Evaluating the impact of delayed study startup on accrual in cancer studies

Background : Drug development in cancer medicine depends on high-quality clinical trials, but these require large investments of time to design, operationalize, and complete; for oncology drugs, this can take 8-10 years. Long timelines are expensive and delay innovative therapies from reaching patients. Delays often arise from study startup, a process that can take 6 months or more. We assessed how study-specific factors affected the study startup duration and the resulting overall success of the study. Method: Data from The University of Kansas Cancer Center (KUCC) were used to analyze studies initiated from 2018 to 2022. Accrual percentage was computed based on the number of enrolled participants and the desired enrollment goal. Accrual success was determined by comparing the percentage of enrollments to predetermined threshold values (50%, 70%, or 90%). Results : Studies that achieve or surpass the 70% activation threshold typically exhibit a median activation time of 140.5 days. In contrast, studies that fall short of the accrual goal tend to have a median activation time of 187 days, demonstrating the shorter median activation times associated with successful studies. Wilcoxon rank-sum test conducted for the study phase (W=13607, p-value=0.001) indicates that late-phase projects took longer to activate compared to early-stage projects. We also conducted the study with 50% and 90% accrual thresholds; our findings remained consistent. Conclusions: Longer activation times are linked to reduced project success, and early-phase studies tend to have higher success than late-phase studies. Therefore, by reducing impediments to the approval process, we can facilitate quicker approvals, increasing the success of studies regardless of phase.

A high fiber diet intervention during pregnancy: The SPROUT (Single goal in PRegnancy to optimize OUTcomes) protocol paper

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.

Statistical assessment of the prognostic and the predictive value of biomarkers-A biomarker assessment framework with applications to traumatic brain injury biomarker studies

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.

Bolstering the complex study start-up process at NCI cancer centers using technology

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.

A secondary analysis of PAIN-CONTRoLS: Pain's impact on sleep, fatigue, and activities of daily living

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.

Quitting Smoking before and after Pregnancy: Study Methods and Baseline Data from a Prospective Cohort Study

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.

Bayesian adaptive design for pediatric clinical trials incorporating a community of prior beliefs

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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-022-01569-x.

The effect of nonpharmaceutical weight-loss interventions in rural patients with diabetes: RE-POWER Diabetes

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.

Accelerating Cancer Patient Recruitment Through a Mobile Application (Clinical Trial Finder)

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.

The Successful Synchronized Orchestration of an Investigator-Initiated Multicenter Trial Using a Clinical Trial Management System and Team Approach: Design and Utility Study

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.

Weight loss in primary care: A pooled analysis of two pragmatic cluster-randomized trials

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.

The need to study rural cancer outcome disparities at the local level: a retrospective cohort study in Kansas and Missouri

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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-12190-w.

Estimating power for clinical trials with Patient Reported Outcomes - using Item Response Theory

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.

A framework for personalized mammogram screening

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.

Barriers to clinical trial participation: a comparative study between rural and urban participants (Preprint)

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.

Bayesian Hierarchical Factor Analysis for Efficient Estimation across Race/Ethnicity

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.

Patient Assisted Intervention for Neuropathy: Comparison of Treatment in Real Life Situations (PAIN-CONTRoLS): Bayesian Adaptive Comparative Effectiveness Randomized Trial

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.

Restart TICrH: An Adaptive Randomized Trial of Time Intervals to Restart Direct Oral Anticoagulants after Traumatic Intracranial Hemorrhage

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.

Non-cancer clinical trials start-up metrics at an academic medical center: Implications for advancing research

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.

•

The 2018 year’s trend shows reduced time to study start.

•

SSU process for non-cancer trial on an average requires four to six months.

•

The activation time of the SSU process varied for different study types and scopes.

Effect of Behavioral Therapy With In-Clinic or Telephone Group Visits vs In-Clinic Individual Visits on Weight Loss Among Patients With Obesity in Rural Clinical Practice: A Randomized Clinical Trial

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.

