Evaluation and Recommendation of the 8th Edition of American Joint Committee on Cancer (AJCC) Staging System for Intrahepatic Cholangiocarcinoma (ICC) in 820 Patients from the Surveillance, Epidemiology, and End Results (SEER) Database

A new stage for predicting the prognosis of granulomatous lobular mastitis

INTRODUCTION

The prognosis of granulomatous lobular mastitis (GLM) had been poor, primarily due to the lack of a unified disease assessment standard.

OBJECTIVE

The purpose of this cohort study was to establish a staging system for GLM to more accurately evaluate the prognosis of patients.

METHODS

This study retrospectively collected data from 264 GLM patients who visited our hospital between January 2017 and December 2023. Through logistic regression analysis, factors associated with prognosis were identified, which served as the basis for creating a new staging system.

RESULTS

Univariate and multivariate logistic regression analysis revealed that hyperlipidemia (HR: 2.031; 95% CI: 1.100-3.750) and microabscesses (HR: 2.087; 95% CI = 1.138-3.827) were significant independent risk factors affecting the prognosis of GLM patients. Based on the results of logistic analysis, three different stages were ultimately established, and it was found that stage C had the highest AUC value (AUC: 0.642), followed by stage B (AUC: 0.628), with stage A (AUC: 0.614) having the lowest. The Delong test revealed no significant difference in AUC values between stage A and stage B (P =  0.255), nor between stage B and stage C (P =  0.263). However, the AUC value of the stage C was found to be higher than that of stage A (P <  0.001). Given that stage C has the highest AUC value, this study selected stage C as the final stage for evaluating the prognosis of GLM patients and named it the 1st edition of GLM stage.

CONCLUSIONS

This study constructed a rigorous and widely applicable GLM staging system (the 1st edition of GLM stage). The system demonstrated good predictive outcomes and provided strong support for clinical decision-making.

To accurately predict lymph node metastasis in patients with mass-forming intrahepatic cholangiocarcinoma by using CT radiomics features of tumor habitat subregions

BACKGROUND

This study aims to introduce the concept of habitat subregions and construct an accurate prediction model by analyzing refined medical images, to predict lymph node metastasis (LNM) in patients with intrahepatic cholangiocarcinoma (ICC) before surgery, and to provide personalized support for clinical decision-making.

METHODS

Clinical, radiological, and pathological data from ICC patients were retrospectively collected. Using information from the arterial and venous phases of multisequence CT images, tumor habitat subregions were delineated through the K-means clustering algorithm. Radiomic features were extracted and screened, and prediction models based on different subregions were constructed and compared with traditional intratumoral models. Finally, a lymph node metastasis prediction model was established by integrating the features of several subregional models, and its performance was evaluated.

RESULTS

A total of 164 ICC patients were included in this study, 103 of whom underwent lymph node dissection. The patients were divided into LNM- and LNM + groups on the basis of lymph node status, and significant differences in white blood cell indicators were found between the two groups. Survival analysis revealed that patients with positive lymph nodes had significantly worse prognoses. Through cluster analysis, the optimal number of habitat subregions was determined to be 5, and prediction models based on different subregions were constructed. A comparison of the performance of each model revealed that the Habitat1 and Habitat5 models had excellent performance. The optimal model obtained by fusing the features of the Habitat1 and Habitat5 models had AUC values of 0.923 and 0.913 in the training set and validation set, respectively, demonstrating good predictive ability. Calibration curves and decision curve analysis further validated the superiority and clinical application value of the model.

CONCLUSIONS

This study successfully constructed an accurate prediction model based on habitat subregions that can effectively predict the lymph node metastasis of ICC patients preoperatively. This model is expected to provide personalized decision support to clinicians and help to optimize treatment plans and improve patient outcomes.

