What the rheumatologist needs to know about skin biopsy.

The skin biopsy plays an important and powerful role in helping diagnose rheumatic diseases that present with cutaneous findings. As the skin is a very accessible organ, and the skin biopsy can be performed quickly as an in-office procedure, the skin biopsy is utilized frequently in patients with rheumatic diseases. However, the more challenging aspects of performing the biopsy, such as identifying the type of biopsy to perform, the site (s) to biopsy, the type of media to use, and the interpretation of histopathologic data are nuanced and require considerable thought. In this review, we discuss the common skin findings in rheumatic diseases and the general indications for skin biopsies in these diseases. We then summarize how to perform various skin biopsy techniques and how to select the biopsy technique. Finally, we discuss important rheumatic disease-specific considerations for skin biopsy, including where to biopsy and how to interpret the pathologic reports.

Patterns of Tumor-Infiltrating Lymphocytes Used to Distinguish Primary Cutaneous Squamous Cell Carcinomas That Metastasize.

This case-control study examines the type, location, and density of tumor-infiltrating lymphocytes in adult patients with vs without metastatic cutaneous squamous cell carcinoma.

A hierarchy of needs for remote undergraduate medical education: lessons from the medical student experience.

PURPOSE: The disruption of undergraduate medical education (UME) by the COVID-19 pandemic has sparked rapid, real-time adjustments by medical educators and students. While much is known about online teaching in general, little guidance is available to medical educators on how to adapt courses not originally designed for the online environment. To guide our faculty in this transition we conducted a needs assessment of students enrolled in virtual courses across all 4 years of UME training. METHODS: Using a mixed-methods approach, we conducted a single-institution virtual learning needs assessment in May and June of 2020. We developed and disseminated a survey to assess student experiences with virtual learning. We conducted quantitative and qualitative analysis of responses (n = 255 or 39%) to identify emergent themes. RESULTS: We identified six interdependent themes that need to be met for medical students to fully reach their learning potential: access to stable internet and quiet study spaces, flexible course design with asynchronous, self-paced components, clear expectations for engagement with content and each other, a sense of connectedness with faculty and peers, synchronous classes that maximize interactivity, and assessments that foster a sense of learning over performance. Interpersonal relationships with faculty and peers affected students' sense of learning more than any other factor. CONCLUSIONS: Based on our findings we propose a hierarchy of needs for virtual learning that provides guidance on adapting existing medical school courses to the remote setting and overcoming common challenges. We highlight opportunities for how virtual elements may enrich in-person courses going forward, including in the clinical setting. Although the solutions required to meet the threshold of need at each level may differ based on the context, attending to these same fundamental needs can be extrapolated and applied to learners across a range of environments beyond the virtual.

Higher metastasis and death rates in cutaneous squamous cell carcinomas with lymphovascular invasion.

BACKGROUND: Lymphovascular invasion (LVI) is an aggressive histologic finding but is excluded from current staging systems due to its lack of demonstrated independent prognostic significance. OBJECTIVE: To evaluate the impact of LVI on cutaneous squamous cell carcinoma tumor outcomes. METHODS: In total, 10,707 cutaneous squamous cell carcinoma tumors from a 20-year, retrospective, multicenter cohort were stratified by the presence (LVI+) or absence (LVI-) of LVI. Outcomes (local recurrence, in-transit metastasis, nodal metastasis, disease-specific death) were compared based on low (Brigham and Women's Hospital [BWH] stage T1/T2a) and high (BWH T2b/T3) tumor stages. RESULTS: Of the 10,707 tumors, 78 had LVI. The analysis of low-stage BWH tumors showed the LVI+ group had a significantly higher 5-year cumulative incidence of local recurrence (LVI+: 12.3%; LVI-: 1.1%; P < .01), metastasis (LVI+: 4.2%; LVI-: 0.4%; P < .01), and disease-specific death (LVI+: 16.2%; LVI-: 0.4%; P < .01). The analysis of BWH high-stage tumors showed the LVI+ group maintained a higher 5-year cumulative incidence of metastasis (LVI+: 28.5%; LVI-: 16.8%; P = .06) and disease-specific death (LVI+: 25.3%; LVI-: 13.9%; P = .03), however, there was no difference in local recurrence (LVI+: 16.3%; LVI-: 15.8%; P = .11). LIMITATIONS: Retrospective study design. CONCLUSION: LVI+ cutaneous squamous cell carcinomas have higher rates of metastasis and death at 5 years. Future staging systems should consider incorporating LVI.

