in offspring born to females who gain excessive weight compared with nonexcessive weight during pregnancy. We also explored if the effect of DHA dose on FM differed by offspring sex., Methods: Infants born to females who participated in the Assessment of DHA on Reducing Early Preterm Birth randomized controlled trial (ADORE) were recruited. In ADORE, females were randomly assigned to either a high or low prenatal DHA supplement. Offspring body composition and adipose tissue distribution were measured using dual-energy x-ray absorptiometry (DXA). GWG was categorized as excessive or not excessive based on clinical guidelines., Results: For total FM, there was a significant main effect for the DHA dose ( P = 0.03); however, the dose by GWG status was nonsignificant ( P = 0.44). Therefore, a higher prenatal DHA dose was related to greater offspring FM (622.9 g greater) and unrelated to GWG status. When investigating a DHA dose by sex effect, a significant main effect for DHA dose ( P = 0.01) was detected for central FM. However, no interaction was detected ( P = 0.98), meaning that both boys and girls had greater central FM if their mother was assigned to the higher DHA dose., Conclusions: Greater prenatal DHA supplementation was associated with greater offspring FM and adipose tissue distribution at 24 mo. It will be important to understand if these effects persist into childhood.This trial was registered at clinicaltrials.gov as NCT03310983., (© 2024 The Author(s).)

Background: Interventions to prevent excessive gestational weight gain (GWG) have had a limited impact on maternal and infant outcomes. Dietary fiber is a nutrient with benefits that counters many of the metabolic and inflammatory changes that occur during pregnancy. We will determine if a high dietary fiber (HFib) intervention provides benefit to maternal and infant outcomes., Methods and Design: Pregnant women will be enrolled in an 18-week intervention and randomized in groups of 6-10 women/group into the intervention or control group. Weekly lessons will include information on high-dietary fiber foods and behavior change strategies. Women in the intervention group will be given daily snacks high in dietary fiber (10-12 g/day) to facilitate increasing dietary fiber intake. The primary aim will assess between-group differences for the change in maternal weight, dietary fiber intake, dietary quality, and body composition during pregnancy and up to two months post-partum. The secondary aim will assess between-group differences for the change in maternal weight, dietary fiber intake, and dietary quality from two months to one year post-partum and infant body composition from birth to one-year-old., Discussion: Effective and simple intervention strategies to improve maternal and offspring outcomes are lacking. Changes during the perinatal period are related to the risk of disease development in the mother and offspring. However, it is unknown which changes can be successfully targeted to have a meaningful impact. We will test the effect of an intervention designed to counter many of the metabolic and inflammatory changes that occur during pregnancy., Ethics and Dissemination: The University of Kansas Medical Center Institutional Review Board (IRB) approved the study protocol (STUDY00145397). The results of the trial will be disseminated at conferences and in peer reviewed publications., Trial Registration: ClinicalTrials.gov ID: NCT04868110., 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 The Authors. Published by Elsevier Inc. All rights reserved.)

Introduction: The Symbol Digit Modalities Test (SDMT) is a highly sensitive neuropsychological tool used for the assessment of information processing speed (IPS) in various neurological disorders., State of the Art: In this review, we have focused on the current knowledge regarding the use of SDMT selectively in the evaluation of progressive multiple sclerosis (PMS) patients. A literature review was performed regarding the application of SDMT in PMS, with a focus on the primary progressive and secondary progressive subtypes. Relationships of diverse disease-associated factors with SDMT have been described, including disease course, imaging findings, molecular biomarkers, treatment and others., Clinical Implications: SDMT is a very useful and easily applicable instrument in the diagnostic armamentarium of neurologists and neuropsychologists. It is especially valuable in the evaluation of PMS patients, in whom the prevalence of IPS deficits is higher than in relapsing-remitting multiple sclerosis subjects or in healthy individuals., Future Directions: An emphasis should be laid on larger study groups and differentiating between individual PMS subtypes and their separate analysis in the context of cognitive assessment.

Background: Lung cancer is the leading cause of cancer related deaths. In Kansas, where coal-fired power plants account for 34% of power, we investigated whether hosting counties had higher age-adjusted lung cancer incidence rates. We also examined demographics, poverty levels, percentage of smokers, and environmental conditions using spatial analysis., Methods: Data from the Kansas Health Matters, and the Behavioral Risk Factor Surveillance System (2010-2014) for 105 counties in Kansas were analyzed. Multiple Linear Regression (MLR) assessed associations between potential risk factors and age-adjusted lung cancer incidence rates while Geographically Weighted Regression (GWR) examined regional risk factors., Results: Moran's I test confirmed spatial autocorrelation in age-adjusted lung cancer incidence rates (p<0.0003). MLR identified percentage of smokers, population size, and proportion of elderly population as significant predictors of age-adjusted lung cancer incidence rates (p<0.05). GWR showed positive associations between percentage of smokers and age-adjusted lung cancer incidence rates in over 50% of counties., Conclusion: Contrary to our hypothesis, proximity to a coal-fired power plant was not a significant predictor of age-adjusted lung cancer incidence rates. Instead, percentage of smokers emerged as a consistent global and regional risk factor. Regional lung cancer outcomes in Kansas are influenced by wind patterns and elderly population., Competing Interests: Competing interests: The authors report there are no competing interests to declare.

Background and Objectives : The aim of this study was to assess the relationship between habitual physical activity, body composition, serum myokine concentration, and all-cause mortality in chronic hemodialysis patients. Materials and Methods : A prospective cohort study with a 7-year follow-up was conducted in a group of 38 patients (24 men, 14 women, mean age 65.6 ± 13.9 years, dialysis vintage 1.17 ± 1.25 years). Baseline serum concentrations of myokines-follistatin and myostatin-were assessed along with a measurement of physical activity with multidimensional accelerometery, body composition, and the force of forearm muscle contraction. Survival analysis was performed using the Kaplan-Meier method for tertiles of follistatin, serum myostatin, body composition, and physical activity expressed in metabolic equivalents (MET). Results : The mean physical activity among patients was 81 min/24 h (median 38.5 min), and the mean weekly 3MET activity was 493 min (median 218 min). The probability of survival of patients was significantly lower in the subgroup with 3MET/24 h less than 26 min/24 h and 3METt less than 148 min per week compared to the other subgroup ( p = 0.006 and p = 0.006, respectively). During the 70-month follow-up, the subgroup with the lowest baseline follistatin concentration showed a significantly lower risk of death ( p = 0.02). Baseline myostatin levels were not significant risk factors for mortality, nor were BMI or lean and fat tissue index categories. Conclusions : Physical activity and low plasma follistatin, but not body composition indexes or plasma myostatin, could serve as predictors of all-cause mortality in hemodialysis patients.

