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      Prediction of pCR based on clinical-radiomic model in patients with locally advanced ESCC treated with neoadjuvant immunotherapy plus chemoradiotherapy

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          Abstract

          Background

          The primary objective of this research is to devise a model to predict the pathologic complete response in esophageal squamous cell carcinoma (ESCC) patients undergoing neoadjuvant immunotherapy combined with chemoradiotherapy (nICRT).

          Methods

          We retrospectively analyzed data from 60 ESCC patients who received nICRT between 2019 and 2023. These patients were divided into two cohorts: pCR-group (N = 28) and non-pCR group (N = 32). Radiomic features, discerned from the primary tumor region across plain, arterial, and venous phases of CT, and pertinent laboratory data were documented at two intervals: pre-treatment and preoperation. Concurrently, related clinical data was amassed. Feature selection was facilitated using the Extreme Gradient Boosting (XGBoost) algorithm, with model validation conducted via fivefold cross-validation. The model’s discriminating capability was evaluated using the area under the receiver operating characteristic curve (AUC). Additionally, the clinical applicability of the clinical-radiomic model was appraised through decision curve analysis (DCA).

          Results

          The clinical-radiomic model incorporated seven significant markers: postHALP, ΔHB, post-ALB, firstorder_Skewness, GLCM_DifferenceAverage, GLCM_JointEntropy, GLDM_DependenceEntropy, and NGTDM_Complexity, to predict pCR. The XGBoost algorithm rendered an accuracy of 0.87 and an AUC of 0.84. Notably, the joint omics approach superseded the performance of solely radiomic or clinical model. The DCA further cemented the robust clinical utility of our clinical-radiomic model.

          Conclusion

          This study successfully formulated and validated a union omics methodology for anticipating the therapeutic outcomes of nICRT followed by radical surgical resection. Such insights are invaluable for clinicians in identifying potential nICRT responders among ESCC patients and tailoring optimal individualized treatment plans.

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          Most cited references50

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          Cancer statistics, 2022

          Each year, the American Cancer Society estimates the numbers of new cancer cases and deaths in the United States and compiles the most recent data on population-based cancer occurrence and outcomes. Incidence data (through 2018) were collected by the Surveillance, Epidemiology, and End Results program; the National Program of Cancer Registries; and the North American Association of Central Cancer Registries. Mortality data (through 2019) were collected by the National Center for Health Statistics. In 2022, 1,918,030 new cancer cases and 609,360 cancer deaths are projected to occur in the United States, including approximately 350 deaths per day from lung cancer, the leading cause of cancer death. Incidence during 2014 through 2018 continued a slow increase for female breast cancer (by 0.5% annually) and remained stable for prostate cancer, despite a 4% to 6% annual increase for advanced disease since 2011. Consequently, the proportion of prostate cancer diagnosed at a distant stage increased from 3.9% to 8.2% over the past decade. In contrast, lung cancer incidence continued to decline steeply for advanced disease while rates for localized-stage increased suddenly by 4.5% annually, contributing to gains both in the proportion of localized-stage diagnoses (from 17% in 2004 to 28% in 2018) and 3-year relative survival (from 21% to 31%). Mortality patterns reflect incidence trends, with declines accelerating for lung cancer, slowing for breast cancer, and stabilizing for prostate cancer. In summary, progress has stagnated for breast and prostate cancers but strengthened for lung cancer, coinciding with changes in medical practice related to cancer screening and/or treatment. More targeted cancer control interventions and investment in improved early detection and treatment would facilitate reductions in cancer mortality.
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            Radiomics: extracting more information from medical images using advanced feature analysis.

            Solid cancers are spatially and temporally heterogeneous. This limits the use of invasive biopsy based molecular assays but gives huge potential for medical imaging, which has the ability to capture intra-tumoural heterogeneity in a non-invasive way. During the past decades, medical imaging innovations with new hardware, new imaging agents and standardised protocols, allows the field to move towards quantitative imaging. Therefore, also the development of automated and reproducible analysis methodologies to extract more information from image-based features is a requirement. Radiomics--the high-throughput extraction of large amounts of image features from radiographic images--addresses this problem and is one of the approaches that hold great promises but need further validation in multi-centric settings and in the laboratory. Copyright © 2011 Elsevier Ltd. All rights reserved.
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              Epidemiology of Esophageal Squamous Cell Carcinoma.

              Esophageal squamous cell carcinoma (ESCC) accounts for about 90% of the 456,000 incident esophageal cancers each year. Regions of high incidence include Eastern to Central Asia, along the Rift Valley in East Africa, and into South Africa. There are many causes of ESCC, which vary among regions. Early studies in France associated smoking cigarettes and heavy alcohol consumption with high rates of ESCC, but these factors cannot explain the high incidence in other regions. We discuss other risk factors for ESCC, including polycyclic aromatic hydrocarbons from a variety of sources, high-temperature foods, diet, and oral health and the microbiome-all require further research. A growing list of defined genomic regions affects susceptibility, but large genome-wide association studies have been conducted with ethnic Chinese subjects only; more studies are called for in the rest of Asia and Africa. ESCC has been understudied, but growing infrastructure in more high-incidence countries will allow rapid progress in our understanding.
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                Author and article information

                Contributors
                URI : https://loop.frontiersin.org/people/2490456Role: Role: Role: Role: Role: Role: Role:
                URI : https://loop.frontiersin.org/people/1714211Role: Role:
                URI : https://loop.frontiersin.org/people/2647925Role: Role:
                URI : https://loop.frontiersin.org/people/1077848Role: Role: Role: Role:
                Journal
                Front Oncol
                Front Oncol
                Front. Oncol.
                Frontiers in Oncology
                Frontiers Media S.A.
                2234-943X
                20 March 2024
                2024
                : 14
                : 1350914
                Affiliations
                [1] 1 Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Science , Jinan, China
                [2] 2 Department of Radiotherapy, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Science , Jinan, China
                [3] 3 Department of Thoracic Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University , Jinan, China
                Author notes

                Edited by: Jiang Chen, Zhejiang University, China

                Reviewed by: Zhongzheng Xiang, Sichuan University, China

                Yi Mu, ClinChoice Inc., United States

                *Correspondence: Xue Meng, mengxue5409@ 123456163.com
                Article
                10.3389/fonc.2024.1350914
                10989074
                38571506
                6c5a0fe6-21c6-4da2-a617-bd6e03d67acc
                Copyright © 2024 Wang, Gong, Sun and Meng

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 06 December 2023
                : 06 March 2024
                Page count
                Figures: 5, Tables: 2, Equations: 0, References: 50, Pages: 12, Words: 5423
                Funding
                Funded by: National Natural Science Foundation of China , doi 10.13039/501100001809;
                Award ID: 82172720, 81972864
                Funded by: Science and Technology Support Plan for Youth Innovation of Colleges and Universities of Shandong Province of China , doi 10.13039/501100018627;
                Award ID: 编号:2019KJL001
                The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This work has been funded by National Natural Science Foundation of China (81972864 and 82172720), Science and Technology Support Plan for Youth Innovation of Colleges and Universities of Shandong Province of China (2019KJL001).
                Categories
                Oncology
                Original Research
                Custom metadata
                Gastrointestinal Cancers: Gastric and Esophageal Cancers

                Oncology & Radiotherapy
                esophageal squamous cell carcinoma,immunotherapy,neoadjuvant therapy,radiomics,inflammatory biomarkers

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