Faculty Bibliography

BACKGROUND:Satellitosis or in-transit metastasis (S-ITM) from cutaneous squamous cell carcinoma (cSCC) is associated with poor outcomes but is not included in current staging guidelines. OBJECTIVE:To determine risk factors and prognostic significance of S-ITM. METHODS:This cohort study included 8,901 patients with cSCC from 12 institutions (1998-2023). Risk factors for S-ITM were calculated using logistic regression. Outcomes were compared with 1:2 propensity score matched controls using a Fine-Gray subdistribution hazard model. RESULTS:Seventy-seven patients developed S-ITM. Increased patient age (OR 1.03, 95% CI 1.01-1.05, p<0.01), history of immunosuppression (OR 4.31, 95% CI 2.59-7.10, p<0.001), higher BWH stage (T2a OR 4.14, 95% CI 2.05-8.41; T2b OR 15.96, 95% CI 8.58-31.19; T3 OR 30.27, 95% CI 10.70-79.04, all p<0.001) and LVI (OR 4.57, 95% CI 1.80-10.38, p=0.001) were independent risk factors for S-ITM. S-ITM was associated with LR (SHR 2.40, 95% CI 1.43-4.04, p<0.001), NM (SHR 1.89 (95% CI .02-3.49, p=0.04), DM (SHR 4.41, 95% CI 1.45-13.27, p=0.01), and DSD (SHR 4.48, 95% CI 2.34-8.58, p<0.001). LIMITATIONS/CONCLUSIONS:Retrospective cohort study. The rarity of S-ITM may limit statistical power. CONCLUSION/CONCLUSIONS:Patients with cSCC and S-ITM are at higher risk for poor outcomes independent of patient, tumor, and treatment characteristics.

IMPORTANCE/UNASSIGNED:There exists substantial heterogeneity in outcomes within T stages for patients with cutaneous squamous cell carcinoma (cSCC). OBJECTIVE/UNASSIGNED:To determine whether a customized generative pretrained transformer model, trained on a comprehensive dataset with more than 1 trillion parameters and equipped with relevant focused context and retrieval augmented generation (RAG), could excel in aggregating and interpreting vast quantities of data to develop a novel class-based risk stratification system that outperforms the current standards. DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:To build the RAG knowledge base, a systematic review of the literature was conducted that addressed risk factors for poor outcomes in cSCC. Using the RAG-enabled generative pretrained transformer (GPT) model, we developed a novel class-based risk stratification system that assigned point values for risk factors, culminating in a GPT-based prognostication system called the artificial intelligence-derived risk score (AIRIS). The system's performance was validated on a combined prospective and retrospective cohort of 2379 primary cSCC tumors (1996-2023) with at least 36 months of follow-up, against Brigham and Women's Hospital (BWH) and American Joint Committee on Cancer Staging Manual, eighth edition (AJCC8) systems in stratifying risk for locoregional recurrence (LR), nodal metastasis (NM), distant metastasis (DM), and disease-specific death (DSD). MAIN OUTCOMES AND MEASURES/UNASSIGNED:Performance metrics evaluated included distinctiveness, homogeneity, and monotonicity, as defined by the AJCC8, as well as sensitivity, specificity, positive predictive value, negative predictive value, accuracy, the area under the receiver operating characteristic curve, and concordance. RESULTS/UNASSIGNED:The median age at diagnosis was 73 (IQR, 64-81) years, with 38.5% female patients and 61.5% male patients. The AIRIS prognostication system demonstrated superior sensitivity across all outcomes (LR, 49.1%; NM, 73.7%; DM, 82.5%; and DSD, 72.2%) and the highest area under the receiver operating characteristic curve values (LR, 0.69; NM, 0.81; DM, 0.85; and DSD, 0.80), indicating significantly enhanced discriminative capability compared with the BWH and AJCC8 systems. While all systems were comparably distinctive, the AIRIS prognostication system consistently demonstrated the lowest proportion of tumors exhibiting poor outcomes in low-risk categories, suggesting its improved homogeneity and monotonicity. CONCLUSIONS AND RELEVANCE/UNASSIGNED:The results of this diagnostic study suggest that the AIRIS system outperforms the existing BWH and AJCC8 prognostication systems, potentially providing a more effective tool for predicting poor outcomes in cSCC. This study illustrates the potential of large language models in refining prognostic tools, offering implications for treating patients with cancer.

BACKGROUND:Minimally invasive cosmetic dermatology procedures continue to be increasingly popular; however, the extant literature has poorly documented the psychological antecedents of interest in cosmetic procedures and their psychological consequences. OBJECTIVE:To better inform dermatologists on their patients' motivations for cosmetic enhancement. MATERIALS AND METHODS/METHODS:In a general population survey, an online representative sample of 984 Americans reported the extent to which they feel authentic using the validated authenticity scale and whether they were interested in undergoing a cosmetic procedure. In a prospective dermatology office survey, 102 participants reported their feelings of authenticity immediately before and 2 weeks after receiving a minimally invasive injectable cosmetic procedure. RESULTS:In the general population survey, participants interested in cosmetic procedures felt significantly less authentic than participants who were not interested ( p = .003). In the prospective dermatology office survey, participants felt significantly more authentic 2 weeks after their minimally invasive injectable cosmetic procedure than before ( p = .018). CONCLUSION/CONCLUSIONS:Lower feelings of authenticity are associated with interest in cosmetic procedures. Participants felt more authentic 2 weeks after receiving a minimally invasive injectable cosmetic procedure. Cosmetic procedures may present patients with an opportunity to feel more like their real, genuine selves.

There is a paucity of information on racial and ethnic disparities relating to barriers to care in healthcare access and utilization in patients with cutaneous malignancies. We conducted a cross-sectional analysis of adults with melanoma, basal cell carcinoma (BCC) and cutaneous squamous cell carcinoma (cSCC) in the National Institutes of Health (NIH) All of Us Research Program collected between May 2018 and July 2022. Participants included adults (aged 18 or older) with cutaneous malignancy who completed the Health Care Access and Utilization survey. We identified 5,817 adults who were diagnosed with BCC (67%), cSCC (28.9%), and melanoma (23.9%). Non-Hispanic Black (NHB) and Hispanic patients were more likely than non-Hispanic White (NHW) patients to delay a primary care visit due to cost (p = 0.005 and p = 0.015, respectively). NHB patients were also more likely to delay care due to lack of transportation (p < 0.001). NHB and Hispanic patients were more likely to place importance on seeing a provider from the same background (NHB p < 0.002; Hispanic p = 0.002) and also were more likely to report never being able to see such a provider (NHB p < 0.001; Hispanic p = 0.002). Medicaid/Medicare patients, non-college graduates, and those with lower incomes also faced increased barriers to care, including delays due to cost and transportation issues. People of color with cutaneous malignancies are more likely to delay care in seeing primary care providers due to cost or transportation issues. This study provides important insights on disproportionate healthcare usage among racial/ethnic groups that may help mitigate healthcare disparities.