Background: Previous preclinical and clinical research has investigated the role of intestinal microbiota in carcinogenesis. Growing evidence exists that intestinal microbiota can influence breast cancer carcinogenesis. However, the role of intestinal microbiota in breast cancer needs to be further investigated. This study aimed to identify the microbiota differences between postmenopausal breast cancer patients and controls. Patients and methods: This prospective cohort study compared the intestinal microbiota richness, diversity, and composition in postmenopausal histologically proven ER+/HER2- breast cancer patients and postmenopausal controls. Patients scheduled for (neo)adjuvant adriamycin, cyclophosphamide (AC), and docetaxel (D), or endocrine therapy (tamoxifen) were prospectively enrolled in a multicentre cohort study in the Netherlands. Patients collected a faecal sample and completed a questionnaire before starting systemic cancer treatment. Controls, enrolled from the National Dutch Breast Cancer Screening Programme, also collected a faecal sample and completed a questionnaire. Intestinal microbiota was analysed by amplicon sequencing of the 16S rRNA V4 gene region. Results: In total, 81 postmenopausal ER+/HER2- breast cancer patients and 67 postmenopausal controls were included, resulting in 148 faecal samples. Observed species richness, Shannon index, and overall microbial community structure were not significantly different between breast cancer patients and controls. There was a significant difference in overall microbial community structure between breast cancer patients scheduled for adjuvant treatment, neoadjuvant treatment, and controls at the phylum (p = 0.042) and genus levels (p = 0.015). Dialister (p = 0.001) and its corresponding family Veillonellaceae (p = 0.001) were higher in patients scheduled for adjuvant treatment, compared to patients scheduled for neoadjuvant treatment. Additional sensitivity analysis to correct for the potential confounding effect of prophylactic antibiotic use, indicated no differences in microbial community structure between patients scheduled for neoadjuvant systemic treatment, adjuvant systemic treatment, and controls at the phylum (p = 0.471) and genus levels (p = 0.124). Conclusions: Intestinal microbiota richness, diversity, and composition are not different between postmenopausal breast cancer patients and controls. The increased relative abundance of Dialister and Veillonellaceae was observed in breast cancer patients scheduled for adjuvant treatment, which might be caused by a relative decrease in other bacteria due to prophylactic antibiotic administration rather than an absolute increase.

This retrospective study investigated the value of pretreatment contrast-enhanced Magnetic Resonance Imaging (MRI)-based radiomics for the prediction of pathologic complete tumor response to neoadjuvant systemic therapy in breast cancer patients. A total of 292 breast cancer patients, with 320 tumors, who were treated with neo-adjuvant systemic therapy and underwent a pretreatment MRI exam were enrolled. As the data were collected in two different hospitals with five different MRI scanners and varying acquisition protocols, three different strategies to split training and validation datasets were used. Radiomics, clinical, and combined models were developed using random forest classifiers in each strategy. The analysis of radiomics features had no added value in predicting pathologic complete tumor response to neoadjuvant systemic therapy in breast cancer patients compared with the clinical models, nor did the combined models perform significantly better than the clinical models. Further, the radiomics features selected for the models and their performance differed with and within the different strategies. Due to previous and current work, we tentatively attribute the lack of improvement in clinical models following the addition of radiomics to the effects of variations in acquisition and reconstruction parameters. The lack of reproducibility data (i.e., test-retest or similar) meant that this effect could not be analyzed. These results indicate the need for reproducibility studies to preselect reproducible features in order to properly assess the potential of radiomics.

Purpose: We aimed to evaluate quality of life (QoL) using the European Quality of Life Five-Dimensions questionnaire (EQ-5D-3L) in a real-world cohort of Dutch advanced breast cancer (ABC) patients. Secondary, we reported differences in QoL between subgroups of patients based on age, comorbidity, tumor-, and treatment characteristics, and assessed the association of duration of metastatic disease and time to death with QoL. Methods: ABC patients who attended the outpatient clinic between October 2010 and May 2011 were asked to fill out the EQ-5D-3L questionnaire. Patient-, disease-, and treatment characteristics were obtained from the medical files. Health-utility scores were calculated. Subgroups were described and compared for utility scores by parametric and non-parametric methods. Results: A total of 92 patients were included with a median utility score of 0.691 (Interquartile range [IQR] 0.244). Patients ≥ 65 years had significantly worse median utility scores than younger patients; 0.638 versus 0.743, respectively (p = 0.017). Moreover, scores were significantly worse for patients with versus those without comorbidity (medians 0.620 versus 0.725, p = 0.005). Utility scores did not significantly differ between subgroups of tumor type, type of systemic treatment, number of previous palliative treatment(s), or number or location of metastatic site(s). The remaining survival was correlated with utility scores (correlation coefficient (r) = 0.260, p = 0.0252), especially in the subgroup < 65 years (r = 0.340, p = 0.0169), whereas there was no significant correlation with time since metastatic diagnosis (r = − 0.106, p = 0.3136). Conclusion: Within this real-world cross-sectional study, QoL was significantly associated with age, comorbidity, and remaining survival duration. The observation of a lower QoL in ABC patients, possibly indicating the last period of life, may assist clinical decision-making on timing of cessation of systemic antitumor therapy.

