Introduction Use of patient-reported outcome measures is advocated to support high-quality cancer care. We 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 Patients had newly diagnosed or recurrent lung cancer, started systemic treatment, and participated in the intervention arm of a previously published randomised 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 or the HADS total score. 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 35 (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 (385% risk of dying within one year) increased from 8% to 28%.
Conclusions Use of the DT allows clinicians to better identify patients with lung cancer at risk for poor survival, further explore sources of distress, and personalize care accordingly.
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