Restarting and timing of oral anticoagulation after traumatic intracranial hemorrhage: a review and summary of ongoing and planned prospective randomized clinical trials

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.

Two-stage Bayesian hierarchical modeling for blinded and unblinded safety monitoring in randomized clinical trials

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.

Feasibility of Delivering a Mobile Nutrition Literacy Intervention via Pediatric Primary Care

Objectives

The objective of this pilot study was to test the feasibility of implementing a mobile health intervention, “Nutricity,” within pediatric well-care and explore outcomes on child diet quality, child BMI and parental nutrition literacy.

Methods

Participants in this single-arm intervention pilot study were 18 parent-child dyads recruited from pediatric primary care before a scheduled well-care visit. Parents were English-speaking, identified as primary food decision-maker, had internet access at home, and owned a web-enabled device; children were 1–5 years old with unrestricted diets. Dyads were given three months’ access to Nutricity mobile tools during the child's well-care visit and were guided on use. Nutricity tools included a mobile formatted website to access instructional videos, games for kids, and quizzes for parents, and weekly text messages for nutrition goal setting. Content was focused on applying nutrition information at supermarkets, home, and restaurants. Feasibility was evaluated by % completion, parent likability survey, website usage, and % text responses logged. At baseline and three months, parent nutrition literacy (Nutrition Literacy Assessment Instrument, NLit); diet quality (2,24-hour diet recalls used to calculate a Healthy Eating Index, HEI – 2015 score), and BMI were collected with differences analyzed by paired t-tests.

Results

Of 18 dyads enrolled, 17 (94%) completed the study. Parents rated likability of the website and text messages as ‘good-excellent,’ reporting they applied ‘half-most’ of goals set through text-messaging. A common emergent theme was need for more individualized text messages. Mean response rate to text messages was 62%, and dyads logged an average of 43.7 minutes and 5.2 sessions on the website. Non-significant improvements were seen in parent NLit and overall child HEI scores, and no difference was seen in child BMI. However, HEI component scores improved for dairy by 1.2 points (P = .055) and seafood/plant proteins by 1.3 points (P = 0.046).

Conclusions

Delivering Nutricity via a pediatric well-care visit is feasible and demonstrated potential for improving child diet quality. A larger, adequately powered study is warranted.

Funding Sources

This work was funded by a CTSA grant from NCATS and the School of Health Professions.

The effect of high dietary fiber intake on gestational weight gain, fat accrual, and postpartum weight retention: a randomized clinical trial

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).

Bayesian accrual modeling and prediction in multicenter clinical trials with varying center activation times

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.

Utilization of Technology to Improve Efficiency in Investigational Drug Management Processes

Background: Background: An investigational pharmacy is responsible for all tasks related to receiving, storing, and dispensing of any investigational drugs. Traditional methods of inventory and protocol tracking on paper binders are very tedious and could be error-prone. Objective: To evaluate the utilization of the IDS to efficiently manage the inventory within an investigational Pharmacy. We hypothesize that the IDS will reduce the drug processing time. Methods: Our pharmacy tracked the drug processing time before and after using the IDS including the receiving, dispensing, and inventory. As part of the receiving the study drug pharmacists tracked the time it took a pharmacist to complete the tasks of logging the study drug before and after the implementation of the IDS system. In addition, the pharmacy also timed the process for drug dispensing and a full investigational drug inventory check. Wilcoxon signed-rank test was used to compare the difference in the meantime of total processing before and after the IDS. Results: Utilization of the IDS system showed significant reduction in processing time, and improvement of efficiency in inventory management. Additionally, the usability survey of the IDS demonstrated that the IDS system helped pharmacists capture data consistently across every clinical trial. Conclusion: Our results demonstrates how technology helps pharmacists to focus on their actual day to day medication-related tasks rather than worrying about other operational aspects. Informatics team continues to further enhance the features such as monitor portal, and features related to finance - generation of invoices, billing reconciliation, etc.

Optimizing Retrieval of Biospecimens Using the Curated Cancer Clinical Outcomes Database (C3OD)

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.

