PURPOSE: The Distress Thermometer (the DT) is a commonly used screening tool to detect distress in cancer patients. This meta-analysis aims to examine the diagnostic role and the optimal cut-off score of the DT compared with various different reference standards. METHODS: We searched PubMed and Embase from 1997 to September 2013 for relevant studies. After extracting data, we estimated the pooled sensitivity, specificity, likelihood ratios, diagnostic odds ratios, and constructed summary receiver operating characteristics curves to determine the optimal cut-off score. RESULTS: Forty-two relevant studies and 14,808 patients were included in total. When we pooled all the results together, the DT showed a good balance between pooled sensitivity (0.81, 95% confidence intervals (CI) 0.79-0.82) and pooled specificity (0.72, 95% CI 0.71-0.72) at the cut-off score of 4. The value of area under the curve (AUC) is 0.8321. When the DT is compared with the HADS-Total, the cut-off score of 4 maximized the balance between the pooled sensitivity (0.82, 95% CI 0.80-0.84) and pooled specificity (0.73, 95% CI 0.72-0.74). The AUC is 0.8432. CONCLUSIONS: This meta-analysis suggests that the DT is a valid tool to detect potential distress in cancer patients. According to our results, 4 as the optimal cut-off, is recommended. Further studies are needed to be done to examine the accuracy and optimal cut-off score in different regions globally and different cancer subtypes to guide the use of the DT for different patients.
PURPOSE: The Distress Thermometer (the DT) is a commonly used screening tool to detect distress in cancerpatients. This meta-analysis aims to examine the diagnostic role and the optimal cut-off score of the DT compared with various different reference standards. METHODS: We searched PubMed and Embase from 1997 to September 2013 for relevant studies. After extracting data, we estimated the pooled sensitivity, specificity, likelihood ratios, diagnostic odds ratios, and constructed summary receiver operating characteristics curves to determine the optimal cut-off score. RESULTS: Forty-two relevant studies and 14,808 patients were included in total. When we pooled all the results together, the DT showed a good balance between pooled sensitivity (0.81, 95% confidence intervals (CI) 0.79-0.82) and pooled specificity (0.72, 95% CI 0.71-0.72) at the cut-off score of 4. The value of area under the curve (AUC) is 0.8321. When the DT is compared with the HADS-Total, the cut-off score of 4 maximized the balance between the pooled sensitivity (0.82, 95% CI 0.80-0.84) and pooled specificity (0.73, 95% CI 0.72-0.74). The AUC is 0.8432. CONCLUSIONS: This meta-analysis suggests that the DT is a valid tool to detect potential distress in cancerpatients. According to our results, 4 as the optimal cut-off, is recommended. Further studies are needed to be done to examine the accuracy and optimal cut-off score in different regions globally and different cancer subtypes to guide the use of the DT for different patients.
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