Gender differences in dermatologist practice locations in the United States: A cross-sectional analysis of current gender gaps.

BACKGROUND: The percentage of female dermatologists has increased from 6.9% in 1970 to 48.9% in 2017. Despite the changing gender composition of the dermatologist workforce, it is unknown whether there are gender-based differences in dermatology practice locations. OBJECTIVE: This study aimed to characterize gender-based differences in dermatology practice locations across the United States. METHODS: A cross-sectional study of all dermatologists in the 2020 Centers for Medicare and Medicaid Services Physician Compare Database was performed. The number of self-identified female dermatologists and total dermatologists in each county and state was tabulated, and Spearman's correlation coefficients between county-level demographic and socioeconomic characteristics and female practices were calculated. RESULTS: Among 11,911 dermatologists, 5945 (49.9%) self-identified as female and 5966 (50.1%) as male. Of the 1052 counties with a dermatologist, 291 (27.7%) had no female dermatologist and 149 (14.2%) had no male dermatologist. The percentage of female dermatologists in each state ranged from 18.4% to 62.2%. Female dermatologists practiced more in areas with a higher percentage of democratic voters (r = +0.22) and higher median household income (r = +0.18), and less in rural counties (r = -0.18) or counties with higher uninsured rates (r = -0.11). CONCLUSION: Female dermatologists remain significantly underrepresented in some regions in the United States, particularly in the Mountain states and rural counties. As women continue entering the dermatologist workforce, these results can inform workforce planning strategies to improve the distribution and accessibility of dermatologists across the United States.

Continuing patient care to underserved communities and medical education during the COVID-19 pandemic through a teledermatology student-run clinic.

A virtual pediatric dermatology student-run clinic was initiated during the COVID-19 pandemic, when in-person educational opportunities were limited. The clinic's aim is to provide high-quality dermatologic care to a diverse, underserved pediatric patient population while teaching trainees how to diagnose and manage common skin conditions. In our initial eight sessions, we served 37 patients, predominantly those with skin of color, and had a low no-show rate of 9.8%. This report describes the general structure of the clinic, goals, and the patient population to provide an overview of our educational model for those interested in similar efforts.

Demographic and medical school characteristics associated with urban versus rural dermatology practice: A national cross-sectional study.

There are significant disparities in access to dermatologists in rural areas relative to urban areas. We examined the associations between demographic and medical school characteristics and entry into dermatology practice in urban versus rural counties. All dermatologists who graduated from U.S. allopathic or osteopathic medical schools in the 2020 Centers for Medicare & Medicaid Services Physician Compare Database were assessed. Dermatology practice locations were coded as metropolitan or non-metropolitan according to the Rural-Urban Continuum Codes. Of 10,076 dermatologists, 543 (5.4%) practiced in non-metropolitan counties. Male gender (odds ratio [OR] 1.48, 95% CI 1.23-1.77), public medical school attendance (OR 1.94, 95% CI 1.61-2.34), DO degree (OR 1.84, 95% CI 1.32-2.51), medical school location in a non-metropolitan county (OR 5.41, 95% CI 3.66-7.84), and medical school rural track program (OR 1.57, 95% CI 1.07-2.26) were associated with higher odds of non-metropolitan dermatology practice. Our findings highlight that male gender, graduation from a non-metropolitan or public medical school, DO degree, and rural tracks are associated with higher likelihood of non-metropolitan dermatology practice. These results can inform efforts within the field of dermatology to strengthen the rural dermatologist workforce and suggest that rural educational experiences during medical school may increase recruitment of rural dermatologists.

The geographic distribution of the US pediatric dermatologist workforce: A national cross-sectional study.

