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Piras A, Morelli I, Colciago RR, Boldrini L, D'Aviero A, De Felice F, Grassi R, Iorio GC, Longo S, Mastroleo F, Desideri I, Salvestrini V. The continuous improvement of digital assistance in the radiation oncologist's work: from web-based nomograms to the adoption of large-language models (LLMs). A systematic review by the young group of the Italian association of radiotherapy and clinical oncology (AIRO). LA RADIOLOGIA MEDICA 2024:10.1007/s11547-024-01891-y. [PMID: 39397129 DOI: 10.1007/s11547-024-01891-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/23/2024] [Accepted: 09/20/2024] [Indexed: 10/15/2024]
Abstract
PURPOSE Recently, the availability of online medical resources for radiation oncologists and trainees has significantly expanded, alongside the development of numerous artificial intelligence (AI)-based tools. This review evaluates the impact of web-based clinical decision-making tools in the clinical practice of radiation oncology. MATERIAL AND METHODS We searched databases, including PubMed, EMBASE, and Scopus, using keywords related to web-based clinical decision-making tools and radiation oncology, adhering to PRISMA guidelines. RESULTS Out of 2161 identified manuscripts, 70 were ultimately included in our study. These papers all supported the evidence that web-based tools can be transversally integrated into multiple radiation oncology fields, with online applications available for dose and clinical calculations, staging and other multipurpose intents. Specifically, the possible benefit of web-based nomograms for educational purposes was investigated in 35 of the evaluated manuscripts. As regards to the applications of digital and AI-based tools to treatment planning, diagnosis, treatment strategy selection and follow-up adoption, a total of 35 articles were selected. More specifically, 19 articles investigated the role of these tools in heterogeneous cancer types, while nine and seven articles were related to breast and head & neck cancers, respectively. CONCLUSIONS Our analysis suggests that employing web-based and AI tools offers promising potential to enhance the personalization of cancer treatment.
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Affiliation(s)
- Antonio Piras
- UO Radioterapia Oncologica, Villa Santa Teresa, 90011, Bagheria, Palermo, Italy
- Ri.Med Foundation, 90133, Palermo, Italy
- Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialties, Molecular and Clinical Medicine, University of Palermo, 90127, Palermo, Italy
- Radiation Oncology, Mater Olbia Hospital, Olbia, Italy
| | - Ilaria Morelli
- Radiation Oncology Unit, Department of Experimental and Clinical Biomedical Sciences, Azienda Ospedaliero-Universitaria Careggi, University of Florence, Florence, Italy
| | - Riccardo Ray Colciago
- Department of Radiation Oncology, Fondazione IRCCS Istituto Nazionale Dei Tumori, 20133, Milan, Italy
| | - Luca Boldrini
- UOC Radioterapia Oncologica, Fondazione Policlinico Universitario IRCCS "A. Gemelli", Rome, Italy
- Università Cattolica del Sacro Cuore, Rome, Italy
| | - Andrea D'Aviero
- Department of Medical, Oral and Biotechnological Sciences, "G. D'Annunzio" University of Chieti, Chieti, Italy
- Department of Radiation Oncology, "S.S. Annunziata" Chieti Hospital, Chieti, Italy
| | - Francesca De Felice
- Radiation Oncology, Policlinico Umberto I, Department of Radiological, Oncological and Pathological Sciences, "Sapienza" University of Rome, Rome, Italy
| | - Roberta Grassi
- Department of Precision Medicine, University of Campania "L. Vanvitelli", Naples, Italy
| | | | - Silvia Longo
- UOC Radioterapia Oncologica, Fondazione Policlinico Universitario IRCCS "A. Gemelli", Rome, Italy
| | - Federico Mastroleo
- Division of Radiation Oncology, European Institute of Oncology IRCCS, Via Ripamonti 435, 20141, Milan, Italy.
- Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy.
| | - Isacco Desideri
- Radiation Oncology Unit, Department of Experimental and Clinical Biomedical Sciences, Azienda Ospedaliero-Universitaria Careggi, University of Florence, Florence, Italy
| | - Viola Salvestrini
- Radiation Oncology Unit, Department of Experimental and Clinical Biomedical Sciences, Azienda Ospedaliero-Universitaria Careggi, University of Florence, Florence, Italy
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Yang S, Fan G, Feng C, Fan Y, Xu N, Zhou H, Wang C, Liao X, He S. Novel Nomograms and Web-Based Tools Predicting Overall Survival and Cancer-specific Survival of Solitary Plasmacytoma of the Spine. Spine (Phila Pa 1976) 2023; 48:1197-1207. [PMID: 37036328 DOI: 10.1097/brs.0000000000004679] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Accepted: 03/30/2023] [Indexed: 04/11/2023]
Abstract
STUDY DESIGN Retrospective analysis. OBJECTIVE This study aimed to establish nomograms for predicting overall survival (OS) and cancer-specific survival (CSS) in patients with solitary plasmacytoma of the spine (SPS). SUMMARY OF BACKGROUND DATA SPS is a rare type of malignant spinal tumor. A systematic study of prognostic factors associated with survival can provide guidance to clinicians and patients. Consideration of other causes of death (OCOD) in CSS will improve clinical practicability. METHODS A total of 1078 patients extracted from the SEER database between 2000 and 2018 were analyzed. Patients were grouped into training and testing data sets (7:3). Factors associated with OS and CSS were identified by Cox regression and competing risk regression, respectively, for the establishment of nomograms on a training data set. The testing data set was used for the external validation of the performance of the nomograms using calibration curves, Brier's scores, C-indexes, time-dependent receiver operating characteristic curves, and decision curve analysis (DCA). RESULTS Age and grade were identified as factors associated with both OS and CSS, along with marital status, radiation for OS, and chemotherapy for CSS. Heart disease, cerebrovascular disease, and diabetes mellitus were found to be the 3 most common causes of OCOD. The nomograms showed satisfactory agreement on calibration plots for both training and testing data sets. Integrated Brier score, C-index, and overall area under the curve on the testing data set were 0.162/0.717/0.789 and 0.173/0.709/0.756 for OS and CSS, respectively. DCA curves showed a good clinical net benefit. Nomogram-based web tools were developed for clinical application. CONCLUSION This study provides evidence for risk factors and prognostication of survival in SPS patients. The novel nomograms and web-based tools we developed demonstrated good performance and might serve as accessory tools for clinical decision-making and SPS management. LEVEL OF EVIDENCE 3.
