Anthony J. Scholer

Background and Objectives: Clinical nomograms have been developed to predict sentinel lymph node (SLN) status in early‐stage melanoma patients, but the clinical utility of these tools remains debatable. We created and validated a nomogram using data from a randomized clinical trial and assessed its accuracy against the well‐validated Melanoma Institute Australia (MIA) nomogram. Methods: We developed our model to predict SLN status using logistic regression on clinicopathological patient data from the Multicenter Selective Lymphadenectomy Trial‐I. The model was externally validated using the National Cancer Database (NCDB) data set, and its performance was compared to that of the MIA nomogram. Results: Our model had good discrimination between positive and negative SLNs, with a training set area under the curve (AUC) of 0.706 (0.661–0.751). Our model achieved an AUC of 0.715 (0.706–0.724) compared to 0.723 (0.715–0.731) with the MIA model, using the NCDB set. Conclusion: Our model performed similarly to the MIA model, confirming that despite using different clinical features and data sets, no clinical nomogram is currently accurate enough for clinical use.

Taxonomy of hepatobiliary cancer (HBC) categorizes tumors by location or histopathology (tissue of origin, TO). Tumors originating from different TOs can also be grouped by overlapping genomic alterations (GA) into molecular subtypes (MS). The aim of this study was to create novel HBC MSs. Next-generation sequencing (NGS) data from the AACR-GENIE database were used to examine the genomic landscape of HBCs. Machine learning and gene enrichment analysis identified MSs and their oncogenomic pathways. Descriptive statistics were used to compare subtypes and their associations with clinical and molecular variables. Integrative analyses generated three MSs with different oncogenomic pathways independent of TO (n = 324; p < 0.05). HC-1 “hyper-mutated-proliferative state” MS had rapidly dividing cells susceptible to chemotherapy; HC-2 “adaptive stem cell-cellular senescence” MS had epigenomic alterations to evade immune system and treatment-resistant mechanisms; HC-3 “metabolic-stress pathway” MS had metabolic alterations. The discovery of HBC MSs is the initial step in cancer taxonomy evolution and the incorporation of genomic profiling into the TNM system. The goal is the development of a precision oncology machine learning algorithm to guide treatment planning and improve HBC outcomes. Future studies should validate findings of this study, incorporate clinical outcomes, and compare the MS classification to the AJCC 8th staging system.

Background and Objectives: Melanoma mutational burden is high and approximately 50% have oncogenic mutations inBRAF. We sought to evaluate age‐related mutational differences in melanoma.Methods: We analyzed melanoma samples in the Genomics Evidence Neoplasia Information Exchange database. Targetable mutations were identified using the Precision Oncology Knowledge Base (OncoKB).Results: We found 1194 patients with a common set of 30 genes. The top mutated genes in patients n = 98) wereBRAF(59%),TP53(31%),NRAS(17%), andPTEN(14%); in 40–59 y/o (n = 354) wereBRAF(51%),NRAS(30%),TP53(26%), andAPC(13%); and in ≥60 y/o (n = 742) wereBRAF(38%),NRAS(33%),TP53(26%), andKDR(19%).BRAFmutations were almost mutually exclusive fromNRASmutations in p < 0.0001). There were 10 targetable mutations meeting OncoKB criteria for melanoma:BRAF(level 1),RET(level 1),KIT(level 2),NRAS(level 3A),TP53(level 3A), andFGFR2,MET,PTEN,PIK3CA, andKRAS(level 4).Conclusions: Mutations in melanoma have age‐related differences and demonstrates potential targetable mutations for personalized therapies.

Background and Objectives: Selecting frail elderly patients with pancreatic cancer (PC) for pancreas resection using biologic age has not been elucidated. This study determined the feasibility of the deficit accumulation frailty index (DAFI) in identifying such patients and its association with surgical outcomes.Methods: The DAFI, which assesses frailty based on biologic age, was used to identify frail patients using clinical and health‐related quality‐of‐life data. The characteristics of frail and nonfrail patients were compared.Results: Of 242 patients (median age, 75.5 years), 61.2% were frail and 32.6% had undergone pancreas resection (surgery group). Median overall survival (mOS) decreased in frail patients (7.13 months, 95% confidence interval [CI]: 5.65–10.1) compared with nonfrail patients (16.1 months, 95% CI: 11.47–34.40, p = 0.001). In the surgery group, mOS improved in the nonfrail patients (49.4%; 49.2 months, 95% CI: 29.3–79.9) compared with frail patients (50.6%, 22.1 months, 95% CI: 18.3–52.4, p = 0.10). In the no‐surgery group, mOS was better in nonfrail patients (54%; 10.81 months, CI 7.85–16.03) compared with frail patients (66%; 5.45 months, 95% CI: 4.34–7.03, p = 0.02).Conclusions: The DAFI identified elderly patients with PC at risk of poor outcomes and can identify patients who can tolerate more aggressive treatments.

Background: Given the survival advantage of neoadjuvant treatment for locally advanced esophageal cancer, accurate clinical staging is necessary. The aim of this study was to assess the clinical (c) and pathologic (p) staging concordance rates for presumably early stage esophageal adenocarcinoma patients that had upfront esophagectomy (UFE) and evaluate if survival (OS) was negatively affected by inaccurate preoperative staging and subsequent treatment selection.Methods: An NCDB retrospective review of nonmetastatic esophageal adenocarcinoma patients that had UFE. The rates of concordance between c and p staging system and OS were calculated.Results: Of 2775 patients, most patients presented with cN0 (82.8%) and cT1 tumors (53.6%). The overall concordance between c and p staging was 78.8% for T‐classification (moderate agreement; weighted κ = 0.729; P < .001) and 78.8% for N‐classification (weak agreement; weighted κ = 0.448; P < .001). Patients that were upstaged due to a lack of concordance between T‐classification had decreased 5‐ and 10‐year OS (30% and 16%, P < .001) and those upstaged due to discordant N‐classification had decreased 5‐ and 10‐year OS (28% and 23%, P < .001).”Conclusions: Preoperative staging of esophageal adenocarcinoma has moderate reliability and accuracy for predicting pT and pN classification. Up to 25% of patients have discordant clinical and pathological staging, which impacts OS.