Assessing readiness to use electronic health record data for outcome ascertainment in clinical trials - A case study.

BACKGROUND: Variable data quality poses a challenge to using electronic health record (EHR) data to ascertain acute clinical outcomes in multi-site clinical trials. Differing EHR platforms and data comprehensiveness across clinical trial sites, especially if patients received care outside of the clinical site's network, can also affect validity of results. Overcoming these challenges requires a structured approach. METHODS: We propose a framework and create a checklist to assess the readiness of clinical sites to contribute EHR data to a clinical trial for the purpose of outcome ascertainment, based on our experience with the Strategies to Reduce Injuries and Develop Confidence in Elders (STRIDE) study, which enrolled 5451 participants in 86 primary care practices across 10 healthcare systems (sites). RESULTS: The site readiness checklist includes assessment of the infrastructure (i.e., size and structure of the site's healthcare system or clinical network), data procurement (i.e., quality of the data), and cost of obtaining study data. The checklist emphasizes the importance of understanding how data are captured and integrated across a site's catchment area and having a protocol in place for data procurement to ensure consistent and uniform extraction across each site. CONCLUSIONS: We suggest rigorous, prospective vetting of the data quality and infrastructure of each clinical site before launching a multi-site trial dependent on EHR data. The proposed checklist serves as a guiding tool to help investigators ensure robust and unbiased data capture for their clinical trials. ORIGINAL TRIAL REGISTRATION NUMBER: NCT02475850.

Impact of complex, partially nested clustering in a three-arm individually randomized group treatment trial: A case study with the wHOPE trial.

BACKGROUND/AIMS: When participants in individually randomized group treatment trials are treated by multiple clinicians or in multiple group treatment sessions throughout the trial, this induces partially nested clusters which can affect the power of a trial. We investigate this issue in the Whole Health Options and Pain Education trial, a three-arm pragmatic, individually randomized clinical trial. We evaluate whether partial clusters due to multiple visits delivered by different clinicians in the Whole Health Team arm and dynamic participant groups due to changing group leaders and/or participants across treatment sessions during treatment delivery in the Primary Care Group Education arm may impact the power of the trial. We also present a Bayesian approach to estimate the intraclass correlation coefficients. METHODS: We present statistical models for each treatment arm of Whole Health Options and Pain Education trial in which power is estimated under different intraclass correlation coefficients and mapping matrices between participants and clinicians or treatment sessions. Power calculations are based on pairwise comparisons. In practice, sample size calculations depend on estimates of the intraclass correlation coefficients at the treatment sessions and clinician levels. To accommodate such complexities, we present a Bayesian framework for the estimation of intraclass correlation coefficients under different participant-to-session and participant-to-clinician mapping scenarios. We simulated continuous outcome data based on various clinical scenarios in Whole Health Options and Pain Education trial using a range of intraclass correlation coefficients and mapping matrices and used Gibbs samplers with conjugate priors to obtain posteriors of the intraclass correlation coefficients under those different scenarios. Posterior means and medians and their biases are calculated for the intraclass correlation coefficients to evaluate the operating characteristics of the Bayesian intraclass correlation coefficient estimators. RESULTS: Power for Whole Health Team versus Primary Care Group Education is sensitive to the intraclass correlation coefficient in the Whole Health Team arm. In these two arms, an increased number of clinicians, more evenly distributed workload of clinicians, or more homogeneous treatment group sizes leads to increased power. Our simulation study for the intraclass correlation coefficient estimation indicates that the posterior mean intraclass correlation coefficient estimator has less bias when the true intraclass correlation coefficients are large (i.e. 0.10), but when the intraclass correlation coefficient is small (i.e. 0.01), the posterior median intraclass correlation coefficient estimator is less biased. CONCLUSION: Knowledge of intraclass correlation coefficients and the structure of clustering are critical to the design of individually randomized group treatment trials with partially nested clusters. We demonstrate that the intraclass correlation coefficient of the Whole Health Team arm can affect power in the Whole Health Options and Pain Education trial. A Bayesian approach provides a flexible procedure for estimating the intraclass correlation coefficients under complex scenarios. More work is needed to educate the research community about the individually randomized group treatment design and encourage publication of intraclass correlation coefficients to help inform future trial designs.

