Development and Validation a Nomogram for Predicting Overall Survival in Patients With Intrahepatic Cholangiocarcinoma

Prognostic value of albumin-bilirubin grade in patients with cholangiocarcinoma: a systematic review and meta-analysis

BACKGROUND

Cholangiocarcinoma (CCA) is a type of cancer that develops in the biliary tract. CCA accounts for 10% of primary hepatic cancers and is characterized by its aggressive nature and poor prognosis. This systematic review and meta-analysis aims to assess the prognostic value of the novel hepatic function assessment measure known as albumin-bilirubin (ALBI) grade in patients with CCA.

METHOD

A comprehensive search was conducted on PubMed, Web of Science, Embase, and Scopus databases until August 11, 2023. Studies examining the prognostic impact of ALBI grade in patients with CCA were included. The prognostic effect was evaluated using hazard ratio (HR) with 95% confidence intervals (CI). The quality of the included studies was assessed using the Newcastle-Ottawa Scale (NOS). The final meta-analysis was performed using R version 4.3.1.

RESULTS

The final meta-analysis included 13 studies with 3,434 patients. In univariate analysis (HR = 1.90, 95% CI: 1.65-2.19, P < 0.01) and multivariate analysis (HR = 1.88, 95% CI: 1.41-2.52, P < 0.01), higher ALBI grade was associated with lower overall survival (OS) in patients with intrahepatic CCA (ICCA). Higher ALBI grade was also correlated with decreased recurrence-free survival (RFS), with an HR of 1.63 (95% CI: 1.36-1.97, P < 0.01). Subgroup analysis of different ALBI grade comparisons showed consistent findings with our pooled data.

CONCLUSION

A high ALBI grade indicates poor OS and RFS in patients with CCA especially intrahepatic type. ALBI should be considered a reliable and clinically useful prognostic indicator.

REGISTRATION

PROSPERO ID: CRD42022379877.

Development and validation of a diagnostic and prognostic model for bone metastasis of intrahepatic cholangiocarcinoma: a population-based analysis

Background

Bone metastasis (BM) is a common site of metastasis in patients with intrahepatic cholangiocarcinoma (ICC), significantly impacting the quality of life and prognosis of affected individuals. This investigation aimed to assess the risk of BM development in ICC patients and to prognosticate for patients with ICC-associated BM (ICCBM) through the construction of two nomograms.

Methods

We conducted a retrospective analysis of data from 2,651 ICC patients, including 148 cases of BM, documented in the Surveillance, Epidemiology, and End Results (SEER) database spanning 2010 to 2017. Independent predictors for the occurrence of BM in ICC patients were identified via univariate and multivariate logistic regression analyses; simultaneously, independent prognostic indicators for ICCBM patients were ascertained through univariate and multivariate Cox regression analyses. The utility of the nomograms was evaluated through calibration curves, receiver operating characteristic (ROC) curves, decision curve analysis (DCA), and Kaplan-Meier (KM) analysis.

Results

Independent risk factors for BM in ICC included sex, tumor size, lung metastasis, brain metastasis, and intrahepatic metastasis. For ICCBM patients, independent prognostic factors comprised age, chemotherapy, and radiotherapy. The prognostic nomogram exhibited C-indexes of 0.737 [95% confidential interval (CI): 0.682-0.792] for the training cohort and 0.696 (95% CI: 0.623-0.769) for the validation cohort. Calibration curves demonstrated strong concordance between predicted outcomes and observed events. The areas under the curve (AUC) for 3-, 6-, and 12-month cancer-specific survival (CSS) were 0.853, 0.781, and 0.739, respectively, in the training cohort, and 0.794, 0.822, and 0.780 in the validation cohort. DCA illustrated significant net benefits across a broad spectrum of threshold probabilities. KM analysis revealed 1-, 2-, and 3-year CSS rates of 23.91%, 7.55%, and 2.35%, respectively, with a median CSS of 6 months, underscoring the nomograms' capacity to distinctly stratify patients according to survival risk.

