Competing-risk nomogram for predicting survival in patients with advanced (stage III/IV) gallbladder cancer: A SEER population-based study

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

BACKGROUND

Radiofrequency ablation (RFA) is one of the primary treatment methods for T1/2 hepatocellular carcinoma (HCC), but the risk factors after RFA remain controversial. This study aims to identify the key factors associated with cancer-specific mortality (CSM) in patients with T1/2 HCC after RFA using competing risk analysis and to establish a prognostic nomogram for improved clinical management.

METHODS

A total of 2,135 T1/2 HCC patients treated with RFA were obtained from the Surveillance, Epidemiology, and End Results (SEER) database and randomly categorized into training and validation sets. Univariate and multivariable competing risk analyses were performed to identify risk factors associated with CSM and construct a competing risk nomogram. Receiver operating characteristic (ROC) curves, concordance indices (C-indexes), calibration plots, and decision curve analysis (DCA) were conducted to evaluate the predictive efficiency and clinical applicability of the nomogram in the training and validation sets. Patients were stratified according to their nomogram score, and the different risk groups were compared using cumulative incidence function (CIF) curves and Gray's validation .

RESULTS

The 5-year CSM rate for HCC patients treated with RFA was 30.1 %. Grade, tumor size, tumor number, cirrhosis, and AFP level were identified as independent risk factors for CSM. A prognostic nomogram was developed based on these risk factors. The time-dependent C-indexes (0.65) were greater than those of the AJCC stage model (0.55) during the 12 to 60 months of follow-up. The calibration plots of the competing risk nomograms demonstrated excellent consistency between actual survival and nomogram predictions. ROC analyses showed that the 1-, 3-, and 5-year AUC values in both the training and validation cohorts were all greater than 0.63 and exceeded those of the AJCC stage model. DCA demonstrated the clinical usefulness of the nomogram. Patients were classified into low-, moderate-, and high-risk groups based on the nomogram scores, with the high-risk group showing significantly higher CSM rates after RFA compared to the other two groups.

CONCLUSIONS

We identified Grade, AFP, cirrhosis, tumor size, and tumor number as independent risk factors associated with CSM. The competing risk nomogram exhibited high performance in predicting the probability of CSM for HCC patients undergoing RFA.

New trends in diagnosis and management of gallbladder carcinoma

Gallbladder (GB) carcinoma, although relatively rare, is the most common biliary tree cholangiocarcinoma with aggressiveness and poor prognosis. It is closely associated with cholelithiasis and long-standing large (> 3 cm) gallstones in up to 90% of cases. The other main predisposing factors for GB carcinoma include molecular factors such as mutated genes, GB wall calcification (porcelain) or mainly mucosal microcalcifications, and GB polyps ≥ 1 cm in size. Diagnosis is made by ultrasound, computed tomography (CT), and, more precisely, magnetic resonance imaging (MRI). Preoperative staging is of great importance in decision-making regarding therapeutic management. Preoperative staging is based on MRI findings, the leading technique for liver metastasis imaging, enhanced three-phase CT angiography, or magnetic resonance angiography for major vessel assessment. It is also necessary to use positron emission tomography (PET)-CT or 18F-FDG PET-MRI to more accurately detect metastases and any other occult deposits with active metabolic uptake. Staging laparoscopy may detect dissemination not otherwise found in 20%-28.6% of cases. Multimodality treatment is needed, including surgical resection, targeted therapy by biological agents according to molecular testing gene mapping, chemotherapy, radiation therapy, and immunotherapy. It is of great importance to understand the updated guidelines and current treatment options. The extent of surgical intervention depends on the disease stage, ranging from simple cholecystectomy (T1a) to extended resections and including extended cholecystectomy (T1b), with wide lymph node resection in every case or IV-V segmentectomy (T2), hepatic trisegmentectomy or major hepatectomy accompanied by hepaticojejunostomy Roux-Y, and adjacent organ resection if necessary (T3). Laparoscopic or robotic surgery shows fewer postoperative complications and equivalent oncological outcomes when compared to open surgery, but much attention must be paid to avoiding injuries. In addition to surgery, novel targeted treatment along with immunotherapy and recent improvements in radiotherapy and chemotherapy (neoadjuvant-adjuvant capecitabine, cisplatin, gemcitabine) have yielded promising results even in inoperable cases calling for palliation (T4). Thus, individualized treatment must be applied.

Competing risk nomogram for predicting prognosis of patients with spinal and pelvic chordoma: A SEER-based retrospective study

PURPOSE

Recently, competing risk nomograms were widely applied to predict prognosis in numerous tumors other than chordoma. Here, we aimed to construct and validate a competing-risk-based prognostic nomogram to predict 3- and 5-year cancer-specific death (CSD) in patients with spinal and pelvic chordoma.