Background: Two randomized trials found women with low blood docosahexaenoic acid (DHA; an omega 3 fatty acid) had fewer early preterm births (<34 weeks gestation) if they were assigned to high dose DHA supplementation, however, there is currently no capacity for clinicians who care for pregnancies to obtain a blood assessment of DHA. Determining a way to identify women with low DHA intake whose risk could be lowered by high dose DHA supplementation is desired., Objective: To determine if assessing DHA intake can identify pregnancies that benefit from high dose DHA supplementation., Study Design: This secondary analysis used birth data from 1310 pregnant women who completed a 7-question food frequency questionnaire (DHA-FFQ) at 16.8 ± 2.5 weeks gestation that is validated to assess DHA status. They were then randomly assigned to a standard (200 mg/day) or high dose (800 or 1000 mg/day) DHA supplement for the remainder of pregnancy. Bayesian logistic regressions were fitted for early preterm birth and preterm birth as a function of DHA intake and assigned DHA dose., Results: Participants who consumed less than 150 mg/day DHA prior to 20 weeks' gestation (n = 810/1310, 58.1%) had a lower Bayesian posterior probability (pp) of early preterm birth if they were assigned to high dose DHA supplementation (1.4% vs 3.9%, pp = 0.99). The effect on preterm birth (<37 weeks) was also significant (11.3% vs 14.8%, pp = 0.97)., Conclusion: The DHA-FFQ can identify pregnancies that will benefit most from high dose DHA supplementation and reduce the risk of preterm birth. The DHA-FFQ is low burden to providers and patients and could be easily implemented in obstetrical practice., Competing Interests: Declaration of competing interest SEC has received honorariums for presentations about DHA in infancy and pregnancy. KMG was the PI of R01HD086001. SEC, BJG and CJV were PIs of R01HD083292, CJV was an employee of RB Nutrition, which produces infant formulas and supplements with DHA at the time the study was conducted, however, RB was not involved in the study execution or analysis. She conducted this study through her role as an Adjunct Professor at The University of Cincinnati. The other authors have no competing interests., (Copyright © 2022 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: Intention-to-treat analyses do not address adherence. Per protocol analyses treat nonadherence as a protocol deviation and assess if the intervention is effective if followed., Objective: To determine the rate of early preterm birth (EPTB, <34 weeks gestation) and preterm birth (PTB, <37 weeks gestation) in participants who adhered to a randomly assigned docosahexaenoic acid (DHA) dose of 1000 mg/day., Study Design: Eleven hundred women with a singleton pregnancy were enrolled before 20-weeks' gestation, provided a capsule with 200 mg/day DHA and randomly assigned to two additional capsules containing a placebo or 800 mg of DHA. In the Bayesian Adaptive Design, new randomization schedules were determined at prespecified intervals. In each randomization, the group with the most EPTB was assigned fewer participants than the other group. Adherence was defined a priori as a postpartum red blood cell phospholipid DHA (RBC-PL-DHA) ≥5.5%.and post hoc as ≥8.0% RBC-PL-DHA, the latter after examination of postpartum RBC-PL-DHA. Bayesian mixture models were fitted for gestational age and dichotomized for EPTB and PTB as a function of baseline RBC-PL-DHA and dose-adherence. Bayesian hierarchical models were also fitted for EPTB by dose adherence and quartiles of baseline RBC-PL-DHA., Results: Adherence to the high dose using both RBC-PL-DHA cut points resulted in less EPTB compared to 200 mg [Bayesian posterior probability (pp) = 0.93 and 0.92, respectively]. For participants in the two lowest quartiles of baseline DHA status, adherence to the higher dose resulted in lower EPTB (≥5.5% RBC-PL-DHA, quartiles 1 and 2, pp = 0.95 and 0.96; ≥8% RBC-PL-DHA, quartiles 1 and 2, pp = 0.94 and 0.95). Using the Bayesian model, EPTB was reduced by 65%, from 3.45% to 1.2%, using both cut points. Adherence also reduced PTB before 35, 36 and 37 weeks using both cut points (pp ≥ 0.95). In general, performance of the nonadherent subgroup mirrored that of participants assigned to 200 mg., Conclusion: Adherence to high dose DHA reduced EPTB and PTB. The largest effect of adherence on reducing EPTB was observed in women with low baseline DHA levels., Clinicaltrials: gov (NCT02626299)., Competing Interests: Conflict of interest SEC has received honorariums for presentations about DHA in infancy and pregnancy. SEC, BJG and CJV were PIs of R01HD083292, CJV was an employee of RB Nutrition, which produces infant formulas and supplements with DHA at the time the study was conducted, however, RB was not involved in the study execution or analysis. She conducted this study through her role as an Adjunct Professor at The University of Cincinnati. The other authors have no competing interests., (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Studies that investigate the performance of prognostic and predictive biomarkers are commonplace in medicine. Evaluating the performance of biomarkers is challenging in traumatic brain injury (TBI) and other conditions when both the time factor (i.e. time from injury to biomarker measurement) and different levels or doses of treatments are in play. Such factors need to be accounted for when assessing the biomarker's performance in relation to a clinical outcome. The Hyperbaric Oxygen in Brain Injury Treatment (HOBIT) trial, a phase II randomized control clinical trial seeks to determine the dose of hyperbaric oxygen therapy (HBOT) for treating severe TBI that has the highest likelihood of demonstrating efficacy in a phase III trial. Hyperbaric Oxygen in Brain Injury Treatment will study up to 200 participants with severe TBI. This paper discusses the statistical approaches to assess the prognostic and predictive performance of the biomarkers studied in this trial, where prognosis refers to the association between a biomarker and the clinical outcome while the predictiveness refers to the ability of the biomarker to identify patient subgroups that benefit from therapy. Analyses based on initial biomarker levels accounting for different levels of HBOT and other baseline clinical characteristics, and analyses of longitudinal changes in biomarker levels are discussed from a statistical point of view. Methods for combining biomarkers that are of complementary nature are also considered and the relevant algorithms are illustrated in detail along with an extensive simulation study that assesses the performance of the statistical methods. Even though the discussed approaches are motivated by the HOBIT trial, their applications are broader. They can be applied in studies assessing the predictiveness and prognostic ability of biomarkers in relation to a well-defined therapeutic intervention and clinical outcome., Competing Interests: Declaration of conflicting interests The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Background: The study startup process for interventional clinical trials is a complex process that involves the efforts of many different teams. Each team is responsible for their startup checklist in which they verify that the necessary tasks are done before a study can move on to the next team. This regulatory process provides quality assurance and is vital for ensuring patient safety [10]. However, without having this startup process centralized and optimized, study approval can take longer than necessary as time is lost when it passes through many different hands., Objective: This manuscript highlights the process and the systems that were developed at The University of Kansas Comprehensive Cancer Center regarding the study startup process. To facilitate this process the regulatory management, site development, cancer center administration, and the Biostatistics & Informatics Shared Resources (BISR) teams came together to build a platform aimed at streamlining the startup process and providing a transparent view of where a study is in the startup process., Process: Ensuring the guidelines are clearly articulated for the review criteria of each of the three review boards, i.e., Disease Working Group (DWG), Executive Resourcing Committee (ERC), and Protocol Review and Monitoring Committee (PRMC) along with a system that can track every step and its history throughout the review process., Results: Well-defined processes and tracking methodologies have allowed the operations teams to track each study closely and ensure the 90-day and 120-day deadlines are met, this allows the operational team to dynamically prioritize their work daily. It also provides Principal investigators a transparent view of where their study stands within the study startup process and allows them to prepare for the next steps accordingly., Conclusion/future Work: The current process and technology deployment has been a significant improvement to expedite the review process and minimize study startup delays. There are still a few opportunities to fine-tune the study startup process; an example of which includes automatically informing the operational managers or the study teams to act upon deadlines regarding study review rather than the current manual communication process which involves them looking it up in the system which can add delays., Competing Interests: 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., (© 2022 The Authors.)