A case study of ascertainment bias for the primary outcome in the Strategies to Reduce Injuries and Develop Confidence in Elders (STRIDE) trial.

BACKGROUND/AIM: In clinical trials, there is potential for bias from unblinded observers that may influence ascertainment of outcomes. This issue arose in the Strategies to Reduce Injuries and Develop Confidence in Elders trial, a cluster randomized trial to test a multicomponent intervention versus enhanced usual care (control) to prevent serious fall injuries, originally defined as a fall injury leading to medical attention. An unblinded nurse falls care manager administered the intervention, while the usual care arm did not involve contact with a falls care manager. Thus, there was an opportunity for falls care managers to refer participants reporting falls to seek medical attention. Since this type of observer bias could not occur in the usual care arm, there was potential for additional falls to be reported in the intervention arm, leading to dilution of the intervention effect and a reduction in study power. We describe the clinical basis for ascertainment bias, the statistical approach used to assess it, and its effect on study power. METHODS: The prespecified interim monitoring plan included a decision algorithm for assessing ascertainment bias and adapting (revising) the primary outcome definition, if necessary. The original definition categorized serious fall injuries requiring medical attention into Type 1 (fracture other than thoracic/lumbar vertebral, joint dislocation, cut requiring closure) and Type 2 (head injury, sprain or strain, bruising or swelling, other). The revised definition, proposed by the monitoring plan, excluded Type 2 injuries that did not necessarily require an overnight hospitalization since these would be most subject to bias. These injuries were categorized into those with (Type 2b) and without (Type 2c) medical attention. The remaining Type 2a injuries required medical attention and an overnight hospitalization. We used the ratio of 2b/(2b + 2c) in intervention versus control as a measure of ascertainment bias; ratios > 1 indicated the likelihood of falls care manager bias. We determined the effect of ascertainment bias on study power for the revised (Types 1 and 2a) versus original definition (Types 1, 2a, and 2b). RESULTS: The estimate of ascertainment bias was 1.14 (95% confidence interval: 0.98, 1.30), providing evidence of the likelihood of falls care manager bias. We estimated that this bias diluted the hazard ratio from the hypothesized 0.80 to 0.86 and reduced power to under 80% for the original primary outcome definition. In contrast, adapting the revised definition maintained study power at nearly 90%. CONCLUSION: There was evidence of ascertainment bias in the Strategies to Reduce Injuries and Develop Confidence in Elders trial. The decision to adapt the primary outcome definition reduced the likelihood of this bias while preserving the intervention effect and study power.

Analysis of the Impact of Antiretroviral Drug Changes on Survival of Patients with Advanced-Stage AIDS with Multidrug-Resistant HIV Infection.

OBJECTIVES: This article aims to elucidate the relationship between antiretroviral (ARV) medication changes and all-cause mortality using a total of 368 patients recruited from the United States (78%), United Kingdom (11%), and Canada (11%). METHODS: Data sources included demographic characteristics, ARV treatment history and modifications, and clinical biomarker data from the completed OPTions In Management with Antiretrovirals clinical trial. Descriptive analysis and graphical trajectory representation of ARV drug modifications and biomarker changes were undertaken. Three hypotheses aimed at assessing the impact of ARV modification parameters on clinical outcomes were tested. Kaplan-Meier survival techniques as well as Cox proportional hazard regression models were employed. RESULTS: Results from the analyses suggest that (1) switching therapy strategy from an intensified ARV regimen to a less intense one or vice versa, (2) having a moderate number (up to 2) of ARV drug changes per 6 months, and (3) changes based on clinical/HIV-related reasons or nonclinical reasons compared to ARV drug regimen changes due to clinical non-HIV reasons improved survival. CONCLUSION: Modifications in the ARV regimens of HIV-infected patients with multidrug resistance are associated with improved survival.

Best Practices for Biostatistical Consultation and Collaboration in Academic Health Centers.

