Treatment Effect Estimates From Pilot Trials Are Unreliable.

CONTEXT: The CONSORT guideline defines a pilot trial as a small-scale version of a desired future efficacy trial that is intended to answer the key questions of whether and how a larger study should be done. For example, a pilot trial might evaluate different approaches to data collection or outcome measurement. However, pilot trials are unreliable for assessing treatment efficacy due to the statistical phenomenon called sampling variability. OBJECTIVES: In this tutorial we use computer simulation to demonstrate the influence of sampling variability on efficacy estimates from pilot trials, illustrating why pilot trial designs should not be used to evaluate whether a treatment is promising or not. METHODS: We simulate a 2-arm parallel group trial (N=20 per group) with a survival outcome as an example. Simulations are done under two scenarios: 1) the treatment is efficacious at the level of a hypothetical minimum clinically important difference (hazard ratio [HR] = 0.75); and 2) the treatment is not efficacious (HR=1). RESULTS: As expected, in both simulated scenarios the range of observed results is distributed around the true treatment effect, HR=0.75 or HR=1. Importantly, ∼20% of trials simulated under scenario 1 incorrectly suggest the treatment may be harmful (HR > 1). Under scenario 2, half of the simulated studies incorrectly suggest the treatment is beneficial. CONCLUSION: Treatment effect estimates from pilot trials should not be used to make future development decisions regarding a novel therapy because of the high risk of misleading conclusions.

Advancing workforce diversity by leveraging the Clinical and Translational Science Awards (CTSA) program.

Clinical trials continue to disproportionately underrepresent people of color. Increasing representation of diverse backgrounds among clinical research personnel has the potential to yield greater representation in clinical trials and more efficacious medical interventions by addressing medical mistrust. In 2019, North Carolina Central University (NCCU), a Historically Black College and University with a more than 80% underrepresented student population, established the Clinical Research Sciences Program with support from the Clinical and Translational Science Awards (CTSA) program at neighboring Duke University. This program was designed to increase exposure of students from diverse educational, racial, and ethnic backgrounds to the field of clinical research, with a special focus on health equity education. In the first year, the program graduated 11 students from the two-semester certificate program, eight of whom now hold positions as clinical research professionals. This article describes how leveraging the CTSA program helped NCCU build a framework for producing a highly trained, competent, and diverse workforce in clinical research responsive to the call for increased diversity in clinical trial participation.

Secondary Prevention Risk Interventions via Telemedicine and Tailored Patient Education (SPRITE): A randomized trial to improve post myocardial infarction management.

OBJECTIVE: We evaluated the impact of a low intensity web-based and intensive nurse-administered intervention to reduce systolic blood pressure (SBP) among patients with prior MI. METHODS: Secondary Prevention Risk Interventions via Telemedicine and Tailored Patient Education (SPRITE) was a three-arm trial. Patients were randomized to 1) post-MI education-only; 2) nurse-administered telephone program; or 3) web-based interactive tool. The study was conducted 2009-2013. RESULTS: Participants (n = 415) had a mean age of 61 years (standard deviation [SD], 11). Relative to the education-only group, the 12-month differential improvement in SBP was - 3.97 and - 3.27 mmHg for nurse-administered telephone and web-based groups, respectively. Neither were statistically significant. Post hoc exploratory subgroup analyses found participants who received a higher dose (>12 encounters) in the nurse-administered telephone intervention (n = 60; 46%) had an 8.8 mmHg (95% CI, 0.69, 16.89; p = 0.03) differential SBP improvement versus low dose (<11 encounters; n = 71; 54%). For the web-based intervention, those who had higher dose (n = 73; 53%; >1 web encounter) experienced a 2.3 mmHg (95% CI, -10.74, 6.14; p = 0.59) differential SBP improvement versus low dose (n = 65; 47%). CONCLUSIONS: The main effects were not statistically significant. PRACTICAL IMPLICATIONS: Completing the full dose of the intervention may be essential to experience the intervention effect. CLINICAL TRIAL REGISTRATION: The unique identifier is NCT00901277 (http://www. CLINICALTRIALS: gov/ct2/show/NCT00901277?term=NCT00901277&rank=1).

