Modeling Local Control After Hypofractionated Stereotactic Body Radiation Therapy for Stage I Non-Small Cell Lung Cancer: A Report From the Elekta Collaborative Lung Research Group

Purpose

Hypofractionated stereotactic body radiation therapy (SBRT) has emerged as an effective treatment option for early-stage non-small cell lung cancer (NSCLC). Using data collected by the Elekta Lung Research Group, we generated a tumor control probability (TCP) model that predicts 2-year local control after SBRT as a function of biologically effective dose (BED) and tumor size.

Methods and Materials

We formulated our TCP model as follows: TCP = e^{[BED10 − c ∗ L − TCD50]/k} ÷ (1 + e^{[BED10 − c ∗ L − TCD50]/k}), where BED10 is the biologically effective SBRT dose, c is a constant, L is the maximal tumor diameter, and TCD50 and k are parameters that define the shape of the TCP curve. Least-squares optimization with a bootstrap resampling approach was used to identify the values of c, TCD50, and k that provided the best fit with observed actuarial 2-year local control rates.

Results

Data from 504 NSCLC tumors treated with a variety of SBRT schedules were available. The mean follow-up time was 18.4 months, and 26 local recurrences were observed. The optimal values for c, TCD50, and k were 10 Gy/cm, 0 Gy, and 31 Gy, respectively. Thus, size-adjusted BED (sBED) may be defined as BED minus 10 times the tumor diameter (in centimeters). Our TCP model indicates that sBED values of 44 Gy, 69 Gy, and 93 Gy provide 80%, 90%, and 95% chances of tumor control at 2 years, respectively. When patients were grouped by sBED, the model accurately characterized the relationship between sBED and actuarial 2-year local control (r=0.847, P=.008).

Conclusion

We have developed a TCP model that predicts 2-year local control rate after hypofractionated SBRT for early-stage NSCLC as a function of biologically effective dose and tumor diameter. Further testing of this model with additional datasets is warranted.

Introduction

In recent years, hypofractionated stereotactic body radiation therapy (SBRT) has emerged as an effective treatment option for medically inoperable stage I non-small cell lung cancer (NSCLC) patients. SBRT in this setting has demonstrated excellent local control rates (1) and has been linked to improvements in overall survival (2). Compared with radiation therapy (RT) delivered via traditional techniques, SBRT uses highly conformal dose distributions, large daily fraction sizes, and shortened overall treatment courses. All of these characteristics contribute to the appeal of SBRT as a safe, effective, and convenient treatment option for medically inoperable stage I NSCLC patients.

The Elekta Collaborative Lung Research Group consists of 5 international institutions that use advanced treatment techniques, including online image guided RT (IGRT) to deliver SBRT for stage I NSCLC. Data from this group have already been presented, and several predictors of local control have been identified (3). The most significant predictor of local control is biologically effective dose (BED), calculated by use of the linear quadratic model with an α/β ratio of 10 Gy. Among patients treated with a relatively low BED, other factors such as tumor size and treatment duration seem to affect outcome.

Here we attempted to generate a robust tumor control probability (TCP) model using data from the Elekta Lung Research Group.