A Novel Prognostic Nomogram for Gallbladder Cancer after Surgical Resection: A Single-Center Experience

What eliminates the chance for cure: a multi-center evaluation on 10-year follow-up of gallbladder cancer after surgical resection

Curative resection stands as the sole potential cure for gallbladder cancer (GBC); nevertheless, a dearth of knowledge persists regarding long-term follow-up data and prognostic factors that hinder achieving a cure post-surgery. A retrospective cohort study was conducted by analyzing pathologically confirmed initial resections for GBC between 2000 and 2013 across three Chinese medical centers. The concept of observed cure refers to a 10-year survival period devoid of any disease recurrence. Employing a semiparametric proportional hazards mixture cure model enabled the identification of clinicopathological factors impeding a cure for GBC post-surgery. In our current study, a total of 331 patients were included, with a follow-up period exceeding a decade. The median overall survival (OS) was recorded at 31.6 months, with 39 patients (11.78%) achieving a 10-year OS, classified as 10-year survivors. Within this subset, 36 patients reached a 10-year relapse-free survival, denoting cure, and yielding an observed cure rate of 10.88%. Notably, factors such as combined surgical resection involving invaded organs, positive lymph node metastasis, and R1 resection (below 1%) were identified as virtually precluding a cure. Additionally, patients with T3-4 stage, hepatic invasion, advanced AJCC stage or poor tumor differentiation exhibited a low likelihood of achieving cure (below 5%). The discovery of these prognostic factors holds significant value in tailoring individualized treatment strategies and enhancing clinical decision-making processes.

Novel multifactor predictive model for postoperative survival in gallbladder cancer: a multi-center study

BACKGROUND

Gallbladder cancer (GBC) is a highly aggressive malignancy, with limited survival profiles after curative surgeries. This study aimed to develop a practical model for predicting the postoperative overall survival (OS) in GBC patients.

METHODS

Patients from three hospitals were included. Two centers (N = 102 and 100) were adopted for model development and internal validation, and the third center (N = 85) was used for external testing. Univariate and stepwise multivariate Cox regression were used for feature selection. A nomogram for 1-, 3-, and 5-year postoperative survival rates was constructed accordingly. Performance assessment included Harrell's concordance index (C-index), receiver operating characteristic (ROC) curves and calibration curves. Kaplan-Meier curves were utilized to evaluate the risk stratification results of the nomogram. Decision curves were used to reflect the net benefit.

RESULTS

Eight factors, TNM stage, age-adjusted Charlson Comorbidity Index (aCCI), body mass index (BMI), R0 resection, blood platelet count, and serum levels of albumin, CA125, CA199 were incorporated in the nomogram. The time-dependent C-index consistently exceeded 0.70 from 6 months to 5 years, and time-dependent ROC revealed an area under the curve (AUC) of over 75% for 1-, 3-, and 5-year survival. The calibration curves, Kaplan-Meier curves and decision curves also indicated good prognostic performance and clinical benefit, surpassing traditional indicators TNM staging and CA199 levels. The reliability of results was further proved in the independent external testing set.

CONCLUSIONS

The novel nomogram exhibited good prognostic efficacy and robust generalizability in GBC patients, which might be a promising tool for aiding clinical decision-making.

A novel nomogram based on inflammatory-nutritional biomarkers for gallbladder cancer after surgical resection

PURPOSE

Systemic inflammation and nutrition are vital for tumor progression. This study aimed to identify prognostic inflammation nutrition markers and develop a predictive nomogram for gallbladder cancer (GBC).

METHODS

A total of 123 patients with GBC who underwent surgical resection at the First Affiliated Hospital of Soochow University and Suzhou Kowloon Hospital were included in our study. The final prognostic variables were identified using univariate and multivariate analyses. A nomogram model was then established, and the consistency index (C-index), calibration curves, and Kaplan-Meier analysis were performed to evaluate the accuracy and discrimination of the nomogram. The area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA) suggested that our nomogram had better predictive ability and clinical feasibility than a published model.

RESULTS

The cox regression analysis showed that carcinoembryonic antigen (CEA) > 4.580, albumin-bilirubin (ALBI) > -2.091, geriatric nutritional risk index (GNRI) < 90.83, T3-T4, and N2 are independent prognostic factors. A predictive nomogram was constructed with a C-index of 0.793. In the calibration curves, the nomogram-predicted 1-, 3-, and 5-year survival matched well with the actual survival. Kaplan-Meier analysis showed that the high-risk group had worse survival than the low-risk group (P < 0.001). Finally, our nomogram achieved better 1-, 3- and 5-year AUCs than an established model (0.871, 0.844, and 0.781 vs. 0.753, 0.750, and 0.693). DCA also confirmed that our model outperformed the established model.

CONCLUSIONS

In conclusion, our study revealed that CEA > 4.580, GNRI < 90.83, ALBI > -2.091, T3-T4 stage, and N2 were related to clinical outcomes of patients with GBC after surgical resection. The constructed nomogram has superior predictive ability and clinical practicality.

