Background The Edmonton Symptom Assessment Scale (ESAS) is widely used for symptom assessment in the clinical and research settings. We used the sensitivity-specificity approach to identify the minimal clinically important difference (MCID) for improvement and deterioration for each of the 10 ESAS symptoms. Methods This multicenter, prospective, longitudinal study enrolled advanced cancer patients. ESAS was measured at first clinic visit and a second visit 3 weeks later. For each symptom, we assessed Patient's Global Impression (“better”, “about the same”, or “worse”) at the second visit as the external criterion, and determined the MCID based on the optimal cutoff in receiver-operating characteristic (ROC) curve. We conducted sensitivity analysis by estimating MCIDs using other approaches. Results Among the 796 participants, the median duration between the 2 study visits was 21 days (interquartile range 18-28 days). The area under the ROC curve varied between 0.70-0.87, suggesting good responsiveness. For all 10 symptoms, the optimal cutoff was ≥1 point for improvement and ≤−1 point for deterioration, with sensitivities of 59%-85% and specificities of 69%-85%. Using other approaches, the MCIDs varied between 0.8 and 2.2 for improvement and between −0.8 and −2.3 for deterioration in within-patient analysis, between 1.2 and 1.6 with the ½ standard deviation approach, and between 1.3 and 1.7 with the standard error of measurement approach. Conclusions ESAS was responsive to change. The optimal cutoffs were ≥1 point for improvement and ≤−1 point for deterioration for each of the 10 symptoms. Our findings have implications for sample size calculations and response determination.

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Context The Edmonton Symptom Assessment System (ESAS) is one of the most commonly used symptom batteries in clinical practice and research. Objectives We used the anchor-based.approach to identify the minimal clinically important difference (MCID) for improvement and deterioration for ESAS physical, emotional and total symptom distress scores. Methods In this multicenter prospective study, we asked patients with advanced cancer to complete their ESAS at the first clinic visit and at a second visit three weeks later. The anchor for MCID determination was Patient's Global Impression regarding their physical, emotional and overall symptom burden (“better,” “about the same,” or “worse”). We identified the optimal sensitivity/specificity cutoffs for both improvement and deterioration for the three ESAS scores and also determined the within-patient changes. Results A total of 796 patients were enrolled from six centers. The ESAS scores had moderate responsiveness, with area under the receiver-operating characteristic curve between 0.69 and 0.76. Using the sensitivity-specificity approach, the optimal cutoffs for ESAS physical, emotional and total symptom distress scores were ≥3/60, ≥2/20 and ≥3/90 for improvement, and ≤−4/60, ≤−1/20 and ≤−4/90 for deterioration, respectively. These cutoffs had moderate sensitivities (59%-68%) and specificities (62%-80%). The within-patient change approach revealed the MCID cutoffs for improvement/deterioration to be 3/−4.3 for the physical score, 2.4/−1.8 for the emotional score, and 5.7/−2.9 for the total symptom distress score. Conclusion We identified the MCIDs for physical, emotional and total symptom distress scores, which have implications for interpretation of symptom response in clinical trials.

Surgery remains the mainstay of the treatment of head and neck osteosarcoma. Adjuvant radiotherapy improves outcome in patients with adverse factors.

Passive decision control preferences were less common (23%) than shared and active decision control preference even among developing countries. Significant predictors of passive decision control preferences were performance status, education, and country of origin.

Background Improving symptoms is a major goal of cancer medicine; however, symptom response is often based on group differences and not individualized. We examined the personalized symptom goal (PSG) for 10 common symptoms in patients with advanced cancer, and identified the factors associated with PSG response. Methods In this prospective longitudinal multicenter study, patients from 5 tertiary care hospitals rated the intensity of 10 symptoms using a 0-10 numeric rating scale at first clinic visit and then a second visit 14-34 days later. PSG was determined for each symptom by asking patients: “At what level would you feel comfortable with this symptom?” using the same 0-10 scale for symptom intensity. PSG response was defined as symptom intensity at second visit less than or equal to PSG. Results Among 728 patients, the median PSG was 1 for nausea, 2 for depression, anxiety, drowsiness, well being, dyspnea and sleep, and 3 for pain, fatigue, and appetite. A greater proportion of patients achieved a PSG response in second visit compared to first visit (P<0.05 except for drowsiness). Symptom response was associated with lower baseline symptom intensity based on PSG criterion but higher baseline symptom intensity based on the traditional minimal clinically important difference definition (P<0.001 for all symptoms). In multivariable analysis, higher PSG and nationality were associated with greater PSG response. Conclusion PSG was ≤3 for a majority of patients. PSG response allows clinicians to tailor treatment goals, while adjusting for individual differences in scale interpretation and factors associated with symptom response.

Context Attrition is common in longitudinal observational studies in palliative care. Few studies have examined predictors of attrition. Objectives To identify patient characteristics at enrollment associated with attrition in palliative oncology outpatient setting. Methods In this longitudinal observational study, advanced cancer patients [ACP] enrolled in an outpatient multicenter study were assessed at baseline and 2–5 weeks later. We compared baseline characteristics between patients who returned for follow-up and those who dropped out. Results 744 patients were enrolled from Jordan, Brazil, Chile, Korea and India. Attrition rate was 33%, with variation among countries (22%–39%; p=.023). In univariate analysis, baseline predictors for attrition were cognitive failure (odds ratio [OR] 1.23 per point in Memorial Delirium Assessment Scale; p<.01), functional status (OR 1.55 per 10 point decrease in Karnofsky Performance Status; p<.01), Edmonton Symptom Assessment System [ESAS] physical score (OR 1.03 per point; p<.01), ESAS emotional score (OR 1.05 per point; p<.01) and shorter duration between cancer diagnosis and palliative care referral in months (OR .89 per log; p=.028). In multivariate analysis, cognitive failure (OR 1.12 per point; p=.007), ESAS physical score (OR 1.18 per point; p=.027), functional status (OR 1.35 per 10 point decrease; p<.001) and shorter duration from cancer diagnosis (OR .86 per log; p=.01) remained independent predictors of attrition. Conclusion ACP with cognitive failure, increased physical symptoms, poorer performance status and shorter duration from cancer diagnosis were more likely to dropout. These results have implications for research design, patient selection and data interpretation in longitudinal observational studies.