Experiential Learning Methods for Biostatistics Students: A Model for Embedding Student Interns in Academic Health Centers.

This manuscript describes an experiential learning program for future collaborative biostatisticians (CBs) developed within an academic medical center. The program is a collaborative effort between the Biostatistics, Epidemiology, and Research Design (BERD) Methods Core and the Master of Biostatistics (MB) program, both housed in the Department of Biostatistics and Bioinformatics at Duke University School of Medicine and supported in partnership with the Duke Clinical and Translational Science Institute. To date, the BERD Core Training and Internship Program (BCTIP) has formally trained over 80 students to work on collaborative teams that are integrated throughout the Duke School of Medicine. This manuscript focuses on the setting for the training program, the experiential learning model on which it is based, the structure of the program, and lessons learned to date.

Methods for training collaborative biostatisticians.

The emphasis on team science in clinical and translational research increases the importance of collaborative biostatisticians (CBs) in healthcare. Adequate training and development of CBs ensure appropriate conduct of robust and meaningful research and, therefore, should be considered as a high-priority focus for biostatistics groups. Comprehensive training enhances clinical and translational research by facilitating more productive and efficient collaborations. While many graduate programs in Biostatistics and Epidemiology include training in research collaboration, it is often limited in scope and duration. Therefore, additional training is often required once a CB is hired into a full-time position. This article presents a comprehensive CB training strategy that can be adapted to any collaborative biostatistics group. This strategy follows a roadmap of the biostatistics collaboration process, which is also presented. A TIE approach (Teach the necessary skills, monitor the Implementation of these skills, and Evaluate the proficiency of these skills) was developed to support the adoption of key principles. The training strategy also incorporates a "train the trainer" approach to enable CBs who have successfully completed training to train new staff or faculty.

Epidemiologic Trends in Clostridioides difficile Infections in a Regional Community Hospital Network.

Importance: Clostridioides difficile infection (CDI) remains a leading cause of health care facility-associated infection. A greater understanding of the regional epidemiologic profile of CDI could inform targeted prevention strategies. Objectives: To assess trends in incidence of health care facility-associated and community-acquired CDI among hospitalized patients over time and to conduct a subanalysis of trends in the NAP1 strain of CDI over time. Design, Setting, and Participants: This long-term multicenter cohort study reviewed records of patients (N = 2 025 678) admitted to a network of 43 regional community hospitals primarily in the southeastern United States from January 1, 2013, through December 31, 2017. Generalized linear mixed-effects models were used to adjust for potential clustering within facilities and changing test method (nucleic acid amplification testing or toxin enzyme immunoassay) over time. Main Outcomes and Measures: Clostridioides difficile infection incidence rates were counted as cases per 1000 admissions for community-acquired and total CDI cases or cases per 10 000 patient-days for health care facility-associated CDI. Long-term trends in the proportion of cases acquired in the community and in NAP1 strain incidence were also evaluated. Results: A total of 2 025 678 admissions and 21 254 CDI cases were included (12 678 [59.6%] female; median [interquartile range] age, 69 [55-80] years). Median (interquartile range) total CDI incidence increased slightly from 7.9 (3.5-12.4) cases per 1000 admissions in 2013 to 9.3 (4.9-13.7) cases per 1000 admissions in 2017. After adjustment, the overall incidence of health care facility-associated CDI declined (incidence rate ratio [IRR], 0.995; 95% CI, 0.990-0.999; P = .03), whereas insufficient evidence was found for either an increase or a decrease in community-acquired CDI (IRR, 1.004; 95% CI, 0.999-1.009; P = .14). The proportion of cases classified as community acquired increased over time from a mean (SD) of 0.49 (0.28) in 2013 to 0.61 (0.26) in 2017 (odds ratio, 1.010 per month; 95% CI, 1.006-1.015; P < .001). Rates of the NAP1 strain of CDI varied widely between facilities, with no statistically significant change in NAP1 strain incidence over time in the community setting (IRR, 1.007; 95% CI, 0.994-1.021) or health care facility setting (IRR, 1.011; 95% CI, 0.990-1.032). Conclusions and Relevance: The findings suggest that, despite the modest improvement in health care facility-associated CDI rates, a better understanding of community-acquired CDI incidence is needed for future infection prevention efforts.