Introduction/aims: Peripheral neuropathies commonly affect quality of life of patients due to pain, sleep disturbances, and fatigue, although trials have not adequately explored these domains of care. The aim of this study was to assess the impact of nortriptyline, duloxetine, pregabalin, and mexiletine on pain, sleep, and fatigue in patients diagnosed with cryptogenic sensory polyneuropathy (CSPN)., Methods: We implemented a Bayesian adaptive design to perform a 12-wk multisite, randomized, prospective, open-label comparative effectiveness study in 402 CSPN patients. Participants received either nortriptyline (n = 134), duloxetine (n = 126), pregabalin (n = 73), or mexiletine (n = 69). At prespecified analysis timepoints, secondary outcomes, Patient Reported Outcomes Measurement Information System (PROMIS) surveys including Short Form (SF)-12, pain interference, fatigue, and sleep disturbance, were collected., Results: Mexiletine had the highest quit rate (58%) due to gastrointestinal side effects, while nortriptyline (38%) and duloxetine (38%) had the lowest quit rates. If tolerated for the full 12 wk of the study, mexiletine had the highest probability (>90%) of positive outcomes for improvements in pain interference and fatigue. There was no significant difference among the medications for sleep disturbance or SF-12 scores. Adverse events and lack of efficacy were the two most common reasons for cessation of therapy., Discussion: Physicians caring for patients with CSPN should consider mexiletine to address pain and fatigue, although nortriptyline and duloxetine are better medications to trial first since they are better tolerated. Future research should compare other commonly used medications for CSPN to determine evidence-based treatment strategies., (© 2022 Wiley Periodicals LLC.)

Smoking during pregnancy and postpartum remains an important public health problem. No known prior study has prospectively examined mutual changes in risk factors and women's smoking trajectory across pregnancy and postpartum. The objective of this study was to report methods used to implement a prospective cohort (Msgs4Moms), present participant baseline characteristics, and compare our sample characteristics to pregnant women from national birth record data. The cohort study was designed to investigate smoking patterns, variables related to tobacco use and abstinence, and tobacco treatment quality across pregnancy through 1-year postpartum. Current smokers or recent quitters were recruited from obstetrics clinics. Analyses included Chi-square and independent sample t-tests using Cohen's d . A total of 62 participants (41 smokers and 21 quitters) were enrolled. Participants were Black (45.2%), White (35.5%), and multiracial (19.3%); 46.8% had post-secondary education; and most were Medicaid-insured (64.5%). Compared with quitters, fewer smokers were employed (65.9 vs 90.5%, Cohen's d = 0.88) and more reported financial strain (61.1% vs 28.6%; Cohen's d = 0.75). Women who continue to smoke during pregnancy cope with multiple social determinants of health. Longitudinal data from this cohort provide intensive data to identify treatment gaps, critical time points, and potential psychosocial variables warranting intervention.

Background: Pediatric population presents several barriers for clinical trial design and analysis, including ethical constraints on the sample size and slow accrual rate. Bayesian adaptive design methods could be considered to address these challenges in pediatric clinical trials., Methods: We developed an innovative Bayesian adaptive design method and demonstrated the approach as a re-design of a published phase III pediatric trial. The innovative design used early success criteria based on skeptical prior and early futility criteria based on enthusiastic prior extrapolated from a historical adult trial, and the early and late stopping boundaries were calibrated to ensure a one-sided type I error of 2.5%. We also constructed several alternative designs which incorporated only one type of prior belief and the same stopping boundaries. To identify a preferred design, we compared operating characteristics including power, expected trial size and trial duration for all the candidate adaptive designs via simulation when performing an increasing number of equally spaced interim analyses., Results: When performing an increasing number of equally spaced interim analyses, the innovative Bayesian adaptive trial design incorporating both skeptical and enthusiastic priors at both interim and final analyses outperforms alternative designs which only consider one type of prior belief, because it allows more reduction in sample size and trial duration while still offering good trial design properties including controlled type I error rate and sufficient power., Conclusions: Designing a Bayesian adaptive pediatric trial with both skeptical and enthusiastic priors can be an efficient and robust approach for early trial stopping, thus potentially saving time and money for trial conduction., (© 2022. The Author(s).)

Background: The National Clinical Trials Network program conducts phase 2 or phase 3 treatment trials across all National Cancer Institute's designated cancer centers. Participant accrual across these clinical trials is a critical factor in deciding their success. Cancer centers that cater to rural populations, such as The University of Kansas Cancer Center, have an additional responsibility to ensure rural residents have access and are well represented across these studies., Objective: There are scant data available regarding the factors that act as barriers to the accrual of rural residents in these clinical trials. This study aims to use electronic screening logs that were used to gather patient data at several participating sites in The Kansas University of Cancer Center's Catchment area., Methods: Screening log data were used to assess what clinical trial participation barriers are faced by these patients. Additionally, the differences in clinical trial participation barriers were compared between rural and urban participating sites., Results: Analysis revealed that the hospital location rural urban category, defined as whether the hospital was in an urban or rural setting, had a medium effect on enrolment of patients in breast cancer and lung cancer trials (Cohen d=0.7). Additionally, the hospital location category had a medium effect on the proportion of recurrent lung cancer cases at the time of screening (d=0.6)., Conclusions: In consideration of the financially hostile nature of cancer treatment as well as geographical and transportation barriers, clinical trials extended to rural communities are uniquely positioned to alleviate the burden of nonmedical costs in trial participation. However, these options can be far less feasible for patients in rural settings. Since the number of patients with cancer who are eligible for a clinical trial is already limited by the stringent eligibility criteria required of such a complex disease, improving accessibility for rural patients should be a greater focus in health policy., (©Dinesh Pal Mudaranthakam, Byron Gajewski, Hope Krebill, James Coulter, Michelle Springer, Elizabeth Calhoun, Dorothy Hughes, Matthew Mayo, Gary Doolittle. Originally published in JMIR Cancer (https://cancer.jmir.org), 21.04.2022.)

