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Comparative Study
. 2021 Apr;124(8):1421-1427.
doi: 10.1038/s41416-020-01251-3. Epub 2021 Feb 9.

Determination of breast cancer prognosis after neoadjuvant chemotherapy: comparison of Residual Cancer Burden (RCB) and Neo-Bioscore

Enora Laas #  1 , Julie Labrosse #  1 , Anne-Sophie Hamy  2 , Gabriel Benchimol  1 , Diane de Croze  3 , Jean-Guillaume Feron  1 , Florence Coussy  3 , Thomas Balezeau  4 , Julien Guerin  4 , Marick Lae  5 , Jean-Yves Pierga  3 , Fabien Reyal  6   7   8
Affiliations
Comparative Study

Determination of breast cancer prognosis after neoadjuvant chemotherapy: comparison of Residual Cancer Burden (RCB) and Neo-Bioscore

Enora Laas et al. Br J Cancer. 2021 Apr.

Abstract

Background: To compare RCB (Residual Cancer Burden) and Neo-Bioscore in terms of prognostic performance and see if adding pathological variables improve these scores.

Methods: We analysed 750 female patients with invasive breast cancer (BC) treated with neoadjuvant chemotherapy (NAC) at Institut Curie between 2002 and 2012. Scores were compared in global population and by BC subtype using Akaike information criterion (AIC), C-Index (concordance index), calibration curves and after adding lymphovascular invasion (LVI) and pre-/post-NAC TILs levels.

Results: RCB and Neo-Bioscore were significantly associated to disease-free and overall survival in global population and for triple-negative BC. RCB had the lowest AICs in every BC subtype, corresponding to a better prognostic performance. In global population, C-Index values were poor for RCB (0.66; CI [0.61-0.71]) and fair for Neo-Bioscore (0.70; CI [0.65-0.75]). Scores were well calibrated in global population, but RCB yielded better prognostic performances in each BC subtype. Concordance between the two scores was poor. Adding LVI and TILs improved the performance of both scores.

Conclusions: Although RCB and Neo-Bioscore had similar prognostic performances, RCB showed better performance in BC subtypes, especially in luminal and TNBC. By generating fewer prognostic categories, RCB enables an easier use in everyday clinical practice.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1. Association between RCB, Neo-Bioscore and disease free survival in the whole population and by pathological subtypes.
a Neo-bioscore in the whole population; b RCB in the whole population; c Neo-bioscore in the Luminal subtype; d RCB in the Luminal subtype; e Neo-bioscore in the Triple negative subtype; f RCB in the Triple negative subtype; g Neo-bioscore in the HER2-positive subtype; h RCB in the HER2-positive subtype.
Fig. 2
Fig. 2. AIC, C-index and calibration curves for RCB and neo-bioscore, in whole population and by pathological substypes.
a AIC in the whole population; b AIC in the luminal subtype; c AIC in the triple negative subtype; d AIC in the HER2-positive subtype; e C-index in the whole population; f C-index in the luminal subtype; g C-index in the triple negative subtype; h C-index in the HER2-positive subtype; i Calibration curves for the whole population; j Calibration curves for the luminal subtype; k Calibration curves for the triple negative subtype; l Calibration curves for the HER2-positive subtype.
Fig. 3
Fig. 3. Concordance between RCB and neo-bioscore in the global population.
a Neo-bioscore repartition according to RCB. b RCB repartition according to neo-bioscore. c Sankey plot of repartition of neo-bioscore according to RCB. d Sankey plot of repartition of RCB according to neo-bioscore.
See this image and copyright information in PMC

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