Conclusions

The development of these nomograms offers substantial clinical utility in forecasting BM risk among ICC patients and prognosticating for those with ICCBM, thereby facilitating the formulation of more efficacious treatment modalities.

Establishment and external validation of prognosis prediction nomogram for patients with distant metastatic intrahepatic cholangiocarcinoma: based on a large population

BACKGROUND

Most patients with intrahepatic cholangiocarcinoma (ICC) have developed distant metastasis at the time of diagnosis, while there is rear related nomogram to predict the prognosis.

METHODS

Clinical data of patients pathologically diagnosed of ICC with distant metastasis were retrospectively collected from the Surveillance, Epidemiology, and End Results (SEER) database during 2005 to 2019. Finally, patients diagnosed as ICC in the Second Affiliated Hospital of Nanchang University from 2014 to 2019 were collected for external verification. All data were divided into training cohort and validation cohort in a ratio of 7:3. The nomogram was established based on independent prognostic factors using Cox univariate and multivariate analyses. The area under the receiver operating characteristic (ROC) curves (AUC), the calibration curve and the decision curve analysis (DCA) were used to determine the prediction accuracy of the nomogram.

RESULTS

This study finally included 572 ICC with distant metastasis patients, another 32 patients collected by the author's hospital were used as external verification. Results showed that age, surgery, radiotherapy and chemotherapy were independent prognostic factors, and nomogram was established. The AUC of predicting 3, 6, 9-month overall survival were 0.866, 0.841 and 0.786. The ROC curves and calibration curves showed that the nomogram had good predictive accuracy, and DCA showed that the nomogram had good clinical applicability.

CONCLUSIONS

The nomogram has good accuracy in predicting prognosis of DM-ICC patients, which would be of good significance to improve the prognosis of these patients.

Development and validation of web-based nomograms for predicting survival status in patients with intrahepatic cholangiocarcinoma depending on the surgical status: a SEER database analysis

This study aimed to develop and validate prognostic nomograms that can estimate the probability of 1-, 3- and 5-year overall survival (OS) as well as cancer-specific survival (CSS) for Intrahepatic cholangiocarcinoma (ICCA) patients. Clinical data of 1446 patients diagnosed with ICCA between 2010 and 2017 from the Surveillance, Epidemiology, and End Results (SEER) database were analyzed. In both the OS and the CSS group, the training cohort and validation cohort were divided into a 7:3 ratio. Age, sex, AJCC T stage, AJCC N stage, AJCC M stage, surgical status, and tumor grade were selected as independent prognostic risk factors to build the nomograms. To compare the efficacy of predicting 1-, 3-, and 5-year OS and CSS rates of the nomogram with the 8th edition of the American Joint Committee on Cancer (AJCC) staging system, we evaluated the Harrell's index of concordance (C-index), area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA) in both cohorts. The results showed the nomogram for 1-, 3-, and 5-year OS and CSS prediction performed better than the AJCC staging system. In the subgroup analysis for patients could not receive surgery as the primary treatment. We developed two nomograms for predicting the 1-, and 2-year OS and CSS rates following the same analysis procedure. Results indicate that the performance of both nomograms, which contained sex, AJCC T stage, AJCC M stage, chemotherapy, and tumor grade and prognostic factors, was also superior to the AJCC staging system. Meanwhile, four dynamic network-based nomograms were published. The survival analysis showed the survival rate of patients classified as high-risk based on the nomogram score was significantly lower compared to those categorized as low-risk (P < 0.0001). Finally, accurate and convenient nomograms were established to assist clinicians in making more personalized prognosis predictions for ICCA patients.

Development and validation of a nomogram to predict cancer-specific survival with unresected cholangiocarcinoma undergoing external radiotherapy

Objective

To analyze the prognostic factors of patients with cholangiocarcinoma (CCA) who were unresected and received radiotherapy to establish a nomogram model for the prediction of patient cancer-specific survival (CSS).