Risk stratification in gastric cancer lung metastasis: Utilizing an overall survival nomogram and comparing it with previous staging

BACKGROUND

Gastric cancer (GC) is prevalent and aggressive, especially when patients have distant lung metastases, which often places patients into advanced stages. By identifying prognostic variables for lung metastasis in GC patients, it may be possible to construct a good prediction model for both overall survival (OS) and the cumulative incidence prediction (CIP) plot of the tumour.

AIM

To investigate the predictors of GC with lung metastasis (GCLM) to produce nomograms for OS and generate CIP by using cancer-specific survival (CSS) data.

METHODS

Data from January 2000 to December 2020 involving 1652 patients with GCLM were obtained from the Surveillance, epidemiology, and end results program database. The major observational endpoint was OS; hence, patients were separated into training and validation groups. Correlation analysis determined various connections. Univariate and multivariate Cox analyses validated the independent predictive factors. Nomogram distinction and calibration were performed with the time-dependent area under the curve (AUC) and calibration curves. To evaluate the accuracy and clinical usefulness of the nomograms, decision curve analysis (DCA) was performed. The clinical utility of the novel prognostic model was compared to that of the 7th edition of the American Joint Committee on Cancer (AJCC) staging system by utilizing Net Reclassification Improvement (NRI) and Integrated Discrimination Improvement (IDI). Finally, the OS prognostic model and Cox-AJCC risk stratification model modified for the AJCC system were compared.

RESULTS

For the purpose of creating the OS nomogram, a CIP plot based on CSS was generated. Cox multivariate regression analysis identified eleven significant prognostic factors (P < 0.05) related to liver metastasis, bone metastasis, primary site, surgery, regional surgery, treatment sequence, chemotherapy, radiotherapy, positive lymph node count, N staging, and time from diagnosis to treatment. It was clear from the DCA (net benefit > 0), time-dependent ROC curve (training/validation set AUC > 0.7), and calibration curve (reliability slope closer to 45 degrees) results that the OS nomogram demonstrated a high level of predictive efficiency. The OS prediction model (New Model AUC = 0.83) also performed much better than the old Cox-AJCC model (AUC difference between the new model and the old model greater than 0) in terms of risk stratification (P < 0.0001) and verification using the IDI and NRI.

CONCLUSION

The OS nomogram for GCLM successfully predicts 1- and 3-year OS. Moreover, this approach can help to appropriately classify patients into high-risk and low-risk groups, thereby guiding treatment.

Artificial intelligence CT radiomics to predict early recurrence of intrahepatic cholangiocarcinoma: a multicenter study

OBJECTIVES

In this multicenter study, we sought to develop and validate a preoperative model for predicting early recurrence (ER) risk after curative resection of intrahepatic cholangiocarcinoma (ICC) through artificial intelligence (AI)-based CT radiomics approach.

MATERIALS AND METHODS

A total of 311 patients (Derivation: 160; Internal and two external validations: 36, 74 and 61) from 8 medical centers who underwent curative resection were collected retrospectively. In derivation cohort, radiomics and clinical-radiomics models for ER prediction were constructed by LightGBM (a machine learning algorithm). A clinical model was also developed for comparison. Model performance was validated in internal and two external cohorts by ROC. In addition, we investigated the interpretability of the LightGBM model.

RESULTS

The combined clinical-radiomics model that included 15 radiomic features and 3 clinical features (CA19-9 > 1000 U/ml, vascular invasion and tumor margin), resulting in the area under the curves (AUCs) of 0.974 (95% CI 0.946-1.000) in the derivation cohort, and 0.871-0.882 (95% CI 0.672-0.962) in the internal and external validation cohorts, respectively, which are higher than the AJCC 8th TNM staging system (AUCs: 0.686-0.717, p all < 0.05). Especially, the sensitivity of this machine learning model could reach 94.6% on average for all the cohorts.

CONCLUSIONS

This AI-driven combined radiomics model may provide as a useful tool to preoperatively predict ER and improve therapeutic management of ICC patients.