A New Stress Test for Knee Joint Cartilage.

Cartilage metabolism-both the synthesis and breakdown of cartilage constituents and architecture-is influenced by its mechanical loading. Therefore, physical activity is often recommended to maintain cartilage health and to treat or slow the progression of osteoarthritis, a debilitating joint disease causing cartilage degeneration. However, the appropriate exercise frequency, intensity, and duration cannot be prescribed because direct in vivo evaluation of cartilage following exercise has not yet been performed. To address this gap in knowledge, we developed a cartilage stress test to measure the in vivo strain response of healthy human subjects' tibial cartilage to walking exercise. We varied both walk duration and speed in a dose-dependent manner to quantify how these variables affect cartilage strain. We found a nonlinear relationship between walk duration and in vivo compressive strain, with compressive strain initially increasing with increasing duration, then leveling off with longer durations. This work provides innovative measurements of cartilage creep behavior (which has been well-documented in vitro but not in vivo) during walking. This study showed that compressive strain increased with increasing walking speed for the speeds tested in this study (0.9-2.0 m/s). Furthermore, our data provide novel measurements of the in vivo strain response of tibial cartilage to various doses of walking as a mechanical stimulus, with maximal strains of 5.0% observed after 60 minutes of walking. These data describe physiological benchmarks for healthy articular cartilage behavior during walking and provide a much-needed baseline for studies investigating the effect of exercise on cartilage health.

Indications for and outcomes of therapeutic plasma exchange after cardiac transplantation: A single center retrospective study.

INTRODUCTION: Limited data are available describing indications for and outcomes of therapeutic plasma exchange (TPE) in cardiac transplantation. METHODS: In a retrospective study of patients who underwent cardiac transplantation at Duke University Medical Center from 2010 to 2014, we reviewed 3 TPE treatment patterns: a Single TPE procedure within 24 h of transplant; Multiple TPE procedures initiated within 24 h of transplant; and 1 or more TPE procedures beginning >24 h post-transplant. Primary and secondary outcomes were overall survival (OS) and TPE survival (TS), respectively. RESULTS: Of 313 patients meeting study criteria, 109 (35%) underwent TPE. TPE was initiated in 82 patients within 24 h, 40 (37%) receiving a single procedure (Single TPE), and 42 (38%) multiple procedures (Multiple TPE). Twenty-seven (25%) began TPE >24 h after transplant (Delayed TPE). The most common TPE indication was elevated/positive panel reactive or human leukocyte antigen antibodies (32%). With a median follow-up of 49 months, the non-TPE treated and Single TPE cohorts had similar OS (HR 1.08 [CI, 0.54, 2.14], P = .84), while the Multiple and Delayed TPE cohorts had worse OS (HR 2.62 [CI, 1.53, 4.49] and HR 1.98 [CI, 1.02, 3.83], respectively). The Multiple and Delayed TPE cohorts also had worse TS (HR 2.59 [CI, 1.31, 5.14] and HR 3.18 [CI, 1.56, 6.50], respectively). Infection rates did not differ between groups but was independently associated with OS (HR 2.31 [CI, 1.50, 3.54]). CONCLUSIONS: TPE is an important therapeutic modality in cardiac transplant patients. Prospective studies are needed to better define TPE's different roles in this patient population.

Outcome by Gender in the Veterans Health Administration Motivating Overweight/Obese Veterans Everywhere Weight Management Program.

