Development and Validation of a Nomogram-Based Prognostic Evaluation Model for Sarcomatoid Hepatocellular Carcinoma

Establishment of a nomogram to predict the overall survival of patients with collecting duct renal cell carcinoma

BACKGROUND

Collecting duct carcinoma (CDC) is a rare histological type of renal cell carcinoma that lacks a prognostic prediction model. In this study, we developed a nomogram to predict the prognosis of CDC patients.

METHODS

Data for patients (n = 247) diagnosed with CDC from 2004 to 2015 were obtained from the Surveillance, Epidemiology, and End Results (SEER) database, and the patients were randomized into training (n = 165) and validation (n = 82) cohorts. Survival outcomes were evaluated by the Kaplan-Meier method. Significant variables determined by univariate and multivariate Cox regression analyses were used to construct the nomogram. C-indexes and calibration plots were applied to evaluate the performance of the nomogram.

RESULTS

CDC patients had a median overall survival (OS) of 18.0 months (95% confidence interval: 13.7-22.3); 1-year, 3-year, and 5-year OS rates were 58.7%, 34.2%, and 29.4%, respectively. Independent prognostic factors, including age at diagnosis, tumor size, tumor grade, T stage, N stage, M stage, and surgery information, were identified by multivariate analysis. The nomogram was constructed based on significant factors in the training cohort. The C-indexes were 0.769 (training cohort) and 0.767 (validation cohort). The calibration curves for survival rates showed that the predicted and observed values were consistent.

CONCLUSIONS

This study constructed a nomogram to predict prognosis in patients with CDC. The nomogram performed well in predicting the 1-year, 3-year, and 5-year OS, which can help doctors actively monitor and follow up patients.

Clinical features and prognostic factors of esophageal signet ring cell carcinoma: construction and validation of a model based on the SEER database

BACKGROUND

Signet ring cell carcinoma (SRCC) of the esophagus is a rare subtype of esophagus cancer with a poor prognosis. Our study aimed to determine the prognostic factors and establish nomograms to predict overall survival (OS) and cancer-specific survival (CSS) for patients with esophageal SRCC.

METHODS

A total of 401 esophageal SRCC patients were identified from Surveillance Epidemiology and End Results (SEER) database and randomly divided into training and validation groups. We integrated the significant prognostic factors identified by multivariate cox analysis and construct nomograms to predict 2- and 5-year OS and CSS. Then, we evaluated the performance of the nomograms through concordance index (C-index), calibration curve, and the area under the curve (AUC) of the receiver operating characteristic curve.

RESULTS

Multivariate Cox analysis revealed that American Joint Committee on Cancer (AJCC) stage, chemotherapy and surgery were associated with both OS and CSS. The C-indexes for OS and CSS predicted nomograms were 0.773 and 0.806, respectively. The calibration curves demonstrated good agreement between the actual observation and the nomogram prediction. Furthermore, the novel nomograms displayed higher AUC values in predicting OS and CSS compared to the 7th Tumor-Node-Metastasis (TNM) staging system.

CONCLUSIONS

AJCC stage, chemotherapy and surgery were independent prognostic factors in esophageal SRCC patients. The proposed three-factor nomogram can assist clinicians predict the accurate prognosis of esophageal SRCC, thus contributing to individualized clinical practice.

Development and validation of a nomogram for predicting the cancer-specific survival of fibrolamellar hepatocellular carcinoma patients

Fibrolamellar hepatocellular carcinoma (FLC) is a rare subtype of hepatocellular carcinoma. Our study aimed to construct a nomogram to predict the cancer-specific survival (CSS) of FLC. Data of 200 FLC patients enrolled in the Surveillance, Epidemiology, and End Results (SEER) database were divided into the training group and the validation group. Prognostic factors identified in the univariate and multivariate Cox regression analyses were used to construct the nomogram. The concordance index (C-index), calibration curves, time-dependent receiver operating characteristic curve (ROC), and decision curve analysis (DCA) were used to evaluate the performance of the nomogram. As a result, age ≥ 59, N1 stage, M1 stage, tumor size ≤ 2.0 cm, and no surgery were significantly associated with lower CSS in multivariate Cox regression analysis. The calibration plot showed good consistency of the nomogram between predicted and observed outcomes in the training and validation groups. Compared with the TNM staging system, the prognostic evaluation model (PEM) showed a higher C-index (0.823 vs 0.656). The PEM also showed better predictive performance, with areas under the curve of 0.909 and 0.890 for predicting the 1- and 5-year survival. The AUCs of the TNM stage model for predicting 1- and 5-year survival were 0.629 and 0.787, respectively. In addition, the DCA curve showed that the nomogram had better clinical utility. Finally, we concluded that Age, N stage, M stage, tumor size, and surgery are independent prognostic factors for FLC. PEM established based on these five prognostic indicators can help predict the CSS of patients with FLC.

Development and Validation of a Clinicopathological-Based Nomogram to Predict the Survival Outcome of Patients with Recurrent Hepatocellular Carcinoma After Hepatectomy Who Underwent Microwave Ablation

Aim

To develop and validate a nomogram for predicting the overall survival (OS) in patients with recurrent hepatocellular carcinoma (HCC) after hepatectomy who underwent microwave ablation (MWA).

Methods

The training cohort included 299 patients with recurrent HCCs after hepatectomy who met the Milan criteria and received MWA from April 2007 to December 2017. Baseline characteristics were collected to identify risk factors for the determination of death after MWA. A multivariate Cox proportional hazards model based on significant risk factors was used to develop the nomogram, which was then assessed for its predictive accuracy using Harrell’s C-index and the area under the curve (AUC). The nomogram was validated by internal (n = 240) and external cohorts (n = 205) from another hospital.

Results

After a median follow-up of 32.3 months, 38.8% (116/299) of patients had died. Multivariate Cox proportional hazards analyses showed that comorbid disease, early recurrence, and albumin-bilirubin (ALBI) grades 2–3 were independent prognostic factors for poor OS. This nomogram accurately stratified patients into subgroups with low or high risk. The 1-, 3- and 5-year OS rates in the low-risk subgroup were 99.4%, 97.2%, and 86.1%, respectively, and they were 92.8%, 70.3%, and 45.8% in the high-risk subgroup (P < 0.001). The nomogram predicted OS in the training cohort with a C-index score of 0.801 (95% CI 0.761–0.841). The nomogram was validated by internal and external cohorts, with C-index scores of 0.792 (95% CI 0.738–0.846) and 0.744 (95% CI 0.703–0.785), respectively.

Conclusion

The nomogram provides individualized risk estimates for long-term OS for patients with recurrent HCC after hepatectomy who underwent MWA.