First-year weight loss with androgen-deprivation therapy increases risks of prostate cancer progression and prostate cancer-specific mortality: results from SEARCH.

PURPOSE: We aimed to study the associations between androgen-deprivation therapy (ADT)-induced weight changes and prostate cancer (PC) progression and mortality in men who had undergone radical prostatectomy (RP). METHODS: Data from the Shared Equal Access Regional Cancer Hospital (SEARCH) cohort were used to study the associations between weight change approximately 1-year post-ADT initiation and metastases, castration-resistant prostate cancer (CRPC), all-cause mortality (ACM), and PC-specific mortality (PCSM) in 357 patients who had undergone RP between 1988 and 2014. We estimated hazard ratios (HR) and 95% confidence intervals (95% CI) using covariate-adjusted Cox regression models for associations between weight loss, and weight gains of 2.3 kg or more, and PC progression and mortality post-ADT. RESULTS: During a median (IQR) follow-up of 81 (46-119) months, 55 men were diagnosed with metastases, 61 with CRPC, 36 died of PC, and 122 died of any cause. In multivariable analysis, weight loss was associated with increases in risks of metastases (HR 3.13; 95% CI 1.40-6.97), PCSM (HR 4.73; 95% CI 1.59-14.0), and ACM (HR 2.16; 95% CI 1.25-3.74) compared with mild weight gains of ≤ 2.2. Results were slightly attenuated but remained statistically significant in analyses that accounted for competing risks of non-PC death. Estimates for the associations between weight gains of ≥ 2.3 kg and metastases (HR 1.58; 95% CI 0.73-3.42), CRPC (HR 1.33; 95% CI 0.66-2.66), and PCSM (HR 2.44; 95% CI 0.84-7.11) were elevated, but not statistically significant. CONCLUSIONS: Our results suggest that weight loss following ADT initiation in men who have undergone RP is a poor prognostic sign. If confirmed in future studies, testing ways to mitigate weight loss post-ADT may be warranted.

A comparison of risk prediction methods using repeated observations: an application to electronic health records for hemodialysis.

An increasingly important data source for the development of clinical risk prediction models is electronic health records (EHRs). One of their key advantages is that they contain data on many individuals collected over time. This allows one to incorporate more clinical information into a risk model. However, traditional methods for developing risk models are not well suited to these irregularly collected clinical covariates. In this paper, we compare a range of approaches for using longitudinal predictors in a clinical risk model. Using data from an EHR for patients undergoing hemodialysis, we incorporate five different clinical predictors into a risk model for patient mortality. We consider different approaches for treating the repeated measurements including use of summary statistics, machine learning methods, functional data analysis, and joint models. We follow up our empirical findings with a simulation study. Overall, our results suggest that simple approaches perform just as well, if not better, than more complex analytic approaches. These results have important implication for development of risk prediction models with EHRs. Copyright © 2017 John Wiley & Sons, Ltd.

Clinical Acuity Shorthand System: a standardized classification tool to facilitate handoffs.

BACKGROUND: The handoff of medical information from one provider to another can be inefficient and error prone, potentially undermining patient safety. Although several tools for structuring handoffs exist, none provide a brief, standardized framework for ensuring that patient acuity is efficiently and reliably communicated. We aim to introduce and perform initial testing of the Clinical Acuity Shorthand System (CLASS) (Copyright 2015, Duke University. All rights reserved.) for surgery, a patient classification tool intended to facilitate efficient communication of key patient information during handoffs. MATERIALS AND METHODS: Surgical trainees at a single center were asked to perform an exercise involving application of CLASS to 10 theoretical patient scenarios and to then complete a brief survey. Responses were scored based on similarity to target answers. Performance was evaluated overall and between groups of trainees. Time required to complete the exercise was also determined and perceived utility of the system was assessed based on survey responses. RESULTS: The study task was completed by 17 participants. Mean time to task completion was 10.3 ± 8.4 min. Accuracy was not decreased, and was in fact superior, in junior trainees. Most respondents indicated that such a system would be feasible and could prevent medical errors. CONCLUSIONS: CLASS is a novel system that can be learned quickly and implemented readily by trainees and can be used to convey patient information concisely and with acceptable fidelity regardless of level of training. Further study examining application of this system on clinical surgical services is warranted.

