The Challenge of Return to Work after Breast Cancer: The Role of Family Situation, CANTO Cohort

International audienceReturn to work (RTW) after breast cancer is associated with improved quality of life. The link between household characteristics and RTW remains largely unknown. The aim of this study was to examine the effect of the family situation on women’s RTW two years after breast cancer. We used data of a French prospective cohort of women diagnosed with stage I-III, primary breast cancer (CANTO, NCT01993498). Among women employed at diagnosis and under 57 years old, we assessed the association between household characteristics (living with a partner, marital status, number and age of economically dependent children, support by the partner) and RTW. Logistic regression models were adjusted for age, household income, stage, comorbidities, treatments and their side effects. Analyzes stratified by age and household income were performed to assess the association between household characteristics and RTW in specific subgroups. Among the 3004 patients included, women living with a partner returned less to work (OR = 0.63 [0.47–0.86]) and decreased their working time after RTW. Among the 2305 women living with a partner, being married was associated with decreased RTW among women aged over 50 (OR = 0.57 [0.34–0.95]). Having three or more children (vs. none) was associated with lower RTW among women with low household income (OR = 0.28 [0.10–0.80]). Household characteristics should be considered in addition to clinical information to identify vulnerable women, reduce the social consequence of cancer and improve their quality of life

Perceived Discrimination at Work: examining social, health and work-related factors as determinants among breast cancer survivors. Evidence from the prospective CANTO cohort

International audienceBackground We assessed the prevalence of self-reported perceived discrimination in the workplace after the end of treatment among breast cancer (BC) survivors and studied its association with social, health-related and work-related factors. Methods We used data from a French prospective cohort (CANcer TOxicities) including women diagnosed with stage I–III BC. Our analysis included 2130 women who were employed, <57 years old at BC diagnosis and were working 2 years afterwards. We assessed the association between social, health-related and work-related factors and perceived discrimination in the workplace using logistic regression models. Results Overall, 26% of women reported perceived discrimination in the workplace after the end of treatment. Women working for a small company, in the public sector or with better overall health status were less likely to report perceived discrimination. Women who benefited from easing dispositions at their workplace, who did not feel supported by their colleagues and those who returned to work because of fear of job loss were more likely to report perceived discrimination. Conclusions One in four BC survivors perceives discrimination in the workplace. Health and work-related factors are associated with increased likelihood of reporting perceived discrimination. Trial registration number NCT01993498

Development and Validation of a Predictive Model of Severe Fatigue After Breast Cancer Diagnosis: Toward a Personalized Framework in Survivorship Care

International audiencePURPOSE Fatigue is common and troublesome among breast cancer survivors; however, limited tools exist to predict its risk. PATIENTS AND METHODS Participants with stage I-III breast cancer were prospectively included from CANTO (ClinicalTrials.gov identifier: NCT01993498 ), collecting longitudinal data at diagnosis (before the initiation of any cancer treatment) and 1 (T1), 2 (T2), and 4 (T3) years after diagnosis. The main outcome was severe global fatigue at T2 (score ≥q 40/100, European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire-C30). Analyses at T3 were exploratory. Secondary outcomes included physical, emotional, and cognitive fatigue (EORTC Quality of Life Questionnaire-FA12). Multivariable logistic regression models retained associations with severe fatigue by bootstrapped Augmented Backward Elimination. Validation methods included 10-fold internal cross-validation, overoptimism-corrected area under the receiver operating characteristic curves, and external validation. RESULTS Among 5,640, 5,000, and 3,400 patients at T1, T2, and T3, respectively, the prevalence of post-treatment severe global fatigue was 35.6%, 34.0%, and 31.5% in the development cohort. Retained risk factors for severe global fatigue at T2 were severe pretreatment fatigue (adjusted odds ratio v no 3.191 [95% CI, 2.704 to 3.767]); younger age (for 1-year decrement 1.015 [1.009 to 1.022]), higher body mass index (for unit increment 1.025 [1.012 to 1.038]), current smoking behavior ( v never 1.552 [1.291 to 1.866]), worse anxiety ( v noncase 1.265 [1.073 to 1.492]), insomnia (for unit increment 1.005 [1.003 to 1.007]), and pain at diagnosis (for unit increment 1.014 [1.010 to 1.017]), with an area under the receiver operating characteristic curve of 0.73 (95% CI, 0.72 to 0.75). Receipt of hormonal therapy was a risk factor for severe fatigue at T3 ( v no 1.448 [1.165 to 1.799]). Dimension-specific risk factors included body mass index for physical fatigue and emotional distress for emotional and cognitive fatigue. CONCLUSION We propose a predictive model to assess fatigue among breast cancer survivors, within a personalized survivorship care framework. This may help clinicians to provide early management interventions or to correct modifiable risk factors and offer more tailored monitoring and education to patients at risk of severe post-treatment fatigue

