The importance of patient characteristics for the prediction of radiation-induced lung toxicity

PurposeExtensive research has led to the identification of numerous dosimetric parameters as well as patient characteristics, associated with lung toxicity, but their clinical usefulness remains largely unknown. We investigated the predictive value of patient characteristics in combination with established dosimetric parameters.Patients and methodsData from 438 lung cancer patients treated with (chemo)radiation were used. Lung toxicity was scored using the Common Toxicity Criteria version 3.0. A multivariate model as well as two single parameter models, including either V20 or MLD, was built. Performance of the models was expressed as the AUC (Area Under the Curve).ResultsThe mean MLD was 13.5 Gy (SD 4.5 Gy), while the mean V20 was 21.0% (SD 7.3%). Univariate models with V20 or MLD both yielded an AUC of 0.47. The final multivariate model, which included WHO-performance status, smoking status, forced expiratory volume (FEV1), age and MLD, yielded an AUC of 0.62 (95% CI: 0.55–0.69).ConclusionsWithin the range of radiation doses used in our clinic, dosimetric parameters play a less important role than patient characteristics for the prediction of lung toxicity. Future research should focus more on patient-related factors, as opposed to dosimetric parameters, in order to identify patients at high risk for developing radiation-induced lung toxicity more accurately.