Scan-stratified case-control sampling for modeling blood-brain barrier integrity in multiple sclerosis.

Multiple sclerosis (MS) is an immune-mediated neurological disease that causes morbidity and disability. In patients with MS, the accumulation of lesions in the white matter of the brain is associated with disease progression and worse clinical outcomes. Breakdown of the blood-brain barrier in newer lesions is indicative of more active disease-related processes and is a primary outcome considered in clinical trials of treatments for MS. Such abnormalities in active MS lesions are evaluated in vivo using contrast-enhanced structural MRI, during which patients receive an intravenous infusion of a costly magnetic contrast agent. In some instances, the contrast agents can have toxic effects. Recently, local image regression techniques have been shown to have modest performance for assessing the integrity of the blood-brain barrier based on imaging without contrast agents. These models have centered on the problem of cross-sectional classification in which patients are imaged at a single study visit and pre-contrast images are used to predict post-contrast imaging. In this paper, we extend these methods to incorporate historical imaging information, and we find the proposed model to exhibit improved performance. We further develop scan-stratified case-control sampling techniques that reduce the computational burden of local image regression models, while respecting the low proportion of the brain that exhibits abnormal vascular permeability.

Peer review of clinical and translational research manuscripts: Perspectives from statistical collaborators.

Research articles in the clinical and translational science literature commonly use quantitative data to inform evaluation of interventions, learn about the etiology of disease, or develop methods for diagnostic testing or risk prediction of future events. The peer review process must evaluate the methodology used therein, including use of quantitative statistical methods. In this manuscript, we provide guidance for peer reviewers tasked with assessing quantitative methodology, intended to complement guidelines and recommendations that exist for manuscript authors. We describe components of clinical and translational science research manuscripts that require assessment including study design and hypothesis evaluation, sampling and data acquisition, interventions (for studies that include an intervention), measurement of data, statistical analysis methods, presentation of the study results, and interpretation of the study results. For each component, we describe what reviewers should look for and assess; how reviewers should provide helpful comments for fixable errors or omissions; and how reviewers should communicate uncorrectable and irreparable errors. We then discuss the critical concepts of transparency and acceptance/revision guidelines when communicating with responsible journal editors.

A Visual Tool to Help Develop a Statistical Analysis Plan for Randomized Trials in Palliative Care.

Collaboration with a statistician about the design of a statistical analysis plan can be enhanced by illustrating how statisticians conceptualize their task. This conceptualization can be represented by a directed acyclic graph (DAG), which illustrates the statistician's approach and also provides an actionable tool to assist in the development of the plan.

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.

Essential team science skills for biostatisticians on collaborative research teams.

Introduction: Despite the critical role that quantitative scientists play in biomedical research, graduate programs in quantitative fields often focus on technical and methodological skills, not on collaborative and leadership skills. In this study, we evaluate the importance of team science skills among collaborative biostatisticians for the purpose of identifying training opportunities to build a skilled workforce of quantitative team scientists. Methods: Our workgroup described 16 essential skills for collaborative biostatisticians. Collaborative biostatisticians were surveyed to assess the relative importance of these skills in their current work. The importance of each skill is summarized overall and compared across career stages, highest degrees earned, and job sectors. Results: Survey respondents were 343 collaborative biostatisticians spanning career stages (early: 24.2%, mid: 33.8%, late: 42.0%) and job sectors (academia: 69.4%, industry: 22.2%, government: 4.4%, self-employed: 4.1%). All 16 skills were rated as at least somewhat important by > 89.0% of respondents. Significant heterogeneity in importance by career stage and by highest degree earned was identified for several skills. Two skills ("regulatory requirements" and "databases, data sources, and data collection tools") were more likely to be rated as absolutely essential by those working in industry (36.5%, 65.8%, respectively) than by those in academia (19.6%, 51.3%, respectively). Three additional skills were identified as important by survey respondents, for a total of 19 collaborative skills. Conclusions: We identified 19 team science skills that are important to the work of collaborative biostatisticians, laying the groundwork for enhancing graduate programs and establishing effective on-the-job training initiatives to meet workforce needs.

Needles in a Haystack: Finding Qualitative and Quantitative Collaborators in Academic Medical Centers.

