Prognostic significance of preoperative systemic inflammatory biomarkers in patients with hepatocellular carcinoma after microwave ablation and establishment of a nomogram
| Autor: | Zhen-Gang Sun, Shuai Wang, Xiao Yu, Xue-Wen Zhang, Yan Deng, Hong Chang, Cheng-Long Huo |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
0301 basic medicine
Oncology Male Neutrophils Diseases Kaplan-Meier Estimate Monocytes Leukocyte Count 0302 clinical medicine Ascites Lymphocytes Microwaves Cancer Aged 80 and over Univariate analysis Multidisciplinary Microwave ablation Liver Neoplasms Middle Aged Prognosis 030220 oncology & carcinogenesis Hepatocellular carcinoma Medicine Female medicine.symptom Liver cancer Adult Blood Platelets medicine.medical_specialty Carcinoma Hepatocellular Science Article Disease-Free Survival 03 medical and health sciences Internal medicine Preoperative Care medicine Biomarkers Tumor Humans Neutrophil to lymphocyte ratio Aged Inflammation Radiofrequency Ablation business.industry Platelet Count Nomogram medicine.disease Nomograms 030104 developmental biology Risk factors business Biomarkers |
| Zdroj: | Scientific Reports Scientific Reports, Vol 11, Iss 1, Pp 1-13 (2021) |
| ISSN: | 2045-2322 |
| Popis: | The study aimed to evaluate the prognostic significance of preoperative systemic inflammatory biomarkers including albumin to globulin ratio (AGR), neutrophil to lymphocyte ratio (NLR), lymphocyte to monocyte ratio (LMR), and platelet to lymphocyte ratio (PLR) and establish a nomogram in hepatocellular carcinoma (HCC) patients after microwave ablation (MWA). 192 HCC patients receiving MWA as initial therapy from the first ward of hepatobiliary surgery were classified as training cohort. Whereas, 84 patients from the second of hepatobiliary surgery were classified as validation cohort. Kaplan–Meier (KM) method and univariate analyses showed that AGR, NLR, LMR, and PLR were significantly associated with OS in the training cohort. Multivariate analysis including clinicopathologic features screened out independent predictors including ascites, tumor size, cancer embolus, AGR, and PLR. Based on those variables, a nomogram for predicting OS was established. The C-index was 0.794 in the training cohort and 0.772 in the validation cohort. Calibration plots identified the nomogram performed well with an ideal model. Compared with Barcelona Clinic Liver Cancer (BCLC) staging system and simple tumor size, the nomogram showed better predictive ability. Besides, the nomogram discovered the highest diagnostic accuracy in predicting postoperative clinical outcome than the combination of the present models with tumor size. In conclusion, the constructed nomogram could accurately predict individualized survival probability and might support clinician in individual treatment optimization and clinical decision-making. |
| Databáze: | OpenAIRE |
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