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Utilization, Challenges, and Outlook of Cell of Origin Classification by Immunohistochemistry (IHC) in DLBCL

Year: 2026
Type: article
Study design: Observational Study
Abstract: Background/Objectives: Cell of origin (COO) classification in treatment-naïve (TN) diffuse large B-cell lymphoma (DLBCL) is universally recommended across guidelines as an essential prognostic tool, yet some patients are not tested or receive equivocal results that impede timely classification. Methods: The current study was informed by 18 qualitative, double-blinded phone interviews and a quantitative double-blinded survey of 60 hematologists/oncologists and 60 pathologists (including hematopathologists). Respondents were selected to represent academic and community practice settings based in the United States. Results: Hematologists/oncologists view COO as a valuable tool that provides prognostic insight and a more comprehensive diagnosis, with 83% of TN DLBCL patients tested for COO and 85% of hematologists/oncologists incorporating COO into treatment decisions. Hematologists/oncologists and pathologists prefer immunohistochemical (IHC) techniques over gene expression profiling (GEP) due to IHC’s accessibility, faster turnaround time, and relatively low cost. Although IHC workflows are routine, 10–15% of samples initially yield equivocal results. After repeat testing and/or multiple reviews and peer discussion, ~3% of submitted samples remain equivocal. Finally, we uncovered sentiment that the lack of pathology report standardization may undermine the use of COO classification in clinical decision-making. Conclusions: Our findings show that IHC is perceived as a reliable method for COO classification in TN DLBCL. Clinicians endorsed the need for guidelines to standardize pathology reports and establish definitive criteria for equivocal cases. These guidelines in combination with education to reinforce the clinical implications of COO can help mitigate testing barriers and increase the proportion of patients who receive timely COO classifications.
Source: Diagnostics
Language: English
Field: Medicine
Open Access status: gold
Estimated APC paid: $3,137
OpenAlex ID: W7171505033
FWCI:
Cites: 16
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