Translational research is a data-driven process that involves transforming scientific laboratory- and clinic-based discoveries into products and activities with real-world impact to improve individual and population health. Successful execution of translational research requires collaboration between clinical and translational science researchers, who have expertise in a wide variety of domains across the field of medicine, and qualitative and quantitative scientists, who have specialized methodologic expertise across diverse methodologic domains. While many institutions are working to build networks of these specialists, a formalized process is needed to help researchers navigate the network to find the best match and to track the navigation process to evaluate an institution's unmet collaborative needs. In 2018, a novel analytic resource navigation process was developed at Duke University to connect potential collaborators, leverage resources, and foster a community of researchers and scientists. This analytic resource navigation process can be readily adopted by other academic medical centers. The process relies on navigators with broad qualitative and quantitative methodologic knowledge, strong communication and leadership skills, and extensive collaborative experience. The essential elements of the analytic resource navigation process are as follows: (1) strong institutional knowledge of methodologic expertise and access to analytic resources, (2) deep understanding of research needs and methodologic expertise, (3) education of researchers on the role of qualitative and quantitative scientists in the research project, and (4) ongoing evaluation of the analytic resource navigation process to inform improvements. Navigators help researchers determine the type of expertise needed, search the institution to find potential collaborators with that expertise, and document the process to evaluate unmet needs. Although the navigation process can create a basis for an effective solution, some challenges remain, such as having resources to train navigators, comprehensively identifying all potential collaborators, and keeping updated information about resources as methodologists join and leave the institution.

A comprehensive survey of collaborative biostatistics units in academic health centers.

The organizational structures of collaborative biostatistics units in academic health centers (AHCs) in the United States and their important contributions to research are an evolving and active area of discussion and inquiry. Collaborative biostatistics units may serve as a centralized resource to investigators across various disciplines or as shared infrastructure for investigators within a discipline (e.g., cancer), or a combination of both. The characteristics of such units vary greatly, and there has been no comprehensive review of their organizational structures described in the literature to date. This manuscript summarizes the current infrastructure of such units using responses from 129 leaders. Most leaders were over 45 years old, held doctoral degrees, and were on a 12-month appointment. Over half were tenured or on a tenure track and held primary appointments in a school of medicine. Career advancement metrics most important included being funded as co-investigator on NIH grants and being either first or second author on peer-reviewed publications. Team composition was diverse in terms of expertise and training, and funding sources were typically hybrid. These results provide a benchmark for collaboration models and evaluation and may be used by institutional administrators as they build, evaluate, or restructure current collaborative quantitative support infrastructure.

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.

Open versus minimally-invasive surgical techniques in pediatric renal tumors: A population-level analysis of in-hospital outcomes.

INTRODUCTION: Minimally-invasive surgery (MIS) has been adopted slowly in pediatric oncology. We attempted to describe contemporary national trends in MIS use; we hypothesized that adolescents (who are more likely to have relatively small renal cell carcinomas) would have a higher proportion of MIS than younger children (who are more likely to have relatively large Wilms tumors) and that this relationship would vary by region. OBJECTIVE: To explore whether pediatric urologic oncology outcomes vary by patient age or by surgical technique. METHODS: We queried the 1998-2014 National Inpatient Sample (NIS) and included encounters in children aged ≤ 18 y, ICD-9 diagnostic code for renal tumor, and procedure code for open or MIS partial or radical nephrectomy. All analyses used weighted descriptive statistics and outcomes are compared based on age group (10 y) or surgery type; Wald-Chi square test was used for differences in proportions and unadjusted weighted ANOVA was used to test for differences in means. RESULTS: 9259 weighted encounters were included; 91% were <10 years old and 50.7% were female. MIS surgery accounted for 1.8% of encounters; there was a difference in proportions by age group (1% <9 y vs. 9.9% >9 y, p < 0.01). The proportion of surgery type was similar across regions within age groups, however. Complications occurred in 13.3% of encounters; mean inpatient length of stay was 8.9 days (SD: 0.3); mean cost was $ 34,457.68 (SD: $1197.00). There was no evidence of a difference between surgery type and proportion of post-operative complications, mean inpatient length of stay or mean inpatient cost. DISCUSSION: The admission-based, retrospective design of NIS left us unable to assess long-term outcomes, repeated admissions, or to track a particular patient across time; this is particularly relevant for oncologic variables on interest such as tumor stage or event-free survival. We were similarly limited in evaluating the effect of pre-surgical referral patterns on patient distributions. CONCLUSION: In this preliminary descriptive analysis, MIS techniques were infrequently used in children, but there was a higher proportion of MIS use among adolescents. There were similar proportions of surgery type across geographic regions within the United States. Whether this infrequent usage is appropriate is as yet unclear given the lack of Level I evidence regarding the relative merits of MIS and open surgery for pediatric and adolescent renal tumors.