Given the increasing level and scope of biostatistics expertise needed at academic health centers today, we developed best practices guidelines for biostatistics units to be more effective in providing biostatistical support to their institutions, and in fostering an environment in which unit members can thrive professionally. Our recommendations focus on the key areas of: 1) funding sources and mechanisms; 2) providing and prioritizing access to biostatistical resources; and 3) interacting with investigators. We recommend that the leadership of biostatistics units negotiate for sufficient long-term infrastructure support to ensure stability and continuity of funding for personnel, align project budgets closely with actual level of biostatistical effort, devise and consistently apply strategies for prioritizing and tracking effort on studies, and clearly stipulate with investigators prior to project initiation policies regarding funding, lead time, and authorship.

Selection of the effect size for sample size determination for a continuous response in a superiority clinical trial using a hybrid classical and Bayesian procedure.

BACKGROUND: When designing studies that have a continuous outcome as the primary endpoint, the hypothesized effect size ([Formula: see text]), that is, the hypothesized difference in means ([Formula: see text]) relative to the assumed variability of the endpoint ([Formula: see text]), plays an important role in sample size and power calculations. Point estimates for [Formula: see text] and [Formula: see text] are often calculated using historical data. However, the uncertainty in these estimates is rarely addressed. METHODS: This article presents a hybrid classical and Bayesian procedure that formally integrates prior information on the distributions of [Formula: see text] and [Formula: see text] into the study's power calculation. Conditional expected power, which averages the traditional power curve using the prior distributions of [Formula: see text] and [Formula: see text] as the averaging weight, is used, and the value of [Formula: see text] is found that equates the prespecified frequentist power ([Formula: see text]) and the conditional expected power of the trial. This hypothesized effect size is then used in traditional sample size calculations when determining sample size for the study. RESULTS: The value of [Formula: see text] found using this method may be expressed as a function of the prior means of [Formula: see text] and [Formula: see text], [Formula: see text], and their prior standard deviations, [Formula: see text]. We show that the "naïve" estimate of the effect size, that is, the ratio of prior means, should be down-weighted to account for the variability in the parameters. An example is presented for designing a placebo-controlled clinical trial testing the antidepressant effect of alprazolam as monotherapy for major depression. CONCLUSION: Through this method, we are able to formally integrate prior information on the uncertainty and variability of both the treatment effect and the common standard deviation into the design of the study while maintaining a frequentist framework for the final analysis. Solving for the effect size which the study has a high probability of correctly detecting based on the available prior information on the difference [Formula: see text] and the standard deviation [Formula: see text] provides a valuable, substantiated estimate that can form the basis for discussion about the study's feasibility during the design phase.

Pioglitazone after Ischemic Stroke or Transient Ischemic Attack.

BACKGROUND: Patients with ischemic stroke or transient ischemic attack (TIA) are at increased risk for future cardiovascular events despite current preventive therapies. The identification of insulin resistance as a risk factor for stroke and myocardial infarction raised the possibility that pioglitazone, which improves insulin sensitivity, might benefit patients with cerebrovascular disease. METHODS: In this multicenter, double-blind trial, we randomly assigned 3876 patients who had had a recent ischemic stroke or TIA to receive either pioglitazone (target dose, 45 mg daily) or placebo. Eligible patients did not have diabetes but were found to have insulin resistance on the basis of a score of more than 3.0 on the homeostasis model assessment of insulin resistance (HOMA-IR) index. The primary outcome was fatal or nonfatal stroke or myocardial infarction. RESULTS: By 4.8 years, a primary outcome had occurred in 175 of 1939 patients (9.0%) in the pioglitazone group and in 228 of 1937 (11.8%) in the placebo group (hazard ratio in the pioglitazone group, 0.76; 95% confidence interval [CI], 0.62 to 0.93; P=0.007). Diabetes developed in 73 patients (3.8%) and 149 patients (7.7%), respectively (hazard ratio, 0.48; 95% CI, 0.33 to 0.69; P<0.001). There was no significant between-group difference in all-cause mortality (hazard ratio, 0.93; 95% CI, 0.73 to 1.17; P=0.52). Pioglitazone was associated with a greater frequency of weight gain exceeding 4.5 kg than was placebo (52.2% vs. 33.7%, P<0.001), edema (35.6% vs. 24.9%, P<0.001), and bone fracture requiring surgery or hospitalization (5.1% vs. 3.2%, P=0.003). CONCLUSIONS: In this trial involving patients without diabetes who had insulin resistance along with a recent history of ischemic stroke or TIA, the risk of stroke or myocardial infarction was lower among patients who received pioglitazone than among those who received placebo. Pioglitazone was also associated with a lower risk of diabetes but with higher risks of weight gain, edema, and fracture. (Funded by the National Institute of Neurological Disorders and Stroke; ClinicalTrials.gov number, NCT00091949.).

