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  • The distress thermometer as a prognostic tool for one-year survival among patients with lung cancer

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    Author(s)
    Geerse, OP
    Brandenbarg, D
    Kerstjens, HAM
    Berendsen, AJ
    Duijts, SFA
    Burger, H
    Holtman, GA
    Hoekstra-Weebers, JEHM
    Hiltermann, TJN
    Griffith University Author(s)
    Duijts, Saskia
    Year published
    2019
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    Abstract
    Introduction: The use of patient-reported outcome measures is increasingly advocated to support high-quality cancer care. We therefore investigated the added value of the Distress Thermometer (DT) when combined with known predictors to assess one-year survival in patients with lung cancer. Methods: All patients had newly diagnosed or recurrent lung cancer, started systemic treatment, and participated in the intervention arm of a previously published randomised controlled trial. A Cox proportional hazards model was fitted based on five selected known predictors for survival. The DT-score was added to this model and contrasted ...
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    Introduction: The use of patient-reported outcome measures is increasingly advocated to support high-quality cancer care. We therefore investigated the added value of the Distress Thermometer (DT) when combined with known predictors to assess one-year survival in patients with lung cancer. Methods: All patients had newly diagnosed or recurrent lung cancer, started systemic treatment, and participated in the intervention arm of a previously published randomised controlled trial. A Cox proportional hazards model was fitted based on five selected known predictors for survival. The DT-score was added to this model and contrasted to models including the EORTC-QLQ-C30 global QoL score (quality of life) or the HADS total score (symptoms of anxiety and depression). Model performance was evaluated through improvement in the -2 log likelihood, Harrell's C-statistic, and a risk classification. Results: In total, 110 patients were included in the analysis of whom 97 patients accurately completed the DT. Patients with a DT score ≥5 (N = 51) had a lower QoL, more symptoms of anxiety and depression, and a shorter median survival time (7.6 months vs 10.0 months; P = 0.02) than patients with a DT score <5 (N = 46). Addition of the DT resulted in a significant improvement in the accuracy of the model to predict one-year survival (P < 0.001) and the discriminatory value (C-statistic) marginally improved from 0.69 to 0.71. The proportion of patients correctly classified as high risk (≥85% risk of dying within one year) increased from 8% to 28%. Similar model performance was observed when combining the selected predictors with QoL and symptoms of anxiety or depression. Conclusions: Use of the DT allows clinicians to better identify patients with lung cancer at risk for poor outcomes, to further explore sources of distress, and subsequently personalize care accordingly.
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    Journal Title
    Lung Cancer
    Volume
    130
    DOI
    https://doi.org/10.1016/j.lungcan.2019.02.008
    Copyright Statement
    © 2019 The Author(s). Published by Elsevier B.V. This is an open access article distributed under the terms of the Creative Commons CC-BY license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
    Subject
    Clinical sciences
    Oncology and carcinogenesis
    Science & Technology
    Life Sciences & Biomedicine
    Oncology
    Respiratory System
    Lung neoplasm
    Publication URI
    http://hdl.handle.net/10072/397267
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    • Journal articles

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