Amputation Rates in More Than 175,000 Open Tibia Fractures in the United States.

Open tibia fractures are often associated with considerable soft tissue injuries. Management of open tibia fractures can be challenging, and some patients require amputation. The patient and treatment factors have not been described on a population level in the United States. A retrospective analysis was completed using the 2000 to 2011 Nationwide Inpatient Sample. Amputation rates during the index hospitalization after open tibia fracture were computed based on injury, patient, and hospital characteristics in patients 18 years or older. The overall amputation rate in open tibia fractures during the index hospitalization was 2.2% (n=3769). Patients with midshaft tibia fractures comprised the largest portion of patients undergoing amputation (46.8% of total amputations) compared with distal tibia (34.0%) and proximal tibia (19.3%) fractures. Patients with no neurovascular injury comprised the largest portion of patients undergoing amputation (85.9%), followed by isolated arterial injury (11.1%), combined neurovascular injury (1.9%), and isolated nerve injury (1.1%). Amputation rates were significantly increased for midshaft tibia fractures with neurovascular injury (odds ratio, 12.39; 95% CI, 5.52-27.83) and distal tibia fractures with neurovascular injury (odds ratio, 5.45; 95% CI, 1.73-17.19) compared with tibia fractures with no neurovascular injury while controlling for confounders. On the basis of a review of the Nationwide In-patient Sample during the past decade, the authors have shown that the early amputation rate in open tibia fractures for all-comers is 2.2%. Rates of amputation varied based on fracture site, associated neurovascular injury, medical comorbidities, and hospital location. [Orthopedics. 2021;44(1):48-53.].

Guidance for biostatisticians on their essential contributions to clinical and translational research protocol review.

Rigorous scientific review of research protocols is critical to making funding decisions, and to the protection of both human and non-human research participants. Given the increasing complexity of research designs and data analysis methods, quantitative experts, such as biostatisticians, play an essential role in evaluating the rigor and reproducibility of proposed methods. However, there is a common misconception that a statistician's input is relevant only to sample size/power and statistical analysis sections of a protocol. The comprehensive nature of a biostatistical review coupled with limited guidance on key components of protocol review motived this work. Members of the Biostatistics, Epidemiology, and Research Design Special Interest Group of the Association for Clinical and Translational Science used a consensus approach to identify the elements of research protocols that a biostatistician should consider in a review, and provide specific guidance on how each element should be reviewed. We present the resulting review framework as an educational tool and guideline for biostatisticians navigating review boards and panels. We briefly describe the approach to developing the framework, and we provide a comprehensive checklist and guidance on review of each protocol element. We posit that the biostatistical reviewer, through their breadth of engagement across multiple disciplines and experience with a range of research designs, can and should contribute significantly beyond review of the statistical analysis plan and sample size justification. Through careful scientific review, we hope to prevent excess resource expenditure and risk to humans and animals on poorly planned studies.

Patterns of inpatient care for prostate cancer in men with spina bifida.

BACKGROUND: Advances in medical care have increased the long-term survival of patients with spina bifida. Despite this growing population, limited knowledge is available on age-related illnesses in adults with spina bifida, particularly prostate cancer for which there is no published data. OBJECTIVE: Our aim was to describe inpatient care for prostate cancer in men with spina bifida in the United States. METHODS: We performed a descriptive, retrospective study utilizing the 1998 to 2014 National Inpatient Sample from the Healthcare Cost and Utilization Project. Weights were applied to the sample to make national level inferences. We identified all adult encounters (≥18 years old) with prostate cancer and spina bifida. RESULTS: We identified 253 encounters (mean age 64.9 years). Most were Caucasian (67.5%) and had public insurance (61.6%). 44% of encounters included a major urologic procedure. 38.4% of encounters included prostatectomies, 28.3% included lymph node dissections, and 7.8% included cystectomies. Robotic surgery was performed in 9.4%. Mean length of stay was 5.6 days (95% CI: 3.7, 7.5). The average total cost was $14,074 (95% CI: $8990.3, $19,158.6). CONCLUSIONS: In this first-ever exploration of inpatient care for prostate cancer in men with spina bifida, we found that length of stay and total costs were higher in men with spina bifida. Almost half of encounters included a prostatectomy, cystectomy, and/or lymph node dissection. More detailed investigations are necessary to assess comparative treatment outcomes and complications, including prevalence and mortality rates of prostate cancer among adult men with SB.

