Early Identification of Pneumonitis in Patients Irradiated for Lung Cancer-Final Results of the PARALUC Trial

Abstract

Radiotherapy of lung cancer may cause pneumonitis that generally occurs weeks or months following therapy and can be missed. This prospective trial aimed to pave the way for a mobile application (app) allowing early diagnosis of pneumonitis. The primary goal was the identification of the optimal cut-off of a score to detect pneumonitis of grade ≥2 after radiotherapy for lung cancer. Based on the severity of symptoms (cough, dyspnea, fever), scoring points were 0−9. Receiver operating characteristic (ROC)-curves were used to describe the sensitivity and specificity. The area under the ROC-curve (AUC) was calculated to judge the accuracy of the score, Youden-index was employed to define the optimal cut-off. Until trial termination, 57 of 98 patients were included. Eight of 42 patients evaluable for the primary endpoint (presence or absence of radiation pneumonitis) experienced pneumonitis. AUC was 0.987 (0.961−1.000). The highest sensitivity was achieved with 0−4 points (100%), followed by 5 points (87.5%), highest specificity with 5−6 points (100%). The highest Youden-index was found for 5 points (87.5%). The rate of patient satisfaction with the symptom-based scoring system was 93.5%. A cut-off of 5 points was identified as optimal to differentiate between pneumonitis and no pneumonitis. Moreover, pneumonitis was significantly associated with an increase of ≥3 points from baseline (p < 0.0001). The scoring system provided excellent accuracy and high patient satisfaction. Important foundations for the development of a mobile application were laid.

Keywords: lung cancer; mobile application; patient reported outcomes; pneumonitis; radiotherapy; symptom-based scoring system.

Figure 1

Patient enrollment and eligibility for the primary endpoint (evaluation of the presence or absence of radiation pneumonitis).

Figure 2

The Receiver Operating Characteristic (ROC) curve used to illustrate the relation between sensitivity and specificity, defined as the plot of sensitivity versus 1-specificity (false-positive rate) across different cut-off values.