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A model-strengthened imaging biomarker for survival prediction in EGFR-mutated non-small-cell lung carcinoma patients treated with tyrosine kinase inhibitors

hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
hal.structure.identifierModélisation Mathématique pour l'Oncologie [MONC]
dc.contributor.authorCOLLIN, Annabelle
dc.contributor.authorGROZA, Vladimir
dc.contributor.authorMISSENARD, Louise
dc.contributor.authorCHOMY, François
dc.contributor.authorCOLIN, Thierry
dc.contributor.authorPALUSSIÈRE, Jean
hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
hal.structure.identifierModélisation Mathématique pour l'Oncologie [MONC]
dc.contributor.authorSAUT, Olivier
dc.date.accessioned2024-04-04T02:44:07Z
dc.date.available2024-04-04T02:44:07Z
dc.date.issued2021-06
dc.identifier.issn0092-8240
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/191381
dc.description.abstractEnNon-small-cell lung carcinoma is a frequent type of lung cancer with a bad prognosis. Depending on the stage, genomics, several therapeutical approaches are used. Tyrosine Kinase Inhibitors (TKI) may be successful for a time in the treatment of EGFR-mutated non-small cells lung carcinoma. Our objective is here to propose a survival assessment as their efficacy in the long run is challenging to evaluate. The study includes 17 patients diagnosed as of EGFR-mutated non-small cell lung cancer and exposed to an EGFR-targeting TKI with 3 computed tomography (CT) scans of the primitive tumor (one before the TKI introduction and two after). An imaging biomarker based on the texture heterogeneity evolution between the first and the third exams is derived and computed from a mathematical model and patient data. Defining the overall survival as the time between the introduction of the TKI treatment and the patient death, we obtain a statistically significant correlation between the overall survival and our imaging marker (p = 0:009). Using the ROC curve, the patients are separated into two populations and the comparison of the survival curves is statistically significant (p = 0:025). The baseline exam seems to have a significant role in the prediction of response to TKI treatment. More precisely, our imaging biomarker defined using only the CT scan before the TKI introduction allows to determine a first classification of the population which is improved over time using the imaging marker as soon as more CT scans are available. This exploratory study leads us to think that it is possible to obtain a survival assessment using only few CT scans of the primary tumor.
dc.language.isoen
dc.publisherSpringer Verlag
dc.title.enA model-strengthened imaging biomarker for survival prediction in EGFR-mutated non-small-cell lung carcinoma patients treated with tyrosine kinase inhibitors
dc.typeArticle de revue
dc.identifier.doi10.1007/s11538-021-00902-7
dc.subject.halMathématiques [math]/Equations aux dérivées partielles [math.AP]
dc.subject.halSciences du Vivant [q-bio]/Cancer
dc.subject.halInformatique [cs]/Modélisation et simulation
bordeaux.journalBulletin of Mathematical Biology
bordeaux.volume83
bordeaux.hal.laboratoriesInstitut de Mathématiques de Bordeaux (IMB) - UMR 5251*
bordeaux.issue6
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.peerReviewedoui
hal.identifierhal-03428532
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-03428532v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Bulletin%20of%20Mathematical%20Biology&rft.date=2021-06&rft.volume=83&rft.issue=6&rft.eissn=0092-8240&rft.issn=0092-8240&rft.au=COLLIN,%20Annabelle&GROZA,%20Vladimir&MISSENARD,%20Louise&CHOMY,%20Fran%C3%A7ois&COLIN,%20Thierry&rft.genre=article


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