Search

Data-intensive research continues to expand with the goal of improving healthcare delivery, clinical decision-making, and patient outcomes. Quantitative scientists, such as biostatisticians, epidemiologists, and informaticists, are tasked with turning data into health knowledge. In academic health centres, quantitative scientists are critical to the missions of biomedical discovery and improvement of health. Many academic health centres have developed centralized Quantitative Science Units which foster dual goals of professional development of quantitative scientists and producing high quality, reproducible domain research. Such units then develop teams of quantitative scientists who can collaborate with researchers. However, existing literature does not provide guidance on how such teams are formed or how to manage and sustain them. Leaders of Quantitative Science Units across six institutions formed a working group to examine common practices and tools that can serve as best practices for Quantitative Science Units that wish to achieve these dual goals through building long-term partnerships with researchers. The results of this working group are presented to provide tools and guidance for Quantitative Science Units challenged with developing, managing, and evaluating Quantitative Science Teams. This guidance aims to help Quantitative Science Units effectively participate in and enhance the research that is conducted throughout the academic health centre-shaping their resources to fit evolving research needs., Competing Interests: CONFLICT OF INTEREST STATEMENT The authors have no conflicts of interest to declare.

Collaborative quantitative scientists, including biostatisticians, epidemiologists, bio-informaticists, and data-related professionals, play vital roles in research, from study design to data analysis and dissemination. It is imperative that academic health care centers (AHCs) establish an environment that provides opportunities for the quantitative scientists who are hired as staff to develop and advance their careers. With the rapid growth of clinical and translational research, AHCs are charged with establishing organizational methods, training tools, best practices, and guidelines to accelerate and support hiring, training, and retaining this staff workforce. This paper describes three essential elements for building and maintaining a successful unit of collaborative staff quantitative scientists in academic health care centers: (1) organizational infrastructure and management, (2) recruitment, and (3) career development and retention. Specific strategies are provided as examples of how AHCs can excel in these areas., Competing Interests: CONFLICT OF INTEREST STATEMENT The authors have no conflicts of interest to declare.

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., Competing Interests: CJL receives research funding to his institution from NIH, DoD, CDC, Biomeme, Entegrion, Endpoint Health, AstraZeneca, bioMerieux, and stock options in Bioscape Digital unrelated to the current work., (© The Author(s) 2024.)

Data science consulting and collaboration units (DSUs) are core infrastructure for research at universities. Activities span data management, study design, data analysis, data visualization, predictive modelling, preparing reports, manuscript writing and advising on statistical methods and may include an experiential or teaching component. Partnerships are needed for a thriving DSU as an active part of the larger university network. Guidance for identifying, developing and managing successful partnerships for DSUs can be summarized in six rules: (1) align with institutional strategic plans, (2) cultivate partnerships that fit your mission, (3) ensure sustainability and prepare for growth, (4) define clear expectations in a partnership agreement, (5) communicate and (6) expect the unexpected. While these rules are not exhaustive, they are derived from experiences in a diverse set of DSUs, which vary by administrative home, mission, staffing and funding model. As examples in this paper illustrate, these rules can be adapted to different organizational models for DSUs. Clear expectations in partnership agreements are essential for high quality and consistent collaborations and address core activities, duration, staffing, cost and evaluation. A DSU is an organizational asset that should involve thoughtful investment if the institution is to gain real value., Competing Interests: CONFLICT OF INTEREST STATEMENT The authors do not declare conflicts of interest.

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., Competing Interests: Disclosures and Acknowledgments This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. There are no competing interests for any author., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

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., Competing Interests: The authors have no conflicts of interest to declare., (© The Author(s) 2023.)

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., (Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the Association of American Medical Colleges.)

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., (Copyright © 2022. Published by Elsevier Inc.)

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., Competing Interests: The authors have no conflicts of interest to declare., (© 2022 The Authors. Stat published by John Wiley & Sons Ltd.)