A longitudinal, observational study with many repeated measures demonstrated improved precision of individual survival curves using Bayesian joint modeling of disability and survival.

UNLABELLED: BACKGROUND/STUDY CONTEXT: It has not been previously demonstrated whether Bayesian joint modeling (BJM) of disability and survival can, under certain conditions, improve precision of individual survival curves. METHODS: A longitudinal, observational study wherein 754 initially nondisabled community-dwelling adults in greater New Haven, Connecticut, were observed on a monthly basis for over 10 years. RESULTS: In this study, BJM exploited many monthly observations to demonstrate, relative to a separate survival model with adjustment, improved precision of individual survival curves, permitting detection of significant differences between survival curves of two similar individuals. The gain in precision was lost when using only those observations from intervals of 6, 9, or 12 months. CONCLUSION: When there are many repeated measures, BJM of longitudinal functional disability and interval-censored survival can potentially increase the precision of individual survival curves relative to those from a separate survival model. This may facilitate the identification of significant differences between individual survival curves, a useful result usually precluded by the large variability inherent to individual-level estimates from stand-alone survival models.

Selection of the treatment effect for sample size determination in a superiority clinical trial using a hybrid classical and Bayesian procedure.

Specification of the treatment effect that a clinical trial is designed to detect (θA) plays a critical role in sample size and power calculations. However, no formal method exists for using prior information to guide the choice of θA. This paper presents a hybrid classical and Bayesian procedure for choosing an estimate of the treatment effect to be detected in a clinical trial that formally integrates prior information into this aspect of trial design. The value of θA is found that equates the pre-specified frequentist power and the conditional expected power of the trial. The conditional expected power averages the traditional frequentist power curve using the conditional prior distribution of the true unknown treatment effect θ as the averaging weight. The Bayesian prior distribution summarizes current knowledge of both the magnitude of the treatment effect and the strength of the prior information through the assumed spread of the distribution. By using a hybrid classical and Bayesian approach, we are able to formally integrate prior information on the uncertainty and variability of the treatment effect into the design of the study, mitigating the risk that the power calculation will be overly optimistic while maintaining a frequentist framework for the final analysis. The value of θA found using this method may be written as a function of the prior mean µ0 and standard deviation τ0, with a unique relationship for a given ratio of µ0/τ0. Results are presented for Normal, Uniform, and Gamma priors for θ.

Proximity to natural gas wells and reported health status: results of a household survey in Washington County, Pennsylvania.

BACKGROUND: Little is known about the environmental and public health impact of unconventional natural gas extraction activities, including hydraulic fracturing, that occur near residential areas. OBJECTIVES: Our aim was to assess the relationship between household proximity to natural gas wells and reported health symptoms. METHODS: We conducted a hypothesis-generating health symptom survey of 492 persons in 180 randomly selected households with ground-fed wells in an area of active natural gas drilling. Gas well proximity for each household was compared with the prevalence and frequency of reported dermal, respiratory, gastrointestinal, cardiovascular, and neurological symptoms. RESULTS: The number of reported health symptoms per person was higher among residents living < 1 km (mean ± SD, 3.27 ± 3.72) compared with > 2 km from the nearest gas well (mean ± SD, 1.60 ± 2.14; p = 0.0002). In a model that adjusted for age, sex, household education, smoking, awareness of environmental risk, work type, and animals in house, reported skin conditions were more common in households < 1 km compared with > 2 km from the nearest gas well (odds ratio = 4.1; 95% CI: 1.4, 12.3; p = 0.01). Upper respiratory symptoms were also more frequently reported in persons living in households < 1 km from gas wells (39%) compared with households 1-2 km or > 2 km from the nearest well (31 and 18%, respectively) (p = 0.004). No equivalent correlation was found between well proximity and other reported groups of respiratory, neurological, cardiovascular, or gastrointestinal conditions. CONCLUSION: Although these results should be viewed as hypothesis generating, and the population studied was limited to households with a ground-fed water supply, proximity of natural gas wells may be associated with the prevalence of health symptoms including dermal and respiratory conditions in residents living near natural gas extraction activities. Further study of these associations, including the role of specific air and water exposures, is warranted.

