ArticleHematology reports2024
Utilizing Clinical Transformation Criteria for Prognostic Stratification in Follicular Lymphoma Prior to Initial Immunochemotherapy.
Article in Hematology reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Beyond Chemoimmunotherapy: Emerging Cellular and Targeted Therapies in Transformed Follicular Lymphoma: A Scoping Review.Cancer control : journal of the Moffitt Cancer CenterArticle
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9 authors.
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Abstract
backgroundAlthough the prognosis of follicular lymphoma (FL) has improved, some patients experience early disease progression, including progression of disease within 24 months (POD24). Histological transformation is a critical event in FL. However, the heterogeneity of FL tumors makes it challenging to diagnose transformation accurately. We retrospectively applied the clinical transformation criteria used for FL transformation assessments at relapse or disease progression to conduct transformation assessments before the initial immunochemotherapy.
methodsSixty-six FL patients who first received immunochemotherapy between January 2009 and February 2023 at our institution were selected. Twenty-three were clinical-transformation-positive (CLT+).
resultsThe progression-free survival (PFS) rate of the CLT+ patients was significantly lower than that of the clinical-transformation-negative (CLT-) patients. In the POD24 assessment subgroup, the CLT+ patients had a higher incidence of POD24 than the CLT- patients. There was no significant difference in PFS between the patients treated with CHOP-like regimens and those treated with bendamustine regimens. In the CHOP-like group, the CLT+ patients exhibited significantly lower PFS than the CLT- patients. In the bendamustine group, the clinical transformation did not affect PFS.
conclusionClinical transformation criteria may be useful for the prognostic stratification of FL prior to immunochemotherapy. Additionally, they may serve as predictors of POD24.
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