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., Competing Interests: Disclosures SCG reports receiving consulting fees from Gilead Sciences for serving on multiple Data Monitoring Committees. Although this relationship is not perceived to represent a conflict with the present work, it has been included in the spirit of full disclosure. There are no other conflicts of interest to report.

The field of data science has great potential to address critical questions relevant for academic medical centers. Data science initiatives are consequently being established within academic medicine. At the cornerstone of such initiatives are scientists who practice data science. These scientists include biostatisticians, clinical informaticians, database and software developers, computational scientists, and computational biologists. Too often, however, those involved in the practice of data science are viewed by academic leadership as providing a noncomplex service to facilitate research and further the careers of other academic faculty. The authors contend that the success of data science initiatives relies heavily on the understanding that the practice of data science is a critical intellectual contribution to the overall science conducted at an academic medical center. Further, careful thought by academic leadership is needed for allocation of resources devoted to the practice of data science. At the Stanford University School of Medicine, the authors have developed an innovative model for a data science collaboratory based on 4 fundamental elements: an emphasis on collaboration over consultation, a subscription-based funding mechanism that reflects commitment by key partners, an investment in the career development of faculty who practice data science, and a strong educational component for data science members in team science and for clinical and translational investigators in data science. As data science becomes increasingly essential to learning health systems, centers that specialize in the practice of data science are a critical component of the research infrastructure and intellectual environment of academic medical centers., (Copyright © 2021 by the Association of American Medical Colleges.)

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., (Copyright © 2021 Journal of Pediatric Urology Company. Published by Elsevier Ltd. All rights reserved.)

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., Competing Interests: The authors have no conflicts of interest to declare., (© The Association for Clinical and Translational Science 2021.)

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.]., (Copyright 2020, SLACK Incorporated.)

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., Competing Interests: SCG reports receiving consulting fees from Gilead Sciences for serving on multiple Data Monitoring Committees. SMT reports receiving consulting fees from Abbvie, Inc. for work on biosimilars and bioequivalence. Although these relationships are not perceived to represent a conflict with the present work, they have been included in the spirit of full disclosure. There are no other conflicts of interest to report., (© The Association for Clinical and Translational Science 2020.)

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., (© The Association for Clinical and Translational Science 2020.)

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., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Objectives: To compare and contrast the use of partial nephrectomy (PN) and radical nephrectomy (RN) in pediatric malignant renal tumors using a nationally representative database., Methods: The 2010-2014 Nationwide Readmissions Database (NRD) was used to obtain PN and RN select postoperative data. ICD-9-CM codes were used to identify children (<10 years), adolescents (10-19 years) and young adults (20-30 years) diagnosed with malignant renal tumors who were treated with a PN or RN. The presence of a 30-day readmission, occurrence of postoperative complications, cost, and length of stay (LOS) were studied and weighted logistic regression models were fit to test for associations., Results: There were 4330 weighted encounters (1289 PNs, 3041 RNs) that met inclusion criteria: 50.8% were children, 7.2% were adolescents, and 42% were young adults. Young adults had the highest rates of PN, whereas children had the highest rates of RN (p < 0.0001). Overall, no evidence was found to suggest a difference in odds between surgical modality and the presence of a 30-day readmission or postoperative complication. While PN was on average $9000 cheaper compared to RN overall, its cost was similar to that of RN for children. Similarly, PN patients had a shorter overall LOS compared to RN patients, but their LOS was similar to that of children who underwent RN., Conclusion: There was no evidence of a difference in odds between RN and PN in terms of postoperative readmissions or in-hospital complication rates. Additionally, we observed descriptive differences in both cost and LOS between the surgical modalities across age groups., Type of Study: Retrospective comparative study (administrative database analysis)., Level of Evidence: Level III., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Our objective was to use community-based, national databases to evaluate diagnostic imaging and antibiotic prophylaxis practice patterns before and after the release of the 2011 American Academy of Pediatrics guidelines for acute febrile urinary tract infection. Using the National Ambulatory and Hospital Ambulatory Medical Care Surveys, urinary tract infection encounters were identified for patients aged 2 months to 18 years. Primary outcomes were utilization of antibiotics (as proxy for prophylaxis) and diagnostic imaging during encounters. Weighted multivariate logistic regression models were used to examine the association between time period (before and after 2011) and each of the primary outcomes. Among 8 588 035 weighted encounters, adjusting for covariates, there was insufficient evidence to suggest a difference between time periods for antibiotic utilization (odds ratio = 0.66, P = .12) or diagnostic imaging (odds ratio = 1.16, P = .56). Thus, we did not find evidence of changes in antibiotic utilization or diagnostic imaging practice patterns after the release of the 2011 American Academy of Pediatrics guidelines.