BACKGROUND: Few evaluations of the Veterans Health Administration Motivating Overweight/Obese Veterans Everywhere (MOVE!) weight management program have assessed 6-month weight change or factors associated with weight change by gender. MATERIALS AND METHODS: Analysis of administrative data from a national sample of veterans in the VA MOVE! RESULTS: A total of 62,882 participants were included, 14.6% were women. Compared with men, women were younger (49.6 years [standard deviation, SD, 10.8] vs. 59.3 years [SD, 9.8], p < 0.0001), less likely to be married (34.1% vs. 56.0%, p < 0.0001), and had higher rates of post-traumatic stress disorder (26.0% vs. 22.4%, p < 0.0001) and depression (49.3% vs. 32.9%, p < 0.001). The mean number of MOVE! visits attended by women was lower than men (5.6 [SD, 5.3] vs. 6.0 [SD, 5.9], p < 0.0001). Women, compared with men, reported lower rates of being able to rely on family or friends (35.7% vs. 40.8%, p < 0.0001). Observed mean percent change in weight for women was -1.5% (SD, 5.2) and for men was -1.9% (SD, 4.8, p < 0.0001). The odds of ≥5% weight loss were no different for women (body-mass index [BMI] >25 kg/m2) compared with men (BMI >25 kg/m2; odds ratio, 1.05 [95% confidence interval, 0.99-1.11; p = 0.13]). CONCLUSIONS: Women veterans lost less weight overall compared with men. There was no difference in the odds of achieving clinically significant weight loss by gender. The majority of women and men enrolled lost <5% weight despite being enrolled in a lifestyle intervention. Future studies should focus on identifying program- and participant-level barriers to weight loss.

Statistical competencies for medical research learners: What is fundamental?

INTRODUCTION: It is increasingly essential for medical researchers to be literate in statistics, but the requisite degree of literacy is not the same for every statistical competency in translational research. Statistical competency can range from 'fundamental' (necessary for all) to 'specialized' (necessary for only some). In this study, we determine the degree to which each competency is fundamental or specialized. METHODS: We surveyed members of 4 professional organizations, targeting doctorally trained biostatisticians and epidemiologists who taught statistics to medical research learners in the past 5 years. Respondents rated 24 educational competencies on a 5-point Likert scale anchored by 'fundamental' and 'specialized.' RESULTS: There were 112 responses. Nineteen of 24 competencies were fundamental. The competencies considered most fundamental were assessing sources of bias and variation (95%), recognizing one's own limits with regard to statistics (93%), identifying the strengths, and limitations of study designs (93%). The least endorsed items were meta-analysis (34%) and stopping rules (18%). CONCLUSION: We have identified the statistical competencies needed by all medical researchers. These competencies should be considered when designing statistical curricula for medical researchers and should inform which topics are taught in graduate programs and evidence-based medicine courses where learners need to read and understand the medical research literature.

The Symptom Experience in Rectal Cancer Survivors.

CONTEXT: As the number of rectal cancer survivors grows, it is important to understand the symptom experience after treatment. Although data show that rectal cancer survivors experience a variety of symptoms after diagnosis, little has been done to study the way these symptoms are grouped and associated. OBJECTIVES: To determine symptom prevalence and intensity in rectal cancer survivors and if clusters of survivors exist, who share similar symptom-defined survivor subgroups that may vary based on antecedent variables. METHODS: A secondary analysis of the Cancer Care and Outcomes Research and Surveillance database was undertaken. Cluster analysis was performed on 15-month postdiagnosis data to form post-treatment survivor subgroups, and these were examined for differences in demographic and clinical characteristics. Data were analyzed using cluster analysis, chi-square, and analysis of variance. RESULTS: A total of 275 rectal cancer survivors were included who had undergone chemotherapy, radiation therapy, and surgery. Most frequently reported symptoms included feeling "worn out" (87%), feeling "tired" (85%), and "trouble sleeping" (66%). Four symptom-defined survivor subgroups (minimally symptomatic n = 40, tired and trouble sleeping n = 138, moderate symptoms n = 42, and highly symptomatic n = 55) were identified with symptom differences existing among each subgroup. Age and being married/partnered were the only two antecedents found to differ across subgroups. CONCLUSION: This study documents differences in the symptom experience after treatment. The identification of survivor subgroups allows researchers to further investigate tailored, supportive care strategies to minimize ongoing symptoms in those with the greatest symptom burden.