Impact of Staging Concordance and Downstaging After Neoadjuvant Therapy on Survival Following Resection of Intrahepatic Cholangiocarcinoma: A Bayesian Analysis

INTRODUCTION

Concordance between clinical and pathological staging, as well as the overall survival (OS) benefit associated with neoadjuvant therapy (NAT) remain ill-defined. We sought to determine the impact of staging accuracy and NAT downstaging on OS among patients with intrahepatic cholangiocarcinoma (ICC).

METHODS

Patients treated for ICC between 2010 and 2018 were identified using the National Cancer Database. A Bayesian approach was applied to estimate NAT downstaging. OS was assessed relative to staging concordant/overstaged disease treated with upfront surgery, understaged disease treated with upfront surgery, no downstaging, and downstaging after NAT.

RESULTS

Among 3384 patients, 2904 (85.8%) underwent upfront surgery, whereas 480 (14.2%) received NAT and 85/480 (18.4%) were downstaged. Patients with cT3 (odds ratio [OR] 2.12, 95% confidence interval [CI] 1.34-3.34), cN1 (OR 2.47, 95% CI 1.71-3.58) disease, and patients treated at high-volume facilities (OR 1.63, 95% CI 1.13-2.36) were more likely to receive NAT (all p < 0.05). Median OS was 40.1 months (95% CI 38.6-43.4). Patients with cT1-2N1 (NAT: 31.5 months vs. upfront surgery: 22.4 months; p = 0.04) and cT3-4N1 (NAT: 27.8 months vs. upfront surgery: 14.4 months; p = 0.01) disease benefited most from NAT. NAT downstaging decreased the risk of death among patients with cT3-4N1 disease (hazard ratio [HR] 0.35, 95% CI 0.15-0.82). In contrast, understaged patients with cT1-2N0/X (HR 2.15, 95% CI 1.83-2.53) and cT3-4N0/X (HR 1.71, 95% CI 1.06-2.74) disease treated with upfront surgery had increased risk of death.

CONCLUSIONS

Patients with N1 ICC treated with NAT demonstrated improved OS compared with upfront surgery. Downstaging secondary to NAT conferred survival benefits among patients with cT3-4N1 versus upfront surgery. NAT should be considered in ICC patients with advanced T disease and/or nodal metastases.

Long-Term Recurrence-Free and Overall Survival Differ Based on Common, Proliferative, and Inflammatory Subtypes After Resection of Intrahepatic Cholangiocarcinoma

INTRODUCTION

While generally associated with poor prognosis, intrahepatic cholangiocarcinoma (ICC) can have a heterogeneous presentation and natural history. We sought to identify specific ICC subtypes that may be associated with varied long-term outcomes and patterns of recurrence after liver resection.

METHODS

Patients who underwent curative-intent resection for ICC from 2000 to 2020 were identified from a multi-institutional database. Hierarchical cluster analysis characterized three ICC subtypes based on morphology (i.e., tumor burden score [TBS]) and biology (i.e., preoperative neutrophil-to-lymphocyte ratio [NLR] and CA19-9 levels).

RESULTS

Among 598 patients, the cluster analysis identified three ICC subtypes: Common (n = 300, 50.2%) (median, TBS: 4.5; NLR: 2.4; CA19-9: 38.0 U/mL); Proliferative (n = 246, 41.1%) (median, TBS: 8.8; NLR: 2.9; CA19-9: 71.2 U/mL); Inflammatory (n = 52, 8.7%) (median, TBS: 5.4; NLR: 12.6; CA19-9: 26.7 U/mL). Median overall survival (OS) (Common: 72.0 months; Proliferative: 31.4 months; Inflammatory: 22.9 months) and recurrence-free survival (RFS) (Common: 21.5 months; Proliferative: 11.9 months; Inflammatory: 9.0 months) varied considerably among the different ICC subtypes (all p < 0.001). Even though patients with Inflammatory ICC had more favorable T-(T1/T2, Common: 84.4%; Proliferative: 80.6%; Inflammatory: 86.5%) and N-(N0, Common: 14.0%; Proliferative: 20.7%; Inflammatory: 26.9%) disease, the Inflammatory subtype was associated with a higher incidence of intra- and extrahepatic recurrence (Common: 15.8%; Proliferative: 24.2%; Inflammatory: 28.6%) (all p = 0.01).

