Hepatocellular Carcinoma (HCC): Classification Systems

Hepatocellular carcinoma (HCC) is the most common primary liver cancer and is closely linked to chronic liver diseases such as viral hepatitis, alcohol-related liver disease, and metabolic dysfunction-associated steatotic liver disease (MASLD, previously referred to as NAFLD/NASH). Accurate classification of HCC is critical for diagnosis, prognosis, and treatment planning. Various classification systems for HCC have been developed, focusing on tumor burden, liver function, and patient performance status. Additionally, biomarker-based tools such as the **GALAD score** have emerged as valuable resources for early detection of HCC.

Here is a detailed overview of the **classification systems for HCC**:

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### **1. Staging Systems for HCC**

Staging systems for HCC aim to assess tumor burden, liver function, and patient performance status to determine prognosis and guide therapeutic decisions. Key staging systems include:

#### **A. Barcelona Clinic Liver Cancer (BCLC) Staging System**

The **BCLC staging system** is the most widely used staging framework for HCC. It integrates tumor burden, liver function (Child-Pugh score), and patient performance status (ECOG) to guide treatment decisions.

| **Stage** | **Tumor Burden** | **Liver Function** | **Performance Status (ECOG)** | **Treatment Options** |

|-----------------|---------------------------------------|--------------------|------------------------------|-----------------------------------------|

| **Stage 0 (Very Early)** | Single tumor ≤2 cm, no vascular invasion | Child-Pugh A | 0 | Resection, ablation |

| **Stage A (Early)** | ≤3 nodules, each ≤3 cm or single tumor >2 cm | Child-Pugh A/B | 0 | Resection, ablation, transplant |

| **Stage B (Intermediate)** | Multinodular tumors without vascular invasion | Child-Pugh A/B | 0 | Transarterial chemoembolization (TACE) |

| **Stage C (Advanced)** | Portal invasion or extrahepatic spread | Child-Pugh A/B | 1–2 | Systemic therapy (e.g., sorafenib, atezolizumab + bevacizumab) |

| **Stage D (Terminal)** | Any tumor burden | Child-Pugh C | ≥3 | Best supportive care |

The BCLC system is highly regarded for its ability to guide treatment strategies, ranging from curative (e.g., resection, transplantation) to palliative (e.g., systemic therapies, supportive care).

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#### **B. TNM Staging System (AJCC 8th Edition)**

The **TNM staging system**, developed by the American Joint Committee on Cancer (AJCC), focuses on tumor size, vascular invasion, lymph node involvement, and metastasis. It is primarily used for surgically resected HCC and provides prognostic information.

| **Stage** | **T (Tumor)** | **N (Nodes)** | **M (Metastasis)** |

|-----------|-------------------------------------------|---------------|---------------------|

| **Stage I** | Single tumor, no vascular invasion | N0 | M0 |

| **Stage II** | Single tumor with vascular invasion | N0 | M0 |

| **Stage IIIA** | Multiple tumors >5 cm | N0 | M0 |

| **Stage IIIB** | Tumor invades major vascular structures | N0 | M0 |

| **Stage IVA** | Any T, regional lymph node involvement | N1 | M0 |

| **Stage IVB** | Any T, any N, distant metastasis | Any N | M1 |

The TNM system is particularly useful in evaluating prognosis after surgical resection.

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#### **C. Child-Pugh Classification**

The **Child-Pugh classification** evaluates liver function in patients with cirrhosis, which is critical because most HCC cases occur in the context of chronic liver disease. It is based on five clinical parameters: bilirubin, albumin, prothrombin time (INR), ascites, and hepatic encephalopathy.

| **Score** | **Points** | **Prognosis** |

|------------------|------------|------------------------|

| **Class A** | 5–6 | Well-compensated liver |

| **Class B** | 7–9 | Significant compromise |

| **Class C** | 10–15 | Decompensated liver |

The Child-Pugh score is commonly used alongside other staging systems to assess liver function and guide treatment decisions.