METHODS

All chordoma patient data were abstracted from the Surveillance, Epidemiology, and End Results (SEER) resource, and a total of 485 chordoma patients were eventually included in this study. Multivariate competing risk model and multivariate Cox model were used to determine independent prognostic factors, respectively, and the results of the two models were compared. Nomogram was employed to visualize the competing risk model. The discrimination, calibration, and clinical utility of this model were evaluated by Harrell concordance index (C-index), time-dependent receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA). Ten-fold cross-validation was further utilized to validate the prognostic nomogram.

RESULTS

Significant prognostic factors affecting CSD were age (P = 0.016), localized involvement (P < 0.0001), and radical resection (P < 0.001) in the multivariate competing risk model. C-indexes were 0.799 and 0.76, and AUC were 0.812 and 0.778 for 3- and 5-year CSD. Calibration plots demonstrated the nomogram was well-fitted, and DCA indicated good clinical utility. The nomogram showed good performance in the 10-fold cross-validation.

CONCLUSION

We successfully built the first competing-risk-based nomogram to predict clinical outcomes in patients with spinal and pelvic chordoma. This well-established nomogram hopes to help clinicians with precise prognostic assessment and thus improve clinical outcomes.

Genetic characteristics and clinical-specific survival prediction in elderly patients with gallbladder cancer: a genetic and population-based study

Background

Biliary system cancers are most commonly gallbladder cancers (GBC). Elderly patients (≥ 65) were reported to suffer from an unfavorable prognosis. In this study, we analyzed the RNA-seq and clinical data of elderly GBC patients to derive the genetic characteristics and the survival-related nomograms.

Methods

RNA-seq data from 14 GBC cases were collected from the Gene Expression Omnibus (GEO) database, grouped by age, and subjected to gene differential and enrichment analysis. In addition, a Weighted Gene Co-expression Network Analysis (WGCNA) was performed to determine the gene sets associated with age grouping further to characterize the gene profile of elderly GBC patients. The database of Surveillance, Epidemiology, and End Results (SEER) was searched for clinicopathological information regarding elderly GBC patients. Nomograms were constructed to predict the overall survival (OS) and cancer-specific survival (CSS) of elderly GBC patients. The predictive accuracy and capability of nomograms were evaluated through the concordance index (C-index), calibration curves, time-dependent operating characteristic curves (ROC), as well as area under the curve (AUC). Decision curve analysis (DCA) was performed to check out the clinical application value of nomograms.

Results

Among the 14 patients with GBC, four were elderly, while the remaining ten were young. Analysis of gene differential and enrichment indicated that elderly GBC patients exhibited higher expression levels of cell cycle-related genes and lower expression levels of energy metabolism-related genes. Furthermore, the WGCNA analysis indicated that elderly GBC patients demonstrated a decrease in the expression of genes related to mitochondrial respiratory enzymes and an increase in the expression of cell cycle-related genes. 2131 elderly GBC patients were randomly allocated into the training cohort (70%) and validation cohort (30%). Our nomograms showed robust discriminative ability with a C-index of 0.717/0.747 for OS/CSS in the training cohort and 0.708/0.740 in the validation cohort. Additionally, calibration curves, AUCs, and DCA results suggested moderate predictive accuracy and superior clinical application value of our nomograms.

Conclusion

Discrepancies in cell cycle signaling and metabolic disorders, especially energy metabolism, were obviously observed between elderly and young GBC patients. In addition to being predictively accurate, the nomograms of elderly GBC patients also contributed to managing and strategizing clinical care.

Development and validation of prognostic nomograms in patients with gallbladder mucinous adenocarcinoma: A population-based study

Background

Gallbladder mucinous adenocarcinoma (GBMAC) is an uncommon malignant gallbladder tumor. There are few studies on its prognosis, with the majority consisting of small series or individual cases. We sought to develop and validate nomograms for predicting overall survival (OS) and cancer-specific survival (CSS) in GBMAC patients.

Methods

The clinicopathological data of GBMAC patients from 1975 to 2019 was extracted from the Surveillance, Epidemiology, and End Results (SEER) database, and all patients were randomly divided into a training cohort (70%) and a validation cohort (30%). Using multivariate Cox regression analyses based on Akaike information criterion (AIC), prognostic and important variables for GBMAC were determined. On the basis of these factors, nomograms were developed to predict the 1-, 3-, and 5-year OS and CSS rates of patients with GBMAC. Multiple parameters, including the area under the subject operating characteristic curve (AUC), the calibration plots, and the decision curve analysis (DCA), were then used to evaluate the accuracy of nomograms.

Results

Following exclusion, a total of 707 GBMAC patients were enrolled, and the training cohort (490, 70%) and validation cohort (217, 30%) were randomly assigned. Grade, surgery, radiation, and SEER stage were predictive factors for patients with GBMAC, as indicated by univariate and multivariate Cox regression analyses based on AIC. We created nomograms for predicting OS and CSS in GBMAC using the four factors. The calibration curves and area under the curves (AUCs) indicated that our nomograms have a moderate degree of predictive accuracy and capability. The results of the DCA revealed that the nomogram has a high predictive value.

Conclusion

We established the first nomograms for predicting 1-, 3-, and 5-year OS and CSS in GBMAC patients, thereby contributing to the prognostication of patients and clinical management.