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Modélisation du risque d’évolution métastatique chez les patients supposés avoir une maladie localisée

Model-based assessment of the risk of metastatic spreading in patients with localized cancer

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Oncologie

Abstract

Classification of cancer as localized or metastatic disease remains the mainstay for determining the best therapeutic strategy to be undertaken at bedside. Although simple, this classification may underestimate the risk of undetectable, early metastatic stages. Many studies have been performed to identify prognostic biomarkers for evaluating the risk of metastatic relapse in patients with apparently localized disease. Here, we have developed an original mathematical model designed to calculate a Metastatic Index. This Metastatic Index should enable to better predict the risk of invasive cancer, even when it does not show with standard imaging techniques. Further validation steps are ongoing, both in tumor-bearing animals and as part of retrospective comparisons with clinical data. This new tool should help the clinician to undertake systemic treatment at the earliest stages of the disease, thus allowing a better efficacy eventually.

Résumé

La stratégie de traitement d’une tumeur solide repose fondamentalement sur le classement initial entre maladie localisée ou avancée. Or, il est possible que des états métastatiques précoces ne soient pas mis en évidence lors des bilans d’extension. Ce risque implicitement reconnu justifierait pourtant l’usage de thérapies adjuvantes après traitement radical de type exérèse chirurgicale. Un grand nombre de travaux ont déjà été réalisés afin d’identifier des marqueurs pronostiques permettant de préciser ce risque invasif chez des patients dont la maladie était apparemment localisée. Dans ce contexte, notre étude, basée sur une modélisation mathématique originale, présente un nouveau marqueur, l’index métastatique (IM), permettant de donner une estimation du nombre et de la taille des métastases en fonction du temps. À terme, cette technologie pourrait fournir un nouvel outil décisionnel précieux permettant de prédire le risque d’évolution métastatique et éclairer au mieux le clinicien sur l’intérêt d’un éventuel traitement adjuvant.

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Authors and Affiliations

  1. Laboratoire de pharmacocinétique, UMR-MD3, Université d’Aix-Marseille, 27, boulevard Jean-Moulin, F-13385, Marseille cedex 05, France

    D. Barbolosi, F. Verga, C. Mercier, J. Ciccolini & C. Faivre

  2. UMR CNRS 6632, université de Provence, LATP, 39, rue F.-Joliot-Curie, F-13453, Marseille cedex 13, France

    F. Verga, A. Benabdallah & F. Hubert

  3. EA 3738, Faculté de Médecine Lyon-Sud, Université de Lyon, F-69622, Lyon, France

    B. You

  4. Service d’oncologie médicale, centre hospitalier Lyon-Sud, hospices civils de Lyon, F-69310, Pierre-Bénite, France

    B. You

  5. Medical Oncology Department, Drug development program, Princess-Margaret Hospital, Toronto, Canada

    B. You

  6. Pôle oncologie, CHU Timone, AP-HM, F-13385, Marseille cedex 05, France

    C. Mercier & J. Ciccolini

Authors
  1. D. Barbolosi
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  2. F. Verga
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  3. B. You
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  4. A. Benabdallah
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  5. F. Hubert
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  6. C. Mercier
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  7. J. Ciccolini
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  8. C. Faivre
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Corresponding author

Correspondence to D. Barbolosi.

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Barbolosi, D., Verga, F., You, B. et al. Modélisation du risque d’évolution métastatique chez les patients supposés avoir une maladie localisée. Oncologie 13, 528–533 (2011). https://doi.org/10.1007/s10269-011-2028-6

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  • DOI: https://doi.org/10.1007/s10269-011-2028-6

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