Readme zur Dokumentation von Forschungsdatensätzen

Ersteller*in Readme:				Wehlte, Lukas

Erstellungsdatum Readme:			2025-07-20
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Titel des Forschungsdatensatzes:		Elevated FDG Uptake in Non-Tumorous Lung Regions Does Not Predict Immune Checkpoint Inhibitor–Related Pneumonitis in Lung Cancer Patients
						
Ort der Datenerhebung:				München, Bayern, Deutschland

Version:					1.0
Versionenänderungen:				

Herausgeber*in:					Universitätsbibliothek der Ludwig-Maximilians-Universität München
Herausgeber*in Identifier:			[Angabe Institution per GND oder ROR]
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Ersteller*in 1 des Datensatzes:			Wehlte, Lukas 
Ersteller*in 1 Identifier:			https://orcid.org/0009-0001-2436-8630
Ersteller*in 1 Affiliation:			Department of Medicine V, LMU University Hospital, München (Germany)		

Beteiligte[*] 1:				Daisenberger, Lea
Beteiligte 1 Identifier:			
Beteiligte 1 Affiliation :			Department of Dermatology and Allergy, LMU University Hospital, München (Germany)

[*] An der Sammlung von Forschungsdaten beteiligte Personen.
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Projektname:					Pneumonitis:
						All lung cancer patients who were treated with an immune checkpoint inhibitor therapy at the Department of Medicine V at LMU Klinikum between 2014 and 2022.
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Abstract:					This dataset is part of a research project that investigated the pretreatment standardized uptake value (SUV) on 18F-fluorodeoxyglucose positron emission tomography/computed tomography ([18F]FDG-PET/CT) of non-tumorous lung tissue as a predictive imaging marker for the development of checkpoint inhibitor pneumonitis (CIP) in patients with lung cancer.

In this retrospective study, we analyzed [18F]FDG-PET/CT datasets from 240 lung cancer patients who were consecutively scanned prior to receiving immune checkpoint inhibitor (ICI) therapy. The study compared SUVMEAN, SUVMAX, and SUV95 values, treatment regimens, and comorbidities between patients who developed CIP and those who did not. Logistic regression analyses were performed to assess the predictive value of pretreatment SUV for CIP development.

This dataset comprises essential components for replicating the research findings presented in my dissertation. Included are a README file offering an overview of the dataset's contents and usage instructions, a cohort file containing the dataset used in the study, and R scripts facilitating the reproduction of the analyses outlined in the dissertation. These resources aim to enhance transparency and reproducibility, enabling fellow researchers to validate and build upon the findings of the original research article: https://doi.org/XXX
						
Schlagwörter:					Medicine, Lung cancer, PET/CT, SUV, Pneumonitis

Methode der Datenerhebung: 			For clinical variables a semi-automatic tool was built to analyze text of doctor’s documentations using keywords for those characteristics. FDG-PET/CT images were evaluated using Visage®7, Visage Imaging, Inc., San Diego, USA

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Datei:						COHORT (Data frame)
Dateiformate: 					XLSX

Datei:						0_Results.R (Runs all R files and includes explanations for each file
						2.2_FDG-PET_CT
						3.1_Patient_Characteristics
						3.2_Pneumonitis
						3.3_PET_CT_Devices
						3.4_SUV_Correlation
						3.4_SUV_Overview
						3.4_SUV_Forest_Plot
Dateiformate: 					XLSX; R

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Anmerkungen: 					This project was funded by the Deutsche Forschungsgemeinschaft (DFG) under Germany’s Excellence Strategy within the framework of the Munich Cluster for Systems Neurology (EXC 2145 SyNergy—ID 390857198). The project is also supported by the Clinician Scientist Program of the Deutsche Forschungsgemeinschaft (DFG) within the framework of the CRC/Transregio 205/1 “The Adrenal: Central Relay in Health and Disease”. Moreover, this study was supported by the German Federal Ministry of Education and Research (BMBF) as part of the project MelAutim (01ZX1905A and 01ZX1905E), which aims a systems medicine investigation of autoimmunity in the context of immune therapies. 
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Verwandte Datensätze:
Wehlte, Lukas und Daisenberger, Lea: Raw Data and R Script for the Association between the Body Mass Index, Chronic Obstructive Pulmonary Disease and SUV of the Non-Tumorous Lung in the Pretreatment [18F]FDG-PET/CT of Patients with Lung Cancer. 1. Juli 2024. Open Data LMU. 10.5282/ubm/data.454