Methods

Suitable patient cases were selected from the Surveillance, Epidemiology, and End Results (SEER) database, survival rates were calculated using the Kaplan-Meier method, prognostic factors were analyzed by Lasso, Cox regression, and nomogram was developed based on independent prognostic factors to predict 6 and 12 months CSS. The consistency index (C-index), calibration curve, and decision curve analysis (DCA) were tested for the predictive efficacy of the model, respectively.

Results

The primary site, tumor size, T-stage, M-stage, and chemotherapy (P < 0.05) were identified as independent risk factors after Cox and Lasso regression analysis. Patients in training cohort had a 6 months CSS rates was 68.6 ± 2.6%, a 12-month CSS rates was 49.0 ± 2.8%. The median CSS time of 12.00 months (95% CI: 10.17-13.83 months). The C-index was 0.664 ± 0.039 for the training cohort and 0.645 ± 0.042 for the validation cohort. The nomogram predicted CSS and demonstrated satisfactory and consistent predictive performance in 6 (73.4 vs. 64.9%) and 12 months (72.2 vs. 64.9%), respectively. The external validation calibration plot is shown AUC for 6- and 12-month compared with AJCC stage was (71.2 vs. 63.0%) and (65.9 vs. 59.8%). Meanwhile, the calibration plot of the nomogram for the probability of CSS at 6 and 12 months indicates that the actual and nomogram predict that the CSS remains largely consistent. DCA showed that using a nomogram to predict CSS results in better clinical decisions compared to the AJCC staging system.

Conclusion

A nomogram model based on clinical prognostic characteristics can be used to provide CSS prediction reference for patients with CCA who have not undergone surgery but have received radiotherapy.

Web-Based Nomograms for Overall Survival and Cancer-Specific Survival of Bladder Cancer Patients with Bone Metastasis: A Retrospective Cohort Study from SEER Database

BACKGROUND

Our study aimed to explore the prognostic factors of bladder cancer with bone metastasis (BCBM) and develop prediction models to predict the overall survival (OS) and cancer-specific survival (CSS) of BCBM patients.

METHODS

A total of 1438 patients with BCBM were obtained from the SEER database. Patients from 2010 to 2016 were randomly divided into training and validation datasets (7:3), while patients from 2017 were divided for external testing. Nomograms were established using prognostic factors identified through Cox regression analyses and validated internally and externally. The concordance index (C-index), calibration plots, and time-dependent receiver operating characteristic (ROC) curves were used to evaluate the discrimination and calibration of nomogram models, while decision curve analyses (DCA) and Kaplan-Meier (KM) curves were used to estimate the clinical applicability.

RESULTS

Marital status, tumor metastasis (brain, liver, and lung), primary site surgery, and chemotherapy were indicated as independent prognostic factors for OS and CSS. Calibration plots and the overall C-index showed a novel agreement between the observed and predicted outcomes. Nomograms revealed significant advantages in OS and CSS predictions. AUCs for internal and external validation were listed as follows: for OS, 3-month AUCs were 0.853 and 0.849; 6-month AUCs were 0.873 and 0.832; 12-month AUCs were 0.825 and 0.805; for CSS, 3-month AUCs were 0.849 and 0.847; 6-month AUCs were 0.870 and 0.824; 12-month AUCs were 0.815 and 0.797, respectively. DCA curves demonstrated good clinical benefit, and KM curves showed distinct stratification performance.

CONCLUSION

The nomograms as web-based tools were proved to be accurate, efficient, and clinically beneficial, which might help in patient management and clinical decision-making for BCBM patients.