CONCLUSIONS

Cluster analysis identified three distinct subtypes of ICC based on TBS, NLR, and CA19-9. ICC subtype was associated with RFS and OS and predicted worse outcomes among patients. Despite more favorable T- and N-disease, the Inflammatory ICC subtype was associated with worse outcomes ICC subtype should be considered in the prognostic stratification of patients.

Knockdown of FGFR3 inhibits the proliferation, migration and invasion of intrahepatic cholangiocarcinoma

The FGF/FGFR signaling axis deregulation of the fibroblast growth factor receptor (FGFR) family is closely related to tumorigenesis, tumor progression and drug resistance to anticancer therapy. And fibroblast growth factor receptor 3 (FGFR3) is one member of this family. In this study, we aimed to investigate the effect of siRNA-induced knockdown of FGFR3 on the biological behaviors of intrahepatic cholangiocarcinoma (ICC). The expression levels of FGFR3 were determined in three intrahepatic cholangiocarcinoma cell lines RBE, HUCCT1 and HCCC9810 cell lines by Western blot. FGFR3 expression in RBE cell line was knocked down by siRNA. Our study found that knockdown of FGFR3 inhibited the migration, invasion and proliferation of ICC cells using Wound healing assay, Transwell migration and invasion assays and Cell proliferation assay. And significantly down-regulated the protein expression levels of MMP2, cyclinD1, and NCadherin, but had no significant effect on MMP9, cyclinD3, vimentin, E-cadherin protein. In addition, we found that ERK/c-Myc presumably is its signaling pathway by bioinformatics analysis and Western blot verification. To sum up, knockdown of FGFR3 inhibited the migration, invasion and proliferation of ICC cells. It demonstrated that FGFR3 probably becomes a therapeutic target for ICC and increases the proportion of potentially curable intrahepatic cholangiocarcinoma patients treated with FGFR inhibitors.

Predictors of Distant Metastasis and Prognosis in Newly Diagnosed T1 Intrahepatic Cholangiocarcinoma

Background

According to American Joint Committee on Cancer (AJCC) 8th staging system, T1 intrahepatic cholangiocarcinoma (T1 ICC) is considered a tumor with no vascular invasion. However, T1 ICC usually occurs distant metastasis (DM), and the clinical features of these patients could help clinicians identify the high-risk population.

Methods

We reviewed 1959 newly diagnosed patients with T1 ICC from the Surveillance, Epidemiology, and End Results (SEER) database during 2004-2018. Logistic regression models and Cox proportional hazards models were conducted to predict the risk of DM and overall survival (OS), respectively, and then, web-based nomograms were constructed. Decision curve analysis (DCA) and clinical impact curves (CIC) were used to measure the clinical utility of the models. The low-, medium-, and high-risk groups were identified by calculating the summary of the risk points. Nomograms on the web were also created to help clinicians better use these prediction models.

Results

Tumor size and lymph node metastasis accounted for the first two largest proportions among the DM nomogram scores, while surgery, DM, age at diagnosis, chemotherapy, and lymph node metastasis occupied the largest percentage in OS nomogram. DM nomogram was established for these newly diagnosed patients with T1 ICC, and OS nomogram was developed to visually predict the OS rate of 3, 5, and 10 years. The calibration curves revealed a valid predictive accuracy of nomograms, of which the C-index was 0.703 and 0.740, respectively, for good discrimination. DCAs, CICs, and risk subgroups showed the clinical validity of these nomograms. Two websites were created to make it easier to use these nomograms.

