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

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

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.

Study Overview

• Status: Completed
• Conditions: Stage IV Non-small Cell Lung Cancer
• Intervention / Treatment: Other: No interventions

Detailed Description

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.

• Study Type: Observational
• Enrollment (Actual): 637

Contacts and Locations

Study Locations

• Netherlands
  • Heerlen, Netherlands, 6419 PC
    • Zuyderland Medical Center
  • Maastricht, Netherlands, 6229 HX
    • MUMC+

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

• Sampling Method: Probability Sample

Study Population

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

Description

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

Study Plan

How is the study designed?

Number of groups / cohorts

2

Cohorts and Interventions

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

What is the study measuring?

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

Collaborators and Investigators

• Sponsor: Maastricht Radiation Oncology
• Collaborators: Maastricht University Medical Center; Zuyderland Medical Centre
• Investigators: Principal Investigator: Dirk De Ruysscher, MD, PhD, Maastro Clinic, The Netherlands

Study record dates

Study Major Dates

• Study Start (Actual): September 1, 2017
• Primary Completion (Actual): January 1, 2021
• Study Completion (Actual): April 1, 2021

Study Registration Dates

• First Submitted: September 21, 2017
• First Submitted That Met QC Criteria: October 3, 2017
• First Posted (Actual): October 10, 2017

Study Record Updates

• Last Update Posted (Actual): September 16, 2021
• Last Update Submitted That Met QC Criteria: September 15, 2021
• Last Verified: September 1, 2021

More Information

Terms related to this study

• Keywords: anti-PD-L1; anti-PD1
• Additional Relevant MeSH Terms: Pathologic Processes; Infections; Respiratory Tract Infections; Respiratory Tract Diseases; Neoplasms; Lung Diseases; Neoplasms by Site; Respiratory Tract Neoplasms; Thoracic Neoplasms; Carcinoma, Bronchogenic; Bronchial Neoplasms; Lung Neoplasms; Carcinoma, Non-Small-Cell Lung; Inflammation; Pneumonia
• Other Study ID Numbers: BMS Radiomics

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No