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#### **D. Cancer of the Liver Italian Program (CLIP) Score**

The **CLIP score** combines tumor stage, liver function, and portal vein thrombosis to provide prognostic information.

| **Parameter** | **Score** |

|------------------------------|-----------|

| **Child-Pugh Class** | A: 0, B: 1, C: 2 |

| **Tumor Morphology** | Uninodular: 0, Multinodular <50%: 1, Massive >50%: 2 |

| **AFP Levels** | <400 ng/mL: 0, ≥400 ng/mL: 1 |

| **Portal Vein Thrombosis** | Absent: 0, Present: 1 |

The CLIP score is particularly useful in prognostication and treatment planning.

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#### **E. Other Staging Systems**

1. **Okuda Classification**:

• Focuses on tumor size, ascites, albumin, and bilirubin.
• Historically significant but less commonly used today.

2. **Japanese Integrated Staging (JIS) Score**:

• Combines **TNM staging** and **Child-Pugh class**.

3. **Hong Kong Liver Cancer (HKLC) Staging**:

• Developed for Asian populations, incorporates tumor burden, liver function, and performance status.

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### **2. Biomarker-Based Classification: The GALAD Score**

The **GALAD score** is a diagnostic and risk prediction model for HCC that uses serum biomarkers and patient demographics. It is particularly valuable for detecting early-stage HCC in patients with chronic liver disease, including non-alcoholic steatohepatitis (NASH).

#### **Components of the GALAD Score**:

The GALAD score integrates:

1. **G**ender

2. **A**ge

3. **L**ectin-bound alpha-fetoprotein (AFP-L3%)

4. **A**lpha-fetoprotein (AFP)

5. **D**es-gamma-carboxy prothrombin (DCP, also known as PIVKA-II)

#### **Formula**:

The GALAD score uses a logistic regression model:

```

GALAD = -10.08 + (0.09 × Age) + (1.67 × Sex) + (2.34 × log10(AFP)) + (0.04 × AFP-L3%) + (1.33 × log10(DCP))

```

• **Sex**: Male = 1, Female = 0.
• The output is a probability value indicating the likelihood of HCC.

#### **Utility of the GALAD Score**:

• **Early Detection**:
• High sensitivity and specificity for identifying early-stage HCC.
• **Comparison with Imaging**:
• The GALAD score performs better than ultrasound or AFP alone.
• **GALADUS Score**:
• Combines the GALAD score with ultrasound findings for improved diagnostic accuracy.

#### **Validation**:

The GALAD score has been validated across diverse populations and is particularly effective in detecting HCC in NASH-related liver disease.

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### **3. Gross and Microscopic Classification of HCC**

#### **A. Gross Classification**:

HCC can be classified based on its macroscopic appearance into:

1. **Nodular Type**:

• Most common.
• Appears as a single nodule or multiple nodules.

2. **Massive Type**:

• A single large tumor, often with central necrosis.

3. **Diffuse Type**:

• Tumor infiltrates large portions of the liver.

#### **B. Microscopic Classification**:

• **Well-Differentiated**:
• Resembles normal hepatocytes; less aggressive.
• **Moderately Differentiated**:
• Intermediate features.
• **Poorly Differentiated**:
• Highly aggressive, with poor prognosis.

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### **Summary of HCC Classification Systems**

| **Classification System** | **Focus** |

|--------------------------------|---------------------------------------------------------------------------|

| **BCLC** | Tumor burden, liver function, and performance status. Guides treatment. |

| **TNM (AJCC)** | Tumor size, vascular invasion, lymph node, and metastasis staging. |

| **Child-Pugh** | Liver function assessment (cirrhosis severity). |

| **CLIP** | Combines liver function, tumor stage, and portal vein thrombosis. |

| **GALAD Score** | Biomarker-based model for early HCC detection. |

| **Okuda, JIS, HKLC** | Regional or historical staging systems. |

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### **Take-Home Points**

• Accurate classification of HCC is essential for prognosis and treatment planning.
• The **BCLC staging system** is the most commonly used, integrating tumor burden, liver function, and performance status.
• The **GALAD score** is a promising biomarker-based tool for **early detection of HCC**, particularly in patients with chronic liver disease.
• Combining staging systems with biomarker models improves diagnostic accuracy and enhances treatment strategies.