Abstract
Background and purpose: Dyspnea evolution after radiotherapy for lung cancer is complex with potential symptom deterioration and improvement from baseline. We developed and internally validated a multinomial normal tissue complication probability (NTCP) model predicting dyspnea grade. Materials and methods: Patient-reported dyspnea was collected pre-treatment and during 6 months follow-up for 182 stage I-IV lung cancer patients treated with radical (chemo) radiotherapy. Dyspnea changes (DDys) from the baseline grade (Dys0) to the follow-up grade (Dys) were evaluated. A multinomial logistic regression model simultaneously predicting 3 grades of Dys (Dys 3, Dys = 2 and Dys 1 (reference level)) was optimized. Reference NTCP models predicting Dys 2 and Dys 3 risks irrespective of Dys0 were generated for comparison. Models were shrunken and performance was assessed using optimism-corrected AUC (bootstrapping). Results: Rates of DDys 1 (deterioration) and DDys -1 (improvement) at 6 months were 31.9% and 12.6%. Dys 3, Dys = 2 and Dys 1 rates were 13.7%, 20.9% and 65.4%, respectively. The multinomial model (combining the risk factors Dys0 and MLD and the protective factor chemotherapy treatment) predicted Dys 3, Dys = 2 and Dys 1 with AUC (95% CI) of 0.72 (0.65-0.75) 0.76 (0.72-0.79) and 0.78 (0.74-0.80), respectively. Reference Dys 2 and Dys 3 models showed worse AUC: 0.64 (0.59-0.67) and 0.66 (0.50-0.70), respectively. Conclusions: Dyspnea grade could be predicted with high accuracy using a multinomial NTCP model, yielding personalized dyspnea symptom improvement and deterioration risks. (C) 2019 Elsevier B.V. All rights reserved. Radiotherapy and Oncology
Original language | English |
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Pages (from-to) | 176-184 |
Number of pages | 9 |
Journal | Radiotherapy and Oncology |
Volume | 136 |
DOIs | |
Publication status | Published - Jul 2019 |
Keywords
- Radiation-induced dyspnea
- Patient-reported outcome
- NTCP modeling
- Lung cancer
- Baseline symptoms
- HIGH-PRECISION RADIOTHERAPY
- RADIATION PNEUMONITIS
- EUROPEAN ORGANIZATION
- CT
- RISK
- IMPROVE
- RECOMMENDATIONS
- CONSTRAINTS
- PREDICTION
- EVOLUTION