Conclusions

Novel web-based nomograms predicting the risk of DM and OS for T1 ICC were constructed. These predictive tools might help clinicians make precise clinical strategies for each patient with T1 ICC.

Sintilimab Combined with Lenvatinib for Advanced Intrahepatic Cholangiocarcinoma in Second-Line Setting—A Multi-Center Observational Study

Background

Patients with advanced intrahepatic cholangiocarcinoma (iCCA) have a poor prognosis and a substantial unmet clinical need. The study was aimed to investigate the efficacy and safety of sintilimab combined with lenvatinib for advanced iCCA in second-line setting.

Methods

The patients at multiple centers, who progressed after the first-line chemotherapy or could not tolerate chemotherapy, were treated with the combination of sintilimab plus lenvatinib. The primary endpoint was time to progression (TTP), and the secondary endpoints included tumor objective response rate (ORR), disease control rate (DCR), overall survival (OS), and toxicity. Prognostic factors were analyzed using Cox regression analysis.

Results

A total of 41 patients with advanced iCCA were enrolled for this multi-center observational study. Under a median follow-up of 12.1 months, the median age was 59 years (range, 33–75 years). Sixteen patients died of disease progression, with a median TTP of 6.6 months (95% CI, 4.9–8.3). ORR and DCR were 46.3% and 70.3%, respectively. The patients with PD-L1 TPS ≥10% reported a significantly higher ORR compared to those with PD-L1 TPS <10%, 93.8% (15/16) vs. 16.0% (4/25), p<0.001. The median TTP was significantly improved in patients with PD-L1 TPS ≥10%, 16.9 months (95% CI, 7.5–26.3) vs. 4.1 months (95% CI, 1.8–6.4), p=0.001. Attaining treatment response predicts favorable TTP in a multivariate Cox model. Treatment-emergent adverse events occurred with 70.3% probability, and no treatment-related death had been reported.

Conclusion

The combination of sintilimab plus lenvatinib is effective and well tolerated for advanced iCCA in the second-line setting. PD-L1 TPS expression may predict the efficacy of the combination therapy. Further investigation is warranted to investigate this combination regimen in advanced iCCA.

Oncological relevance of major hepatectomy with inferior vena cava resection for intrahepatic cholangiocarcinoma

BACKGROUND

This study aimed to investigate the short- and long-terms outcomes of patients undergoing major hepatectomy (MH) with inferior vena cava (IVC) resection for intrahepatic cholangiocarcinoma (ICC).

METHODS

Data from all patients who underwent MH for ICC with or without IVC resection between 2010 and 2018 were analysed retrospectively. Postoperative outcomes, overall survival (OS), and recurrence-free survival (RFS) were compared in the whole population. A propensity score matching (PSM) analysis and an inverse probability weighting analysis (IPW) were performed to assess the influence of IVC resection on short- and long-terms outcomes.

RESULTS

Among the 78 patients who underwent MH, 20 had IVC resection (IVC patients). Overall, the mortality and severe complication rate were 8% and 20%, respectively. IVC patients required more extended hepatectomies (p = 0.001) and had increased rates of transfusions (p = 0.001), however they did not experience increased postoperative morbidity, even after PSM. The 1-, 3- and 5-years OS and DFS were 78%, 45%, and 32% and 48%, 20%, and 16%, respectively. IVC was not associated with decreased OS (p = 0.52) and/or RFS (p = 0.85), even after IPW.

CONCLUSION

MH with IVC resection for ICC seems to provide acceptable short- and long-term results in a selected population of patients.

A Nomogram in Predicting Risks of Intrahepatic Cholangiocarcinoma After Partial Hepatectomy for Hepatolithiasis

BACKGROUND

Hepatolithiasis is associated with the development of intrahepatic cholangiocarcinoma (ICC). This study sought to investigate risk factors of ICC for hepatolithiasis after partial hepatectomy (PH) and to develop a model for predicting ICC risk.

