A Novel FDG PET and Mean Lung Dose Model to Identify Stage III NSCLC Patients at High Risk of Developing Early Radiation Pneumonitis

PURPOSE/OBJECTIVE(S)

Early radiation pneumonitis (RPEarly) is a primary reason for the premature discontinuation of durvalumab consolidation and can lead to poor survival in patients with stage III non-small cell lung cancer (NSCLC). Currently, there are no RP risk models specifically tested for RPEarly. Here, we tested the applicability of published RP models for predicting RPEarly and explored the value of integrating pretreatment FDG-PET parameters.

MATERIALS/METHODS

The cohort consisted of all 178 LA-NSCLC patients treated with concurrent chemoradiation (cCRT) and durvalumab between May 2017 and December 2021. RPEarly was defined as RP occurring within three months of cCRT completion; late RP (RPLate) was defined as any later occurring RP. The three published RP models analyzed included: 1) Mean lung dose (MLD), 2) MLD, age, pulmonary comorbidity, smoking status, and tumor location, and 3) MLD, age and pulmonary comorbidity. In addition, pretreatment FDG PET-CT scans were used to calculate SUV parameters from auto-segmented normal lung contours: 10th- and 90th percentile (SUVP10, SUVP90), maximum, mean (SUVmean), minimum, and standard deviation. The RP models were fit to RPEarly, RPLate, and RPEarly+Late in the 178 patients. To assess the association between FDG PET parameters and RP unbiasedly, the cohort was then randomly split, but enforcing similar RP rates, into a two-thirds derivation and a one-third validation subset. Model performance was assessed by AUC, p-values and the Hosmer-Lemeshow test (pHL; ideally ∼0.50).

RESULTS

The rates of RPEarly, RPLate, and RPEarly+Late were 12%, 11%, and 23%, respectively (corresponding to 21, 20, and 41 events). Only the MLD model significantly predicted RPEarly (AUC = 0.70; p = 0.04; pHL = 0.84); none of the three models predicted RPLate or RPEarly+Late. Among the FDG PET parameters, SUVP10, SUVP90 and SUVmean predicted RPEarly with similar performance (AUC = 0.69-0.73; p = 0.005-0.01; pHL = 0.68-0.72), and, therefore, bivariate models were built between MLD and each of SUVP10, SUVP90 and SUVmean. Only the MLD + SUVP90 model generalized in the validation subset (AUC = 0.63; p = 0.03; pHL = 0.89) and was thus deemed the final model for RPEarly. A final re-fitting of all model coefficients to the whole cohort indicated improvement over using the published MLD alone model (AUC = 0.75 vs. 0.70; p-value = 0.0006 vs. 0.04; pHL = 0.67 vs. 0.84). Risk of RPEarly is thus estimated as: RPEarly = 1/(1 = e-x); x = -5.79 + (1.57*MLD) + (0.14* SUVP90).

CONCLUSION

Patients at risk for RPEarly can be accurately identified prior to treatment by combining a re-fitted version of the published Mean Lung Dose model and pre-treatment FDG PET SUVP90 of the normal lung. This refined model can be used to identify patients with an exacerbated risk for premature durvalumab discontinuation due to RPEarly and could allow for interventions and/or the generation of "RPEarly sparing" treatment plans to improve overall treatment outcomes.