Development and Validation of a Predictive Model of Severe Fatigue After Breast Cancer Diagnosis: Toward a Personalized Framework in Survivorship Care

International audiencePURPOSE Fatigue is common and troublesome among breast cancer survivors; however, limited tools exist to predict its risk. PATIENTS AND METHODS Participants with stage I-III breast cancer were prospectively included from CANTO (ClinicalTrials.gov identifier: NCT01993498 ), collecting longitudinal data at diagnosis (before the initiation of any cancer treatment) and 1 (T1), 2 (T2), and 4 (T3) years after diagnosis. The main outcome was severe global fatigue at T2 (score ≥q 40/100, European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire-C30). Analyses at T3 were exploratory. Secondary outcomes included physical, emotional, and cognitive fatigue (EORTC Quality of Life Questionnaire-FA12). Multivariable logistic regression models retained associations with severe fatigue by bootstrapped Augmented Backward Elimination. Validation methods included 10-fold internal cross-validation, overoptimism-corrected area under the receiver operating characteristic curves, and external validation. RESULTS Among 5,640, 5,000, and 3,400 patients at T1, T2, and T3, respectively, the prevalence of post-treatment severe global fatigue was 35.6%, 34.0%, and 31.5% in the development cohort. Retained risk factors for severe global fatigue at T2 were severe pretreatment fatigue (adjusted odds ratio v no 3.191 [95% CI, 2.704 to 3.767]); younger age (for 1-year decrement 1.015 [1.009 to 1.022]), higher body mass index (for unit increment 1.025 [1.012 to 1.038]), current smoking behavior ( v never 1.552 [1.291 to 1.866]), worse anxiety ( v noncase 1.265 [1.073 to 1.492]), insomnia (for unit increment 1.005 [1.003 to 1.007]), and pain at diagnosis (for unit increment 1.014 [1.010 to 1.017]), with an area under the receiver operating characteristic curve of 0.73 (95% CI, 0.72 to 0.75). Receipt of hormonal therapy was a risk factor for severe fatigue at T3 ( v no 1.448 [1.165 to 1.799]). Dimension-specific risk factors included body mass index for physical fatigue and emotional distress for emotional and cognitive fatigue. CONCLUSION We propose a predictive model to assess fatigue among breast cancer survivors, within a personalized survivorship care framework. This may help clinicians to provide early management interventions or to correct modifiable risk factors and offer more tailored monitoring and education to patients at risk of severe post-treatment fatigue

Dynamics of Long-Term Patient-Reported Quality of Life and Health Behaviors After Adjuvant Breast Cancer Chemotherapy

