ArticleFrontiers in public health2022
Development and Validation of a Nomogram to Predict Cancer-Specific Survival for Middle-Aged Patients With Early-Stage Hepatocellular Carcinoma.
Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Construction of webZhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2023Trial
- Establishment and validation of a prognostic nomogram for patients with early-onset stage I-II colon cancer.World journal of surgical oncology · 2023Trial
- Identification of Patients with Early-Stage Hepatocellular Carcinoma Benefiting from Neoadjuvant Chemotherapy-A SEER-Based Study.Journal of gastrointestinal cancer · 2025Article
- Dynamic conditional survival nomogram for primary hepatocellular carcinoma: a population-based analysis.Discover oncology · 2025Article
- Establishment of nomogram of early death in elderly pancreatic cancer patients with liver metastasis.Discover oncology · 2025Article
- Preoperative serum inflammatory markers in the prognostic assessment of hepatocellular carcinoma resection in stages I/II.Frontiers in molecular biosciences · 2025Article
- A nomogram for predicting cancer-specific survival for elderly patients with gallbladder cancer.BMC gastroenterology · 2022Article
- Clinical Characteristics, Prognostic Factor and a Novel Dynamic Prediction Model for Overall Survival of Elderly Patients With Chondrosarcoma: A Population-Based Study.Frontiers in public health · 2022Article
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3 authors.
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Abstract
Background: Hepatocellular carcinoma is a common cause of death in middle-aged patients. We aimed to construct a new nomogram to predict cancer-specific survival (CSS) in middle-aged patients with hepatocellular carcinoma at an early stage. Method: We collected clinicopathological information on early middle-aged patients with hepatocellular carcinoma from the SEER database. Univariate and multivariate Cox regression models were used to screen the independent risk factors for prognosis. These risk factors were used to construct predictions of CSS in patients with hepatocellular carcinoma. Consistency index (C- index), calibration curve, area under the receiver operating curve (AUC) were used. A decision analysis curve (DCA) was used to evaluate the clinical utility of the predictive model. Results: A total of 6,286 patients with hepatocellular carcinoma in early middle age were enrolled. Univariate and multivariate Cox regression analysis showed that sex, marriage, race, histological tumor grade, T stage, surgery, chemotherapy, AFP, and tumor size were independent risk factors for prognosis. All independent risk factors were included in the nomogram to predict CSS at 1-, 3-, and 5-years in early middle age patients with hepatocellular carcinoma. In the training cohort and validation cohort, the C-index of the prediction model was 0.728 (95%CI: 0.716-0.740) and 0.733 (95%CI: 0.715-0.751), respectively. The calibration curve showed that the predicted value of the prediction model is highly consistent with the observed value. AUC also suggested that the model has good discrimination. DCA suggested that the nomogram had better predictive power than T staging. Conclusion: We constructed a new nomogram to predict CSS in middle-aged patients with early-stage hepatocellular carcinoma. This prediction model has good accuracy and reliability, which can help patients and doctors to judge prognosis and make clinical decisions.
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