BACKGROUND /OBJECTIVES: Although 82% of pediatricians report that their patients have difficulty accessing pediatric dermatologists, the regions with greatest need for the specialty are not well-defined. We aimed to determine the geographic distribution of pediatric dermatologists relative to the number of children and pediatric generalists. METHODS: We performed a cross-sectional study of all US board-certified pediatric dermatologists, generalists (defined as pediatricians and family medicine physicians), and children in 2020. Data were obtained from the Society for Pediatric Dermatology, American Board of Pediatrics, Centers for Medicare and Medicaid, and US Census Bureau. Number of children, pediatric dermatologists, and pediatric generalists were tabulated in each county and state, and the distributions of pediatric dermatologists and generalists relative to the population of children were quantified with the Gini coefficient. RESULTS: Of 317 pediatric dermatologists, 243 (76.7%) were women and 311 (98.1%) worked in a metropolitan county. A pediatric dermatologist was present in 41/50 (82%) states and 142/3228 (4.4%) counties. Not a single pediatric dermatologist was found in 54/92 (58.7%) counties with 100 000-199 999 children, 15/53 (28.3%) counties with 200 000-499 999 children, and 4/13 (30.8%) counties with ≥500 000 children. The Gini coefficient for the state-level distribution of pediatric dermatologists relative to population of children was 0.488 compared to 0.132 for that of pediatric generalists. CONCLUSION: There is a maldistribution of pediatric dermatologists, resulting in children with unmet dermatologic needs in nine states and 96 heavily populated counties. These results can inform initiatives to recruit pediatric dermatologists and to expand telehealth access to specific high-density areas.

Genetic and environmental factors underlying keratinocyte carcinoma risk.

Recent large-scale GWAS and large epidemiologic studies have accelerated the discovery of genes and environmental factors that contribute to the risk of keratinocyte carcinoma (KC), which includes basal cell carcinoma (BCC) and squamous cell carcinoma (SCC). This Review summarizes the genomic regions associated with SCC and BCC risk, examines the genetic overlap between SCC and BCC, and discusses biological pathways involved in SCC and BCC development. Next, we review environmental factors that are associated with KC risk, including those that are shared between SCC and BCC as well as others that associated with only one type of KC. We conclude with a critical appraisal of current research and potential directions for future research.

Using Implementation Science to Optimize the Uptake of Evidence-Based Medicine into Dermatology Practice.

An estimated 17-year lag exists between evidence generation and its integration into routine clinical care. The field of implementation science has emerged to close this gap by applying rigorous methods to systematically study the obstacles and facilitators of the uptake of evidence-based practices. However, implementation science has not gained wide traction in dermatology. In this narrative review, we use literature and expert input to introduce implementation science and key frameworks for implementing interventions and evaluating their uptake. We then highlight opportunities for dermatology-specific interventions at the patient-, provider-, system-, and population-levels, and advocate for the field's expansion into dermatology.

Research Techniques Made Simple: Interpreting Measures of Association in Clinical Research.

To bring evidence-based improvements in medicine and health care delivery to clinical practice, health care providers must know how to interpret clinical research findings and critically evaluate the strength of evidence. This requires an understanding of differences in clinical study designs and the various statistical methods used to identify associations. We aim to provide a foundation for understanding the common measures of association used in epidemiologic studies to quantify relationships between exposures and outcomes, including relative risks, odds ratios, and hazard ratios. We also provide a framework for critically assessing clinical research findings and highlight specific methodologic concerns.

Potential Impact of Initial Clinical Data on Adjustment of Pediatric Readmission Rates.

OBJECTIVE: Comparison of readmission rates requires adjustment for case-mix (ie, differences in patient populations), but previously only claims data were available for this purpose. We examined whether incorporation of relatively readily available clinical data improves prediction of pediatric readmissions and thus might enhance case-mix adjustment. METHODS: We examined 30-day readmissions using claims and electronic health record data for patients ≤18 years and 29 days of age who were admitted to 3 children's hospitals from February 2011 to February 2014. Using the Pediatric All-Condition Readmission Measure and starting with a model including age, gender, chronic conditions, and primary diagnosis, we examined whether the addition of initial vital sign and laboratory data improved model performance. We employed machine learning to evaluate the same variables, using the L2-regularized logistic regression with cost-sensitive learning and convolutional neural network. RESULTS: Controlling for the core model variables, low red blood cell count and mean corpuscular hemoglobin concentration and high red cell distribution width were associated with greater readmission risk, as were certain interactions between laboratory and chronic condition variables. However, the C-statistic (0.722 vs 0.713) and McFadden's pseudo R2 (0.085 vs 0.076) for this and the core model were similar, suggesting minimal improvement in performance. In machine learning analyses, the F-measure (harmonic mean of sensitivity and positive predictive value) was similar for the best-performing model (containing all variables) and core model (0.250 vs 0.243). CONCLUSIONS: Readily available clinical variables do not meaningfully improve the prediction of pediatric readmissions and would be unlikely to enhance case-mix adjustment unless their distributions varied widely across hospitals.