Tumor Control Probability Modeling for Radiation Therapy of Keratinocyte Carcinoma

Area of Science:

• Oncology
• Radiation Oncology
• Medical Physics

Background:

• Radiotherapy (RT) is a primary treatment for keratinocyte carcinoma (KC), especially for patients unsuitable for surgery.
• Modeling tumor control probability (TCP) is crucial for optimizing RT fractionation and dosage.
• This study focuses on primary basal cell carcinoma (BCC) and cutaneous squamous cell carcinoma (cSCC).

Approach:

• Developed four distinct TCP models based on a sigmoidal function of biological effective dose (BED).
• Utilized pooled clinical outcome data for BCC and cSCC, categorized by tumor size (≤2 cm and >2 cm).
• Derived model parameters (TD, k, L) for each cancer type and size category.

Key Points:

• TCP model parameters were successfully obtained for BCC and cSCC across different tumor sizes.
• Results indicate that higher radiation doses, achieved through increased fractions or dose per fraction, enhance TCP.
• This effect is particularly pronounced for KCs larger than 2 cm.

Conclusions:

• Four novel TCP models for primary KCs have been established using pooled clinical data.
• These models can inform testing of 2020 ASTRO guideline-recommended RT regimens (kV, MV x-ray, electron beams).
• Adjusting fractionation and dose per fraction significantly impacts tumor control for BCC and cSCC tumors >2 cm.