Mobile health devices: will patients actually use them?

Although mobile health (mHealth) devices offer a unique opportunity to capture patient health data remotely, it is unclear whether patients will consistently use multiple devices simultaneously and/or if chronic disease affects adherence. Three healthy and three chronically ill participants were recruited to provide data on 11 health indicators via four devices and a diet app. The healthy participants averaged overall weekly use of 76%, compared to 16% for those with chronic illnesses. Device adherence declined across all participants during the study. Patients with chronic illnesses, with arguably the most to benefit from advanced (or increased) monitoring, may be less likely to adopt and use these devices compared to healthy individuals. Results suggest device fatigue may be a significant problem. Use of mobile technologies may have the potential to transform care delivery across populations and within individuals over time. However, devices may need to be tailored to meet the specific patient needs.

Cell phone intervention for you (CITY): A randomized, controlled trial of behavioral weight loss intervention for young adults using mobile technology.

OBJECTIVE: To determine the effect on weight of two mobile technology-based (mHealth) behavioral weight loss interventions in young adults. METHODS: Randomized, controlled comparative effectiveness trial in 18- to 35-year-olds with BMI ≥ 25 kg/m(2) (overweight/obese), with participants randomized to 24 months of mHealth intervention delivered by interactive smartphone application on a cell phone (CP); personal coaching enhanced by smartphone self-monitoring (PC); or Control. RESULTS: The 365 randomized participants had mean baseline BMI of 35 kg/m(2) . Final weight was measured in 86% of participants. CP was not superior to Control at any measurement point. PC participants lost significantly more weight than Controls at 6 months (net effect -1.92 kg [CI -3.17, -0.67], P = 0.003), but not at 12 and 24 months. CONCLUSIONS: Despite high intervention engagement and study retention, the inclusion of behavioral principles and tools in both interventions, and weight loss in all treatment groups, CP did not lead to weight loss, and PC did not lead to sustained weight loss relative to Control. Although mHealth solutions offer broad dissemination and scalability, the CITY results sound a cautionary note concerning intervention delivery by mobile applications. Effective intervention may require the efficiency of mobile technology, the social support and human interaction of personal coaching, and an adaptive approach to intervention design.

Physician Non-adherence to Colonoscopy Interval Guidelines in the Veterans Affairs Healthcare System.

BACKGROUND & AIMS: Colonoscopy can decrease colorectal cancer (CRC) mortality, although performing this procedure more frequently than recommended could increase costs and risks to patients. We aimed to determine rates and correlates of physician non-adherence to guidelines for repeat colonoscopy screening and polyp surveillance intervals. METHODS: We performed a multi-center, retrospective, observational study using administrative claims, physician databases, and electronic medical records (EMR) from 1455 patients (50-64 y old) who underwent colonoscopy in the Veterans Affairs healthcare system in fiscal year 2008. Patients had no prior diagnosis of CRC or inflammatory bowel disease, and had not undergone colonoscopy examinations in the previous 10 years. We compared EMR-documented, endoscopist-recommended intervals for colonoscopies with intervals recommended by the 2008 Multi-Society Task Force guidelines. RESULTS: The overall rate of non-adherence to guideline recommendations was 36% and ranged from 3% to 80% among facilities. Non-adherence was 28% for patients who underwent normal colonoscopies, but 45%-52% after colonoscopies that identified hyperplastic or adenomatous polyps. Most of all recommendations that were not followed recommended a shorter surveillance interval. In adjusted analyses, non-adherence was significantly higher for patients whose colonoscopies identified hyperplastic (odds ratio [OR] = 3.1; 95% CI, 1.7-5.5) or high-risk adenomatous polyps (OR = 3.0; 95% CI, 1.2-8.0), compared to patients with normal colonoscopy examinations, but not for patients with low-risk adenomatous polyps (OR = 1.8; 95% CI, 0.9-3.7). Nonadherence was also associated with bowel preparation quality, geographic region, Charlson comorbidity score, and colonoscopy indication. CONCLUSIONS: In a managed care setting with salaried physicians, endoscopists recommend repeat colonoscopy sooner than guidelines for more than one third of patients. Factors associated with non-adherence to guideline recommendations were colonoscopy findings, quality of bowel preparation, and geographic region. Targeting endoscopist about non-adherence to colonoscopy guidelines could reduce overuse of colonoscopy and associated healthcare costs.