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Affiliation(s)
- Sheng Yang
- Department of Orthopedics, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China
- Spinal Pain Research Institute, Tongji University School of Medicine, Shanghai, China
| | - Guoxin Fan
- Department of Pain Medicine, Huazhong University of Science and Technology Union Shenzhen Hospital, Shenzhen, China
- Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, School of Biomedical Engineering, Shenzhen University Medical school
- Department of Spine Surgery, Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Chaobo Feng
- Department of Orthopedics, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China
- Spinal Pain Research Institute, Tongji University School of Medicine, Shanghai, China
| | - Yunshan Fan
- Department of Orthopedics, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China
- Spinal Pain Research Institute, Tongji University School of Medicine, Shanghai, China
| | - Ningze Xu
- Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China
| | - Hongmin Zhou
- Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China
| | - Chuanfeng Wang
- Department of Orthopedics, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China
- Spinal Pain Research Institute, Tongji University School of Medicine, Shanghai, China
| | - Xiang Liao
- Department of Pain Medicine, Huazhong University of Science and Technology Union Shenzhen Hospital, Shenzhen, China
- Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, School of Biomedical Engineering, Shenzhen University Medical school
| | - Shisheng He
- Department of Orthopedics, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China
- Spinal Pain Research Institute, Tongji University School of Medicine, Shanghai, China
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Liang M, Chen M, Singh S, Singh S. Prognostic Nomogram for Overall Survival in Small Cell Lung Cancer Patients Treated with Chemotherapy: A SEER-Based Retrospective Cohort Study. Adv Ther 2022; 39:346-359. [PMID: 34729705 DOI: 10.1007/s12325-021-01974-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Accepted: 10/21/2021] [Indexed: 12/25/2022]
Abstract
INTRODUCTION Small cell lung cancer (SCLC) is known for its rapid clinical progression and poor prognosis. In this study, we sought to establish a prognostic nomogram among SCLC patients who received chemotherapy. METHODS We obtained 4971 SCLC patients' clinical information from the Surveillance, Epidemiology, and End Results (SEER) database for the period between 2004 and 2015. Patients were divided into training and validation sets. Two nomograms were established based on limited stage (LS) and extensive stage (ES) SCLC patients to predict 1-, 2-, and 3-year overall survival (OS) incorporating superior parameters from multivariate Cox regression. Receiver-operating characteristic curves (ROCs) were applied to assess the discrimination ability of the nomogram while the calibration plots were applied to verify the model. Kaplan-Meier method was applied to find survival curves. Decision curve analysis (DCA) was applied to compare OS between the nomograms and 7th American Joint Committee on Cancer (AJCC) tumor node metastasis (TNM) staging system. RESULTS Four and six clinical parameters were identified as significant prognostic factors for LS-SCLC and ES-SCLC patient's OS, respectively. The ROC curves indicated satisfactory discrimination capacity of the nomogram, with 1-, 2-, and 3-year area under curve (AUC) values of 0.89, 0.81, and 0.79 in LS-SCLC patients and 0.71, 0.66, and 0.66 in ES-SCLC patients, respectively. Calibration curves indicated that the nomogram showed good agreement with actual observations in survival rate probability. The survival curves among the LS-SCLC and ES-SCLC cohorts were consistent with the high-risk group having a worse prognosis than the low-risk group. Moreover, ROC and DCA curves showed our nomograms had more benefits than the 7th AJCC-TNM staging system. CONCLUSIONS We established two nomograms that can present individual predictions of OS among LS-SCLC and ES-SCLC patients who received chemotherapy. These proposed nomograms may aid clinicians in treatment strategy and design of clinical trials.
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Affiliation(s)
- Min Liang
- Department of Respiratory and Critical Care Medicine, Maoming People's Hospital, Maoming, China.
| | - Mafeng Chen
- Department of Otolaryngology, Maoming People's Hospital, Maoming, China
| | - Shantanu Singh
- Division of Pulmonary, Critical Care and Sleep Medicine, Marshall University, Huntington, WV, USA
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