Objective: In this secondary analysis of the Rural Engagement in Primary Care for Optimizing Weight Reduction (RE-POWER) randomized trial, the authors determined the effectiveness of weight-loss interventions in people with diabetes compared with those without diabetes living in rural areas., Methods: The RE-POWER study was a randomized trial designed to determine the effectiveness of nonpharmacological behavioral weight-loss interventions in rural participants with obesity, comparing the individual in-clinic visit model to in-person group sessions and phone group sessions over 24 months. In this secondary analysis, weight loss was compared in participants with and without diabetes. The effects of factors such as medications, insulin, and behavioral factors were compared., Results: Participants with diabetes were less likely to lose weight during the study compared with those without diabetes up to 18 months (4.12% vs. 5.31%; net difference = 1.46%; 95% CI: 0.63%-2.28%). Participants with diabetes on insulin lost less weight than patients with diabetes not on insulin at 6 months (4.52% vs. 6.88%; net difference = 2.35%; 95% CI: 0.55%-4.16%). The group with diabetes had significantly lower changes in blood pressure and lipid parameters versus the group without diabetes., Conclusions: Patients with diabetes in rural areas were less likely to lose weight, and metabolic parameters were less responsive to weight loss, compared with patients without diabetes., (© 2022 The Obesity Society (TOS). This article has been contributed to by US Government employees and their work is in the public domain in the USA.)

The secondary analyses of two large, recently completed randomized clinical trials of DHA supplementation in pregnancy found that women with a low baseline DHA status benefited from randomization to a higher dose (800 vs 0 and 1000 vs 200 mg/day DHA). To obtain DHA status, it is necessary to obtain a blood sample and conduct an analysis using gas chromatography (GC) or GC-mass spectrometry (GCMS), both barriers to clinics where pregnant women receive advice on nutrition. Participants consuming less than 150 mg/day of DHA at baseline in our recent trial had a lower risk of early preterm birth and preterm birth when assigned to 1000 vs 200 m/day DHA. DHA intake was determined using a 7-question food frequency questionnaire administered by a trained nutritionist. Because the need for trained personnel to administer the questionnaire would be a barrier to implementing this finding in clinical management of pregnancy, the goal of this study was to determine if an online version of the questionnaire could be validly completed without assistance., (Copyright © 2022. Published by Elsevier Ltd.)

Docosahexaenoic acid (DHA) intake was estimated in pregnant women between 12- and 20-weeks' gestation using the National Cancer Institute's (NCI) Diet History Questionnaire-II (DHQ-II) and a 7-question screener designed to capture DHA intake (DHA Food Frequency Questionnaire, DHA-FFQ). Results from both methods were compared to red blood cell phospholipid DHA (RBC-DHA) weight percent of total fatty acids. DHA intake from the DHA-FFQ was more highly correlated with RBC-DHA (r s =0.528) than the DHQ-II (r s =0.352). Moreover, the DHA-FFQ allowed us to obtain reliable intake data from 1355 of 1400 participants. The DHQ-II provided reliable intake for only 847 of 1400, because many participants only partially completed it and it was not validated for Hispanic participants. Maternal age, parity, and socioeconomic status (SES) were also significant predictors of RBC-DHA. When included with estimated intake from the DHA-FFQ, the model accounted for 36% of the variation in RBC-DHA., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Objective: Participant recruitment is a challenge for any clinical trial but is especially complex in cancer specifically due to the need to initiate treatment urgently. Most participants enrolled in oncology clinical trials are identified as potential participants by the oncologist or other referring provider. Optimal clinical care for patients with cancer includes consideration of participation in a clinical trial. However, the process of finding a clinical trial that is appropriate the patient can be cumbersome and time consuming., Material and Methods: The University of Kansas Cancer Center has developed a mobile application (app) which streamlines the clinical trial search process for physicians, patients, and caregivers by cohesively integrating all clinical trials currently recruiting in the center and making them easy to browse., Results: Key aspects of the app include simple filtering options, the ability to search for trials by name, easily accessible assistance, and in-app referral by phone or email. Initial feedback on the app has been very positive, with several suggestions already being implemented in future development. The app was designed to be used both by physicians to find trials, as well as patients in collaboration with their physicians., Conclusion: While long-term results will be crucial to understanding how the app can best serve our patient population, our initial results suggest that health system specific clinical trial apps can address a currently unmet need in the clinical trial recruitment process., Competing Interests: Declaration of Conflicting Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2022.)

Objectives: Patient reported outcomes (PRO) are widely used in quality of life (QOL) studies, health outcomes research, and clinical trials. The importance of PRO has been advocated by health authorities. Patient Reported Outcomes Measurement Information System (PROMIS) is a collection of standardized measures of PROs using Item Response Theory (IRT). However, in clinical trials with PROs as endpoints, observed scores are routinely used for power estimation rather than IRT scores. This paper aims to fill this gap and estimate power in a two-arm clinical trials with PROMIS measures as endpoints with IRT model., Study Design and Setting: We conducted a series of simulations to study the IRT power with validated PROMIS measures controlling factors including sample size, effect size, number of items, and missing data proportion., Results: Our results showed that sample size, effect size, and number of items are important indicators of IRT based power estimation for PROMIS measures. When effect size is small and sample size is limited, IRT model provides higher power than the closed form formula., Conclusion: IRT based simulation should be used for power estimation in two-armed clinical, especially when there is small effect size or small sample size., (Copyright © 2021. Published by Elsevier Inc.)

Background: As the cost of clinical trials continues to rise, novel approaches are required to ensure ethical allocation of resources. Multisite trials have been increasingly utilized in phase 1 trials for rare diseases and in phase 2 and 3 trials to meet accrual needs. The benefits of multisite trials include easier patient recruitment, expanded generalizability, and more robust statistical analyses. However, there are several problems more likely to arise in multisite trials, including accrual inequality, protocol nonadherence, data entry mistakes, and data integration difficulties., Objective: The Biostatistics & Data Science department at the University of Kansas Medical Center developed a clinical trial management system (comprehensive research information system [CRIS]) specifically designed to streamline multisite clinical trial management., Methods: A National Institute of Child Health and Human Development-funded phase 3 trial, the ADORE (assessment of docosahexaenoic acid [DHA] on reducing early preterm birth) trial fully utilized CRIS to provide automated accrual reports, centralize data capture, automate trial completion reports, and streamline data harmonization., Results: Using the ADORE trial as an example, we describe the utility of CRIS in database design, regulatory compliance, training standardization, study management, and automated reporting. Our goal is to continue to build a CRIS through use in subsequent multisite trials. Reports generated to suit the needs of future studies will be available as templates., Conclusions: The implementation of similar tools and systems could provide significant cost-saving and operational benefit to multisite trials., Trial Registration: ClinicalTrials.gov NCT02626299; https://tinyurl.com/j6erphcj., (©Dinesh Pal Mudaranthakam, Alexandra Brown, Elizabeth Kerling, Susan E Carlson, Christina J Valentine, Byron Gajewski. Originally published in JMIR Formative Research (https://formative.jmir.org), 22.12.2021.)