Pioglitazone for secondary prevention after ischemic stroke and transient ischemic attack: rationale and design of the Insulin Resistance Intervention after Stroke Trial.

BACKGROUND: Recurrent vascular events remain a major source of morbidity and mortality after stroke or transient ischemic attack (TIA). The IRIS Trial is evaluating an approach to secondary prevention based on the established association between insulin resistance and increased risk for ischemic vascular events. Specifically, IRIS will test the effectiveness of pioglitazone, an insulin-sensitizing drug of the thiazolidinedione class, for reducing the risk for stroke and myocardial infarction (MI) among insulin resistant, nondiabetic patients with a recent ischemic stroke or TIA. DESIGN: Eligible patients for IRIS must have had insulin resistance defined by a Homeostasis Model Assessment-Insulin Resistance > 3.0 without meeting criteria for diabetes. Within 6 months of the index stroke or TIA, patients were randomly assigned to pioglitazone (titrated from 15 to 45 mg/d) or matching placebo and followed for up to 5 years. The primary outcome is time to stroke or MI. Secondary outcomes include time to stroke alone, acute coronary syndrome, diabetes, cognitive decline, and all-cause mortality. Enrollment of 3,876 participants from 179 sites in 7 countries was completed in January 2013. Participant follow-up will continue until July 2015. SUMMARY: The IRIS Trial will determine whether treatment with pioglitazone improves cardiovascular outcomes of nondiabetic, insulin-resistant patients with stroke or TIA. Results are expected in early 2016.

A dynamic trajectory class model for intensive longitudinal categorical outcome.

This paper presents a novel dynamic latent class model for a longitudinal response that is frequently measured as in our prospective study of older adults with monthly data on activities of daily living for more than 10 years. The proposed method is especially useful when the longitudinal response is measured much more frequently than other relevant covariates. The trajectory classes are latent classes that represent distinct temporal patterns of the longitudinal response wherein an individual may remain in a trajectory class or switch to another as the class membership predictors are updated periodically over time. The identification of a common set of trajectory classes allows changes among the temporal patterns to be distinguished from local fluctuations in the response. Within a trajectory class, the longitudinal response is modeled by a class-specific generalized linear mixed model. An informative event such as death is jointly modeled by class-specific probability of the event through shared random effects with that for the longitudinal response. We do not impose the conditional independence assumption given the classes. We illustrate the method by analyzing the change over time in activities of daily living trajectory class among 754 older adults with 70,500 person-months of follow-up in the Precipitating Events Project. We also investigate the impact of jointly modeling the class-specific probability of the event on the parameter estimates in a simulation study. The primary contribution of our paper is the periodic updating of trajectory classes for a longitudinal categorical response without assuming conditional independence.

Effect of vitamin E and memantine on functional decline in Alzheimer disease: the TEAM-AD VA cooperative randomized trial.