Preoperative Fibrinogen Albumin Ratio is an Effective Biomarker for Prognostic Evaluation of Gallbladder Carcinoma After Radical Resection: A 10-Year Retrospective Study at a Single Center

Background

To explore and screen preoperative serum immune response level-related biomarkers with better prognostic ability and developed a prognostic model for decision-making in clinical practice for gallbladder carcinoma (GBC) patients.

Methods

A total of 427 patients who underwent radical resection for GBC in the Department of Hepatobiliary Surgery of the First Affiliated Hospital of Xi'an Jiaotong University from January 2011 to December 2020 were retrospectively analyzed. Time-dependent receiver operating characteristic (time-ROC) was performed to determine the prognostic predictive power of preoperative biomarkers. A nomogram survival model was established and validated.

Results

Time-ROC indicated that the preoperative fibrinogen-to-albumin ratio (FAR) had a better predictive ability for overall survival among preoperative serum immune response level-related biomarkers. Multivariate analysis indicated that FAR was an independent risk factor (P<0.05). The proportion of clinicopathological characteristics of poor prognosis (such as advanced T stage, and N1-2 stage) was significantly higher in high FAR group (P<0.05). Subgroup analyses indicate the prognostic discrimination ability of FAR depended on CA19-9, CA125, liver involvement, major vascular invasion, perineural invasion, T stage, N stage, and TNM stage (all P <0.05). A nomogram model was established based on the prognostic independent risk factors with the C-index of 0.803 (95% CI:0.771~0.835) and 0.774 (95% CI:0.696~0.852) in the training and testing sets, respectively. The decision curve analysis indicated the nomogram model had a better predictive ability than the FAR and TNM staging system in the training and testing sets.

Conclusion

Preoperative serum FAR has a better predictive ability for overall survival among preoperative serum immune response level-related biomarkers, and it can be used for survival assessment of GBC and guide clinical decision-making.

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.

A novel nomogram based on log odds of positive lymph nodes to predict survival for non-metastatic gallbladder adenocarcinoma after surgery

The prognosis of non-metastatic gallbladder adenocarcinoma (NM-GBA) patients is affected by the status of metastatic lymph nodes. The purpose of this study was to explore the prognostic value of the log odds of positive lymph nodes (LODDS) and develop a novel nomogram to predict the overall survival in NM-GBA patients. A total of 1035 patients confirmed to have NM-GBA were selected from the Surveillance, Epidemiology, and End Results (SEER) database and further divided into training and validation cohorts. The discrimination and calibration of the nomogram were evaluated using the concordance index (C-index), the area under the time-dependent receiver operating characteristic curve (time-dependent AUC), and calibration plots. The net benefits and clinical utility of the nomogram were quantified and compared with those of the 8th edition American Joint Committee on Cancer (AJCC) Tumor-Node-Metastasis (TNM) staging system using decision curve analysis (DCA), net reclassification index (NRI), and integrated discrimination improvement (IDI). The risk stratifications of the nomogram and the TNM-staging system were compared. LODDS showed the highest accuracy in predicting OS for NM-GBA. The C-index (0.730 for the training cohort and 0.746 for the validation cohort) and the time-dependent AUC (> 0.7) indicated the satisfactory discriminative ability of the nomogram. The calibration plots showed a high degree of consistency. The DCA, NRI, and IDI indicated that the nomogram performed significantly better than the TNM-staging (P < 0.05). A novel LODDS-included nomogram was developed and validated to assist clinicians in evaluating the prognosis of NM-GBA patients.

Contrast-enhanced CT radiomics for prediction of recurrence-free survival in gallbladder carcinoma after surgical resection

OBJECTIVES

Gallbladder carcinoma (GBC) is the most common and aggressive biliary tract malignancy with high postoperative recurrence rates. This single-center study aimed to develop and validate a radiomics signature to estimate GBC recurrence-free survival (RFS).

METHODS

This study retrospectively included 204 consecutive patients with pathologically diagnosed GBC and were randomly divided into development (n = 142) and validation (n = 62) cohorts (7:3). The radiomics features of tumor were extracted from preoperative contrast-enhanced CT imaging for each patient. In the development cohort, the least absolute shrinkage and selection operator (LASSO) Cox regression was employed to develop a radiomics signature for RFS prediction. The patients were stratified into high-score or low-score groups according to their median value of radiomics score. A nomogram was established using multivariable Cox regression by incorporating significant pathological predictors and radiomics signatures.

RESULTS

The radiomics signature based on 12 features could discriminate high-risk patients with poor RFS. Multivariate Cox analysis revealed that pT3/4 stage (hazard ratio, [HR] = 2.691), pN2 stage (HR = 3.60), poor differentiation grade (HR = 2.651), and high radiomics score (HR = 1.482) were independent risk variables associated with worse RFS and were incorporated to construct a nomogram. The nomogram displayed good prediction performance in estimating RFS with AUC values of 0.895, 0.935, and 0.907 at 1, 3, and 5 years, respectively.

CONCLUSIONS

The radiomics signature and combined nomogram may assist in predicting RFS in GBC patients.

KEY POINTS

• A radiomics signature extracted from preoperative contrast-enhanced CT can be a useful tool to preoperatively predict RFS of GBC. • T3/T4 stage, N2, poor tumor differentiation, and high radiomics score were positively associated with postoperative recurrence.