Objective: The aim of this study was to report the results of five weight-loss interventions in primary care settings in underserved patients and to compare the level of pragmatism across the interventions using the Pragmatic Explanatory Continuum Indicator Summary (PRECIS-2) tool., Methods: Data from 54 primary care clinics (2,210 patients) were pooled from the Promoting Successful Weight Loss in Primary Care in Louisiana (PROPEL) and Rural Engagement in Primary Care for Optimizing Weight Reduction (REPOWER) cluster-randomized trials. Clinics were randomized to one of five comparators: PROPEL usual care, PROPEL combination of in-clinic and telephone visits, REPOWER in-clinic individual visits, REPOWER in-clinic group visits, or REPOWER telephone group visits., Results: At 24 months, weight loss (kilograms) was -0.50 (95% CI: -1.77 to 0.76), -3.05 (-4.10 to -2.01), -4.30 (-5.35 to -3.26), -4.79 (-5.83 to -3.75), and -4.80 (-5.96 to -3.64) in the PROPEL usual care, REPOWER in-clinic individual visits, REPOWER telephone group visits, REPOWER in-clinic group visits, and PROPEL in-clinic and telephone visits arms, respectively. At 24 months, percentage of weight loss was -0.360 (-1.60 to 0.88), -3.00 (-4.02 to -1.98), -4.23 (-5.25 to -3.20), -4.67 (-5.69 to -3.65), and -4.69 (-5.82 to -3.56), respectively, in the five arms. The REPOWER in-clinic individual visits intervention was the most pragmatic and reflects the current Centers for Medicare and Medicaid Services funding model, although this intervention produced the least weight loss., Conclusions: Clinically significant weight loss over 6 months in primary care settings is achievable using a variety of lifestyle-based treatment approaches. Longer-term weight-loss maintenance is more difficult to achieve., (© 2021 The Obesity Society.)

Background: Rural residence is commonly thought to be a risk factor for poor cancer outcomes. However, a number of studies have reported seemingly conflicting information regarding cancer outcome disparities with respect to rural residence, with some suggesting that the disparity is not present and others providing inconsistent evidence that either urban or rural residence is associated with poorer outcomes. We suggest a simple explanation for these seeming contradictions: namely that rural cancer outcome disparities are related to factors that occur differentially at a local level, such as environmental exposures, lack of access to care or screening, and socioeconomic factors, which differ by type of cancer., Methods: We conducted a retrospective cohort study examining ten cancers treated at the University of Kansas Medical Center from 2011 to 2018, with individuals from either rural or urban residences. We defined urban residences as those in a county with a U.S. Department of Agriculture Urban Influence Code (UIC) of 1 or 2, with all other residences defines a rural. Inverse probability of treatment weighting was used to create a pseudo-sample balanced for covariates deemed likely to affect the outcomes modeled with cumulative link and weighted Cox-proportional hazards models., Results: We found that rural residence is not a simple risk factor but rather appears to play a complex role in cancer outcome disparities. Specifically, rural residence is associated with higher stage at diagnosis and increased survival hazards for colon cancer but decreased risk for lung cancer compared to urban residence., Conclusion: Many cancers are affected by unique social and environmental factors that may vary between rural and urban residents, such as access to care, diet, and lifestyle. Our results show that rurality can increase or decrease risk, depending on cancer site, which suggests the need to consider the factors connected to rurality that influence this complex pattern. Thus, we argue that such disparities must be studied at the local level to identify and design appropriate interventions to improve cancer outcomes., (© 2021. The Author(s).)

Patient reported outcomes are gaining more attention in patient-centered health outcomes research and quality of life studies as important indicators of clinical outcomes, especially for patients with chronic diseases. Factor analysis is ideal for measuring patient reported outcomes. If there is heterogeneity in the patient population and when sample size is small, differential item functioning and convergence issues are challenges for applying factor models. Bayesian hierarchical factor analysis can assess health disparity by assessing for differential item functioning, while avoiding convergence problems. We conducted a simulation study and used an empirical example with American Indian minorities to show that fitting a Bayesian hierarchical factor model is an optimal solution regardless of heterogeneity of population and sample size.

Breast cancer screening guidelines serve as crucial evidence-based recommendations in deciding when to begin regular screenings. However, due to developments in breast cancer research and differences in research interpretation, screening guidelines can vary between organizations and within organizations over time. This leads to significant lapses in adopting updated guidelines, variable decision making between physicians, and unnecessary screening for low to moderate risk patients (Jacobson and Kadiyala, 2017; Corbelli et al., 2014). For analysis, risk factors were assessed for patient screening behaviors and results. The outcome variable for the first analysis was whether the patient had undergone screening. The risk factors considered were age, marital status, education level, rural versus urban residence, and family history of breast cancer. The outcome variable for the second analysis was whether patients who had undergone breast cancer screening presented abnormal results. The risk factors considered were age, Body Mass Index, family history, smoking and alcohol status, hormonal contraceptive use, Hormone Replacement Therapy use, age of first pregnancy, number of pregnancies (parity), age of first menses, rural versus urban residence, and whether or not patients had at least one child. Logistic regression analysis displayed strong associations for both outcome variables. Risk of screening nonattendance was negatively associated with age as a continuous variable, age as a dichotomous variable, being married, any college education, and family history. Risk of one or more abnormal mammogram findings was positively associated with family history, and hormonal contraceptive use. This procedure will be further developed to incorporate additional risk factors and refine the analysis of currently implemented risk factors., Competing Interests: 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., (© 2021 The Author(s).)

Anticoagulants prevent thrombosis and death in patients with atrial fibrillation and venous thromboembolism (VTE) but also increase bleeding risk. The benefit/risk ratio favors anticoagulation in most of these patients. However, some will have a bleeding complication, such as the common trip-and-fall brain injury in elderly patients that results in traumatic intracranial hemorrhage. Clinicians must then make the difficult decision about when to restart the anticoagulant. Restarting too early risks making the bleeding worse. Restarting too late risks thrombotic events such as ischemic stroke and VTE, the indications for anticoagulation in the first place. There are more data on restarting patients with spontaneous intracranial hemorrhage, which is very different than traumatic intracranial hemorrhage. Spontaneous intracranial hemorrhage increases the risk of rebleeding because intrinsic vascular changes are widespread and irreversible. In contrast, traumatic cases are caused by a blow to the head, usually an isolated event portending less future risk. Clinicians generally agree that anticoagulation should be restarted but disagree about when. This uncertainty leads to long restart delays causing a large, potentially preventable burden of strokes and VTE, which has been unaddressed because of the absence of high quality evidence. Restart Traumatic Intracranial Hemorrhage (the "r" distinguished intracranial from intracerebral) (TICrH) is a prospective randomized open label blinded end-point response-adaptive clinical trial that will evaluate the impact of delays to restarting direct oral anticoagulation (1, 2, or 4 weeks) on the composite of thrombotic events and bleeding in patients presenting after traumatic intracranial hemorrhage.