Introduction/Objectives: Despite minimal evidence that evaluates the effect of age on percutaneous nephrolithotomy (PCNL) morbidity, pediatric and elderly patients are considered high-risk groups. Our objective was to assess the effect of the extremes of ages on PCNL readmission and postoperative complication rates. Methods: We identified all PCNL encounters in the 2013 and 2014 Nationwide Readmission Database. Encounters were divided into five age groups: pediatric (<18 years old), young adult (18-25 years old), adult (26-64 years old), geriatric (65-74 years old), and elderly (≥75 years old). Weighted descriptive statistics were used to describe population demographics. We fit an adjusted weighted logistic regression model for 30-day readmission and complication rates. Results: We identified 23,357 encounters. Testing average effect of pediatric and elderly encounters to all other age groups did not reveal a difference in odds for 30-day readmissions, but did result in increased odds for 30-day GU readmissions (odds ratio: 17.7 [95% confidence interval (CI): 2.65-118.9]; p  = 0.003). Compared to all other age groups, elderly encounters had 7.5 (95% CI: 2.5-22.7; p  = 0.0004) times the odds of a 30-day readmission and 68.3 (95% CI: 29.1-160.4; p  < 0.0001) times the odds of a postoperative complication. Conclusions: When comparing the average effect of the extremes of ages to all other age groups, we did not find evidence to suggest a difference in odds for 30-day GU readmissions, but did find increased odds for complications. Further examination revealed that PCNL encounters of elderly patients had significantly increased odds for both readmission and complications, whereas PCNL encounters of pediatric patients did not.

Background: More children with spina bifida (SB) are surviving into adulthood. Unfortunately, little data exist regarding the economic implications of modern SB care., Objective: We examined economic data from two national databases to estimate the annual nationwide hospital and emergency charges of SB from 2006-14., Methods: We analyzed the 2006-2014 Nationwide Inpatient Sample (NIS) and Nationwide Emergency Department Sample (NEDS). SB patients were defined using ICD-9-CM codes. Demographic and charge data were obtained from each database. Multiple imputation was used to estimate missing data (1.6% for NIS and 22% in NEDS). The principal outcomes were mean, median, and total charges for encounters each year., Results: There were 725,646 encounters for individuals with SB between 2006 and 2014. The average age of captured SB patients who were admitted to a hospital or seen in an ER was 29 years. In 2014, the median charge for inpatient encounters was $31,071 (IQR: $15,947, $63,063) and for ER encounters was $2407.02 (IQR: $1321.91, $4211.35). In total, the sum of charges from all SB-related admissions in 2014 was $1,862,016,217 (95% CI: $1.69 billion, $2.03 billion), while the sum of charges of all SB-related ER encounters in 2014 was $176,843,522 (95% CI: $158 million, $196 million). There was a steady increase in charges over the study period., Conclusion: Charges for SB-related inpatient and emergency care in the US in 2014 was in excess of $2 billion in contrast to $1.2 billion in 2006, after adjusting for inflation; this is an impressively high figure for a relatively small number of patients., (Copyright © 2019 Elsevier Inc. All rights reserved.)