Which hospitalized smokers receive a prescription for quit-smoking medication at discharge? A secondary analysis of a smoking cessation randomized clinical trial

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.

Relevant Word Order Vectorization for Improved Natural Language Processing in Electronic Health Records

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.

Preliminary Investigation of a Mobile Nutrition Literacy Website for Parents and Young Children

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.

Optimizing Sample Size Allocation and Power in a Bayesian Two-Stage Drop-The-Losers Design

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.

Measuring Nutrition Literacy in Spanish-Speaking Latinos: An Exploratory Validation Study

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.

A Curated Cancer Clinical Outcomes Database (C3OD) for accelerating patient recruitment in cancer clinical trials

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.

The Nutrition Literacy Assessment Instrument is a Valid and Reliable Measure of Nutrition Literacy in Adults with Chronic Disease

OBJECTIVE

To test the reliability and validity of the Nutrition Literacy Assessment Instrument (NLit) in adult primary care and identify the relationship between nutrition literacy and diet quality.

DESIGN

This instrument validation study included a cross-sectional sample participating in up to 2 visits 1 month apart.

SETTING/PARTICIPANTS

A total of 429 adults with nutrition-related chronic disease were recruited from clinics and a patient registry affiliated with a Midwestern university medical center.

MAIN OUTCOME MEASURES

Nutrition literacy was measured by the NLit, which was composed of 6 subscales: nutrition and health, energy sources in food, food label and numeracy, household food measurement, food groups, and consumer skills. Diet quality was measured by Healthy Eating Index-2010 with nutrient data from Diet History Questionnaire II surveys.

ANALYSIS

The researchers measured factor validity and reliability by using binary confirmatory factor analysis; test-retest reliability was measured by Pearson r and the intraclass correlation coefficient, and relationships between nutrition literacy and diet quality were analyzed by linear regression.

RESULTS

The NLit demonstrated substantial factor validity and reliability (0.97; confidence interval, 0.96-0.98) and test-retest reliability (0.88; confidence interval, 0.85-0.90). Nutrition literacy was the most significant predictor of diet quality (β = .17; multivariate coefficient = 0.10; P < .001).

CONCLUSIONS

The NLit is a valid and reliable tool for measuring nutrition literacy in adult primary care patients.

Subgroup identification of early preterm birth (ePTB): informing a future prospective enrichment clinical trial design

BACKGROUND

Despite the widely recognized association between the severity of early preterm birth (ePTB) and its related severe diseases, little is known about the potential risk factors of ePTB and the sub-population with high risk of ePTB. Moreover, motivated by a future confirmatory clinical trial to identify whether supplementing pregnant women with docosahexaenoic acid (DHA) has a different effect on the risk subgroup population or not in terms of ePTB prevalence, this study aims to identify potential risk subgroups and risk factors for ePTB, defined as babies born less than 34 weeks of gestation.

METHODS

The analysis data (N = 3,994,872) were obtained from CDC and NCHS' 2014 Natality public data file. The sample was split into independent training and validation cohorts for model generation and model assessment, respectively. Logistic regression and CART models were used to examine potential ePTB risk predictors and their interactions, including mothers' age, nativity, race, Hispanic origin, marital status, education, pre-pregnancy smoking status, pre-pregnancy BMI, pre-pregnancy diabetes status, pre-pregnancy hypertension status, previous preterm birth status, infertility treatment usage status, fertility enhancing drug usage status, and delivery payment source.

RESULTS

Both logistic regression models with either 14 or 10 ePTB risk factors produced the same C-index (0.646) based on the training cohort. The C-index of the logistic regression model based on 10 predictors was 0.645 for the validation cohort. Both C-indexes indicated a good discrimination and acceptable model fit. The CART model identified preterm birth history and race as the most important risk factors, and revealed that the subgroup with a preterm birth history and a race designation as Black had the highest risk for ePTB. The c-index and misclassification rate were 0.579 and 0.034 for the training cohort, and 0.578 and 0.034 for the validation cohort, respectively.

