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1.
Hepatol Int ; 18(2): 623-635, 2024 Apr.
Article in English | MEDLINE | ID: mdl-37880566

ABSTRACT

BACKGROUND: The impact of hepatic resection type on long-term oncological prognosis of patients with early-stage hepatocellular carcinoma (HCC) has not been systematically investigated. We sought to determine risk factors, recurrence patterns, and survival outcomes after anatomical resection (AR) versus non-anatomical resection (NAR) for early-stage HCC. METHODS: From a prospectively collected multicenter database, consecutive patients undergoing curative hepatectomy for early-stage HCC were identified. Recurrence patterns, overall survival (OS), recurrence-free survival (RFS), and risk factors were investigated in patients undergoing AR versus NAR using propensity score matching (PSM), subgroup analysis, and COX regression analysis. RESULTS: A total of 3585 patients with early-stage HCC were enrolled, including 1287 and 2298 in the AR and NAR groups, respectively. After PSM, the OS and RFS of patients in the AR group were 58.8% and 42.7%, which were higher than those in the NAR group (52.2% and 30.6%, both p < 0.01). The benefits of AR were consistent across most subgroup analyses of OS and RFS. Multivariable COX regression analysis showed that AR was independently associated with better OS and RFS. Notably, although recurrence patterns were comparable, the risk factors for recurrence were not identical for AR versus NAR. Microvascular invasion and narrow resection margin were only associated with a higher recurrence rate after NAR. CONCLUSIONS: This study demonstrated that AR decreases the risk of tumor recurrence and improves OS and RFS in patients with early-stage HCC. AR should be adopted as long as such a surgical maneuver is feasible for initial treatment of early-stage HCC.


Subject(s)
Carcinoma, Hepatocellular , Liver Neoplasms , Humans , Carcinoma, Hepatocellular/pathology , Liver Neoplasms/pathology , Propensity Score , Retrospective Studies , Hepatectomy , Neoplasm Recurrence, Local
2.
Anticancer Res ; 24(2C): 1159-65, 2004.
Article in English | MEDLINE | ID: mdl-15154641

ABSTRACT

BACKGROUND: Tumor markers are routinely measured in clinical oncology. However, their value in cancer detection has been controversial largely because no single tumor marker is sensitive and specific enough to meet strict diagnostic criteria. One strategy to overcome the shortcomings of single tumor markers is to measure a combination of tumor markers to increase sensitivity and look for distinct patterns to increase specificity. This study aimed to develop a system for parallel detection of tumor markers as a tool for tumor detection in both cancer patients and asymptomatic populations at high risk. MATERIALS AND METHODS: A protein chip was fabricated with twelve monoclonal antibodies against the following tumor markers respectively: CA125, CA15-3, CA19-9, CA242, CEA, AFP, PSA, free-PSA, HGH, beta-HCG, NSE and ferritin. Tumor markers were captured after the protein chip was incubated with serum samples. A secondary antibody conjugated with HRP was used to detect the captured tumor markers using chemiluminescence technique. Quantification of the tumor markers was obtained after calibration with standard curves. RESULTS: The chip system showed an overall sensitivity of 68.18% after testing 1147 cancer patients, with high sensitivities for liver, pancreas and ovarian tumors and low sensitivities for gastrointestinal tumors, and a specificity of 97.1% after testing 793 healthy individuals. Application of the chip system in physical checkups of 15,867 individuals resulted in 16 cases that were subsequently confirmed as having cancers. Analysis of the detection results with a Support Vector Machine algorithm considerably increased the specificity of the system as reflected in healthy individuals and hepatitis/cirrhosis patients, but only modestly decreased the sensitivity for cancer patients. CONCLUSION: This protein chip system is a potential tool for assisting cancer diagnosis and for screening cancer in high-risk populations.


Subject(s)
Biomarkers, Tumor/blood , Neoplasms/blood , Protein Array Analysis/methods , Antibodies, Monoclonal/chemistry , Antibodies, Monoclonal/immunology , Artificial Intelligence , Biomarkers, Tumor/immunology , Calibration , Female , Horseradish Peroxidase/chemistry , Horseradish Peroxidase/metabolism , Humans , Male , Neoplasms/diagnosis , Sensitivity and Specificity
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