The impact of the Patient Protection and Affordable Care Act (PPACA) on children's access to surgical care is not well-defined. Our objective was to describe the early impact of PPACA on children's surgical care before and after Medicaid expansion in 2014. We compared pediatric and young adult surgical outcomes in 2013 and 2014 in Medicaid expansion and nonexpansion states; young adults were included as a control group. From 4 states, 1 597 708 encounters met all inclusion criteria. Comparing expansion to nonexpansion states, modest increases were noted in elective instead of urgent/emergent admissions; in ambulatory instead of inpatient surgeries; in inpatient length of stays; in discharges to home instead of other inpatient care facilities; and in charges for inpatient admissions. A modest decrease of -1.1% was noted in ambulatory admission charges. Overall, we conclude that Medicaid expansion likely increased children's access to surgical care, resulting in improved delivery and slightly reduced charges.

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.

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.

Introduction: The surgical comorbidity assessment is important for patient risk stratification, counseling, and research. In adults, risk assessment indices, such as the Charlson Co-morbidity Score (CCS) or Van Walraven Index (VWI), are well established. In pediatrics, however, risk assessment indices are scarce. Recently, a pediatric-specific risk assessment index, the Rhee index, was developed to discriminate mortality for pediatric general surgery patients. Currently, there is no validated risk assessment tool in pediatric urology., Objective: We compared the performance of the CCS, VWI, and Rhee Index in discriminating postoperative complications and readmissions to the emergency room/inpatient unit after pediatric urological procedures., Methods: We analyzed the Nationwide Readmissions Database (NRD), State Inpatient Databases (SID), and State Emergency Department Databases (SEDD). We included patients (<18 years) who underwent the following urological procedures: ureteroneocystostomy, ureteroureterostomy, radical/partial nephrectomy, pyeloplasty, appendicovesicostomy, enterocystoplasty, vesicostomy, and bladder neck sling. Complications were identified based on definitions in the National Surgical Quality Improvement Program (NSQIP). Thirty-day emergency room admission and inpatient readmissions were extracted. Comorbidity scores were calculated using each of the three indices. We compared the performance of each index in discriminate primarily postoperative complications in the NRD and both admission types in the SID/SEDD by constructing a receiver operating characteristics (ROC). AUCs were compared using the Delong method. This protocol was reviewed by our Institutional Review Board and deemed to be exempt., Results: We identified a total of 8006 patients in NRD and 6236 patients in SID/SEDD. The Rhee index had the best performance for discriminating postoperative complications (AUC = 0.67, 95% CI 0.64-0.70) compared to CCS (AUC = 0.62, 95% CI 0.60-0.65) and VWI (AUC = 0.62, 95% CI 0.59-0.65); p < 0.01. The CCS had the best performance for discriminating 30-day inpatient readmissions (AUC = 0.63, 95% CI 0.61-0.66) than VWI (AUC = 0.54, 95% CI 0.52-0.57), and Rhee Index (AUC = 0.56, 95% CI 0.54-0.59); p < 0.0001. All three indices had similarly poor discrimination for 30-day ER admissions: CCS (AUC = 0.52), VWI (AUC = 0.51), and Rhee Index (AUC = 0.50); p = 0.5 (see Table)., Discussion: The Rhee Index had the best performance for discriminating postoperative complications, while the CCS was superior for discriminating inpatient readmissions among the three indices. Limitations to our study include inpatient-only procedures, inability to identify complications managed in clinics, omission of secondary operations, accounting for parental anxiety, and the generalizability of SID., Conclusions: The three comorbidity indices evaluated are poor discriminators for postoperative complications, 30-day inpatient readmissions or 30-day ER admissions. A new index is needed for pediatric urology patients., (Copyright © 2018 Journal of Pediatric Urology Company. Published by Elsevier Ltd. All rights reserved.)