Willingness of Patients to Use Computers for Health Communication and Monitoring Following Myocardial Infarction.

We describe the computer use characteristics of 406 post-myocardial infarction (MI) patients and their willingness to engage online for health communication and monitoring. Most participants were computer users (n = 259; 63.8%) and half (n = 209; 51.5%) read health information online at least monthly. However, most participants did not go online to track health conditions (n = 283; 69.7%), look at medical records (n = 287; 70.7%), or e-mail doctors (n = 351; 86.5%). Most participants would consider using a Web site to e-mail doctors (n = 275; 67.7%), share medical information with doctors (n = 302; 74.4%), send biological data to their doctor (n = 308; 75.9%), look at medical records (n = 321; 79.1%), track health conditions (n = 331; 81.5%), and read about health conditions (n = 332; 81.8%). Sharing health information online with family members (n = 181; 44.6%) or for support groups (n = 223; 54.9%) was not of much interest. Most post-MI participants reported they were interested in communicating with their provider and tracking their health conditions online. Because patients with a history of MI tend to be older and are disproportionately minority, researchers and clinicians must be careful to design interventions that embrace post-MI patients of diverse backgrounds that both improve their access to care and health outcomes.

Impact of Smoking Cessation on Subsequent Pain Intensity Among Chronically Ill Veterans Enrolled in a Smoking Cessation Trial.

CONTEXT: Prior cross-sectional studies have reported greater pain intensity among persistent smokers compared with nonsmokers or former smokers; yet, few prospective studies have examined how smoking abstinence affects pain intensity. OBJECTIVES: To determine the impact of smoking cessation on subsequent pain intensity in smokers with chronic illness enrolled in a smoking cessation trial. METHODS: We recruited veteran smokers with chronic illness (heart disease, cancer, chronic obstructive pulmonary disease, diabetes, or hypertension) for a randomized controlled smoking cessation trial and prospectively examined pain intensity and smoking status. Participants (n = 380) were asked to rate their pain in the past week from 0 to 10 at baseline and the five-month follow-up. The primary outcome measure was self-reported pain intensity at the five-month follow-up survey. Self-reported smoking status was categorized as an abstainer if patients reported no cigarettes in the seven days before the follow-up survey. RESULTS: In unadjusted analyses, abstainers reported significantly lower pain levels at the five-month follow-up compared with patients who continued to smoke (parameter estimate = -1.07; 95% CI = -1.77, -0.36). In multivariable modeling, abstaining from cigarettes was not associated with subsequent pain intensity at five-month follow-up (parameter estimate = -0.27; 95% CI = -0.79, 0.25). CONCLUSION: Participants who were classified as abstainers did not report significantly different levels of pain intensity than patients who continued to smoke. Future studies should expand on our findings and monitor pain intensity in smoking cessation trials. TRIAL REGISTRATION: ClinicalTrials.govNCT00448344.

Patient-provider communication, self-reported medication adherence, and race in a postmyocardial infarction population.

OBJECTIVES: Our objectives were to: 1) describe patient-reported communication with their provider and explore differences in perceptions of racially diverse adherent versus nonadherent patients; and 2) examine whether the association between unanswered questions and patient-reported medication nonadherence varied as a function of patients' race. METHODS: We conducted a cross-sectional analysis of baseline in-person survey data from a trial designed to improve postmyocardial infarction management of cardiovascular disease risk factors. RESULTS: Overall, 298 patients (74%) reported never leaving their doctor's office with unanswered questions. Among those who were adherent and nonadherent with their medications, 183 (79%) and 115 (67%) patients, respectively, never left their doctor's office with unanswered questions. In multivariable logistic regression, although the simple effects of the interaction term were different for patients of nonminority race (odds ratio [OR]: 2.16; 95% confidence interval [CI]: 1.19-3.92) and those of minority race (OR: 1.19; 95% CI: 0.54-2.66), the overall interaction effect was not statistically significant (P=0.24). CONCLUSION: The quality of patient-provider communication is critical for cardiovascular disease medication adherence. In this study, however, having unanswered questions did not impact medication adherence differently as a function of patients' race. Nevertheless, there were racial differences in medication adherence that may need to be addressed to ensure optimal adherence and health outcomes. Effort should be made to provide training opportunities for both patients and their providers to ensure strong communication skills and to address potential differences in medication adherence in patients of diverse backgrounds.

