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Diagnostics for Targeted NSCLC Therapy

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  • Verena Schildgen

    (Kliniken der Stadt Köln gGmbH, Klinikum der Privaten Universität Witten/Herdecke, Institut für Pathologie, D-51109 Cologne, Germany)

  • Ilija Nenadic

    (Kliniken der Stadt Köln gGmbH, Klinikum der Privaten Universität Witten/Herdecke, Institut für Pathologie, D-51109 Cologne, Germany)

  • Michael Brockmann

    (Kliniken der Stadt Köln gGmbH, Klinikum der Privaten Universität Witten/Herdecke, Institut für Pathologie, D-51109 Cologne, Germany)

  • Oliver Schildgen

    (Kliniken der Stadt Köln gGmbH, Klinikum der Privaten Universität Witten/Herdecke, Institut für Pathologie, D-51109 Cologne, Germany)

Abstract

Despite an increasing number of molecular biomarkers identified in non-small cell lung cancer (NSCLC), the number of approved therapy options targeting these biomarkers remains limited. Although some biomarkers may influence the therapy outcome of a distinct drug and have been shown to be useful in phase 2 or 3 clinical studies, diagnostics of biomarkers without an approved drug available or a possible off-label use is currently too expensive for routine diagnostics in non-academic institutions. For this reason, the present review is intended to summarize the current state of the art of molecular diagnostics that is both available and could lead to therapy guidance in NSCLC courses. Thereby, economic aspects are taken into account in order to take up the cudgels for a more comprehensive, even if more expensive, diagnostic scheme that in turn may save enormous costs by reducing therapy costs.

Suggested Citation

  • Verena Schildgen & Ilija Nenadic & Michael Brockmann & Oliver Schildgen, 2017. "Diagnostics for Targeted NSCLC Therapy," Challenges, MDPI, vol. 8(2), pages 1-6, November.
    • Handle: RePEc:gam:jchals:v:8:y:2017:i:2:p:29-:d:119640
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    References listed on IDEAS

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    1. Bogojeska Jasmina & Lengauer Thomas, 2012. "Hierarchical Bayes Model for Predicting Effectiveness of HIV Combination Therapies," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(3), pages 1-21, April.
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      Keywords

      lung cancer; NSCLC; diagnostics;
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