Prognostic nomogram for cancer-specific survival in patients with intrahepatic cholangiocarcinoma after hepatectomy: A population study of 919 patients

Background and Aims

Intrahepatic cholangiocarcinoma has an increasing global incidence and mortality rate. Hepatectomy is still the most effective curative treatment for patients with ICC, but the prognosis of patients with ICC is still poor even after curative resection. This study aimed to incorporate important factors obtained from SEER database to construct and validate a nomogram for predicting the cancer-specific survival of patients with ICC after hepatectomy.

Methods

We obtained patient data from SEER database. The nomogram was constructed base on six prognostic factors for predicting CSS rates in ICC patients. The nomogram was validated by C-index, ROC curve and calibration curves.

Results

A total of 919 patients with ICC after hepatectomy between 2000 and 2018 were included in this study. A nomogram based on six independent prognostic factors (Black race, AJCC T, AJCC N, AJCC M, chemotherapy and PLNR ≥ 0.15) was developed for the prediction of CSS at 3 and 5 years. The C-index of the nomogram and AJCC stage system were 0.709 and 0.657 in the training cohort respectively. The 3- and 5-year AUCs of nomogram were 0.744 and 0.75 in the training cohort. The calibration plots indicated that there was good agreement between the actual observations and predictions.

Conclusions

In conclusion, we constructed and validated a nomogram for predicting the 3- and 5-year CSS in ICC patients after hepatectomy. We have confirmed the precise calibration and acceptable discrimination power of our nomogram. The predictive power of this nomogram may be improved by considering other potential important factors and also by external validation.

Personalized intrahepatic cholangiocarcinoma prognosis prediction using radiomics: Application and development trend

Radiomics was proposed by Lambin et al. in 2012 and since then there has been an explosion of related research. There has been significant interest in developing high-throughput methods that can automatically extract a large number of quantitative image features from medical images for better diagnostic or predictive performance. There have also been numerous radiomics investigations on intrahepatic cholangiocarcinoma in recent years, but no pertinent review materials are readily available. This work discusses the modeling analysis of radiomics for the prediction of lymph node metastasis, microvascular invasion, and early recurrence of intrahepatic cholangiocarcinoma, as well as the use of deep learning. This paper briefly reviews the current status of radiomics research to provide a reference for future studies.

Establishment and validation of a prognostic nomogram for extrahepatic cholangiocarcinoma

Simple summary

Accurately estimate the prognosis of patients with ECCA is important. However, the TNM system has some limitations, such as low accuracy, exclusion of other factors (e.g., age and sex), and poor performance in predicting individual survival risk. In contrast, a nomogram-based clinical model related to a comprehensive analysis of all risk factors is intuitive and straightforward, facilitating the probabilistic analysis of tumor-related risk factors. Simultaneously, a nomogram can also effectively drive personalized medicine and facilitate clinicians for prognosis prediction. Therefore, we construct a novel practical nomogram and risk stratification system to predict CSS in patients with ECCA.

Background

Accurately estimate the prognosis of patients with extrahepatic cholangiocarcinoma (ECCA) was important, but the existing staging system has limitations. The present study aimed to construct a novel practical nomogram and risk stratification system to predict cancer-specific survival (CSS) in ECCA patients.

Methods

3415 patients diagnosed with ECCA between 2010 and 2015 were selected from the SEER database and randomized into a training cohort and a validation cohort at 7:3. The nomogram was identified and calibrated using the C-index, receiver operating characteristic curve (ROC), and calibration plots. Decision curve analysis (DCA), net reclassification index (NRI), integrated discrimination improvement (IDI) and the risk stratification were used to compare the nomogram with the AJCC staging system.

Results

Nine variables were selected to establish the nomogram. The C-index (training cohort:0.785; validation cohort:0.776) and time-dependent AUC (>0.7) showed satisfactory discrimination. The calibration plots also revealed that the nomogram was consistent with the actual observations. The NRI (training cohort: 1-, 2-, and 3-year CSS:0.27, 0.27,0.52; validation cohort:1-,2-,3-year CSS:0.48,0.13,0.34), IDI (training cohort: 1-, 2-, 3-year CSS:0.22,0.18,0.16; validation cohort: 1-,2-,3-year CSS:0.18,0.16,0.17), and DCA indicated that the established nomogram significantly outperformed the AJCC staging system (P<0.05) and had better recognition compared to the AJCC staging system.

