Faculty Bibliography

BACKGROUND:Solid organ transplant recipients (SOTRs) face frequent advanced cutaneous malignancies, yet data guiding systemic therapy are limited. MATERIALS AND METHODS/METHODS:We conducted a Preferred Reporting Items for Systematic Reviews and Meta-Analyses systematic review of immune checkpoint inhibitors (ICIs), talimogene laherparepvec (T-VEC), and Sonic Hedgehog Pathway Inhibitors (HPIs) for locally advanced or metastatic cutaneous squamous cell carcinoma, melanoma, Merkel cell carcinoma, and basal cell carcinoma in SOTRs, including a novel case from our institution. Outcomes included tumor response, graft rejection, and graft failure. RESULTS:Among 196 SOTRs treated with ICIs (101 cutaneous squamous cell carcinoma, 83 melanoma, 12 Merkel cell carcinoma), the overall response rate (ORR) was 39.3%, and lack of progression occurred in 58.0%. Graft rejection occurred in 36.9% and graft failure in 22.3%. A higher number of baseline immunosuppressive agents decreased odds of rejection (OR 0.55) and failure (OR 0.38). Tacrolimus was associated with reduced tumor response (OR 0.41), whereas mTOR-based regimens and cemiplimab were associated with fewer transplant rejection. T-VEC was reported in 10 SOTRs with an ORR of 90% and no graft rejection or failure. HPIs in six SOTRs with basal cell carcinoma demonstrated ORR of 83% without graft loss. CONCLUSION/CONCLUSIONS:ICIs provide antitumor activity but substantial graft-related risk, while T-VEC and HPIs show high response rates with no reported rejection.

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.

Primary cutaneous squamous cell carcinoma (cSCC) is responsible for ~10,000 deaths annually in the United States. Stratification of risk of poor outcome at initial biopsy would significantly impact clinical decision-making during the initial post operative period where intervention has been shown to be most effective. Using whole-slide images (WSI) from 163 patients from 3 institutions, we developed a self supervised deep-learning model to predict poor outcomes in cSCC patients from histopathological features at initial diagnosis, and validated it using WSI from 563 patients, collected from two other academic institutions. For disease-free survival prediction, the model attained a concordance index of 0.73 in the development cohort and 0.84 in the Mayo cohort. The model's interpretability revealed that features like poor differentiation and deep invasion were strongly associated with poor prognosis. Furthermore, the model is effective in stratifying risk among BWH T2a and AJCC T2, known for outcome heterogeneity.

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.

IMPORTANCE/UNASSIGNED:Cutaneous squamous cell carcinoma (CSCC) is the second most common malignant disease in the US. Although it typically carries a good prognosis, a subset of CSCCs are highly aggressive, carrying regional and distant metastatic potential. Due to its high incidence, this aggressive subset is responsible for considerable mortality, with an overall annual mortality estimated to equal or even surpass melanoma. Despite this morbidity, CSCC is excluded from national cancer registries, making it difficult to study its epidemiology and outcomes. Therefore, the bulk of the CSCC literature is composed of single-center and multi-institutional retrospective cohort analyses. Given variations in reporting measures and analyses in these studies, interpretability between studies and the ability to pool results are limited. OBJECTIVE/UNASSIGNED:To define standardized reporting measures for retrospective CSCC studies. FINDINGS/UNASSIGNED:An expert panel was convened to determine standardized guidelines for recording and analyzing retrospective CSCC data. A total of 13 dermatologists and dermatologic surgeons with more than 5 years of posttraining experience and considerable experience with performing CSCC outcomes research were recruited to the panel. Consensus recommendations were achieved for CSCC retrospective study reporting measures, definitions, and analyses. CONCLUSIONS AND RELEVANCE/UNASSIGNED:The recommendations in this report present the potential to standardize future CSCC retrospective studies. With such standardization, future work may have greater interstudy interpretability and allow for pooled analyses.