International audiencePURPOSE We aimed to characterize long-term quality of life (QOL) trajectories among patients with breast cancer treated with adjuvant chemotherapy and to identify related patterns of health behaviors. METHODS Female stage I-III breast cancer patients receiving chemotherapy in CANTO (CANcer TOxicity; ClinicalTrials.gov identifier: NCT01993498 ) were included. Trajectories of QOL (European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire\textendash C30 Summary Score) and associations with trajectory group membership were identified by iterative estimations of group-based trajectory models and multivariable multinomial logistic regression, respectively. RESULTS Four trajectory groups were identified (N = 4,131): excellent (51.7%), very good (31.7%), deteriorating (10.0%), and poor (6.6%) QOL. The deteriorating trajectory group reported fairly good baseline QOL (mean [95% CI], 78.3/100 [76.2 to 80.5]), which significantly worsened at year-1 (58.1/100 [56.4 to 59.9]) and never recovered to pretreatment values through year-4 (61.1/100 [59.0 to 63.3]) postdiagnosis. Healthy behaviors were associated with better performing trajectory groups. Obesity (adjusted odds ratio [aOR] v lean, 1.51 [95% CI, 1.28 to 1.79]; P < .0001) and current smoking (aOR v never, 1.52 [95% CI, 1.27 to 1.82]; P < .0001) at diagnosis were associated with membership to the deteriorating group, which was also characterized by a higher prevalence of patients with excess body weight and insufficient physical activity through year-4 and by frequent exposure to tobacco smoking during chemotherapy. Additional factors associated with membership to the deteriorating group included younger age (aOR, 1-year decrement 1.01 [95% CI, 1.01 to 1.02]; P = .043), comorbidities (aOR v no, 1.22 [95% CI, 1.06 to 1.40]; P = .005), lower income (aOR v wealthier households, 1.21 [95% CI, 1.07 to 1.37]; P = .002), and endocrine therapy (aOR v no, 1.14 [95% CI, 1.01 to 1.30]; P = .047). CONCLUSION This latent-class analysis identified some patients with upfront poor QOL and a high-risk cluster with severe, persistent postchemotherapy QOL deterioration. Screening relevant patient-level characteristics may inform tailored interventions to mitigate the detrimental impact of chemotherapy and preserve QOL, including early addressal of behavioral concerns and provision of healthy lifestyle support programs

Dynamics of Long-Term Patient-Reported Quality of Life and Health Behaviors After Adjuvant Breast Cancer Chemotherapy

PURPOSE We aimed to characterize long-term quality of life (QOL) trajectories among patients with breast cancer treated with adjuvant chemotherapy and to identify related patterns of health behaviors. METHODS Female stage I-III breast cancer patients receiving chemotherapy in CANTO (CANcer TOxicity; ClinicalTrials.gov identifier: NCT01993498 ) were included. Trajectories of QOL (European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire\textendash C30 Summary Score) and associations with trajectory group membership were identified by iterative estimations of group-based trajectory models and multivariable multinomial logistic regression, respectively. RESULTS Four trajectory groups were identified (N = 4,131): excellent (51.7%), very good (31.7%), deteriorating (10.0%), and poor (6.6%) QOL. The deteriorating trajectory group reported fairly good baseline QOL (mean [95% CI], 78.3/100 [76.2 to 80.5]), which significantly worsened at year-1 (58.1/100 [56.4 to 59.9]) and never recovered to pretreatment values through year-4 (61.1/100 [59.0 to 63.3]) postdiagnosis. Healthy behaviors were associated with better performing trajectory groups. Obesity (adjusted odds ratio [aOR] v lean, 1.51 [95% CI, 1.28 to 1.79]; P < .0001) and current smoking (aOR v never, 1.52 [95% CI, 1.27 to 1.82]; P < .0001) at diagnosis were associated with membership to the deteriorating group, which was also characterized by a higher prevalence of patients with excess body weight and insufficient physical activity through year-4 and by frequent exposure to tobacco smoking during chemotherapy. Additional factors associated with membership to the deteriorating group included younger age (aOR, 1-year decrement 1.01 [95% CI, 1.01 to 1.02]; P = .043), comorbidities (aOR v no, 1.22 [95% CI, 1.06 to 1.40]; P = .005), lower income (aOR v wealthier households, 1.21 [95% CI, 1.07 to 1.37]; P = .002), and endocrine therapy (aOR v no, 1.14 [95% CI, 1.01 to 1.30]; P = .047). CONCLUSION This latent-class analysis identified some patients with upfront poor QOL and a high-risk cluster with severe, persistent postchemotherapy QOL deterioration. Screening relevant patient-level characteristics may inform tailored interventions to mitigate the detrimental impact of chemotherapy and preserve QOL, including early addressal of behavioral concerns and provision of healthy lifestyle support programs