Conclusions

We developed a practical prognostic nomogram to help clinicians assess the prognosis of patients with ECCA.

Lymph Node Ratio Nomogram-Based Prognostic Model for Resected Distal Cholangiocarcinoma

BACKGROUND

Several variables have been described as prognostic factors for resected distal cholangiocarcinoma (dCC), including lymph node metastases (N status) and lymph node ratio (LNR). The present study aimed to evaluate the prognostic value of LNR on survival and to establish a novel prognostic nomogram to predict the cancer-specific recurrence-free survival (RFS) of dCC.

STUDY DESIGN

Between December 2006 and September 2020, 415 consecutive patients who underwent pancreaticoduodenectomy (PD) for dCC in 10 centers were identified. Multivariate Cox analysis was used to identify all independent risk factors among several prognostic factors. A nomogram was then developed and assessed by integrating the independent prognostic factors into the model, and the concordance index (C-index) was used to evaluate its performance.

RESULTS

According to Cox regression multivariate analysis, a nomogram based on independent prognostic factor for RFS was performed including LNR 15 (hazard ratio [HR] 2.442, 95% CI 1.348-4.425, p = 0.003), perineural invasion (HR 3.100, 95% CI 1.183-8.122, p = 0.025), differentiation grade (HR 2.100, 95% CI 1.172-4.143, p = 0.021), and radicality of PD (HR 2.276, 95% CI 1.223-4.234, p = 0.009). The C-index of the nomogram, tailored based on the previous significant factors, was 0.8.

CONCLUSIONS

LNR15 yields a high prognostic efficiency for RFS. The nomogram based on LNR can provide an accurate prognosis assessment for patients with resected dCC.

Diagnostic and prognostic nomograms for newly diagnosed intrahepatic cholangiocarcinoma with brain metastasis: A population-based analysis

Brain metastasis (BM) is one of the rare metastatic sites of intrahepatic cholangiocarcinoma (ICC). ICC with BM can seriously affect the quality of life of patients and lead to a poor prognosis. The aim of this study was to establish two nomograms to estimate the risk of BM in ICC patients and the prognosis of ICC patients with BM. Data on 19,166 individuals diagnosed with ICC were retrospectively collected from the Surveillance, Epidemiology, and End Results (SEER) database. Independent risk factors and prognostic factors were identified by the logistic and the Cox regression, respectively. Next, two nomograms were developed, and their discrimination was estimated by concordance index (C-index) and calibration plots, while the clinical benefits of the prognostic nomogram were evaluated using the receiver operating characteristic (ROC) curves, the decision curve analysis (DCA), and the Kaplan-Meier analyses. The independent risk factors for BM were T stage, N stage, surgery, alpha-fetoprotein (AFP) level, and tumor size. T stage, surgery, radiotherapy, and bone metastasis were prognostic factors for overall survival (OS). For the prognostic nomogram, the C-index was 0.759 (95% confidence interval (CI) = 0.745-0.773) and 0.764 (95% CI = 0.747-0.781) in the training and the validation cohort, respectively. The calibration curves revealed a robust agreement between predictions and actual observations probability. The area under curves (AUCs) for the 3-, 6-, and 9-month OS were 0.721, 0.727, and 0.790 in the training cohort and 0.702, 0.777, and 0.853 in the validation cohort, respectively. The DCA curves yielded remarkable positive net benefits over a wide range of threshold probabilities. The Kaplan-Meier analysis illustrated that the nomogram could significantly distinguish the population with different survival risks. We successfully established the two nomograms for predicting the incidence of BM and the prognosis of ICC patients with BM, which may assist clinicians in choosing more effective treatment strategies.