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Article Dans Une Revue Clinical Chemistry and Laboratory Medicine Année : 2019

A novel machine learning-derived decision tree including uPA/PAI-1 for breast cancer care

Résumé

Abstract Background uPA and PAI-1 are breast cancer biomarkers that evaluate the benefit of chemotherapy (CT) for HER2-negative, estrogen receptor-positive, low or intermediate grade patients. Our objectives were to observe clinical routine use of uPA/PAI-1 and to build a new therapeutic decision tree integrating uPA/PAI-1. Methods We observed the concordance between CT indications proposed by a canonical decision tree representative of French practices (not including uPA/PAI-1) and actual CT prescriptions decided by a medical board which included uPA/PAI-1. We used a method of machine learning for the analysis of concordant and non-concordant CT prescriptions to generate a novel scheme for CT indications. Results We observed a concordance rate of 71% between indications proposed by the canonical decision tree and actual prescriptions. Discrepancies were due to CT contraindications, high tumor grade and uPA/PAI-1 level. Altogether, uPA/PAI-1 were a decisive factor for the final decision in 17% of cases by avoiding CT prescription in two-thirds of cases and inducing CT in other cases. Remarkably, we noted that in routine practice, elevated uPA/PAI-1 levels seem not to be considered as a sufficient indication for CT for N≤3, Ki 67≤30% tumors, but are considered in association with at least one additional marker such as Ki 67>14%, vascular invasion and ER-H score <150. Conclusions This study highlights that in the routine clinical practice uPA/PAI-1 are never used as the sole indication for CT. Combined with other routinely used biomarkers, uPA/PAI-1 present an added value to orientate the therapeutic choice.

Domaines

Cancer
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Dates et versions

hal-03417166 , version 1 (05-11-2021)

Identifiants

Citer

Nathalie Reix, Massimo Lodi, Stéphane Jankowski, Sébastien Molière, Elisabeth Luporsi, et al.. A novel machine learning-derived decision tree including uPA/PAI-1 for breast cancer care. Clinical Chemistry and Laboratory Medicine, 2019, 57 (6), pp.901-910. ⟨10.1515/cclm-2018-1065⟩. ⟨hal-03417166⟩
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