Background - Social media has become a major source of communication in medicine. We aimed to understand the relationship between physicians' social media influence and their scholarly and clinical activity. Methods - We identified attending, US electrophysiologists on Twitter. We compared physician Twitter activity to (a) scholarly publication record (h-index) and (b) clinical volume according to CMS. The ratio of observed vs. expected Twitter followers (obs/exp) was calculated based on each scholarly (K-index) and clinical activity. Results - We identified 284 physicians, with mean Twitter age of 5.0 (SD 3.1) years and median 568 followers (25 th , 75 th : 195, 1146). They had a median 34.5 peer-reviewed papers (25 th , 75 th : 14, 105), 401 citations (25 th , 75 th : 102, 1677), and h-index 9 (25 th , 75 th : 4, 19.8). The median K-index was 0.4 (25 th , 75 th : 0.15, 1.0), ranging 0.0008 - 29.2. The median EP procedures was 77 (25 th , 75 th : 0, 160) and E&M visits 264 (25 th , 75 th : 59, 516) in 2017. The top 1% electrophysiologists for followers accounted for 20% of all followers, 17% of status updates, had a mean h-index of 6 (vs. 15 for others, p=0.3), and accounted for 1% of procedural and E&M volumes. They had a mean K-index of 21 (vs. 0.77 for others, p<0.0001), and clinical obs/exp follower ratio of 17.9 and 18.1 for procedures and E&M (p<0.001 each, vs. others [0.81 for each]). Conclusions - Electrophysiologists are active on Twitter, with modest influence often representative of scholarly and clinical activity. However, the most influential physicians appear to have relatively modest scholarly and clinical activity.

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Clinical trial outcome comparison methodology can affect trial efficiency and interpretation. Our goal was to describe current trends in clinical trial outcome comparison methods among high-impact dermatology trials and perform simulations comparing direct comparison (DC), change-score based (CS), and baseline-adjusted analyses (BAA) to demonstrate the more subtle differences in these methods. We performed a cross-sectional examination of top-cited dermatology clinical trials over five years. Trials were retrieved from journal websites and extracted from PubMed. All clinical trials published in The Journal of the American Academy of Dermatology (JAAD), JAMA Dermatology, Journal of Investigative Dermatology (JID), The British Journal of Dermatology (BJD), and The Journal of the European Academy of Dermatology and Venereology (JEADV) from 2015–2019. Clinical trial analysis type including DC, CS, BAA, percent change from baseline (PoB), and responder analysis (RA). We evaluated the proportion of trials reporting each endpoint were reported and simulations assessing impact of analysis type on outcomes. Among 252 eligible trials, outcome comparison techniques included DC (75/252), CS (40/252), PoB (36/252), RA (98/252), and BAA (3/252). Among trials using CS, PoB, or RA, 25/174 adjusted for baseline score. No trials discussed relationship between baseline and final values; 85/252 selected patients based on baseline score; 8/85 gathered a post-randomization baseline score; 20/85 used a pre-randomization run-in period. Simulations demonstrated that BAA maximized trial efficiency for continuous outcomes. CS, PoB, and RA were common; however, when trials have continuous or ordinal outcomes, BAA is most efficient. PoB and RA are particularly inefficient. RA can promote misleading inference. Use of BAA optimizes inference, trial efficiency, and resource utilization.

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Biologic therapy is associated with better outcomes for moderate to severe psoriasis compared to systemic or topical therapies. Do prescription patterns in a national expenditure database identify gaps in financial assistance and equity in optimal care delivery? To determine the degree to which adults below the federal poverty level (FPL) are prescribed biologics, we performed a retrospective cross-sectional study using pooled data from the Medical Expenditure Panel Survey (MEPS). A prescription was defined by a biologic Multum Lexicon code linked to a psoriasis ICD code. Demographics and biologic prescriptions were compared between psoriasis patients below versus at or above the FPL using weighted-subject designs. We identified 1,437,792 yearly-weighted patients with active psoriasis (1,356 total unweighted) between 2007 and 2018, of whom 123,392 were below the FPL (166 total unweighted). Psoriasis patients below the FPL were less likely to be prescribed biologics for psoriasis than psoriasis patients at or above the FPL (5% vs 12%, p¼0.01). In addition, they were more likely to be black (p¼0.02), be formerly or never married (p<0.001), have public or no insurance (p<0.001), have no degree (p¼0.02), and self-report poor/fair physical or mental health (p<0.001). Finally, psoriasis patients below the FPL taking biologics had lower median biologic medication expenditures per person than psoriasis patients at or above the FPL taking biologics ($6,511 vs. $12,152, p¼0.003). Biologics are not prescribed equally among all socioeconomic cohorts, notably across racial and socioeconomic strata such as black patients and patients with no degree. Further studies are needed to identify the financial assistance programs that best address the persistent hurdles to equity in the delivery of holistic care in the United States.