The primary goal for any clinical trial after it receives a funding notification is to receive regulatory approval and initiate the trial for recruitment. Every trial must go through documentation and regulatory process before it can start recruiting participants and collecting data; this initial process of review and approval is known as the study start-up process (SSU). We evaluated the average time taken for studies to receive approvals. Using data from clinical trials conducted at the University of Kansas Medical Center, various times to reach the start of the study were calculated based on the dates of individual study. The results of this analysis showed that chart review studies and investigator-initiated trials had a shorter time to activation than other types of studies. Additionally, single-center studies had a shorter activation time than multi-center studies. The analysis also demonstrated that the overall processing time consistently had been reduced over time., Competing Interests: 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., (© 2021 The Authors. Published by Elsevier Inc.)

Importance: Rural populations have a higher prevalence of obesity and poor access to weight loss programs. Effective models for treating obesity in rural clinical practice are needed., Objective: To compare the Medicare Intensive Behavioral Therapy for Obesity fee-for-service model with 2 alternatives: in-clinic group visits based on a patient-centered medical home model and telephone-based group visits based on a disease management model., Design, Setting, and Participants: Cluster randomized trial conducted in 36 primary care practices in the rural Midwestern US. Inclusion criteria included age 20 to 75 years and body mass index of 30 to 45. Participants were enrolled from February 2016 to October 2017. Final follow-up occurred in December 2019., Interventions: All participants received a lifestyle intervention focused on diet, physical activity, and behavior change strategies. In the fee-for-service intervention (n = 473), practice-employed clinicians provided 15-minute in-clinic individual visits at a frequency similar to that reimbursed by Medicare (weekly for 1 month, biweekly for 5 months, and monthly thereafter). In the in-clinic group intervention (n = 468), practice-employed clinicians delivered group visits that were weekly for 3 months, biweekly for 3 months, and monthly thereafter. In the telephone group intervention (n = 466), patients received the same intervention as the in-clinic group intervention, but sessions were delivered remotely via conference calls by centralized staff., Main Outcomes and Measures: The primary outcome was weight change at 24 months. A minimum clinically important difference was defined as 2.75 kg., Results: Among 1407 participants (mean age, 54.7 [SD, 11.8] years; baseline body mass index, 36.7 [SD, 4.0]; 1081 [77%] women), 1220 (87%) completed the trial. Mean weight loss at 24 months was -4.4 kg (95% CI, -5.5 to -3.4 kg) in the in-clinic group intervention, -3.9 kg (95% CI, -5.0 to -2.9 kg) in the telephone group intervention, and -2.6 kg (95% CI, -3.6 to -1.5 kg) in the in-clinic individual intervention. Compared with the in-clinic individual intervention, the mean difference in weight change was -1.9 kg (97.5% CI, -3.5 to -0.2 kg; P = .01) for the in-clinic group intervention and -1.4 kg (97.5% CI, -3.0 to 0.3 kg; P = .06) for the telephone group intervention., Conclusions and Relevance: Among patients with obesity in rural primary care clinics, in-clinic group visits but not telephone-based group visits, compared with in-clinic individual visits, resulted in statistically significantly greater weight loss at 24 months. However, the differences were small in magnitude and of uncertain clinical importance., Trial Registration: ClinicalTrials.gov Identifier: NCT02456636.

Importance: Cryptogenic sensory polyneuropathy (CSPN) is a common generalized slowly progressive neuropathy, second in prevalence only to diabetic neuropathy. Most patients with CSPN have significant pain. Many medications have been tried for pain reduction in CSPN, including antiepileptics, antidepressants, and sodium channel blockers. There are no comparative studies that identify the most effective medication for pain reduction in CSPN., Objective: To determine which medication (pregabalin, duloxetine, nortriptyline, or mexiletine) is most effective for reducing neuropathic pain and best tolerated in patients with CSPN., Design, Setting, and Participants: From December 1, 2014, through October 20, 2017, a bayesian adaptive, open-label randomized clinical comparative effectiveness study of pain in 402 participants with CSPN was conducted at 40 neurology care clinics. The trial included response adaptive randomization. Participants were patients with CSPN who were 30 years or older, with a pain score of 4 or greater on a numerical rating scale (range, 0-10, with higher scores indicating a higher level of pain). Participant allocation to 1 of 4 drug groups used the utility function and treatment's sample size for response adaptation randomization. At each interim analysis, a decision was made to continue enrolling (up to 400 participants) or stop the whole trial for success (80% power). Patient engagement was maintained throughout the trial, which helped guide the study and identify ways to communicate and disseminate information. Analysis was performed from December 11, 2015, to January 19, 2018., Interventions: Participants were randomized to receive nortriptyline (n = 134), duloxetine (n = 126), pregabalin (n = 73), or mexiletine (n = 69)., Main Outcomes and Measures: The primary outcome was a utility function that was a composite of the efficacy (participant reported pain reduction of ≥50% from baseline to week 12) and quit (participants who discontinued medication) rates., Results: Among the 402 participants (213 men [53.0%]; mean [SD] age, 60.1 [13.4] years; 343 White [85.3%]), the utility function of nortriptyline was 0.81 (95% bayesian credible interval [CrI], 0.69-0.93; 34 of 134 [25.4%] efficacious; and 51 of 134 [38.1%] quit), of duloxetine was 0.80 (95% CrI, 0.68-0.92; 29 of 126 [23.0%] efficacious; and 47 of 126 [37.3%] quit), pregabalin was 0.69 (95% CrI, 0.55-0.84; 11 of 73 [15.1%] efficacious; and 31 of 73 [42.5%] quit), and mexiletine was 0.58 (95% CrI, 0.42-0.75; 14 of 69 [20.3%] efficacious; and 40 of 69 [58.0%] quit). The probability each medication yielded the highest utility was 0.52 for nortriptyline, 0.43 for duloxetine, 0.05 for pregabalin, and 0.00 for mexiletine., Conclusions and Relevance: This study found that, although there was no clearly superior medication, nortriptyline and duloxetine outperformed pregabalin and mexiletine when pain reduction and undesirable adverse effects are combined to a single end point., Trial Registration: ClinicalTrials.gov Identifier: NCT02260388.

