Radiomics to Identify Patients at Risk for Developing Pneumonitis, Differentiate Immune Checkpoint Inhibitor-induced Pneumonitis From Other Lung Inflammation and Distinguish Tumour Pseudo-progression From Real Tumour Growth

Study Overview
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Brief Summary
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The investigators will develop a radiomics signature for immune checkpoint-induced pneumonitis in 40 patients with a pulmonary event under anti-PD1 or anti-PD-L1 (cases) and 40 patients without a pulmonary event under anti-PD1 or anti-PD-L1 (controls). On the basis of the case-control study of patients treated with anti-PD1 or anti-PD-L1, they will further optimise the model using reinforcement machine learning. The model will then be validated in 300 prospective patients.

Detailed Description
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Preliminary analyses on a dataset showed a clear distinction in radiomics features for patients with and without pneumonitis from anti-PD1 or anti-PD-L1. Prior experience of the investigators of training and validating radiomics signatures combined with their preliminary exploratory results presented here, will be used to develop a radiomics signature for immune checkpoint-induced pneumonitis in 40 patients with a pulmonary event under anti-PD1 or anti-PD-L1 (cases) and 40 patients without a pulmonary event under anti-PD1 or anti-PD-L1 (controls). On the basis of the case-control study of patients treated with anti-PD1 or anti-PD-L1, the investigators will be able to further optimise the model using reinforcement machine learning. The model will then be validated in 300 prospective patients.

Official Title
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Radiomics to 1. Identify Patients at Risk for Developing Pneumonitis, 2. Differentiate Immune Checkpoint Inhibitor-induced Pneumonitis From Other Lung Inflammation and 3. Distinguish Tumour Pseudo-progression From Real Tumour Growth, in Patients With Non-small Cell Lung Cancer Treated With Anti-PD1 or Anti-PD-L1

Conditions
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Stage IV Non-small Cell Lung Cancer

Intervention / Treatment
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* Other: No interventions


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Patients who receive standard anti-PD1 or anti-PD-L1 treatment in routine clinical practice for first or second line stage IV non-small cell lung cancer Exclusion Criteria: The opposite of the above

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Patients with a pulmonary event<br>(under anti-PD1 or anti-PD-L1) This is the first group of the retrospective part of the study. | Other: No interventions<br>* As this is a patient registry, there are no interventions.<br>|
| Patients without a pulmonary event<br>(under anti-PD1 or anti-PD-L1) This is the second group of the retrospective part of the study. | Other: No interventions<br>* As this is a patient registry, there are no interventions.<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Cause of pneumonitis | Determining cause of the pneumonitis by medical status of the patient | 6 months | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Predictive accuracy of radiomics for determining the cause of pneumonitis | Three subgroups of immune checkpoint induced pneumonitis: Immune checkpoint-induced pneumonitis from tumour progression Immune checkpoint-induced pneumonitis from other types of pneumonitis Patients with interstitial lung disease that are at risk to develop immune checkpoint-induced pneumonitis and those who are not. Radiomics will be used to predict the cause of pneumonitis | 6 months | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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anti-PD1, anti-PD-L1