Development and validation of a prognostic nomogram including inflammatory indicators for overall survival in hepatocellular carcinoma patients treated primarily with surgery or loco-regional therapy: A single-center retrospective study.

Hepatocellular carcinoma (HCC) is among the most prevalent malignant tumors, but the current staging system has limited efficacy in predicting HCC prognosis. The authors sought to develop and validate a nomogram model for predicting overall survival (OS) in HCC patients primarily undergoing surgery or loco-regional therapy. Patients diagnosed with HCC from January 2017 to June 2023 were enrolled in the study. The data were randomly split into a training cohort and a validation cohort. Utilizing univariate and multivariate Cox regression analyses, independent risk factors for OS were identified, and a nomogram model was constructed to predict patient survival. Therapy, body mass index, portal vein tumor thrombus, leukocyte, γ-glutamyl transpeptidase to platelet ratio, monocyte to lymphocyte ratio, and prognostic nutritional index were used to build the nomogram for OS. The nomogram demonstrated strong predictive ability, with high C-index values (0.745 for the training cohort and 0.650 for the validation cohort). ROC curves, calibration plots, and DCA curves all indicated satisfactory performance of the nomogram. Kaplan-Meier curve analysis showed a significant difference in prognosis between patients in the low- and high- risk groups. This nomogram provides precise survival predictions for HCC patients and helps identify individuals with varying prognostic risks, emphasizing the need for individualized follow-up and treatment plans.

Wang X ，Xu J ，Jia Z ，Sun G ... -  《-》

Prognostic value of preoperative systemic immune-inflammation index/albumin for patients with hepatocellular carcinoma undergoing curative resection.

Hepatocellular carcinoma (HCC) is a major factor for cancer-associated mortality globally. Although the systemic immune-inflammation index (SII) and albumin (ALB) show individual prognostic value for various cancers, their combined significance (SII/ALB) in HCC patients undergoing curative hepatectomy is still unknown. It is hypothesized that a higher SII/ALB ratio correlates with poorer outcomes with regard to overall survival (OS) and recurrence-free survival (RFS). To investigate the effect of preoperative SII/ALB in predicting the prognosis of HCC patients undergoing hepatectomy. Patients who received curative surgery for HCC at a single institution between 2014 and 2019 were retrospectively analyzed. Cox proportional hazards models and Kaplan-Meier curves were utilized to estimate OS and RFS. A nomogram was created using prognostic factors determined by the least absolute shrinkage and selection operator method and analyzed using multivariate Cox regression. This nomogram was assessed internally through the calibration plots, receiver operating characteristic (ROC) analysis, decision curve analysis (DCA) and the concordance index (C-index). This study enrolled 1653 HCC patients. Multivariate analyses demonstrated that SII/ALB independently predicted OS [hazard ratio (HR) = 1.22, 95%CI: 1.03-1.46, P = 0.025] and RFS (HR = 1.19, 95%CI: 1.03-1.38, P = 0.022). Age, alpha-fetoprotein, hepatitis B surface antigen, albumin-bilirubin grade, tumor diameter, portal vein tumor thrombus, tumor number, and SII/ALB were incorporated into the nomogram to predict OS. The nomogram had a C-index of 0.73 (95%CI: 0.71-0.76) and 0.71 (95%CI: 0.67-0.74) for the training and validation cohorts, respectively. The area under the ROC curve, DCA and calibration curves demonstrated high accuracy and clinical benefits. The SII/ALB may independently predict outcomes in HCC patients who receive curative surgical treatment. In addition, the nomogram can be used in HCC treatment decision-making.

Chen KL ，Qiu YW ，Yang M ，Wang T ，Yang Y ，Qiu HZ ，Sun T ，Wang WT ... -  《-》

Construction of a random survival forest model based on a machine learning algorithm to predict early recurrence after hepatectomy for adult hepatocellular carcinoma.

Zhang J ，Chen Q ，Zhang Y ，Zhou J ... -  《BMC CANCER》

Development and validation of a tumor size-stratified prognostic nomogram for patients with gastric signet ring cell carcinoma.

Gastric signet ring cell carcinoma (GSRC) is a rare malignancy without a commonly acknowledged prognostic assessment and treatment system. This study aimed to determine the optimal cut-off value of tumor size (TS), and construct a prognostic nomogram in combination with other independent prognostic factors (PFs) to predict 3 year and 5 year overall survival (OS) in GSRC patients. From the Surveillance, Epidemiology, and End Results (SEER) database, this study collected 4744 patients diagnosed with GSRC. These patients were randomized into a training cohort (n = 2320,) and a validation cohort (n = 1142). A restricted cubic spline (RCS) was used to determine the cut-off value for TS, and univariate and multivariate Cox regression analyses were performed in the training cohort to identified significant predictors. A prognostic nomogram was constructed to predict OS at 3 and 5 years. Concordance index (C index), receiver operating characteristics curve (ROC curve), area under curve (AUC), and calibration curve were used to test the predictive accuracy of the model. A non-linear relationship was observed between TS and the risk of OS in GSRC, with TS thresholds at 4.4 cm and 9.6 cm. Survival was significantly lower in GSRC patients with TS > 4.4 cm. Age, marriage, chemotherapy, surgery, TS, SEER stage, regional lymph node status, and total number were independent predictors of OS. The C index in the training cohort was 0.748, and the AUC values for both 3- and 5-year OS were higher than 0.80. Similar results were observed in the validation cohort. In addition, the calibration curves showed good agreement between the predicted 3 year and 5 year OS and the actual OS. TS is a key prognostic factor for patients with GSRC, and patients with a TS of 4.4-9.6 cm and > 9.6 cm may have a poorer prognosis than those with a TS of < 4.4 cm. The TS-stratified nomogram we constructed and validated has favorable accuracy and calibration precision, and may be helpful in predicting the survival rate of patients.

Hui X ，Zhou G ，Zheng Y ，Wang Y ，Guo Q ... -  《-》

Predicting cancer-specific mortality in T1/2 hepatocellular carcinoma after radiofrequency ablation by competing risk nomogram: A population-based analysis.

He Q ，Xiong Y ，Xia P ，Yang X ，Yu Y ，Chen Z ... -  《-》