Anticoagulant-associated traumatic intracranial hemorrhage (tICrH) is a devastating injury with high morbidity and mortality. For survivors, treating clinicians face the dilemma of restarting oral anticoagulation with scarce evidence to guide them. Thromboembolic risk is high from the bleeding event, patients' high baseline risks, that is, the pre-existing indication for anticoagulation, and the risk of immobility after the bleeding episode. This must be balanced with potentially devastating hematoma expansion or new hemorrhagic lesions. Retrospective evidence and expert opinion support restarting oral anticoagulants in most patients with tICrH, but timing is uncertain. Researchers have failed to make clear distinctions between tICrH and spontaneous intracranial hemorrhage (sICrH), which have differing natural histories. While both appear to benefit from restarting, sICrH has a higher rebleeding risk and similar or lower thrombotic risk. Clinical equipoise on restarting is also divergent. In sICrH, equipoise is centered on whether to restart. In tICrH, it is centered on when. Several prospective randomized clinical trials are ongoing or about to start to examine the risk-benefit of restarting. Most of them are restricted to patients with sICrH, with antiplatelet control groups. Most are also restricted to direct oral anticoagulants (DOACs), as they are associated with a lower overall risk of ICrH. There is some overlap with tICrH via subdural hematoma, and one trial is specific to restart timing with DOACs in only traumatic cases. This is a narrative review of the current evidence for restarting anticoagulation and restart timing after tICrH along with a summary of the ongoing and planned clinical trials., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Investigators who manage multicenter clinical trials need to pay careful attention to patterns of subject accrual, and the prediction of activation time for pending centers is potentially crucial for subject accrual prediction. We propose a Bayesian hierarchical model to predict subject accrual for multicenter clinical trials in which center activation times vary. We define center activation time as the time at which a center can begin enrolling patients in the trial. The difference in activation times between centers is assumed to follow an exponential distribution, and the model of subject accrual integrates prior information for the study with actual enrollment progress. We apply our proposed Bayesian multicenter accrual model to two multicenter clinical studies. The first is the PAIN-CONTRoLS study, a multicenter clinical trial with a goal of activating 40 centers and enrolling 400 patients within 104 weeks. The second is the HOBIT trial, a multicenter clinical trial with a goal of activating 14 centers and enrolling 200 subjects within 36 months. In summary, the Bayesian multicenter accrual model provides a prediction of subject accrual while accounting for both center- and individual patient-level variation., (© 2020 John Wiley & Sons Ltd.)

Background: Poor recruitment of patients is the predominant reason for early termination of randomized clinical trials (RCTs). Systematic empirical investigations and validation studies of existing recruitment models, however, are lacking. We aim to provide evidence-based guidance on how to predict and monitor recruitment of patients into RCTs. Our specific objectives are the following: (1) to establish a large sample of RCTs (target n = 300) with individual patient recruitment data from a large variety of RCTs, (2) to investigate participant recruitment patterns and study site recruitment patterns and their association with the overall recruitment process, (3) to investigate the validity of a freely available recruitment model, and (4) to develop a user-friendly tool to assist trial investigators in the planning and monitoring of the recruitment process., Methods: Eligible RCTs need to have completed the recruitment process, used a parallel group design, and investigated any healthcare intervention where participants had the free choice to participate. To establish the planned sample of RCTs, we will use our contacts to national and international RCT networks, clinical trial units, and individual trial investigators. From included RCTs, we will collect patient-level information (date of randomization), site-level information (date of trial site activation), and trial-level information (target sample size). We will examine recruitment patterns using recruitment trajectories and stratifications by RCT characteristics. We will investigate associations of early recruitment patterns with overall recruitment by correlation and multivariable regression. To examine the validity of a freely available Bayesian prediction model, we will compare model predictions to collected empirical data of included RCTs. Finally, we will user-test any promising tool using qualitative methods for further tool improvement., Discussion: This research will contribute to a better understanding of participant recruitment to RCTs, which could enhance efficiency and reduce the waste of resources in clinical research with a comprehensive, concerted, international effort.

Background: Monitoring and reporting of drug safety during a clinical trial is essential to its success. More recent attention to drug safety has encouraged statistical methods development for monitoring and detecting potential safety signals. This paper investigates the potential impact of the process of the blinded investigator identifying a potential safety signal, which should be further investigated by the Data and Safety Monitoring Board with an unblinded safety data analysis., Methods: In this paper, two-stage Bayesian hierarchical models are proposed for safety signal detection following a pre-specified set of interim analyses that are applied to efficacy. At stage 1, a hierarchical blinded model uses blinded safety data to detect a potential safety signal and at stage 2, a hierarchical logistic model is applied to confirm the signal with unblinded safety data., Results: Any interim safety monitoring analysis is usually scheduled via negotiation between the trial sponsor and the Data and Safety Monitoring Board. The proposed safety monitoring process starts once 53 subjects have been enrolled into an eight-arm phase II clinical trial for the first interim analysis. Operating characteristics describing the performance of this proposed workflow are investigated using simulations based on the different scenarios., Conclusions: The two-stage Bayesian safety procedure in this paper provides a statistical view to monitor safety during the clinical trials. The proposed two-stage monitoring model has an excellent accuracy of detecting and flagging a potential safety signal at stage 1, and with the most important feature that further action at stage 2 could confirm the safety issue.

Background: Interventions to prevent excessive gestational weight gain (GWG) have had limited success This pilot study examined the effectiveness of a single goal (SG) high dietary fiber intervention to prevent excessive GWG., Methods: Twelve weekly lessons focused on consuming a high fiber diet (≥30 g/day). Snacks containing 10-12 g of dietary fiber were given for the first 6 weeks only. Body composition was measured at baseline and at the end of the intervention. At one-year postpartum, body weight retention and dietary practices were assessed. A p-value is reported for the primary analysis only. For all other comparisons, Cohen's d is reported to indicate effect size., Results: The SG group increased fiber intake during the study (32 g/day at 6 weeks, 27 g/day at 12 weeks), whereas the UC group did not (~ 17 g/day). No differences were found for the proportion of women classified as excessive gainers (p = 0.13). During the intervention, the SG group gained less body weight (- 4.1 kg) and less fat mass (- 2.8 kg) (d = 1.3). At 1 year postpartum, the SG group retained less weight (0.35 vs. 4.4 kg, respectively, d = 1.8), and reported trying to currently eat high fiber foods., Conclusion: The SG intervention resulted in less weight gain, fat accrual, and weight retention at 1 year postpartum. A residual intervention effect was detected postpartum with the participants reporting continued efforts to consume a high fiber diet., Trial Registration: NCT03984630; Trial registered June 13, 2019 (retrospectively registered).

To fully support their role in translational and personalized medicine, biorepositories and biobanks must continue to advance the annotation of their biospecimens with robust clinical and laboratory data. Translational research and personalized medicine require well-documented and up-to-date information, but the infrastructure used to support biorepositories and biobanks can easily be out of sync with the host institution. To assist researchers and provide them with accurate pathological, epidemiological, and bio-molecular data, the Biospecimen Repository Core Facility (BRCF) at the University of Kansas Medical Center (KUMC) merges data from medical records, the tumor registry, and pathology reports using the Curated Cancer Clinical Outcomes Database (C3OD). In this report, we describe the utilization of C3OD to optimally retrieve and dispense biospecimen samples using these 3 data sources and demonstrate how C3OD greatly increases the efficiency of obtaining biospecimen samples for the researchers., Competing Interests: Declaration of conflicting interests:The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2019.)