METHODS

Data on consecutive patients who underwent PH for hepatolithiasis at the Eastern Hepatobiliary Surgery Hospital between January 2009 and December 2011 were reviewed. Independent risk factors of ICC identified by Cox regression model were used to develop a nomogram in predicting ICC after PH for hepatolithiasis.

RESULTS

Of 2056 patients, 168 developed ICC at a median follow-up of 7.2 years. The cumulative incidences of ICC at 3, 5, and 8 years after PH for hepatolithiasis were 3.0%, 6.5%, and 12.9%, respectively. Independent risk factors of ICC were identified to be a long duration of hepatolithiasis-related symptoms (hazard ratio, 1.088 [95% confidence interval, 1.057-1.120]), metabolic syndrome (2.036 [1.210-3.425]), a high neutrophil-to-lymphocyte ratio (1.250 [1.009-2.816] for 3-5 vs ≤3; 1.538 [1.048-2.069] for ≥5 vs ≤3), hepatic atrophy (1.711 [1.189-2.462]), segmental intensity differences (1.513 [1.052-2.176]), persistent biliary strictures (2.825 [1.480-5.391]), and residual stone disease (2.293 [1.511-3.481]). By incorporating these factors, a constructed nomogram showed a concordance index of 0.721 to predict ICC. The calibration plots demonstrated good agreement between observed and predicted morbidities. The optimal cutoff point for the nomogram was 48 in differentiating between high and low-risk of ICC.

CONCLUSIONS

A nomogram for predicting ICC after PH for hepatolithiasis was constructed based on risk factors of developing ICC. Patients with a nomogram point of ≥48 were predicted to have a high risk of ICC.

Reappraisal of the T Category for Solitary Intrahepatic Cholangiocarcinoma by Tumor Size in 611 Early-Stage (T1-2N0M0) Patients After Hepatectomy: a Surveillance, Epidemiology, and End Results (SEER) Analysis

BACKGROUND

The association between tumor size and survival in patients with intrahepatic cholangiocarcinoma (ICC) after hepatectomy is controversial, and the T category in the American Joint Committee on Cancer (AJCC) stage for ICC is a topic of debate.

METHODS

Data from 611 T1-2N0M0 ICC patients classified by the AJCC 8th edition who underwent hepatectomy were extracted from the Surveillance, Epidemiology, and End Results (SEER) database during 1988-2015. Cancer-specific survival was evaluated using Kaplan-Meier analysis. The optimal cutoff value of solitary tumor size was used an adjusted p value approach to discriminating patient survival.

RESULTS

In the AJCC 8th staging system, using a 5-cm cut-off value of tumor size for solitary ICC without vascular invasion (S/VI-) was not associated with survival in T1 category (p = 0.201), and multifocal ICC with vascular invasion had a worse survival than solitary ICC with vascular invasion (S/VI+) in T2 category (p = 0.014). Tumor size was a prognostic factor for both S/VI- and S/VI+, the optimal cutoff value of tumor size was obtained 8 cm for S/VI- and 3 cm for S/VI+. S/VI- ≤ 8 cm had a similar survival to S/VI+ ≤ 3 cm (p = 0.126), S/VI- > 8 cm had a similar survival to S/VI+ > 3 cm (p = 0.655), and multifocal ICC had a similar survival with S/VI- > 8 cm (p = 0.159) and S/VI+ > 3 cm (p = 0.196). When the cohort was divided into two groups-new T1 (S/VI- ≤ 8 cm and S/VI+ ≤ 3 cm) and new T2 (S/VI- > 8 cm, S/VI+ > 3 cm and multifocal ICC)-significant survival difference was observed (p < 0.0001).

CONCLUSIONS

The discriminatory power of the AJCC 8th edition for solitary ICC could be further enhanced by subdividing tumors according to size and vascular invasion (8 cm for S/VI- and 3 cm for S/VI+).

