Predictors of enduring clinical distress in women with breast cancer

To date, little is known about enduring clinical distress as measured with the commonly used distress thermometer. We therefore used the distress thermometer to examine: (a) the prevalence of enduring clinical distress, distress-related problems, and subsequent wish for referral of women with breast cancer, and (b) sociodemographic, clinical, and psychosocial predictors of enduring clinical distress. The study had a multicenter, prospective, observational design. Patients with primary breast cancer completed a questionnaire at 6 and 15 months postdiagnosis. Medical data were retrieved from chart reviews. Enduring clinical distress was defined as heightened distress levels over time. The prevalence of enduring clinical distress, problems, and wish for referral was examined with descriptive analyses. Associations between predictors and enduring clinical distress were examined with multivariate analyses. One hundred sixty-four of 746 patients (22 %) reported having enduring clinical distress at 6 and 15 months postdiagnosis. Of these, 10 % wanted to be referred for care. Fatigue was the most frequently reported problem by patients with and without clinical distress, at both time points. Lack of muscle strength (OR = 1.82, 95 % CI 1.12–2.98), experience of a low level of life satisfaction (OR = 0.77, 95 % CI 0.67–0.89), more frequent cancer worry (OR = 1.40, 95 % CI 1.05–1.89), and neuroticism (OR = 1.09, 95 % CI 1.00–1.18) were predictors of enduring clinical distress. In conclusion, one in five women with breast cancer develops enduring clinical distress. Oncologists, nurse practitioners, and cancer nurses are advised to use single-item questions about distress and distress-related problems to ensure timely detection of high-risk patients. Providers should also routinely assess fatigue and its causes, as fatigue is the most frequently reported distress-related problem over time

Health care use and remaining needs for support among women with breast cancer in the first 15 months after diagnosis:the role of the GP

Background: The number of women with breast cancer in general practice is rising. To address their needs and wishes for a referral, GPs might benefit from more insight into women's health care practices and need for additional support. Objective: To examine the prevalence of health care use and remaining needs among women with breast cancer in the first 15 months after diagnosis. Methods: In this multicentre, prospective, observational study women with breast cancer completed a questionnaire at 6 and 15 months post-diagnosis. Medical data were retrieved through chart reviews. The prevalence of types of health care used and remaining needs related to medical, psychosocial, paramedical and supplementary service care (such as home care), was examined with descriptive analyses. Results: Seven hundred forty-six women completed both questionnaires. At both assessments patients reported that they had most frequent contact with medical and paramedical providers, independent of types of treatment received. Three to fifteen percent of the patients expressed a need for more support. Prominent needs included a wish for more frequent contact with a physiotherapist, a clinical geneticist and a psychologist. Patients also wanted more help for chores around the house, particularly in the early post-treatment phase. Conclusion: A small but relevant percentage of women with breast cancer report having unmet needs. GPs may need to be particularly watchful of their need for more support from specific providers. Future research into the necessity of structural needs assessment among cancer patients in general practice is warranted

Risk factors of unmet needs among women with breast cancer in the post-treatment phase

Objective: Unmet health care needs require additional care resources to achieve optimal patient well-being. In this nationwide study we examined associations between a number of risk factors and unmet needs after treatment among women with breast cancer, while taking into account their health care practices. We expected that more care use would be associated with lower levels of unmet needs. Methods: A multicenter, prospective, observational design was employed. Women with primary breast cancer completed questionnaires 6 and 15 months post-diagnosis. Medical data were retrieved from medical records. Direct and indirect associations between sociodemographic and clinical risk factors, distress, care use, and unmet needs were investigated with structural equation modeling. Results: Seven hundred forty-six participants completed both questionnaires (response rate 73.7%). The care services received were not negatively associated with the reported levels of unmet needs after treatment. Comorbidity was associated with higher physical and daily living needs. Higher age was associated with higher health system-related and informational needs. Having had chemotherapy and a mastectomy were associated with higher sexuality needs and breast cancer-specific issues, respectively. A higher level of distress was associated with higher levels of unmet need in all domains. Conclusions: Clinicians may use these results to timely identify which women are at risk of developing specific unmet needs after treatment. Evidence-based, cost-effective (online) interventions that target distress, the most influential risk factor, should be further implemented and disseminated among patients and clinicians

Risk factors of unmet needs among women with breast cancer in the post-treatment phase

Objective: Unmet health care needs require additional care resources to achieve optimal patient well-being. In this nationwide study we examined associations between a number of risk factors and unmet needs after treatment among women with breast cancer, while taking into account their health care practices. We expected that more care use would be associated with lower levels of unmet needs. Methods: A multicenter, prospective, observational design was employed. Women with primary breast cancer completed questionnaires 6 and 15 months post-diagnosis. Medical data were retrieved from medical records. Direct and indirect associations between sociodemographic and clinical risk factors, distress, care use, and unmet needs were investigated with structural equation modeling. Results: Seven hundred forty-six participants completed both questionnaires (response rate 73.7%). The care services received were not negatively associated with the reported levels of unmet needs after treatment. Comorbidity was associated with higher physical and daily living needs. Higher age was associated with higher health system-related and informational needs. Having had chemotherapy and a mastectomy were associated with higher sexuality needs and breast cancer-specific issues, respectively. A higher level of distress was associated with higher levels of unmet need in all domains. Conclusions: Clinicians may use these results to timely identify which women are at risk of developing specific unmet needs after treatment. Evidence-based, cost-effective (online) interventions that target distress, the most influential risk factor, should be further implemented and disseminated among patients and clinicians.Health and self-regulationMultivariate analysis of psychological dat

