Coping Strategy Influences Quality of Life in Patients With Advanced Lung Cancer by Mediating Mood.

INTRODUCTION: Patients with advanced lung cancer experience high physical symptom burden with substantial psychological distress. Depressive and anxiety symptoms are common and associated with worse quality of life (QoL). Early palliative care (EPC) addresses the complex supportive care needs improving QoL and mood. The mechanisms of EPC are uncertain. We examined whether and how coping strategy, a primary component of EPC, influenced QoL in these patients. MATERIALS AND METHODS: We conducted a multicenter cross-sectional study of patients with advanced lung cancer. A total of 125 patients completed assessments of QoL (QLQ-C15-PAL), depressive and anxiety symptoms (HADS), and coping (brief COPE questionnaire). The data were analyzed by descriptive statistics. To determine whether and how coping strategy influences QoL, correlations and logistic regressions were performed. RESULTS: Positive reframing correlates significantly with global QoL (r = 0.25, P < .01), emotional well-being (r = 0.33, P < .01), pain (r = -0.30, P < .01), fatigue (r = -0.22, P < .01), loss of appetite (r = -0.22, P < .01) and nausea (r = -0.24, P < .01). Self-blame correlates significantly with worse emotional well-being (r = -0.19, P < .05) and insomnia (r = 0.19, P < .05). Using a 4-step logistic regression model, it was found that anxiety and depressive symptoms fully mediated the relationship between positive reframing and QoL. CONCLUSIONS: Patients with advanced lung cancer using positive reframing as coping strategy, experience higher QoL. The mechanism behind it seems that positive reframing goes along with less anxiety and depressive symptoms leading to a better QoL. Self-blame leads to more insomnia and worse emotional well-being. Providing skills to cope effectively could impact QoL in these patients.

Prognostic Understanding and Quality of Life in Patients With Advanced Lung Cancer: A Multicenter Study.

INTRODUCTION: Communication about the palliative setting remains a barrier for many physicians because they are afraid to harm the patient by giving bad news. We sought to determine whether this a valid concern; the influence of prognostic understanding on patients' quality of life (QoL); and which factors influence this relationship. METHODS: The present multicenter, cross-sectional study used a questionnaire to measure patients' prognostic understanding, QoL, mood, and coping strategy. RESULTS: We surveyed 125 patients with advanced lung cancer. Prognostic understanding correlated significantly with emotional well-being (r = -0.20; P = .01) and pain (r = 0.43; P = .00) but not with anxiety (r = 0.12, P = .12) or depression (r = 0.05; P = .29). Patients with anxiety (r = -0.23; P = .01) and patients with depressive feelings (r = -0.63; P = .00) experienced poorer QoL. Four in 10 patients reported feelings of anxiety and/or depression. Positive reframing as a coping strategy was associated with a better QoL (r = 0.25; P = .00). CONCLUSION: Prognostic understanding was related to poorer emotional well-being and more pain but does not affect mood. Four in 10 patients reported feelings of anxiety and/or depression, which were associated with a poorer QoL. A holistic approach seems necessary when physicians communicate about the palliative setting.

A Multicenter Study to Assess EGFR Mutational Status in Plasma: Focus on an Optimized Workflow for Liquid Biopsy in a Clinical Setting.

