ArticleFrontiers in oncology2021
A New Clinical Nomogram From the TCGA Database to Predict the Prognosis of Hepatocellular Carcinoma.
Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- EXTL3 could serve as a potential biomarker of prognosis and immunotherapy for prostate cancer and its potential mechanisms.European journal of medical research · 2022Article
- Molecular Biology in Treatment Decision Processes-Neuro-Oncology Edition.International journal of molecular sciences · 2021Review
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Abstract
BACKGROUND AND
aimHepatocellular carcinoma is a common malignant tumor of the digestive system with a poor prognosis. The high recurrence rate and metastasis after surgery reduce the survival time of patients. Therefore, assessing the overall survival of patients with hepatocellular carcinoma after hepatectomy is critical to clinicians' clinical decision-making. Conventional hepatocellular carcinoma assessment systems (such as tumor lymph node metastasis and Barcelona clinical hepatocellular carcinoma) are obviously insufficient in assessing the overall survival rate of patients. This research is devoted to the development of nomogram assessment tools to assess the overall survival probability of patients undergoing liver resection.
methodsWe collected the clinical and pathological information of 438 hepatocellular carcinoma patients undergoing surgery from The Cancer Genome Atlas (TCGA) database, then excluded 87 patients who did not meet inclusion criteria. Univariate and multivariate analyses were performed on patient characteristics and related pathological factors. Finally, we developed a nomogram model to predict patient's prognosis.
resultsA retrospective analysis of 438 consecutive samples from the TCGA database of patients with hepatocellular carcinoma who underwent potentially curative liver resections. Six risk factors were included in the final model. In the training set, the discriminative ability of the nomogram was very good (concordance index = 0.944), and the external verification method (concordance index = 0.962) was used for verification. At the same time, the internal and external calibration of the model was verified, showing that the model was well calibrated. The calibration between the evaluation of the nomogram and the actual observations was good. According to the patient's risk factors, we determined the patient's Kaplan-Meyer survival analysis curve. Finally, the clinical decision curve was used to compare the benefits of two different models in evaluating patients' clinical outcomes.
conclusionsThe nomogram can be used to evaluate the post-hepatectomy 1-, 3-, and 5-year survival rates of patients with hepatocellular carcinoma. The Kaplan-Meyer curve can intuitively display the survival differences among patients with various risk factors. The clinical decision curve is a good reference guide for clinical application.
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