Study Results
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View full resultsBasic Information
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COMPLETED
152 participants
OBSERVATIONAL
2020-04-01
2021-07-30
Brief Summary
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Detailed Description
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This study aims to develop 18F-FDG PET radiomic signature, and investigate whether the radiomic signature could improve the prognostic value of the IPI score in predicting progression-free survival (PFS) and overall survival (OS) in DLBCL.
Conditions
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Study Design
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OTHER
RETROSPECTIVE
Interventions
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FDG PET radiomic feature evaluation
A total of 1245 radiomic features will be calculated and extracted from baseline FDG PET scans. These features include shape features, first order features, textural features and wavelet features.
In the second part, based on the results of least absolute shrinkage and selection operator Cox regression algorithm, the most significant radiomic features will be selected to construct the radiomic signature.
Eligibility Criteria
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Inclusion Criteria
2. Over 18 years old when diagnosed;
3. Have undergone pre-treatment 18F-FDG PET/CT;
4. Have been initially treated with the combination of rituximab, cyclophosphamide, doxorubicin, vincristine and prednisone (R-CHOP) or R-EPOCH (etoposide, prednisone, vincristine, cyclophosphamide, doxorubicin).
Exclusion Criteria
2. Have undergone surgical resection;
3. With an incomplete follow-up.
18 Years
ALL
No
Sponsors
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Second Affiliated Hospital, School of Medicine, Zhejiang University
OTHER
Responsible Party
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Principal Investigators
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Mei Tian, M.D.
Role: STUDY_DIRECTOR
Second Affiliated Hospital, School of Medicine, Zhejiang University
Locations
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Second Affiliated Hospital, School of Medicine, Zhejiang University
Hangzhou, Zhejiang, China
Countries
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References
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Zhang X, Chen L, Jiang H, He X, Feng L, Ni M, Ma M, Wang J, Zhang T, Wu S, Zhou R, Jin C, Zhang K, Qian W, Chen Z, Zhuo C, Zhang H, Tian M. A novel analytic approach for outcome prediction in diffuse large B-cell lymphoma by [18F]FDG PET/CT. Eur J Nucl Med Mol Imaging. 2022 Mar;49(4):1298-1310. doi: 10.1007/s00259-021-05572-0. Epub 2021 Oct 15.
Provided Documents
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Document Type: Study Protocol and Statistical Analysis Plan
Other Identifiers
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2019-350
Identifier Type: -
Identifier Source: org_study_id