Background: While early gastric cancer (EGC) patients are likely to experience relatively long postoperative survival, certain disease-related findings are associated with a poorer prognosis. This study sought to develop and validate a novel predictive model capable of estimating conditional disease-specific survival (CDSS) in EGC patients.
Methods: A total of 3016 patients diagnosed with pT1NxM0 GC after gastrectomy between 1998 and 2016 were selected from the Surveillance, Epidemiology, and End Results (SEER) database and were separated into training and validation cohorts. Kaplan‒Meier curves and log-rank tests were employed to evaluate DSS, after which univariate and multivariate Cox regression analyses were used to construct a predictive nomogram and to estimate CDSS at 1, 2, and 3 years postoperatively in these patients.
Results: In the training cohort, the 3-year CDSS rose from 89.1% to 94.6% from 0 to 5 years postoperatively, while the 5-year CDSS rose from 84.5% to 92.0%. Cox regression analyses led to the construction of a nomogram that was able to reliably predict 3- and 5-year CDSS at 1, 2, and 3 years postoperatively (all < 0.05) based upon patient age, tumor size, pT stage, pN stage, and the number of retrieved lymph nodes. This model exhibited good discriminative power in the training and validation cohorts (concordance index: 0.791 and 0.813, respectively), and nomogram calibration curves confirmed that actual and predicted survival outcomes were close to one another.
Conclusions: We herein developed a nomogram capable of accurately predicting the CDSS of EGC patients that had survived for multiple years after undergoing surgery.
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http://dx.doi.org/10.1155/2023/8629166 | DOI Listing |
Exp Biol Med (Maywood)
December 2024
Department of Laboratory Medicine, Affiliated Hospital of Nantong University, Nantong University, Nantong, China.
Gastric cancer (GC) is the kind of carcinoma that has the highest rates of morbidity and death worldwide. In the early stages of GC, there is currently an absence of sensitive and specific biomarkers. The newly-discovered class of non-coding RNAs (ncRNAs) known as transfer RNA-derived small RNAs (tsRNAs) is highly expressed in bodily fluids and neoplastic cells.
View Article and Find Full Text PDFOncol Res
December 2024
Department of General Surgery, Affiliated Hospital of Nantong University, Nantong, 226001, China.
Objective: Gastric cancer (GC) is a globally common cancer characterized by high incidence and mortality worldwide. Advances in the molecular understanding of GC provide promising targets for GC diagnosis and therapy. Long non-coding RNAs (lncRNAs) and their downstream regulators are regarded to be implicated in the progression of multiple types of malignancies.
View Article and Find Full Text PDFOncol Res
December 2024
Department of Pathology, College of Medicine, King Khalid University, Abha, 62521, Saudi Arabia.
Background: Gastric cancer (GC) remains a global health burden and is often characterized by heterogeneous molecular profiles and resistance to conventional therapies. The phosphoinositide 3-kinase and PI3K and Janus kinase (JAK) signal transducer and activator of transcription (JAK-STAT) pathways play pivotal roles in GC progression, making them attractive targets for therapeutic interventions.
Methods: This study applied a computational and molecular dynamics simulation approach to identify and characterize SBL-JP-0004 as a potential dual inhibitor of JAK2 and PI3KCD kinases.
Front Oncol
December 2024
Department of Orthopedics, Chengdu Fifth People's Hospital, Chengdu, China.
Background: Prostate cancer (PCa) ranks as the second leading cause of cancer-related mortality among men. Long non-coding RNAs (lncRNAs) are known to play a regulatory role in the development of various human cancers. LncRNA MAFG-divergent transcript (MAFG-DT) was reported to play a crucial role in tumor progression of multiple human cancers, such as pancreatic cancer, colorectal cancer, bladder cancer, and gastric cancer.
View Article and Find Full Text PDFFront Oncol
November 2024
Department of Oncology, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China.
Purpose: This study aimed to develop and validate a model for accurately assessing the risk of distant metastases in patients with gastric cancer (GC).
Methods: A total of 301 patients (training cohort, n = 210; testing cohort, n = 91) with GC were retrospectively collected. Relevant clinical predictors were determined through the application of univariate and multivariate logistic regression analyses.
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