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Despite therapeutic advances, a 13% two-year recurrence rate persists, with about 30% of recurrences presenting as distant metastases. Because screening test selection and imaging accuracy vary widely, the study evaluates differential scanning calorimetry (DSC) thermogram parameters for diagnostic and prognostic stratification. Regression and Cox modeling show DSC features—especially PC3—can separate controls from melanoma and predict overall survival in active disease.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/plasma-thermogram-parameters-differentiate-status-and-overall-survival-of-melanoma-patients/381373/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/plasma-thermogram-parameters-differentiate-status-and-overall-survival-of-melanoma-patients/381373.png","ImageObject",300,407,{"name":92,"@type":93},"Maya Linwood","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-09-27","2026-09-24",true,{"@type":102,"interactionType":103,"userInteractionCount":14},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"Why is identifying high-risk melanoma patients important in the study?","Question",{"text":112,"@type":113},"The study targets the need to recognize patients at high risk for recurrence or advanced disease to improve clinical decision-making. 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Nguyen 1,†,‡, Gabriela Schneider 1,‡, Alagammai Kaliappan 1, Robert Buscaglia 2, Guy N. Brock 3, Melissa Barousse Hall 1, Donald M. Miller 1, Jason A. Chesney 1 and Nichola C. Garbett 1, *  \nCitation: Nguyen, T.Q.; Schneider, G.; Kaliappan, A.; Buscaglia, R.; Brock, G.N.; Hall, M.B.; Miller, D.M.; Chesney, J.A.; Garbett, N.C. Plasma Thermogram Parameters Differentiate Status and Overall Survival of Melanoma Patients. Curr. Oncol. 2023, 30, 6079–6096. [https://](https://)[ ](https://)[doi.org/10.3390/curroncol30070453](doi.org/10.3390/curroncol30070453)  \nReceived: 21 March 2023  \nRevised: 31 May 2023  \nAccepted: 21 June 2023  \nPublished: 24 June 2023  \nCopyright: © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([https://](https://)[ ](https://)[creativecommons.org/licenses/by/](creativecommons.org/licenses/by/)[ ](creativecommons.org/licenses/by/)[4.0/](4.0/)) .  \n1 UofL Health–Brown Cancer Center and Division of Medical Oncology and Hematology, Department of Medicine, University of Louisville, Louisville, KY 40202, USA  \n2 Department of Mathematics and Statistics, Northern Arizona University, Flagstaff, AZ 86011, USA  \n3 Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH 43210, USA  \n* [Correspondence: nichola.garbett@louisville.edu](Correspondence: nichola.garbett@louisville.edu)  \n† Current address: Department of Medicine, University of Kentucky, Lexington, KY 40506, USA.  \n‡ These authors contributed equally to this work.  \nAbstract: Melanoma is the fifth most common cancer in the United States and the deadliest of all skin cancers. Even with recent advancements in treatment, there is still a 13% two-year recurrence rate, with approximately 30% of recurrences being distant metastases. Identifying patients at high risk for recurrence or advanced disease is critical for optimal clinical decision-making. Currently, there is substantial variability in the selection of screening tests and imaging, with most modalities characterized by relatively low accuracy. In the current study, we built upon a preliminary examination of differential scanning calorimetry (DSC) in the melanoma setting to examine its utility for diagnostic and prognostic assessment. Using regression analysis, we found that selected DSC profile (thermogram) parameters were useful for differentiation between melanoma patients and healthy controls, with more complex models distinguishing melanoma patients with no evidence of disease from patients with active disease. Thermogram features contributing to the third principal component (PC3) were useful for differentiation between controls and melanoma patients, and Cox proportional hazards regression analysis indicated that PC3 was useful for predicting the overall survival of active melanoma patients. With the further development and optimization of the classification method, DSC could complement current diagnostic strategies to improve screening, diagnosis, and prognosis of melanoma patients.  \nKeywords: differential scanning calorimetry (DSC); thermogram; melanoma; diagnosis; overall survival (OS); no evidence of disease (NED)  \n1. Introduction  \nStaging and recurrence risk is heavily dependent on the initial presentation of melanoma (i.e., tumor thickness, distant metastasis, lymph node involvement) . The American Joint Committee on Cancer (AJCC) and National Comprehensive Cancer Network (NCCN) guidelines provide a framework in which linear clinical decision-making can be performed. Yet, there is discrepancy within each stage, and there is substantial variability in the timing and selection of follow-up laboratory tests and imaging [1,2] . Dinnes et al. conducted a meta-analysis on imaging studies for prognosticatio","cbCaifAvXvPHycyT","https://ap.wps.com/l/cbCaifAvXvPHycyT","pdf",2114516,18,"English","# Abstract\n# Keywords\n# 1. Introduction\n# Staging, recurrence risk, and imaging variability\n# Biomarkers and genomic techniques for melanoma","[{\"question\":\"Why is identifying high-risk melanoma patients important in the study?\",\"answer\":\"The study targets the need to recognize patients at high risk for recurrence or advanced disease to improve clinical decision-making. Variability and limited accuracy in current screening tests motivate better diagnostic and prognostic tools.\"},{\"question\":\"What role do DSC thermogram parameters play in differentiating melanoma status?\",\"answer\":\"Using regression analysis, the study finds selected DSC (thermogram) parameters can distinguish melanoma patients from healthy controls. More complex models further separate melanoma patients with no evidence of disease from those with active disease.\"},{\"question\":\"How does the study evaluate overall survival prediction?\",\"answer\":\"The researchers apply Cox proportional hazards regression and identify PC3-related thermogram features as useful for predicting overall survival among patients with active melanoma.\"}]","Plasma Thermogram Parameters Differentiate Status and Overall Survival of Melanoma Patients | PDF",1790245055,45]