Predicting Lung Cancer-Associated Cachexia With PET Imaging
NCT ID: NCT05912465
Last Updated: 2023-06-27
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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UNKNOWN
NA
150 participants
INTERVENTIONAL
2023-07-01
2025-03-01
Brief Summary
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Detailed Description
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Background: Cancer cachexia is a debilitating syndrome characterized by progressive weight loss, muscle wasting, and metabolic abnormalities. It significantly impacts patients' quality of life and survival outcomes. Psychological stress has been suggested as a potential contributor to cachexia development and progression. This study aims to investigate the association between cancer cachexia, stress levels, and metabolic changes in lung cancer patients.
Methods: This multicenter, prospective observational study will enroll 150 lung cancer patients. Eligible participants will undergo comprehensive assessments, including medical history review, physical examinations, laboratory tests, and diagnostic imaging. Cancer cachexia will be diagnosed based on established criteria, including weight loss, reduced food intake, and systemic inflammation markers. Psychological stress will be evaluated using validated questionnaires and stress biomarkers. Metabolic changes will be assessed through positron emission tomography-computed tomography (PET-CT) scans to measure fluorodeoxyglucose (FDG) uptake in organs and lesions.
Primary Objectives: The primary objective is to determine differences in FDG uptake between cachectic and non-cachectic lung cancer patients in various organs and lesions. Secondary objectives include evaluating changes in amygdalar FDG uptake after stress intervention and exploring the relationship between stress, inflammatory markers, and metabolic changes.
Statistical Analysis: Student's t-test will be used to compare FDG uptake between groups, and descriptive statistics will be calculated for each brain region. Sample size calculations indicate a need for approximately 30 subjects per group to detect significant differences. Data will be analyzed using appropriate statistical software.
Ethical Considerations: Informed consent will be obtained from all participants, and the study will adhere to the principles outlined in the Declaration of Helsinki and Good Clinical Practice guidelines. The study protocol has been submitted to the Ethics Committee and regulatory authorities for approval.
Conclusion: This study aims to provide insights into the relationship between cancer cachexia, stress, and metabolic changes in lung cancer patients. By investigating FDG uptake in different organs and lesions, as well as amygdalar FDG uptake before and after stress intervention, this research may contribute to the development of targeted interventions for cachexia management and improve patient outcomes.
Conditions
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Study Design
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NA
SINGLE_GROUP
DIAGNOSTIC
NONE
Study Groups
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Treatment-Naive Lung Cancer Patients
This arm includes 150 treatment-naive lung cancer patients. Assessments include medical history, physical exams, lab tests, and imaging. Objective: investigate cancer cachexia, stress, and metabolic changes. Cachexia criteria: weight loss, reduced food intake, inflammation markers. Stress assessment: questionnaires, biomarkers. Metabolic changes measured by PET-CT scans analyzing FDG uptake in organs/lesions. Data will uncover the relationship between cancer cachexia, stress, and metabolic changes in treatment-naive lung cancer patients, leading to improved interventions/outcomes.
Stress Reduction Training
A subgroup of patients from Vienna will undergo an additional PET/CT scan after the first follow-up PET/CT, which takes place one month after stress reduction training. The stress reduction training involves performing a breathing technique.
Interventions
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Stress Reduction Training
A subgroup of patients from Vienna will undergo an additional PET/CT scan after the first follow-up PET/CT, which takes place one month after stress reduction training. The stress reduction training involves performing a breathing technique.
Eligibility Criteria
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Inclusion Criteria
* Confirmed diagnosis of lung cancer.
* Willingness to participate in the study and provide informed consent.
* Ability to comply with study procedures and follow-up visits.
Exclusion Criteria
* Concurrent participation in another clinical trial involving an investigational product.
* Known contraindications or intolerance to PET/CT imaging or fluorodeoxyglucose (FDG).
* Presence of severe comorbidities that may interfere with study participation or affect the interpretation of results.
* Pregnant or lactating women, or those planning to become pregnant during the study period.
* Any other condition that, in the opinion of the investigator, would make the patient unsuitable for participation in the study.
18 Years
ALL
No
Sponsors
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University of Leipzig
OTHER
Careggi Hospital
OTHER
University of Copenhagen
OTHER
Medical University of Vienna
OTHER
Responsible Party
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Univ.-Prof. Dr. Marcus Hacker
Head of the Division of Nuclear Medicine
Principal Investigators
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Marcus Hacker, Prof.
Role: PRINCIPAL_INVESTIGATOR
Medical University of Vienna, Department of Radiology and Nuclear Medicine
Thomas Beyer, Prof.
Role: PRINCIPAL_INVESTIGATOR
Medical University of Vienna, Center for Medical Physics and Biomedical Engineering
Osama Sabri, Prof.
Role: PRINCIPAL_INVESTIGATOR
University of Leipzig Medical Center
Roberto Sciagrà , Prof.
Role: PRINCIPAL_INVESTIGATOR
Careggi University Hospital
Locations
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Medical University of Vienna
Vienna, , Austria
University of Leipzig Medical Center
Leipzig, , Germany
AOUC Azienda Ospedaliero-Universitaria Careggi
Florence, , Italy
Countries
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Central Contacts
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Facility Contacts
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Osama Sabri, Prof.
Role: primary
Roberto Sciagra, Prof.
Role: primary
References
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Shiyam Sundar LK, Yu J, Muzik O, Kulterer OC, Fueger B, Kifjak D, Nakuz T, Shin HM, Sima AK, Kitzmantl D, Badawi RD, Nardo L, Cherry SR, Spencer BA, Hacker M, Beyer T. Fully Automated, Semantic Segmentation of Whole-Body 18F-FDG PET/CT Images Based on Data-Centric Artificial Intelligence. J Nucl Med. 2022 Dec;63(12):1941-1948. doi: 10.2967/jnumed.122.264063. Epub 2022 Jun 30.
Fearon K, Strasser F, Anker SD, Bosaeus I, Bruera E, Fainsinger RL, Jatoi A, Loprinzi C, MacDonald N, Mantovani G, Davis M, Muscaritoli M, Ottery F, Radbruch L, Ravasco P, Walsh D, Wilcock A, Kaasa S, Baracos VE. Definition and classification of cancer cachexia: an international consensus. Lancet Oncol. 2011 May;12(5):489-95. doi: 10.1016/S1470-2045(10)70218-7. Epub 2011 Feb 4.
Related Links
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Other Identifiers
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2091/2022
Identifier Type: -
Identifier Source: org_study_id
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