Prospective assessment of dosimetric/physiologic-based models for predicting radiation pneumonitis.
PURPOSE: Clinical and 3D dosimetric parameters are associated with symptomatic radiation pneumonitis rates in retrospective studies. Such parameters include: mean lung dose (MLD), radiation (RT) dose to perfused lung (via SPECT), and pre-RT lung function. Based on prior publications, we defined pre-RT criteria hypothesized to be predictive for later development of pneumonitis. We herein prospectively test the predictive abilities of these dosimetric/functional parameters on 2 cohorts of patients from Duke and The Netherlands Cancer Institute (NKI). METHODS AND MATERIALS: For the Duke cohort, 55 eligible patients treated between 1999 and 2005 on a prospective IRB-approved study to monitor RT-induced lung injury were analyzed. A similar group of patients treated at the NKI between 1996 and 2002 were identified. Patients believed to be at high and low risk for pneumonitis were defined based on: (1) MLD; (2) OpRP (sum of predicted perfusion reduction based on regional dose-response curve); and (3) pre-RT DLCO. All doses reflected tissue density heterogeneity. The rates of grade > or =2 pneumonitis in the "presumed" high and low risk groups were compared using Fisher's exact test. RESULTS: In the Duke group, pneumonitis rates in patients prospectively deemed to be at "high" vs. "low" risk are 7 of 20 and 9 of 35, respectively; p = 0.33 one-tailed Fisher's. Similarly, comparable rates for the NKI group are 4 of 21 and 6 of 44, respectively, p = 0.41 one-tailed Fisher's. CONCLUSION: The prospective model appears unable to accurately segregate patients into high vs. low risk groups. However, considered retrospectively, these data are consistent with prior studies suggesting that dosimetric (e.g., MLD) and functional (e.g., PFTs or SPECT) parameters are predictive for RT-induced pneumonitis. Additional work is needed to better identify, and prospectively assess, predictors of RT-induced lung injury.
Kocak, Z; Borst, GR; Zeng, J; Zhou, S; Hollis, DR; Zhang, J; Evans, ES; Folz, RJ; Wong, T; Kahn, D; Belderbos, JSA; Lebesque, JV; Marks, LB
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