IMPORTANCE: Although vitamin E and memantine have been shown to have beneficial effects in moderately severe Alzheimer disease (AD), evidence is limited in mild to moderate AD. OBJECTIVE: To determine if vitamin E (alpha tocopherol), memantine, or both slow progression of mild to moderate AD in patients taking an acetylcholinesterase inhibitor. DESIGN, SETTING, AND PARTICIPANTS: Double-blind, placebo-controlled, parallel-group, randomized clinical trial involving 613 patients with mild to moderate AD initiated in August 2007 and concluded in September 2012 at 14 Veterans Affairs medical centers. INTERVENTIONS: Participants received either 2000 IU/d of alpha tocopherol (n = 152), 20 mg/d of memantine (n = 155), the combination (n = 154), or placebo (n = 152). MAIN OUTCOMES AND MEASURES: Alzheimer's Disease Cooperative Study/Activities of Daily Living (ADCS-ADL) Inventory score (range, 0-78). Secondary outcomes included cognitive, neuropsychiatric, functional, and caregiver measures. RESULTS: Data from 561 participants were analyzed (alpha tocopherol = 140, memantine = 142, combination = 139, placebo = 140), with 52 excluded because of a lack of any follow-up data. Over the mean (SD) follow-up of 2.27 (1.22) years, ADCS-ADL Inventory scores declined by 3.15 units (95% CI, 0.92 to 5.39; adjusted P = .03) less in the alpha tocopherol group compared with the placebo group. In the memantine group, these scores declined 1.98 units less (95% CI, -0.24 to 4.20; adjusted P = .40) than the placebo group's decline. This change in the alpha tocopherol group translates into a delay in clinical progression of 19% per year compared with placebo or a delay of approximately 6.2 months over the follow-up period. Caregiver time increased least in the alpha tocopherol group. All-cause mortality and safety analyses showed a difference only on the serious adverse event of "infections or infestations," with greater frequencies in the memantine (31 events in 23 participants) and combination groups (44 events in 31 participants) compared with placebo (13 events in 11 participants). CONCLUSIONS AND RELEVANCE: Among patients with mild to moderate AD, 2000 IU/d of alpha tocopherol compared with placebo resulted in slower functional decline. There were no significant differences in the groups receiving memantine alone or memantine plus alpha tocopherol. These findings suggest benefit of alpha tocopherol in mild to moderate AD by slowing functional decline and decreasing caregiver burden. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT00235716.

Design of "neuropsychological and mental health outcomes of operation Iraqi freedom: a longitudinal cohort study".

OBJECTIVE: This study aimed to describe methodological challenges encountered in designing a follow-up assessment of US Army Soldiers who served in Operation Iraqi Freedom. STUDY DESIGN AND SETTING: The Neurocognition Deployment Health Study (NDHS) enrolled 1595 soldiers at 2 military installations, starting in 2003. Prior work compared predeployment and postdeployment assessments among Iraq-deployed and nondeployed soldiers. The current phase, as VA Cooperative Studies Program #566, is collecting follow-up data on participants who were deployed to Iraq or Afghanistan. Specific aims include evaluating the prevalence and course of posttraumatic stress disorder (PTSD), the persistence of previously observed neuropsychological changes, and the relationship of these changes-and traumatic brain injury-to subsequent PTSD. The target sample size is 817 participants, with 200 participants also receiving performance-based neuropsychological assessments. RESULTS: We describe 6 methodological challenges and their implications for longitudinal research among a "closed," young, mobile study population: transitioning from cluster-based (battalion) sampling to individual-level sampling; overcoming practical barriers (such as location searches); selecting exposure and outcome measures that combine previously collected and current study data; accounting for loss of an exposed (deployed) versus (nonexposed) nondeployed comparison; determining timing of assessments; and developing a complex statistical analysis plan. Enrollment is ongoing. CONCLUSIONS: The study provides unique insights regarding elements of study design and analysis that are relevant to longitudinal research. In particular, the dynamic "real-life" context of military deployment provides a basis for applying observational methodology to characterize mental health disorders associated with exposure to war-zone deployment and other contexts associated with exposure to extreme stress.

Efficacy and effectiveness as aspects of cluster randomized trials with nursing home residents: methodological insights from a pneumonia prevention trial.

This report discusses how methodological aspects of study efficacy and effectiveness combine in cluster randomized trials in nursing homes. Discussion focuses on the relationships between these study aspects in the Pneumonia Reduction in Institutionalized Disabled Elders (PRIDE) trial, an ongoing cluster randomized clinical trial of pneumonia prevention among nursing home residents launched in October 2009 in Greater New Haven, Connecticut. This clinical trial has enrolled long-term care nursing home residents, over 65years in age, who have either inadequate oral care or swallowing difficulty, previously identified risk factors for pneumonia. It has used a multicomponent intervention consisting of manual tooth/gum brushing, 0.12% chlorhexidine oral rinse administered twice daily by nurses, and upright feeding positioning at meals to reduce rates of radiographically documented pneumonia. Cluster randomization is attractive for nursing home intervention studies because physical proximity and administrative arrangements make it difficult to deliver different interventions to residents of the same nursing home. Implementing an intervention in an entire home requires integration into the daily life of residents and into the administrative procedures of the nursing home. This characteristic of nursing home cluster randomized trials makes them approximate "real-world" research contexts, but implementation can be challenging. The PRIDE trial of pneumonia prevention utilized specific methodological choices that include both efficacy and effectiveness elements. Cluster randomized trials in nursing homes having elements of both efficacy and effectiveness (i.e., hybrid designs) can address some of the methodological challenges of conducting clinical research in nursing homes; they have distinctive advantages and some limitations.

