A Non Interventional Pilot Study on Machine Learning for ILD Detection Based on the Patient Data From Digital Devices in Unresectable Stage III Non-Small Cell Lung Cancer Patients Receiving Durvalumab

Summary

Participation Requirements

Description

Study design: Multicentre, prospective, non-interventional pilot study Data Source(s): Medical records, wearable devices, and mobile application. Study Population:Patients treated durvalumab following chemoradiation therapy for stage III unresectable NSCLC in Japan from the June 2021 to June 2022. T...

Study design: Multicentre, prospective, non-interventional pilot study Data Source(s): Medical records, wearable devices, and mobile application. Study Population:Patients treated durvalumab following chemoradiation therapy for stage III unresectable NSCLC in Japan from the June 2021 to June 2022. They must fulfil all of the inclusion /exclusion criteria. Exposure(s): dulvalumab Outcome(s): Disease progression, ILD including radiation pneumonitis. Sample Size Estimations : 150 patients Statistical Analysis: Continuous variables will be reported as mean, median, standard deviation, IQR, maximum, and minimum. Categorical variables will be summarized as absolute frequency and percentage. Ninety-five percent confidence intervals (CIs) will be presented where appropriate. Time-to event for ILD/Disease progression will be estimated by Kaplan-Meir method. Also, in the process of developing model, data production such as per-patient plots of the physiological data(multivariate time series) and physiological data before and after (in a shorter time-scale) the ILD event per event will be considered.

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