Trait emotional intelligence and quality of life among breast cancer patients: The mediating role of fear of cancer recurrence

Author(s):  
Wen Yu Chen ◽  
Shuang Wang ◽  
Xue Peng ◽  
Yun Zhu
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Yue Ban ◽  
Mengyao Li ◽  
Mingli Yu ◽  
Hui Wu

Abstract Background Women with breast cancer are prone to have mental stress and be stimulated by the fear of progression (FOP), then giving rise to a lower quality of life (QOL). The study aimed to examine the relationships between FOP, social support and QOL, and further explore whether social support mediates the association between FOP and QOL among Chinese patients with breast cancer. Methods The cross-sectional study was conducted from October 2019 to May 2020 at Anshan Cancer Hospital in Liaoning, China. 244 female breast cancer patients completed questionnaires including the Functional Assessment of Cancer Therapy for Breast (FACT-B), Multi-Dimensional Scale of Perceived Social Support (MSPSS), and Fear of Progression (FOP). Hierarchical multiple regression analysis was performed to assess the associations between FOP, social support and QOL. Asymptotic and resampling strategies were used to explore the mediating role of social support. Results The mean QOL score was 90.6 ± 17.0 among the patients with breast cancer. FOP was negatively correlated with QOL, while social support was positively related to QOL. Social support partly mediated the association between FOP and QOL, and the proportion of the mediating effect accounted for by social support was 25%. Conclusions Chinese breast cancer patients expressed low QOL. Social support could mediate the association between FOP and QOL. Medical staffs and cancer caregivers should alleviate patients’ FOP to improve their QOL by facilitating social support.


2022 ◽  
Author(s):  
Zhensheng Li ◽  
Yue Li ◽  
Yunjiang Liu ◽  
Jun Zhang ◽  
Xiaohui Ji ◽  
...  

Abstract Objective: To characterize the fear of cancer recurrence (FCR) and its relationship with anxiety and depression and quality of life (QoL) among Chinese breast cancer (BC) patients in China. Methods: Patients completed the questionnaires of QLQ-C30, QLQ-BR32 and HAD to assess FCR, QoL, anxiety and depression before radiotherapy. A cross-sectional analysis was performed. Chi-square and non-parametric tests and multivariate ordinal logistic regressions (mOLR) were utilized for reference analysis. Final covariates included age, BMI, TNM, surgery, chemotherapy, pain, and sleep disturbance. Results: From July 2015 to December 2016, 463 patients were prospectively enrolled. Their age mean (range) were 47 (19 - 89) years old. In total, 327 patients (70.6%) reported having FCR ‘a little bit’ (51.2%), ‘some’ (12.1%) and ‘very much’ (7.3%) in the past week. FCR severity ordered above (incl. ‘no’) was associated with anxiety score (median 1.5, 5.0, 7.0, 8.5 and level (‘abnormal’ rate 0%, 3.4%, 12.5%, 26.5%), depression score (median 2.0, 4.0, 6.0, 6.5) and level (‘abnormal’ rate 2.2%, 3.4%, 5.4%, 17.7%) (all p<0.001). mOLR showed that compared to ‘no’, three higher levels of FCR were associated with one level increase of anxiety with OR (p) as 1.983 (0.076), 4.291 (0.001), 8.282 (<0.001) and depression with OR (p) as 1.903 (0.062), 2.262 (0.065), 4.205 (0.004), respectively. FCR severity also was inversely associated with most QoL function scores (p<0.001). Conclusions: FCR was prevalent in Chinese BC patients and linearly associated with anxiety, depression and low QoL. It seems that a single-item question for FCR is a valid surrogate tool for distress screening in this population.


2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Qing Yang ◽  
Xuexin Yu ◽  
Wei Zhang

Abstract Background This study aimed to obtain health utility parameters among Chinese breast cancer patients in different disease states for subsequent health economics model. In addition, we aimed to explore the feasibility of establishing a breast cancer health utility mapping model in China. Methods Multiple patient-reported health attributes were assessed, including quality of life, which was measured by the Functional Assessment of Cancer Therapy-Breast (FACT-B) instrument; health utility and self-rated health, which were measured by the EuroQol-5 Dimension-5 Level (EQ-5D-5L) questionnaire. Multivariate regression models, including a linear regression model, an ordinal logistic regression model and a Tobit model, were employed to analyze health differences among 446 breast cancer patients. Subgroup analyses were performed to examine differences in multiple dimensions of health derived from the FACT-B and EQ-5D-5L instruments. A mapping function was used to estimate health utility from quality of life. Rank correlation analyses were employed to examine the correlation between estimated and observed health utility values. Results A total of 446 breast cancer patients with different disease states were analyzed. The health utility values of breast cancer patients in the P state (without cancer recurrence and metastasis), R state (with cancer recurrence within a year), S state (with primary and recurrent breast cancer for the second year and above), and M state (metastatic cancer) were 0.81 (SD ± 0.23), 0.90 (SD ± 0.12), 0.78 (SD ± 0.31), and 0.74 (SD ± 0.27), respectively. There were positive correlations between all scores, including every domain of the FACT-B instrument (p < 0.001). Results from multivariate analysis suggested that patients in the R and M states had lower scores for overall quality of life (R, β = − 9.45, p < 0.01; M, β = − 6.72, p < 0.05). Patients in the M state had lower health utility values than patients in the P state (β = − 0.11, p < 0.05). Estimated health utility values, which were derived from quality of life by using a mapping function, were significantly correlated with directly measured health utility values (p < 0.001). Conclusions We obtained the health utility and health-related quality of life (HRQoL) scores of Chinese breast cancer patients in different disease states. Mapping health utility values from quality of life using four disease states could be feasible in health economic modelling, but the mapping function may need further revision.


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