Learning gaps among statistical competencies for clinical and translational science learners.

INTRODUCTION: Statistical literacy is essential in clinical and translational science (CTS). Statistical competencies have been published to guide coursework design and selection for graduate students in CTS. Here, we describe common elements of graduate curricula for CTS and identify gaps in the statistical competencies. METHODS: We surveyed statistics educators using e-mail solicitation sent through four professional organizations. Respondents rated the degree to which 24 educational statistical competencies were included in required and elective coursework in doctoral-level and master's-level programs for CTS learners. We report competency results from institutions with Clinical and Translational Science Awards (CTSAs), reflecting institutions that have invested in CTS training. RESULTS: There were 24 CTSA-funded respondents representing 13 doctoral-level programs and 23 master's-level programs. For doctoral-level programs, competencies covered extensively in required coursework for all doctoral-level programs were basic principles of probability and hypothesis testing, understanding the implications of selecting appropriate statistical methods, and computing appropriate descriptive statistics. The only competency extensively covered in required coursework for all master's-level programs was understanding the implications of selecting appropriate statistical methods. The least covered competencies included understanding the purpose of meta-analysis and the uses of early stopping rules in clinical trials. Competencies considered to be less fundamental and more specialized tended to be covered less frequently in graduate courses. CONCLUSION: While graduate courses in CTS tend to cover many statistical fundamentals, learning gaps exist, particularly for more specialized competencies. Educational material to fill these gaps is necessary for learners pursuing these activities.

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.

Clinical Features and Outcomes of Patients with Sarcoidosis-associated Pulmonary Hypertension.

The presence of pulmonary hypertension (PH) significantly worsens outcomes in patients with advanced sarcoidosis, but its optimal management is unknown. We aimed to characterize a large sarcoidosis-associated pulmonary hypertension (SAPH) cohort to better understand patient characteristics, clinical outcomes, and management strategies including treatment with PH therapies. Patients at Duke University Medical Center with biopsy-proven sarcoidosis and SAPH confirmed by right heart catheterization (RHC) were identified from 1990-2010. Subjects were followed for up to 11 years and assessed for differences by treatment strategy for their SAPH, including those who were not treated with PH-specific therapies. Our primary outcomes of interest were change in 6-minute walk distance (6MWD) and change in N-terminal pro-brain natriuretic peptide (NT-proBNP) by after therapy. We included 95 patients (76% women, 86% African American) with SAPH. Overall, 70% of patients had stage IV pulmonary sarcoidosis, and 77% had functional class III/IV symptoms. Median NT-proBNP value was elevated (910 pg/mL), and right ventricular dysfunction was moderate/severe in 55% of patients. Median values for mean pulmonary artery pressure (49 mmHg) and pulmonary vascular resistance (8.5 Woods units) were consistent with severe pulmonary hypertension. The mortality rate over median 3-year follow-up was 32%. Those who experienced a clinical event and those who did not had similar overall echocardiographic findings, hemodynamics, 6MWD and NT-proBNP at baseline, and unadjusted analysis showed that only follow-up NT-proBNP was associated with all-cause hospitalization or mortality. A sign test to evaluate the difference between NT-Pro-BNP before and after PH therapy produced evidence that a significant difference existed between the median pre- and post-NT-Pro-BNP (-387.0 (IQR: -1373.0-109), p = 0.0495). Use of PH-specific therapy may be helpful in selected patients with SAPH and pre-capillary pulmonary vascular disease. Prospective trials are needed to characterize responses to PH-specific therapy in this subset of patients with SAPH.