Association between perceived life chaos and medication adherence in a postmyocardial infarction population.

BACKGROUND: The benefits of medication adherence to control cardiovascular disease (CVD) are well defined, yet multiple studies have identified poor adherence. The influence of life chaos on medication adherence is unknown. Because this is a novel application of an instrument, our preliminary objective was to understand patient factors associated with chaos. The main objective was to evaluate the extent to which an instrument designed to measure life chaos is associated with CVD-medication nonadherence. METHODS AND RESULTS: Using baseline data from an ongoing randomized trial to improve postmyocardial infarction (MI) management, multivariable logistic regression identified the association between life chaos and CVD-medication nonadherence. Patients had hypertension and a myocardial infarction in the past 3 years (n=406). Nearly 43% reported CVD-medication nonadherence in the past month. In simple linear regression, the following were associated with higher life chaos: medication nonadherence (ß=1.86; 95% confidence interval [CI], 0.96-2.76), female sex (ß=1.22; 95% CI [0.22-2.24]), minority race (ß=1.72; 95% CI [0.78-2.66]), having less than high school education (ß=2.05; 95% CI [0.71-3.39]), low health literacy (ß=2.06; 95% CI [0.86-3.26]), and inadequate financial status (ß=1.93; 95% CI [0.87-3.00]). Being married (ß=-2.09, 95% CI [-3.03 to -1.15]) was associated with lower life chaos. As chaos quartile increased, patients exhibited more nonadherence. In logistic regression, adjusting for sex, race, marital status, employment, education, health literacy, and financial status, a 1-unit life chaos increase was associated with a 7% increase (odds ratio, 1.07; 95% CI [1.02-1.12]) in odds of reporting medication nonadherence. CONCLUSIONS: Our results suggest that life chaos may be an important determinant of medication adherence. Life chaos screenings could identify those at risk for nonadherence. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT000901277.

Variability in resource use: diagnosing colorectal cancer.

OBJECTIVES: Efficient resource use is relevant in all healthcare systems. Although colorectal cancer is common, little has been published regarding the utilization of clinical resources in diagnosis. STUDY DESIGN: The primary aim was to evaluate the patterns and factors associated with clinical services used to diagnose colorectal cancer at 14 US Department of Veterans Affairs facilities. The secondary aim was to investigate whether using more clinical services was associated with time to diagnosis. METHODS: We reviewed medical records for 449 patients with colorectal cancer in an observational study. Study end points were the use of clinical diagnostic services grouped as laboratory tests, imaging studies, and subspecialty consultations. Cumulative logistic regression models were used to explore factors associated with each outcome. RESULTS: Facility variability contributed to the variability of resource use in all models. In adjusted analyses, older patients had higher use of laboratory tests (odds ratio [OR], 1.20; 95% confidence interval [CI], 1.02-1.43) and incidentally discovered colorectal cancer was associated with increased use of consultations (OR, 1.97; 95% CI, 1.27-3.05), imaging studies (OR, 1.70; 95% CI, 1.12-2.58), and laboratory tests (OR, 3.14; 95% CI, 2.06-4.77) compared with screen-detected cancers. There was a strong direct correlation between thenumber of diagnostic services performed and the median time to diagnosis (Spearman correlation coefficient, 0.99; P < .001). CONCLUSIONS: Variability in utilization of diagnostic clinical services was associated with patient age, patient presentation, and facility. Increased resource use was highly correlated with increased time to diagnosis.