Prognostic factors and survival outcome of primary pulmonary acinar cell carcinoma

Purpose

The objective of our study was to investigate the epidemiologic characteristics and prognostic factors in patients with pulmonary acinar cell carcinoma (PACC).

Methods

PACC patients diagnosed between 1975 and 2016 were identified from the Surveillance, Epidemiology, and End Results (SEER) database. The trend in PACC incidence was assessed using joinpoint regression software. Overall survival (OS) and disease‐specific survival (DSS) were evaluated using the Kaplan–Meier method and log‐rank test. Univariate and multivariate Cox regression analysis was performed to identify the independent prognostic factors for OS and DSS. Nomograms to predict survival possibilities were constructed based on the identified independent prognostic factors.

Results

A total of 2918 patients were identified with PACC. The mean age was 65.2 ± 8.95 years with a female to male of 1.6:1. The incidence of PACC steadily increased by an annual percentage change (APC) of 3.2% (95% CI 2.1–4.4, p < 0.05). Multivariate Cox regression analysis revealed that age, gender, race, stage, grade, tumor size, number of positive lymph nodes, surgery, and chemotherapy were independent prognostic factors for survival. Nomograms specifically for PACC were constructed to predict 1‐ and 5‐year OS and DSS possibility, respectively. The concordance index (C‐index) and calibration plots showed the established nomograms had robust and accurate performance.

Conclusion

PACC was rare but the incidence has been steadily increasing over the past four decades. Survival has improved in recent years. Surgery or chemotherapy could provide better OS and DSS. The established nomograms specifically for PACC were robust and accurate in predicting 1‐ and 5‐year OS and DSS.

Liver Metastases of Intrahepatic Cholangiocarcinoma: Implications for an Updated Staging System

BACKGROUND AND AIMS

Intrahepatic cholangiocarcinoma (iCCA) with liver metastases is perceived to have a poor prognosis, but the American Joint Committee on Cancer (AJCC) classifies them as early stage in the absence of lymph nodes or extrahepatic spread.

APPROACH AND RESULTS

Patients with iCCA from the European Network for the Study of Cholangiocarcinoma (ENS-CCA) and Surveillance, Epidemiology, and End Results (SEER) registries with survival/staging (AJCC v.7) data were eligible. Modified staging was used (mAJCC v.7): group A: stages I-III (excluding T2bN0); group B: stage IVa (excluding T2bN1M0); group C: liver metastases (T2bN0/1); and group D: stage IVb (extrahepatic metastases). Survival analysis (Kaplan-Meier and Cox regression) was performed in an ENS-CCA training cohort (TC) and findings internally (ENS-CCA iVC) and externally (SEER) validated. The aim was to assess whether liver metastases (group C) had a shorter survival compared to other early stages (group A) to propose a modified version of AJCC v.8 (mAJCC v.8). A total of 574 and 4,171 patients from the ENS-CCA and SEER registries were included. Following the new classification, 19.86% and 17.31% of patients from the ENS-CCA and SEER registries were reclassified into group C, respectively. In the ENS-CCA TC, multivariable Cox regression was adjusted for obesity (p = 0.026) and performance status (P < 0.001); patients in group C (HR, 2.53; 95% CI, 1.18-5.42; P = 0.017) had a higher risk of death (vs. group A). Findings were validated in the ENS-CCA iVC (HR, 2.93; 95% CI, 2.04-4.19; P < 0.001) and in the SEER registry (HR, 1.88; 95% CI, 1.68-2.09; P < 0.001).

CONCLUSIONS

iCCA with liver metastases has a worse outcome than other early stages of iCCA. Given that AJCC v.8 does not take this into consideration, a modification of AJCC v.8 (mAJCC v.8), including "liver metastases: multiple liver lesions, with or without vascular invasion" as an "M1a stage," is suggested.