A multicenter study was performed to determine an optimal workflow for liquid biopsy in a clinical setting. In total, 549 plasma samples from 234 non-small cell lung cancer (NSCLC) patients were collected. Epidermal Growth Factor Receptor (EGFR) circulating cell-free tumor DNA (ctDNA) mutational analysis was performed using digital droplet PCR (ddPCR). The influence of (pre-) analytical variables on ctDNA analysis was investigated. Sensitivity of ctDNA analysis was influenced by an interplay between increased plasma volume (p < 0.001) and short transit time (p = 0.018). Multistep, high-speed centrifugation both increased plasma generation (p < 0.001) and reduced genomic DNA (gDNA) contamination. Longer transit time increased the risk of hemolysis (p < 0.001) and low temperatures were shown to have a negative effect. Metastatic sites were found to be strongly associated with ctDNA detection (p < 0.001), as well as allele frequency (p = 0.034). Activating mutations were detected in a higher concentration and allele frequency compared to the T790M mutation (p = 0.003, and p = 0.002, respectively). Optimization of (pre-) analytical variables is key to successful ctDNA analysis. Sufficient plasma volumes without hemolysis or gDNA contamination can be achieved by using multistep, high-speed centrifugation, coupled with short transit time and temperature regulation. Metastatic site location influenced ctDNA detection. Finally, ctDNA levels might have further value in detecting resistance mechanisms.

Geriatric screening results and the association with severe treatment toxicity after the first cycle of (radio)chemotherapy.

BACKGROUND: Screening tools are used in geriatric oncology to determine who should receive a Comprehensive Geriatric Assessment (CGA). However, in this prospective study, we evaluated the association between geriatric screening results, measured with the G8 and Groningen Frailty Indicator (GFI), and severe treatment toxicity. METHODS: Patients over 65 years with various types and stages of cancer were screened with the G8 and the GFI prior to the start of treatment. The association between geriatric screening results and Serious Adverse Events (SAE) after the first cycle of (radio)chemotherapy were studied with bivariate analysis (normal versus abnormal screening test) and logistic regression analysis. RESULTS: From 170 screened patients, 85 patients were eligible for this study. The median age was 76 years (range: 66-88 years). The treatment intent was curative in 46% and palliative in 54%. A SAE occurred in 15 patients (18%) of which three resulted in death. There was no significant association between the G8, as a dichotomous predictor (p = 0.376) or as a continuous predictor (p = 0.298), and risk of a SAE. We also found no significant association for the GFI analysed as a dichotomous predictor (cut-off ≥4: p = 0.384; cut-off ≥3: p = 0.773), nor as a continuous predictor (p = 0.734). All associations remained insignificant when adjusted for treatment type and comorbidity. CONCLUSION: The G8 and the GFI can be used to select patients for CGA, but they do not seem to be predictive for short-term severe treatment toxicity.

Evaluation of the Groningen Frailty Indicator and the G8 questionnaire as screening tools for frailty in older patients with cancer.

OBJECTIVE: In this study, we evaluated the Groningen Frailty Indicator (GFI) and the G8 questionnaire as screening tools for a Comprehensive Geriatric Assessment (CGA) in older patients with cancer. PATIENTS AND METHODS: Eligible patients with various types and stages of cancer were evaluated for frailty before treatment. Patients were categorized as patients with a normal CGA and abnormal CGA (≥2 impaired tests). The diagnostic performance of the screening tools was evaluated against the CGA with Receiver Operating Characteristic analysis. RESULTS: In total, 170 patients (79 women) with median age 77years old (range 66-97years) were included. Sixty-four percent of patients had an abnormal CGA while according to the GFI (GFI≥4) and G8 questionnaire (G8≤14) 47% and 76% of patients had an abnormal screening test, respectively. Overall, there was no significant difference (p=0.97) in diagnostic performance between the two screening tools. The Area Under the Curve was 0.87 for both tools. For the GFI and G8 questionnaire the sensitivity was respectively 66% (95% CI: 56-75%), 92% (95% CI: 85-96%); the negative predictive value (NPV): 59% (95 CI%: 49-69%), 78% (95% CI: 63-88%); and the specificity: 87% (95% CI: 76-94%), 52% (95% CI: 39-65%). CONCLUSION: In this study, we showed that overall both the GFI and the G8 questionnaire were able to separate older patients with cancer with a normal and abnormal CGA. For the G8 questionnaire, an adequate sensitivity and NPV were demonstrated, however at the expense of the specificity. For the GFI, we suggest to lower the threshold with one point to GFI ≥3 to screen patients for a CGA.