Epidemiological and Clinical Characteristics of Five Rare Pathological Subtypes of Hepatocellular Carcinoma

Abstract

Background: Hepatocellular carcinoma (HCC) is a highly heterogeneous tumor with several rare pathological subtypes and which is still poorly understood. This study aimed to describe the epidemiological and clinical spectrum of five rare HCC subtypes and develop a competing risk nomogram for cancer-specific survival prediction.

Methods: The study cohort was recruited from the Surveillance, Epidemiology, and End Results database. The clinicopathological data of 50,218 patients histologically diagnosed with classic HCC and five rare subtypes (ICD-O-3 Histology Code = 8170/3-8175/3) between 2004 and 2018 were reviewed. The annual percent change (APC) was calculated utilizing Joinpoint regression. The nomogram was developed based on multivariable competing risk survival analyses. Akaike information criterion, Bayesian information criterion, C-index, calibration curve, and area under the receiver operating characteristic curve were obtained to evaluate the prognostic performance. A decision curve analysis was introduced to examine the clinical value of the models.

Results: Despite scirrhous carcinoma, which showed a decreasing trend (APC = -6.8%, P = 0.025), the morbidity of other rare subtypes remained stable from 2004 to 2018. The incidence-based mortality was plateau in all subtypes during the period. Clear cell carcinoma is the most common subtype (n = 551, 1.1%), followed by subtypes of fibrolamellar (n = 241, 0.5%), scirrhous (n = 82, 0.2%), spindle cell (n = 61, 0.1%), and pleomorphic (n = 17, ~0%). The patients with fibrolamellar carcinoma were younger and more likely to have a non-cirrhotic liver and better prognoses. Scirrhous carcinoma shared almost the same macro-clinical characteristics and outcomes as the classic HCC. Clear cell carcinoma tended to occur in the Asia-Pacific elderly male population, and more than half of them were large HCC (Size>5cm). Sarcomatoid (including spindle cell and pleomorphic) carcinoma was associated with a larger tumor size, poorer differentiation, and more dismal prognoses. The pathological subtype, T stage, M stage, surgery, alpha-fetoprotein, and cancer history were confirmed as the independent predictors in patients with rare subtypes. The nomogram showed good calibration, discrimination, and net benefits in clinical practice.

Conclusion: The rare subtypes had unique clinicopathological features and biological behaviors compared with the classic HCC. Our findings could provide a valuable reference for clinicians. The constructed nomogram could predict the prognoses with good performance, which is meaningful to individualized management.

Keywords: The SEER Program; clear cell carcinoma; fibrolamellar carcinoma; hepatocellular carcinoma; pathological subtype; pleomorphic carcinoma; scirrhous carcinoma; spindle cell carcinoma.

Figure 1

Stepwise extraction process from the Surveillance, Epidemiology, and End Results database. ICD, International Classification of Diseases; HCC, hepatocellular carcinoma.

Figure 2

Variation trends for the overall morbidity of different pathological subtypes of HCC from 2004 to 2018. (A) Classic HCC, (B) fibrolamellar carcinoma, (C) scirrhous carcinoma, (D) spindle cell carcinoma, (E) clear cell carcinoma, and (F) pleomorphic carcinoma. HCC, hepatocellular carcinoma.

Figure 3

Variation trends for the overall IBM of different pathological subtypes of HCC from 2004 to 2018. (A) Classic HCC, (B) fibrolamellar carcinoma, (C) scirrhous carcinoma, (D) spindle cell carcinoma, (E) clear cell carcinoma, and (F) pleomorphic carcinoma. IBM, incidence-based mortality; HCC, hepatocellular carcinoma.

Figure 4

Incidence of extrahepatic distant metastases at different sites of HCC. (A) All pathological subtypes, (B) classic HCC, (C) fibrolamellar carcinoma, (D) scirrhous carcinoma, (E) spindle carcinoma, and (F) clear cell carcinoma. HCC, hepatocellular carcinoma; LN, lymph node.

Figure 5

Cumulative incidence function curves of mortality in hepatocellular carcinoma patients stratified by different factors: (A) histology and (B–F) nodal status. LND, lymph node dissection; LNM, lymph node metastasis; CSD, cancer-specific death; OCSD, other cause-specific death.

Figure 6

Developing and validating a novel model to predict the prognoses of patients with rare pathological subtypes of hepatocellular carcinoma. (A) The nomogram to predict cancer-specific survival was developed from the training set. (B, C) Calibration curve analyses of the nomogram and the current AJCC staging system (8th edition) to evaluate the prognosis effects at the 5-year point in the training and validation sets. (D, E) Receiver operating characteristic curve analyses of the nomogram and the current AJCC staging system (8th edition) to evaluate the prognosis effects at the 5-year point in the training and validation sets. (F, G) Decision curve analyses of the nomogram and the current AJCC staging system (8th edition) to evaluate the prognosis effects at the 5-year point in the training and validation sets. LT, liver transplantation; LR, liver resection; LD, local destruction; UNK, unknown; AFP, alpha-fetoprotein.