American Thyroid Association design and feasibility of a prospective randomized controlled trial of prophylactic central lymph node dissection for papillary thyroid carcinoma.

BACKGROUND: The role of prophylactic central lymph node dissection in papillary thyroid cancer (PTC) is controversial in patients who have no pre- or intraoperative evidence of nodal metastasis (clinically N0; cN0). The controversy relates to its unproven role in reducing recurrence rates while possibly increasing morbidity (permanent hypoparathyroidism and unintentional recurrent laryngeal nerve injury). METHODS AND RESULTS: We examined the design and feasibility of a multi-institutional prospective randomized controlled trial of prophylactic central lymph node dissection in cN0 PTC. Assuming a 7-year study with 4 years of enrollment, 5 years of average follow-up, a recurrence rate of 10% after 7 years, a 25% relative reduction in the rate of the primary endpoint (newly identified structural disease; i.e., persistent, recurrent, or distant metastatic disease) with central lymph node dissection and an annual dropout rate of 3%, a total of 5840 patients would have to be included in the study to achieve at least 80% statistical power. Similarly, given the low rates of morbidity, several thousands of patients would need to be included to identify a significant difference in rates of permanent hypoparathyroidism and unintentional recurrent laryngeal nerve injury. CONCLUSION: Given the low rates of both newly identified structural disease and morbidity after surgery for cN0 PTC, prohibitively large sample sizes would be required for sufficient statistical power to demonstrate significant differences in outcomes. Thus, a prospective randomized controlled trial of prophylactic central lymph node dissection in cN0 PTC is not readily feasible.

Contribution of multiple chronic conditions to universal health outcomes.

OBJECTIVES: To determine the relative effect of five chronic conditions on four representative universal health outcomes. DESIGN: Cross-sectional. SETTING: Cardiovascular Health Study. PARTICIPANTS: Five thousand two hundred and ninety-eight community-living participants aged 65 and older. MEASUREMENTS: Multiple regression and Cox models were used to determine the effect of heart failure (HF), chronic obstructive pulmonary disease (COPD), osteoarthritis, depression, and cognitive impairment on self-rated health, 12 basic and instrumental activities of daily living (ADLs and IADLs), six-item symptom burden scale, and death. RESULTS: Each condition adversely affected self-rated health (P < .001) and ADLs and IADLs (P < .001). For example, persons with HF performed 0.70 ± 0.08 fewer ADLs and IADLs than those without; persons with depression and persons with cognitive impairment performed 0.59 ± 0.04 and 0.58 ± 0.06 fewer activities, respectively, than those without these conditions. Depression, HF, COPD, and osteoarthritis were associated with 1.18 ± 0.04, 0.40 ± 0.08, 0.40 ± 0.05, and 0.57 ± 0.03 more symptoms, respectively, in individuals with these conditions than in those without. HF (hazard ratio (HR) = 2.84, 95% confidence interval (CI) = 1.97-4.10), COPD (2.62, 95% CI = 1.94-3.53), cognitive impairment (2.05, 95% CI = 1.47-2.85), and depression (1.47, 95% CI = 1.08-2.01) were each associated with death within 2 years. Several paired combinations of conditions had synergistic effects on ADLs and IADLs. For example, individuals with HF plus depression performed 2.0 fewer activities than persons with neither condition, versus the 1.3 fewer activities expected from adding the effects of the two conditions together. CONCLUSION: Universal health outcomes may provide a common metric for measuring the effects of multiple conditions and their treatments. The varying effects of the conditions across universal outcomes could inform care priorities.

