AI Article Synopsis
- The study focuses on creating an automated algorithm to quickly identify patients who might qualify for specific anti-cancer treatments, reducing the lengthy prescreening process for clinical trials.
- It analyzed 640 anonymized reports from multidisciplinary team meetings related to lung cancer, using regular expressions to extract relevant eligibility criteria, achieving impressive metrics: an average F1-score of 93%, 98% precision, and 92% recall.
- Despite these successes, there were significant inconsistencies in the completeness of patient and tumor information, with genetic mutations being particularly underreported and challenging to extract automatically.
Article Abstract
Defining profiles of patients that could benefit from relevant anti-cancer treatments is essential. An increasing number of specific criteria are necessary to be eligible to specific anti-cancer therapies. This study aimed to develop an automated algorithm able to detect patient and tumor characteristics to reduce the time-consuming prescreening for trial inclusions without delay. Hence, 640 anonymized multidisciplinary team meetings (MTM) reports concerning lung cancers from one French teaching hospital data warehouse between 2018 and 2020 were annotated. To automate the extraction of eight major eligibility criteria, corresponding to 52 classes, regular expressions were implemented. The RegEx's evaluation gave a F1-score of 93% in average, a positive predictive value (precision) of 98% and sensitivity (recall) of 92%. However, in MTM, fill rates variabilities among patient and tumor information remained important (from 31% to 100%). Genetic mutations and rearrangement test results were the least reported characteristics and also the hardest to automatically extract. To ease prescreening in clinical trials, the PreScIOUs study demonstrated the additional value of rule based and machine learning based methods applied on lung cancer MTM reports.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1177/14604582221146709 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Outcome of Soft Tissue Popliteal Sarcomas: 15 Years of Experience.
Indian J Orthop
January 2025
Department of Orthopedics and Traumatology, Abdurrahman Yurtaslan Training and Research Hospital, Ankara, Turkey.
Background: Soft-tissue sarcoma involving the popliteal fossa remains challenging because it is difficult to achieve wide margins with limb salvage in this location. Adjuvant therapy is frequently necessary, and limb function can be adversely affected. We reviewed our experience with these tumors.
View Article and Find Full Text PDFCAF-derived exosome-miR-3124-5p promotes malignant biological processes in NSCLC via the TOLLIP/TLR4-MyD88-NF-κB pathway.
Oncol Res
December 2024
Department of Respiratory and Critical Care Medicine, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong, 226001, China.
Background: Lung cancer is a life-threatening disease that occurs worldwide, but is especially common in China. The crucial role of the tumour microenvironment (TME) in non-small cell lung cancer (NSCLC) has attracted recent attention. Cancer-associated fibroblasts (CAFs) are the main factors that contribute to the TME function, and CAF exosomes are closely linked to NSCLC.
View Article and Find Full Text PDFDisseminated tumor cells in bone marrow as predictive classifiers for small cell lung cancer patients.
J Natl Cancer Cent
December 2024
Department of Medical Oncology, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China.
Background: Small cell lung cancer (SCLC) is a highly aggressive disease characterized by early metastasis. Aneuploid CD31 disseminated tumor cells (DTCs) and CD31 disseminated tumor endothelial cells (DTECs) residing in the bone marrow are generally considered as the initiators of metastatic process. However, the clinical significance of DTCs and DTECs in SCLC remains poorly understood.
View Article and Find Full Text PDFDeciphering Antigen Processing Machinery (APM) as One of the Determinants for Responsiveness of Affected Patients towards Anticancer Immunotherapy.
Asian Pac J Cancer Prev
December 2024
Research Center for Vaccine and Drugs, The National Research and Innovation Agency (BRIN), South Tangerang 15310, Republic of Indonesia.
Immunotherapy is one of the rising stars in the field of anticancer regiments. Aimed at reinvigorating immune cytotoxicity, this platform is capable of bulking up memory subsets by which protection against tumors is served. The most commonly applied immunotherapy is immune checkpoint inhibitor (ICIs) which received FDA approval for non-small lung cancer (NSLC) in 2014.
View Article and Find Full Text PDFEvaluating the Use of Environmental and Polygenic Risk Scores to Inform Colorectal Cancer Risk-Based Surveillance Intervals.
Clin Transl Gastroenterol
December 2024
Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, USA.
Introduction: United States Multi-Society Task Force colonoscopy surveillance intervals are based solely on adenoma characteristics, without accounting for other risk factors. We investigated whether a risk model including demographic, environmental, and genetic risk factors could individualize surveillance intervals under an "equal management of equal risks" framework.
Methods: Using 14,069 individuals from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial who had a diagnostic colonoscopy following an abnormal flexible sigmoidoscopy, we modeled the risk of colorectal cancer, considering the diagnostic colonoscopy finding, baseline risk factors (e.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!