CONCLUSIONS

This study revealed 14 maternal characteristic variables that reliably identified risk for ePTB through either logistic regression model and/or a CART model. Moreover, both models efficiently identify risk subgroups for further enrichment clinical trial design.

Confirmatory Factor Analysis Alternative: Free, Accessible CBID Software

New software that performs Classical and Bayesian Instrument Development (CBID) is reported that seamlessly integrates expert (content validity) and participant data (construct validity) to produce entire reliability estimates with smaller sample requirements. The free CBID software can be accessed through a website and used by clinical investigators in new instrument development. Demonstrations are presented of the three approaches using the CBID software: (a) traditional confirmatory factor analysis (CFA), (b) Bayesian CFA using flat uninformative prior, and (c) Bayesian CFA using content expert data (informative prior). Outcomes of usability testing demonstrate the need to make the user-friendly, free CBID software available to interdisciplinary researchers. CBID has the potential to be a new and expeditious method for instrument development, adding to our current measurement toolbox. This allows for the development of new instruments for measuring determinants of health in smaller diverse populations or populations of rare diseases.

Technology Dependence in Home Care: Impact on Patients and Their Family Caregivers

BACKGROUND

The purpose of this review is to explore how home technology care affects patients, family caregivers, and quality of life (QOL).

METHODS

A literature search was conducted to identify studies of home parenteral nutrition (HPN) and other technology prescribed home care.

RESULTS

Technology dependence influences health-related QOL. Patients and their family caregivers must balance the positive aspects of being in the home environment with the challenges of administering complex therapies at home. Patients and caregivers need additional support to reduce the physical, emotional, social, and financial burdens they experience.

CONCLUSIONS

More research is needed to address effective interventions to reduce patient and caregiver burdens and to improve outcomes for technology-dependent individuals. A greater level of preparedness for managing home technology and technology-related problems may improve quality of life.

Measuring Nutrition Literacy in Breast Cancer Patients: Development of a Novel Instrument

No nutrition literacy instruments have been tested in breast cancer survivors, yet nutrition is a critical lifestyle factor for optimizing weight and improving quality of life in breast cancer survival. Our objectives were to adapt our Nutrition Literacy Assessment Instrument for breast cancer populations and to pilot test its validity and reliability. We modified the instrument based on review by content experts in cancer and nutrition and cognitive interviews with 18 cancer survivors. The modified instrument (Nutrition Literacy Assessment Instrument for Breast Cancer, NLit-BCa) was pilot-tested with 17 high-risk women and 55 breast cancer survivors. We conducted the NLit-BCa on two separate occasions 4 weeks apart and assessed reliability by confirmatory factor analysis. Construct validity was evaluated by comparing results of the NLit-BCa to a Healthy Eating Index score derived from two separate 24-h dietary recalls. Content validity of the NLit-BCa was acceptable (0.93). Entire reliability for three instrument domains was substantial (>0.80), while remaining domains demonstrated fair or moderate reliability. Significant relationships were found between five of the six domains of nutrition literacy and diet quality (P < 0.05). The NLit-BCa is content valid and demonstrates promising reliability and construct validity related to diet quality, through a larger sample size, and removal of non-discriminating items is needed to confirm these findings. Thus, the NLit-BCa demonstrates potential for comprehensively measuring nutrition literacy in breast cancer populations.

The Role of Spirituality in Holistic Weight Management

This descriptive, feasibility study was designed to determine how weight management patients defined spirituality and its connection with weight management. Relationships among spirituality assessment, spiritual well-being, selfesteem, and quality of life were explored. This study arose from clinical observations of possible relationships among patients' weight management failures, negative beliefs about self, and spiritual distress. Participants were 34 of 104 adult potential participants from a holistic weight management clinical practice. Survey data were analyzed using qualitative content analysis and quantitative linear regression analyses. Participants readily defined spirituality; significant linear relationships were found: Total spiritual well-being explained approximately 47% of the variance for self-esteem and existential spiritual well-being accounted for approximately 68% of the variance for self-esteem. Similarly, existential spiritual well-being explained approximately 35% of the variance of quality of life. For this convenience sample, spiritual well-being was significantly related to self-esteem and quality of life.

