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Poster display session: Biomarkers, Gynaecological cancers, Haematological malignancies, Immunotherapy of cancer, New diagnostic tools, NSCLC - early stage, locally advanced & metastatic, SCLC, Thoracic malignancies, Translational research

4312 - Inmunohistochemical (IHQ) classification of DLBCL into CGB and non-CGB subtypes to predict survival after chemoimmunotherapy, at the Virgen de la Victoria University Hospital

Date

20 Oct 2018

Session

Poster display session: Biomarkers, Gynaecological cancers, Haematological malignancies, Immunotherapy of cancer, New diagnostic tools, NSCLC - early stage, locally advanced & metastatic, SCLC, Thoracic malignancies, Translational research

Topics

Tumour Site

Lymphomas

Presenters

LAURA Galvez Carvajal

Citation

Annals of Oncology (2018) 29 (suppl_8): viii359-viii371. 10.1093/annonc/mdy286

Authors

L. Galvez Carvajal, C. Quero Blanco, M. Robles Lasarte, I. Moreno Perez, L. Vicioso, I. Ramos Garcia, C. Bandera Lopez, J. Baena Espinar, C. Ithurbisquy, E. Alba

Author affiliations

  • Oncología Médica, Hospital Universitario Virgen de la Victoria, 29010 - Málaga/ES
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Abstract 4312

Background

It is known that diffuse large-B-cell lymphoma (DLBCL) is a clinically heterogeneous entity. The most important clinical predictor of survival is the International Prognostic Index, which does not provide information regarding the heterogeneous biology of tumors. Two major subtypes of DLBCL have been identified by gene expression profiling (GEP) and classified by cell of origin into germinal center B-cell–like (GCB) and activated B-cell–like (ABC). GEP has become a reliable method for predicting the outcome of patients with DLBCL treated with R-CHOP chemotherapy. However, that it´s not easily applicable in clinical practise. Several IHC algorithms have been developed to assign patients into GCB and non-GCB/ABC subtypes.

Methods

We retrospectively analyzed 142 patients diagnosed of de novo DLBCL from 1999 to 2017 at our Hospital treated with chemoimmunotherapy. DLBCL was classified using the Hans algorithm into GCB and non-GCB subtypes. The primary end point was progression-free survival (PFS) according to the Hans algorithm, that it was estimated by the Kaplan–Meier method.

Results

The percentage of GCB and non-GCB subtypes was 54% and 46%, respectively. After a median follow-up of 37 months, the median progression-free survival was 100 months in the global population. No significant differences were found in PFS, although there was a trend to favor CGB subtype (PFS at 24 months 70% in CGB group and 59% in non-CGB group, with a median of 60 months in non-CGG and not reached in CGB group, p = 0.177). Despite of being a retrospective study and the low median follow-up of patients, in CGB subtype there was a trend towards better overall survival (OS) (2-year OS: 72% vs. 68%), not statistically significant (p = 0.661).

Conclusions

In our study there is a lack of evidence supporting the use of the Hans algorithm for stratifying patients into distinct prognostic groups, probably due to the low median follow-up. Rather, GEP remains the preferred method for predicting prognosis. IHQ for subclassification of DLBCL is feasible and reproducible, but the harmonization of techniques and centralized consensus review is necessary.

Clinical trial identification

Legal entity responsible for the study

Laura Galvez Carvajal.

Funding

Has not received any funding.

Editorial Acknowledgement

Disclosure

All authors have declared no conflicts of interest.

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