ELCC 2017: Development and Validation of Lung Toxicity Prediction Models Aids Effective Use of Radiotherapy in NSCLC
Validation using patient data of an outcome prediction model for the development of dyspnea subsequent to radiotherapy revealed that the prognostic factors in the model did not adequately predict for delta toxicity endpoints, according to results reported by Defraene et al at the 2017 European Lung Cancer Conference (ELCC) (Abstract 74PD). The model was developed to identify patients at risk of dyspnea, or breathing difficulty, after radiotherapy. The dataset was comprised of patients with non–small cell lung cancer (NSCLC) who had undergone radiotherapy.
Gilles Defraene, MSc, of the Department of Oncology, KU–University of Leuven, and colleagues evaluated the prognostic factors for lung toxicity contained within an outcome prediction model published by Appelt et al in Acta Oncologicathat was identified in a literature search. The model is based on a review of radiation pneumonitis reports and retained the most important predictors for its development: mean lung dose (MLD) as dosimetric factor, and six other factors that influence the susceptibility of a patient to this condition, including preexisting pulmonary comorbidity; age > 63 years; mid/inferior tumor location; and sequential chemotherapy as risk factors. The model identified current smoking and smoking history as protective factors.
The team retrospectively assessed a dataset of 109 patients with NSCLC who were treated at the MAASTRO Clinic using 1.8-Gy fraction doses administered in two fractions per day up to 79.2 Gy. All treatments had been performed using 3D-conformal radiotherapy techniques to be consistent with the study that was the basis of the model. The required parameters were retrospectively collected together with the dyspnea endpoint, according to common toxicity criteria (CTC 3.0) scoring at baseline and at 6 months after radiotherapy.
Study Findings
Within 6 months after radiotherapy, 19.3% of patients had developed dyspnea ≥ 2 per CTC scoring. Using logistic regression modelling on the dataset, current smoking and pulmonary comorbidity were confirmed as prognostic factors for this dyspnea. The odds ratios (OR) were 0.28 for current smoking (P = .02) and 2.95 for presence of a pulmonary comorbidity (P = .02).
The OR for tumor location was outside of the reported 95% confidence interval (CI). The dosimetric factor in the published model, MLD, did not associate with outcome in any of the models employed in this study.
An evaluation of the change in dyspnea with respect to the baseline score (delta dyspnea ≥1) which had a prevalence of 18.6%, revealed that current smoking and pulmonary comorbidity were no longer significant prognostic factors (OR = 0.56, P = .27; and OR = 0.47, P = .21, respectively).
The reason for this different result is that both factors associated strongly with the baseline dyspnea status. According to the authors, worse baseline dyspnea is often a manifestation of existing comorbidities and may affect the probability of smoking cessation.
Conclusions
The authors underscored that validated outcome prediction models with high discriminative power are important for cost-effective use of proton therapy for locally advanced NSCLC, and stressed the importance of including the consideration of delta toxicity, or change from baseline, in the development of meaningful prognostic models for radiotherapy outcome.
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