Purpose: As the prognosis for adolescents and young adults (AYAs) with breast cancer has improved, long-term health-related quality of life (HRQoL) has become increasingly important. This study aimed to analyze the long-term HRQoL of AYA breast cancer survivors compared to an age-matched normative population and to identify factors associated with HRQoL. Methods: Secondary analyses were conducted using data from the SURVAYA study. The European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core-30 (EORTC QLQ-C30) was used to assess HRQoL. The Mann–Whitney U test was used to compare HRQoL scores of AYA breast cancer survivors with those of the normative population (n = 409). Linear regression models were constructed to identify patient and treatment characteristics associated with HRQoL. Results: A total of 944 female AYA breast cancer survivors were included, with a median age of 36.0 years and a median follow-up of 12.2 years. AYA breast cancer survivors scored significantly lower on five functional scales: physical, role, emotional, cognitive, and social, and higher on five symptom scales: fatigue, pain, dyspnea, insomnia, and financial impact compared to the normative population. Being in a relationship, having a positive body image, and adaptive coping were positively associated with HRQoL, while older age, chemotherapy, unemployment, and maladaptive coping were negatively associated. Conclusion: AYA breast cancer survivors experience significantly compromised long-term HRQoL compared to an age-matched normative population. These results highlight the need for tailored follow-up care and long-term support, as well as the importance of shared decision-making about the benefits and risks of treatments before initiation.

New treatment options in cancer have resulted in increased use of health care resources near the end of life. We assessed health care use near the end of life of patients with advanced breast cancer (ABC). From the Southeast Netherlands Breast cancer (SONABRE) registry, we selected all deceased patients diagnosed with ABC in Maastricht University Medical Center between January 2007 and October 2017. Frequency of health care use in the last six months of life was described and predictors for health care use were assessed. Of 203 patients, 76% were admitted during the last six months, 6% to the intensive care unit (ICU) and 2% underwent cardiopulmonary resuscitation (CPR). Death in hospital occurred in 25%. Nine percent of patients received a new line of chemotherapy ≤30 days before death, which was associated with age <65 years and <1 year survival since diagnosis of metastases. In these patients, the hospital admission rate was 95%, of which 79% died in the hospital, mostly due to progressive disease (80%). In conclusion, the frequency of ICU-admission, CPR or a new line of chemotherapy ≤30 days before death was low. Most patients receiving a new line of chemotherapy ≤30 days before death, died in the hospital.

Background: Eribulin provided significant overall survival (OS) benefit in heavily pretreated advanced breast cancer patients in the EMBRACE trial. We investigated the use of eribulin in daily clinical practice, the relative effectiveness of eribulin versus non-eribulin chemotherapy, and the safety of eribulin in real-world patients included in the SOutheast Netherlands Advanced BREast cancer (SONABRE) registry. Material and methods: Patients treated with eribulin and eligible patients for eribulin who received a different chemotherapy (i.e., non-eribulin group) in ten hospitals in 2013–2017 were included. A multivariate matching algorithm was applied to correct for differences in baseline characteristics between the groups, including the number of previous treatment lines. Progression-free survival (PFS) and OS of eribulin were compared with the matched non-eribulin group through Kaplan-Meier curves and multivariate Cox proportional hazard models. The occurrence of dose delay and reduction was described. Results: Forty-five patients received eribulin according to its registration criteria and 74 patients were eligible for eribulin but received non-eribulin chemotherapy. Matching increased the similarity in baseline characteristics between the eribulin and non-eribulin groups. Median PFS was 3.5 months (95% confidence interval (CI): 2.7–5.5) in the eribulin group and 3.2 months (95% CI: 2.0–4.8) in the matched non-eribulin group (adjusted hazard ratio (HR): 0.83, 95% CI: 0.49–1.38). Median OS was 5.9 months (95% CI: 4.6–11.0) and 5.2 months (95% CI: 4.6–9.5) in the eribulin and non-eribulin groups, respectively (adjusted HR: 0.66, 95% CI: 0.38–1.13). Dose delay or reduction occurred in 14 patients (31%) receiving eribulin. Conclusions: No difference in PFS and OS was observed between eribulin and non-eribulin treated patients. Eribulin had a manageable toxicity profile.