Background and purpose

Histology was found to be an important prognostic factor for local tumor control probability (TCP) after stereotactic body radiotherapy (SBRT) of early-stage non-small-cell lung cancer (NSCLC). A histology-driven SBRT approach has not been explored in routine clinical practice and histology-dependent fractionation schemes remain unknown. Here, we analyzed pooled histologic TCP data as a function of biologically effective dose (BED) to determine histology-driven fractionation schemes for SBRT and hypofractionated radiotherapy of two predominant early-stage NSCLC histologic subtypes adenocarcinoma (ADC) and squamous cell carcinoma (SCC).

Material and methods

The least-χ² method was used to fit the collected histologic TCP data of 8510 early-stage NSCLC patients to determine parameters for a well-developed radiobiological model per the Hypofractionated Treatment Effects in the Clinic (HyTEC) initiative.

Results

A fit to the histologic TCP data yielded independent radiobiological parameter sets for radiotherapy of early-stage lung ADC and SCC. TCP increases steeply with BED and reaches an asymptotic maximal plateau, allowing us to determine model-independent optimal fractionation schemes of least doses in 1-30 fractions to achieve maximal tumor control for early-stage lung ADC and SCC, e.g., 30, 44, 48, and 51 Gy for ADC, and 32, 48, 54, and 58 Gy for SCC in 1, 3, 4, and 5 fractions, respectively.

Conclusion

We presented the first determination of histology-dependent radiobiological parameters and model-independent histology-driven optimal SBRT and hypofractionated radiation therapy schemes for early-stage lung ADC and SCC. SCC requires substantially higher radiation doses to maximize tumor control than ADC, plausibly attributed to tumor genetic diversity and microenvironment. The determined optimal SBRT schemes agree well with clinical practice for early-stage lung ADC. These proposed optimal fractionation schemes provide first insights for histology-based personalized radiotherapy of two predominant early-stage NSCLC subtypes ADC and SCC, which require further validation with large-scale histologic TCP data.