Longitudinal Serum Protein Analysis of Women with a High Risk of Developing Breast Cancer Reveals Large Interpatient Versus Small Intrapatient Variations:First Results from the TESTBREAST Study

The prospective, multicenter TESTBREAST study was initiated with the aim of identifying a novel panel of blood-based protein biomarkers to enable early breast cancer detection for moderate-to-high-risk women. Serum samples were collected every (half) year up until diagnosis. Protein levels were longitudinally measured to determine intrapatient and interpatient variabilities. To this end, protein cluster patterns were evaluated to form a conceptual basis for further clinical analyses. Using a mass spectrometry-based bottom-up proteomics strategy, the protein abundance of 30 samples was analyzed: five sequential serum samples from six high-risk women; three who developed a breast malignancy (cases) and three who did not (controls). Serum samples were chromatographically fractionated and an in-depth serum proteome was acquired. Cluster analyses were applied to indicate differences between and within protein levels in serum samples of individuals. Statistical analyses were performed using ANOVA to select proteins with a high level of clustering. Cluster analyses on 30 serum samples revealed unique patterns of protein clustering for each patient, indicating a greater interpatient than intrapatient variability in protein levels of the longitudinally acquired samples. Moreover, the most distinctive proteins in the cluster analysis were identified. Strong clustering patterns within longitudinal intrapatient samples have demonstrated the importance of identifying small changes in protein levels for individuals over time. This underlines the significance of longitudinal serum measurements, that patients can serve as their own controls, and the relevance of the current study set-up for early detection. The TESTBREAST study will continue its pursuit toward establishing a protein panel for early breast cancer detection

Risk factors of unmet needs among women with breast cancer in the post-treatment phase

OBJECTIVE: Unmet health care needs require additional care resources to achieve optimal patient well-being. In this nationwide study we examined associations between a number of risk factors and unmet needs after treatment among women with breast cancer, while taking into account their health care practices. We expected that more care use would be associated with lower levels of unmet needs. METHODS: A multicenter, prospective, observational design was employed. Women with primary breast cancer completed questionnaires 6 and 15 months post-diagnosis. Medical data were retrieved from medical records. Direct and indirect associations between sociodemographic and clinical risk factors, distress, care use, and unmet needs were investigated with structural equation modeling. RESULTS: Seven hundred forty-six participants completed both questionnaires (response rate 73.7%). The care services received were not negatively associated with the reported levels of unmet needs after treatment. Comorbidity was associated with higher physical and daily living needs. Higher age was associated with higher health system-related and informational needs. Having had chemotherapy and a mastectomy were associated with higher sexuality needs and breast cancer-specific issues, respectively. A higher level of distress was associated with higher levels of unmet need in all domains. CONCLUSIONS: Clinicians may use these results to timely identify which women are at risk of developing specific unmet needs after treatment. Evidence-based, cost-effective (online) interventions that target distress, the most influential risk factor, should be further implemented and disseminated among patients and clinicians

A prediction model for underestimation of invasive breast cancer after a biopsy diagnosis of ductal carcinoma in situ: based on 2892 biopsies and 589 invasive cancers

Background: Patients with a biopsy diagnosis of ductal carcinoma in situ (DCIS) might be diagnosed with invasive breast cancer at excision, a phenomenon known as underestimation. Patients with DCIS are treated based on the risk of underestimation or progression to invasive cancer. The aim of our study was to expand the knowledge on underestimation and to develop a prediction model. Methods: Population-based data were retrieved from the Dutch Pathology Registry and the Netherlands Cancer Registry for DCIS between January 2011 and June 2012. Results: Of 2892 DCIS biopsies, 21% were underestimated invasive breast cancers. In multivariable analysis, risk factors were high-grade DCIS (odds ratio (OR) 1.43, 95% confidence interval (CI): 1.05–1.95), a palpable tumour (OR 2.22, 95% CI: 1.76–2.81), a BI-RADS (Breast Imaging Reporting and Data System) score 5 (OR 2.36, 95% CI: 1.80–3.09) and a suspected invasive component at biopsy (OR 3.84, 95% CI: 2.69–5.46). The predicted risk for underestimation ranged from 9.5 to 80.2%, with a median of 14.7%. Of the 596 invasive cancers, 39% had unfavourable features. Conclusions: The risk for an underestimated diagnosis of invasive breast cancer after a biopsy diagnosis of DCIS is considerable. With our prediction model, the individual risk of underestimation can be calculated based on routinely available preoperatively known risk factors (https://www.evidencio.com/models/show/1074)