Scientific and organizational collaboration in comparative effectiveness research: the VA cooperative studies program model.

Comparative effectiveness research (CER) has the ability to improve health and inform patients, clinicians, and decision makers. However, calls for more devoted efforts with regard to CER have been countered by methodological, resource, and translational challenges related to conducting these studies. The Department of Veterans Affairs (VA) Cooperative Studies Program (CSP) is a clinical research infrastructure that has contributed much evidence to support clinical practice for several decades. Although the CSP does not exclusively focus on CER, it employs strategies that lend themselves toward the planning and execution of studies that seek to compare interventions and/or strategies for treating disease. Consequently, the CSP provides a model for addressing important scientific, structural, and operational factors for clinical research, including large, national and multinational comparative effectiveness studies. Exploration of the difficulties the CSP has encountered can help to elucidate barriers that face CER. This article discusses factors and approaches for collaboratively developing and conducting definitive studies that produce outcomes aimed at influencing clinical practice, lessons that have resulted from such efforts, and ongoing challenges. Future program directions are also presented to highlight areas of emphasis and implications for CER within the VA and nationally.

Outcomes following endovascular vs open repair of abdominal aortic aneurysm: a randomized trial.

CONTEXT: Limited data are available to assess whether endovascular repair of abdominal aortic aneurysm (AAA) improves short-term outcomes compared with traditional open repair. OBJECTIVE: To compare postoperative outcomes up to 2 years after endovascular or open repair of AAA in a planned interim report of a 9-year trial. DESIGN, SETTING, AND PATIENTS: A randomized, multicenter clinical trial of 881 veterans (aged > or = 49 years) from 42 Veterans Affairs Medical Centers with eligible AAA who were candidates for both elective endovascular repair and open repair of AAA. The trial is ongoing and this report describes the period between October 15, 2002, and October 15, 2008. INTERVENTION: Elective endovascular (n = 444) or open (n = 437) repair of AAA. MAIN OUTCOME MEASURES: Procedure failure, secondary therapeutic procedures, length of stay, quality of life, erectile dysfunction, major morbidity, and mortality. RESULTS: Mean follow-up was 1.8 years. Perioperative mortality (30 days or inpatient) was lower for endovascular repair (0.5% vs 3.0%; P = .004), but there was no significant difference in mortality at 2 years (7.0% vs 9.8%, P = .13). Patients in the endovascular repair group had reduced median procedure time (2.9 vs 3.7 hours), blood loss (200 vs 1000 mL), transfusion requirement (0 vs 1.0 units), duration of mechanical ventilation (3.6 vs 5.0 hours), hospital stay (3 vs 7 days), and intensive care unit stay (1 vs 4 days), but required substantial exposure to fluoroscopy and contrast. There were no differences between the 2 groups in major morbidity, procedure failure, secondary therapeutic procedures, aneurysm-related hospitalizations, health-related quality of life, or erectile function. CONCLUSIONS: In this report of short-term outcomes after elective AAA repair, perioperative mortality was low for both procedures and lower for endovascular than open repair. The early advantage of endovascular repair was not offset by increased morbidity or mortality in the first 2 years after repair. Longer-term outcome data are needed to fully assess the relative merits of the 2 procedures. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT00094575.

A semiparametric transition model with latent traits for longitudinal multistate data.

SUMMARY: We propose a general multistate transition model. The model is developed for the analysis of repeated episodes of multiple states representing different health status. Transitions among multiple states are modeled jointly using multivariate latent traits with factor loadings. Different types of state transition are described by flexible transition-specific nonparametric baseline intensities. A state-specific latent trait is used to capture individual tendency of the sojourn in the state that cannot be explained by covariates and to account for correlation among repeated sojourns in the same state within an individual. Correlation among sojourns across different states within an individual is accounted for by the correlation between the different latent traits. The factor loadings for a latent trait accommodate the dependence of the transitions to different competing states from a same state. We obtain the semiparametric maximum likelihood estimates through an expectation-maximization (EM) algorithm. The method is illustrated by studying repeated transitions between independence and disability states of activities of daily living (ADL) with death as an absorbing state in a longitudinal aging study. The performance of the estimation procedure is assessed by simulation studies.