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Background: To support patients in shared decision‐making about treatment options, patient decision aids (PtDAs) usually provide benefit/harm information and value clarification methods (VCMs). Recently, personalized risk information from prediction models is also being integrated into PtDAs. This study aimed to design decision‐relevant information (i.e., personalized survival rates, harm information and VCMs) about adjuvant breast cancer treatment in cocreation with patients, in a way that suits their needs and is easily understandable. Methods: Three cocreation sessions with breast cancer patients (N = 7–10; of whom N = 5 low health literate) were performed. Participants completed creative assignments and evaluated prototypes of benefit/harm information and VCMs. Prototypes were further explored through user testing with patients (N = 10) and healthcare providers (N = 10). The researchers interpreted the collected data, for example, creative and homework assignments, and participants' presentations, to identify key themes. User tests were transcribed and analysed using ATLAS.ti to assess the understanding of the prototypes. Results: Important information needs were: (a) need for overview/structure of information directly after diagnosis and; (b) need for transparent benefit/harm information for all treatment options, including detailed harm information. Regarding VCMs, patients stressed the importance of a summary/conclusion. A bar graph seemed the most appropriate way of displaying personalized survival rates; the impact of most other formats was perceived as too distressful. The concept of 'personalization' was not understood by multiple patients. Conclusions: A PtDA about adjuvant breast cancer treatment should provide patients with an overview of the steps and treatment options, with layers for detailed information. Transparent information about the likelihood of benefits and harm should be provided. Given the current lack of information on the likelihood of side effects/late effects, efforts should be made to collect and share these data with patients. Further quantitative studies are needed to validate the results and to investigate how the concept of 'personalization' can be communicated. Patient or Public Contribution: Ten breast cancer patients participated in three cocreation sessions to develop decision‐relevant information. Subsequent user testing included 10 patients. The Dutch Breast Cancer Association (BVN) was involved as an advisor in the general study design. [ABSTRACT FROM AUTHOR]

Objective: In breast cancer patients, treatment at the end of life accounts for a major share of medical spending. However, little is known about the variability of cost trajectories between patients. This study aims to identify underlying latent groups of advanced breast cancer patients with similar cost trajectories over the last year before death. Methods: Data from deceased advanced breast cancer patients, diagnosed between 2010 and 2017, were retrieved from the Southeast Netherlands Advanced Breast Cancer (SONABRE) Registry. Costs of hospital care over the last twelve months before death were analyzed, and the variability of longitudinal patterns between patients were explored using group-based trajectory modeling. Descriptive statistics and multinomial logistic regression were applied to investigate differences between the identified latent groups. Results: We included 558 patients. Over the last twelve months before death, mean hospital costs were €2,255 (SD = €492) per month. Costs increased over the last five months and reached a maximum of €3,614 in the last month of life, driven by hospital admissions, while spending for medication declined over the last three months of life. Based on patients' individual cost trajectories, we identified six latent groups with distinct longitudinal patterns, of which only two showed a marked increase in costs over the last twelve months before death. Latent groups were constituted of heterogeneous patients, and clinical characteristics explained membership only to a limited extent. Conclusions: The average costs of advanced breast cancer patients increased towards the end of life. However, we uncovered several latent groups of patients with divergent cost trajectories, which did not reflect the overall increasing trend. The mechanisms underlying the variability in cost trajectories warrants further research. [ABSTRACT FROM AUTHOR]

Background: The aim was to study the impact of comorbidities and age on breast cancer mortality, taking into account competing causes of death. Subjects, Materials, and Methods: Cohort analysis of Dutch and Belgian patients with postmenopausal, early hormone receptor‐positive breast cancer included in the Tamoxifen and Exemestane Adjuvant Multinational (TEAM) trial between 2001 and 2006. This is a randomized controlled trial of patients who had completed local treatment with curative intent and were randomized to receive exemestane for 5 years, or sequential treatment of tamoxifen followed by exemestane for a duration of 5 years. Patients were categorized by number of comorbidities (no comorbidities, 1–2 comorbidities, and >2 comorbidities) and age (<70 years and ≥70 years). Main outcome was breast cancer mortality considering other‐cause mortality as competing event; cumulative incidences were calculated using the Cumulative Incidence Competing Risk Methods, and the Fine and Gray model was used to calculate the effect of age and comorbidities for the cause‐specific incidences of breast cancer death, taking into account the effect of competing causes of death. Results: Overall, 3,159 patients were included, of which 2,203 (69.7%) were aged <70 years and 956 (30.3%) were aged ≥70 years at diagnosis. Cumulative incidence of breast cancer mortality was higher among patients ≥70 without comorbidities (22.2%, 95% CI, 17.5–26.9) compared with patients <70 without comorbidities (15.6%, 95% CI, 13.6–17.7, reference group), multivariable subdistribution hazard ratio (sHR) 1.49 (95% CI, 1.12–1.97, p =.005) after a median follow‐up of 10 years. Use of chemotherapy was lower in older patients (1%, irrespective of the number of comorbidities) compared with younger patients (50%, 44%, and 38% for patients with no, 1–2, or >2 comorbidities, p <.001). Conclusion: Older patients without comorbidities have a higher risk of dying due to breast cancer than younger counterparts, even when taking into account higher competing mortality, while use of chemotherapy in this group was low. These findings underline the need to take into account comorbidities, age, and competing mortality in the prognosis of breast cancer for accurate decision making. Implications for Practice: Older patients without comorbidity are at increased risk of dying from breast cancer, despite a higher other‐cause mortality. This study shows that including age and comorbidity for the assessment of breast cancer mortality and other‐cause mortality is indispensable for treatment decision making in older patients. Future prognostic tools for breast cancer prognosis should incorporate these items as well as risk of toxicity of adjuvant chemotherapy to adequately predict outcomes to optimize personalized treatment for older patients with early breast cancer. This analysis of TEAM trial data focuses on the effects of comorbidities and age on breast cancer mortality and other cause mortality after 10 years of follow‐up, taking into account competing causes of death. [ABSTRACT FROM AUTHOR]

Patients with breast cancer have a (very) good long-term prognosis, albeit exhibiting a small but significant excess mortality at least up to 15 years after diagnosis. Potential explanations for excess mortality include late recurrences, second tumours and late side effects of treatment. Caregivers can use this information to better inform cancer survivors about their actual prognosis.Background Coinciding with the relatively good and improving prognosis for patients with stage I–III breast cancer, late recurrences, new primary tumours and late side-effects of treatment may occur. We gained insight into prognosis for long-term breast cancer survivors. Patients and methods Data on all 205 827 females aged 15–89 diagnosed with stage I–III breast cancer during 1989–2008 were derived from the Netherlands Cancer Registry. Conditional 5-year relative survival was calculated for every subsequent year from diagnosis up to 15 years. Results For stage I, conditional 5-year relative survival remained ∼95% up to 15 years after diagnosis (a stable 5-year excess mortality rate of 5%). For stage II, excess mortality remained 10% for those aged 15–44 or 45–59 and 15% for those aged 60–74. For stage III, excess mortality decreased from 35% at diagnosis to 10% at 15 years for those aged 15–44 or 45–59, and from ∼40% to 30% for those aged ≥60. Conclusions Patients with stage I or II breast cancer had a (very) good long-term prognosis, albeit exhibiting a small but significant excess mortality at least up to 15 years after diagnosis. Improvements albeit from a lower level were mainly seen for patients who had been diagnosed with stage III disease. Caregivers can use this information to better inform (especially disease-free) cancer survivors about their actual prognosis. [ABSTRACT FROM AUTHOR]