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Objective: Early detection through mammographic screening and various treatment modalities of cancer may have changed life expectancy and cause-specific mortality of breast cancer patients. We aimed to determine the long-term cause of death patterns in screening-detected patients and clinically diagnosed patients in the Netherlands compared with the general population. Methods: Using data from the Netherlands Cancer Registry and Statistics Netherlands of around 26,000 women, aged 50–75 at diagnosis and surgically treated for invasive breast cancer in 2004–2008, we compared patients with screening-detected and clinically diagnosed cancer for major causes of death until 2020. The expected number of all-cause and cause-specific deaths was calculated using rates of the general population. Results: During the follow-up period, 4310 women died. The age-standardised all-cause mortality ratio for the screening-detected cancer group was 1.41 (95% confidence interval (95% CI), 1.37–1.46). A higher mortality ratio was observed for patients with clinically detected cancer: 2.27 (95% CI, 2.19–2.34). The observed versus expected breast cancer mortality ratio in the screening-detected patient group was 8.92 (95% CI, 8.45–9.40) and 20.23 (19.38–21.09) in the clinical group. Excess mortality was found for lung cancer in both patient groups, and small elevations for circulatory and respiratory disease in the clinically detected group. Conclusion: Our results indicate that for the screening group no other causes of death but breast and lung cancer were prominent compared with the general population. The clinical group showed excess mortality for some other causes of death as well, suggesting a less healthy group compared with the general population. [ABSTRACT FROM AUTHOR]

In older patients with breast cancer, the risk of dying from other causes than breast cancer strongly increases after the age of 70. The aim of this study was to assess contributions of breast cancer mortality versus other-cause mortality after locoregional or distant recurrence in a population-based cohort of older patients analysed by multi-state models. Surgically treated patients ≥70 years diagnosed with stage I-III breast cancer in 2003–2009 were selected from the Netherlands Cancer Registry. A novel multi-state model with locoregional and distant recurrence that incorporates relative survival was fitted. Other-cause and breast cancer mortality were indicated as population and excess mortality. Overall, 18,419 patients were included. Ten-year cumulative incidences of locoregional and distant recurrence were 2.8% (95%CI 2.6–3.1%) and 12.5% (95%CI 11.9–13.1%). Other-cause mortality increased from 23.9% (95%CI 23.7–24.2%) in patients 70–74 years to 73.8% (95%CI 72.2–75.4%) in those ≥80 years. Ten-year probabilities of locoregional or distant recurrence with subsequent breast cancer death were 0.4–1.3% and 10.2–14.6%, respectively. For patients with a distant recurrence in the first two years after diagnosis, breast cancer death probabilities were 95.3% (95%CI 94.2–96.4%), 93.1% (95%CI 91.6–94.6%), and 88.6% (95%CI 86.5–90.8%) in patients 70–74, 75–79, and ≥80 years. In older patients without recurrence, prognosis is driven by other-cause mortality. Although locoregional recurrence is a predictor for worse outcome, given its low incidence it contributes little to breast cancer mortality after diagnosis. For patients who develop a distant recurrence, breast cancer remains the dominant cause of death, even at old age. • Older patients with breast cancer often die from competing causes. • Competing mortality after recurrence has not been extensively studied so far. • Novel multi-state models were used including time after recurrence. • These models can be applied to different datasets as input for clinical decision tools. [ABSTRACT FROM AUTHOR]

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]