Objective: To determine the prevalence and predictors of receiving a smoking cessation medication prescription at discharge., Methods: Retrospective analysis of ongoing Human Studies Committee-approved clinical trial data at large tertiary care center, The University of Kansas Medical Center. Patients included were smokers over 18, either Spanish or English speaking, those admitted between October 1, 2016 through May 31, 2018. Other eligibility criteria include access to a telephone or mobile phone, not currently be pregnant or breastfeeding, have no significant co-morbidity that precludes participation (acute, life-threatening illness, and communication barriers such as tracheal tube or altered mental status). Those included in this analysis were those randomized into the trial who expressed interest in receiving a smoking cessation medication prescription at discharge., Results: Two hundred fourteen patients were recommended a prescription by their smoking cessation counselor, 88 patients (41.12%) were approved a prescription at discharge. Out of those approved, 50.70 (14.05 SD) was the average age, 12.84 (8.47 SD) was the average number of cigarettes used per day, 47 patients (53.41%) were White, 49 patients (55.68%) were admitted through the emergency department, 55 patients (62.50%) had used smoking cessation medication in the past, 49 patients (55.68%) had used inpatient smoking cessation, 36 patients (40.91%) had Medicaid. A binary logistic regression determined to show insurance status (P = 0.042) and use of inpatient smoking cessation medication use (P < 0.001) as statistically significant predictors of receiving a prescription at discharge., Conclusion: It was determined that among the population recommended for medication, 41.12% actually received a prescription at discharge. The variables of "health insurance status" and "use of inpatient smoking cessation medication" demonstrated to be predictors of receiving a prescription. It is important to further study this as many patients rely on a prescription to afford these medications that are useful in a quit attempt., (Copyright © 2019 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.)

Electronic health records (EHR) represent a rich resource for conducting observational studies, supporting clinical trials, and more. However, much of the data contains unstructured text, presenting an obstacle to automated extraction. Natural language processing (NLP) can structure and learn from text, but NLP algorithms were not designed for the unique characteristics of EHR. Here, we propose Relevant Word Order Vectorization (RWOV) to aid with structuring. RWOV is based on finding the positional relationship between the most relevant words to predicting the class of a text. This facilitates machine learning algorithms to use the interaction of not just keywords but positional dependencies (e.g. a relevant word occurs 5 relevant words before some term of interest). As a proof-of-concept, we attempted to classify the hormone receptor status of breast cancer patients treated at the University of Kansas Medical Center, comparing RWOV to other methods using the F1 score and AUC. RWOV performed as well as, or better than other methods in all but one case. For F1 score, RWOV had a clear edge on most tasks. AUC tended to be closer, but for HER2, RWOV was significantly better for most comparisons. These results suggest RWOV should be further developed for EHR-related NLP.

When a researcher desires to test several treatment arms against a control arm, a two-stage adaptive design can be more efficient than a single-stage design where patients are equally allocated to all treatment arms and the control. We see this type of approach in clinical trials as a seamless Phase II - Phase III design. These designs require more statistical support and are less straightforward to plan and analyze than a standard single-stage design. To diminish the barriers associated with a Bayesian two-stage drop-the-losers design, we built a user-friendly point-and-click graphical user interface with R Shiny to aid researchers in planning such designs by allowing them to easily obtain trial operating characteristics, estimate statistical power and sample size, and optimize patient allocation in each stage to maximize power. We assume that endpoints are distributed normally with unknown but common variance between treatments. We recommend this software as an easy way to engage statisticians and researchers in two-stage designs as well as to actively investigate the power of two-stage designs relative to more traditional approaches. The software is freely available at https://github.com/stefangraw/Allocation-Power-Optimizer.

Parental nutrition literacy (PNL) correlates positively with child diet quality, but interventions for improving PNL are lacking. "Nutricity" is a novel bilingual (English/Spanish) mobile tool designed by the research team to engage parents and young children to interact with nutrition information to make nutrition decisions. The purpose of this study was to inform a future intervention through (1) assessing parental likability of Nutricity, and (2) collecting perceptions of pediatric clinic personnel on the feasibility of introducing Nutricity in pediatric clinics. PNL scores and feedback about Nutricity were collected using mixed methods from 15 English-speaking and 15 Spanish-speaking parents of 1-5 year-old children. Three parents from each language group provided additional feedback via semi-structured interviews. Interviews with 11 pediatric clinic personnel were also conducted to anticipate barriers and formulate strategies for implementing Nutricity as a clinic-based intervention. Nutricity was liked by both language groups and across all PNL levels, with a mean rating of 4.6 on a 5-point scale. Clinic personnel interviews affirmed need for and feasibility of offering Nutricity in clinics.

Nutrition is important for preventing and treating chronic diseases highly prevalent among Latinos, yet no tool exists for measuring nutrition literacy among Spanish speakers. This study aimed to adapt the validated Nutrition Literacy Assessment Instrument for Spanish-speaking Latinos. This study was developed in two phases: adaptation and validity testing. Adaptation included translation, expert item content review, and interviews with Spanish speakers. For validity testing, 51 participants completed the Short Assessment of Health Literacy-Spanish (SAHL-S), the Nutrition Literacy Assessment Instrument in Spanish (NLit-S), and socio-demographic questionnaire. Validity and reliability statistics were analyzed. Content validity was confirmed with a Scale Content Validity Index of 0.96. Validity testing demonstrated NLit-S scores were strongly correlated with SAHL-S scores (r = 0.52, p < 0.001). Entire reliability was substantial at 0.994 (CI 0.992-0.996) and internal consistency was excellent (Cronbach's α = 0.92). The NLit-S demonstrates validity and reliability for measuring nutrition literacy among Spanish-speakers.

Data used to determine patient eligibility for cancer clinical trials often come from disparate sources that are typically maintained by different groups within an institution, use differing technologies, and are stored in different formats. Collecting data and resolving inconsistencies across sources increase the time it takes to screen eligible patients, potentially delaying study completion. To address these challenges, the Biostatistics and Informatics Shared Resource at The University of Kansas Cancer Center developed the Curated Cancer Clinical Outcomes Database (C3OD). C3OD merges data from the electronic medical record, tumor registry, bio-specimen and data registry, and allows querying through a single unified platform. By centralizing access and maintaining appropriate controls, C3OD allows researchers to more rapidly obtain detailed information about each patient in order to accelerate eligibility screening. This case report describes the design of this informatics platform as well as initial assessments of its reliability and usability.