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

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.