This study aimed to describe the demographic characteristics, hospital utilizations, patterns of inpatient surgical management, and the overall state/regional variation in surgery rate among patients with disorders of sex development (DSD). We analyzed the Nationwide Inpatient Sample from 2001 to 2012 for patients younger than 21 years. DSD-related diagnoses and procedures were identified via International Classification of Diseases, Ninth Revision (ICD-9) codes. We identified a total of 43,968 DSD-related admissions. Of these, 73.4% of the admissions were designated as female and 642 (1.9%) were inpatient surgical admissions. Among neonates, less than 1% underwent any type of genital surgery. Nonsurgical admissions were associated with longer length of stay and higher cost. There was no significant regional variation in the rate of DSD surgeries, but we observed higher concentrations of DSD surgeries in states associated with tertiary referral centers.

Background: Intraoperative resident education is an integral mission of academic medical centers and serves as the basis for training the next generation of surgeons. The actual effort associated with teaching residents is unknown as it pertains to additional operative time. Using a large validated multi-institutional dataset, this study aims to quantify the effect of having a resident present in common plastic surgery procedures on operative time. Future directions for developing standardized methods to record and report teaching time are proposed, which can help inform prospective studies., Study Design: The 2006-2012 American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database was queried to identify seven isolated plastic surgical procedures that were categorized based on resident involvement and supervision. Linear regression models were used to calculate the difference in operative time with respect to resident participation while controlling for patient and operative factors., Results: Resident involvement was associated with longer operative times for muscle flap trunk procedures (53 min, 95% CI = [25, 80], p-value = 0.0002) and breast reconstruction procedures with a latissimus dorsi flap (55 min, 95% CI = [22, 88], p-value = 0.001). For six of the seven surgeries evaluated, resident involvement was associated with longer operative times, as compared to no resident involvement., Conclusion: Resident involvement is associated with an increase in operative time for certain plastic surgery procedures. This finding underscores the need for a mechanism to quantify the time and effort that the attending surgeons allocate toward intraoperative resident education. Further study is also necessary to determine the causal impact on patient care., (Copyright © 2017 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.)

Competing Interests: Financial Disclosure: None of the authors have a financial interest in any of the products, devices, or drugs mentioned in this manuscript.

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., (Copyright © 2017 John Wiley & Sons, Ltd.)

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., (Copyright © 2016 Elsevier Inc. All rights reserved.)

We propose a lag functional linear model to predict a response using multiple functional predictors observed at discrete grids with noise. Two procedures are proposed to estimate the regression parameter functions: (1) an approach that ensures smoothness for each value of time using generalized cross-validation; and (2) a global smoothing approach using a restricted maximum likelihood framework. Numerical studies are presented to analyze predictive accuracy in many realistic scenarios. The methods are employed to estimate a magnetic resonance imaging (MRI)-based measure of tissue damage (the magnetization transfer ratio, or MTR) in multiple sclerosis (MS) lesions, a disease that causes damage to the myelin sheaths around axons in the central nervous system. Our method of estimation of MTR within lesions is useful retrospectively in research applications where MTR was not acquired, as well as in clinical practice settings where acquiring MTR is not currently part of the standard of care. The model facilitates the use of commonly acquired imaging modalities to estimate MTR within lesions, and outperforms cross-sectional models that do not account for temporal patterns of lesion development and repair.

Motivated by an imaging study, this paper develops a nonparametric testing procedure for testing the null hypothesis that two samples of curves observed at discrete grids and with noise have the same underlying distribution. The objective is to formally compare white matter tract profiles between healthy individuals and multiple sclerosis patients, as assessed by conventional diffusion tensor imaging measures. We propose to decompose the curves using functional principal component analysis of a mixture process, which we refer to as marginal functional principal component analysis . This approach reduces the dimension of the testing problem in a way that enables the use of traditional nonparametric univariate testing procedures. The procedure is computationally efficient and accommodates different sampling designs. Numerical studies are presented to validate the size and power properties of the test in many realistic scenarios. In these cases, the proposed test has been found to be more powerful than its primary competitor. Application to the diffusion tensor imaging data reveals that all the tracts studied are associated with multiple sclerosis and the choice of the diffusion tensor image measurement is important when assessing axonal disruption.

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., (Copyright © 2015 John Wiley & Sons, Ltd.)