An Exploration of Nursing Home Organizational Processes

The purpose of this study is to explore the relationship between nursing home staffs' perceptions of organizational processes (communication, teamwork, and leadership) with characteristics (turnover, tenure, and educational preparation) of the nursing home administrator (NHA) and director of nursing (DON). NHAs and DONs rate communication, teamwork, and leadership significantly higher than direct care staff do (registered nurses, licensed practical nurses, certified nurse aides [CNAs]). CNAs have the lowest ratings of communication and teamwork. Turnover of the NHA and DON is significantly and negatively associated with communication and teamwork. Two thirds of DONs surveyed hold less than a baccalaureate degree; this does not influence staffs' ratings of communication, teamwork, and leadership. Findings from this study highlight the need to explore differences in perceptions between administrative and direct care staff and how these may or may not influence staff development and quality improvement activities in nursing homes.

Assessing the Nutrition Literacy of Parents and Its Relationship With Child Diet Quality

OBJECTIVE

To estimate the reliability and validity of the Nutrition Literacy Assessment Instrument for Parents (NLit-P) and to investigate relationships among parental nutrition literacy, parental and child body mass index, and child diet quality (Healthy Eating Index).

METHODS

Cross-sectional study of 101 parent-child dyads that collected measures of socioeconomic status, nutrition literacy, 2 24-hour child diet recalls, and body mass index. Reliability of NLit-P was assessed by confirmatory factor analysis. Pearson correlation and multiple linear regression were used.

RESULTS

Fair to substantial reliability was seen across 5 NLit-P domains, whereas Pearson correlations support concurrent validity for the NLit-P related to child diet quality and parental income, age, and educational attainment (P < .001). For every 1% increase in NLit-P, there was a 0.51 increase in child Healthy Eating Index (multivariate coefficient, 0.174; P < .001).

CONCLUSIONS AND IMPLICATIONS

The NLit-P demonstrates potential for measuring parental nutrition literacy, which may be an important educational target for improving child diet quality.

Response to Sijtsma and van der Ark (2015): "Conceptions of reliability revisited and practical recommendations"

Sijtsma and van der Ark present a broad set of models and methods for reliability estimation, and their discussion of similarities and differences provides clear information for nurse researchers to move forward in their instrument development projects. In particular, we applaud the authors' clear exposition of the factor analytic model and its utility for providing a framework for unifying reliability and validity. However, we do not want to be constrained only to the point estimates. We also need to ascertain the uncertainty in the point estimate-usually in the form of a 95% confidence interval-or, as the Bayesians refer to, a credible interval. Another issue not discussed by Sijtsma and van der Ark is conditional standard errors of measurement along the score scale measuring latent traits or true scores. In our response, practical tools for estimating intervals and a brief discussion of conditional standard errors of measurement are presented.

Treatment response to the RENEW weight loss intervention in schizophrenia: impact of intervention setting

BACKGROUND

Individuals with serious mental illness have high rates of obesity and a need for specialized weight loss intervention programs. This study examines the efficacy of the RENEW weight loss intervention and examines the impact of the intervention setting on outcomes.

METHOD

136 individuals with serious mental illness from 4 different settings were randomly assigned to receive the RENEW weight loss intervention or a control condition of treatment as usual. The RENEW intervention is a one year program that includes an intensive, maintenance and intermittent supports phase.

RESULTS

The intervention group experienced a modest weight loss of 4.8 lbs at 3 months, 4.1 lbs at 6 months and a slight weight gain of 1.5 lbs at 12 months. The control group gained a total of 6.2 lbs at 12 months. However when settings were examined separately the responder sites had a weight loss of 9.4 lbs at 3 months, 10.9 lbs at 6 months and 7 lbs at 12 months.

DISCUSSION

These results suggest that the settings in which individuals receive services may act as a support or hindrance toward response to weight loss interventions. The concept of the obesogenic environment deserves further examination as a factor in the success of weight loss programs.