Previous studies have shown that survival outcomes for older patients with breast cancer vary substantially across Europe, with worse survival reported in the United Kingdom. It has been hypothesised that these differences in survival outcomes could be related to treatment variation. We aimed to compare patient and tumour characteristics, treatment selection and survival outcomes between two large prospective cohorts of older patients with operable breast cancer from the United Kingdom (UK) and The Netherlands. Women diagnosed with operable breast cancer aged ≥70 years were included. A baseline comprehensive geriatric assessment was performed in both cohorts, with data collected on age, comorbidities, cognition, nutritional and functional status. Baseline tumour characteristics and treatment type were collected. Univariable and multivariable Cox regression models were used to compare overall survival between the cohorts. 3262 patients from the UK Age Gap cohort and 618 patients from the Dutch Climb cohort were included, with median ages of 77.0 (IQR: 72.0–81.0) and 75.0 (IQR: 72.0–81.0) years, respectively. The cohorts were generally comparable, with slight differences in rates of comorbidity and frailty. Median follow-up for overall survival was 4.1 years (IQR 2.9–5.4) in Age Gap and 4.3 years (IQR 2.9–5.5) in Climb. In Age Gap, both the rates of primary endocrine therapy and adjuvant hormonal therapy after surgery were approximately twice those in Climb (16.6% versus 7.3%, p < 0.001 for primary endocrine therapy, and 62.2% versus 38.8%, p < 0.001 for adjuvant hormonal therapy). There was no evidence of a difference in overall survival between the cohorts (adjusted HR 0.94, 95% CI 0.74–1.17, p = 0.568). In contrast to previous studies, this comparison of two large national prospective longitudinal multi-centre cohort studies demonstrated comparable survival outcomes between older patients with breast cancer treated in the UK and The Netherlands, despite differences in treatment allocation. • No survival difference between UK and Netherlands for older breast cancer patients. • Similar patient and tumour characteristics seen in both cohorts. • Higher rates of mastectomy for older breast cancer patients in Netherlands. • Higher rates of adjuvant therapies for older breast cancer patients in UK. [ABSTRACT FROM AUTHOR]

The validity of the PREDICT breast cancer prognostic model is unclear for young patients without adjuvant systemic treatment. This study aimed to validate PREDICT and assess its clinical utility in young women with node-negative breast cancer who did not receive systemic treatment. We selected all women from the Netherlands Cancer Registry who were diagnosed with node-negative breast cancer under age 40 between 1989 and 2000, a period when adjuvant systemic treatment was not standard practice for women with node-negative disease. We evaluated the calibration and discrimination of PREDICT using the observed/expected (O/E) mortality ratio, and the area under the receiver operating characteristic curve (AUC), respectively. Additionally, we compared the potential clinical utility of PREDICT for selectively administering chemotherapy to the chemotherapy-to-all strategy using decision curve analysis at predefined thresholds. A total of 2264 women with a median age at diagnosis of 36 years were included. Of them, 71.2% had estrogen receptor (ER)-positive tumors and 44.0% had grade 3 tumors. Median tumor size was 16 mm. PREDICT v2.2 underestimated 10-year all-cause mortality by 33% in all women (O/E ratio:1.33, 95%CI:1.22–1.43). Model discrimination was moderate overall (AUC 10-year :0.65, 95%CI:0.62–0.68), and poor for women with ER-negative tumors (AUC 10-year :0.56, 95%CI:0.51–0.62). Compared to the chemotherapy-to-all strategy, PREDICT only showed a slightly higher net benefit in women with ER-positive tumors, but not in women with ER-negative tumors. PREDICT yields unreliable predictions for young women with node-negative breast cancer. Further model updates are needed before PREDICT can be routinely used in this patient subset. • We validated PREDICT in young, systemic therapy-naïve women with N0 breast cancers. • PREDICT significantly underestimated mortality in these women. • Model discrimination was moderate for women with ER-positive tumors. • Model discrimination was poor for women with ER-negative tumors. • The clinical utility of PREDICT in young women with N0 breast cancers was limited. [ABSTRACT FROM AUTHOR]

Objective: To assess the decision‐making process in fit and frail older breast cancer patients. Methods: Breast cancer patients aged ≥70 years who completed the G8 frailty screening tool (G8) were included in this retrospective study. Socio‐demographic and clinical characteristics were collected, as well as information from geriatric assessment (GA). Treatment decisions were compared with national guidelines. Results: Of 177 patients, 85 patients were considered fit by the G8 (G8‐fit) and 92 patients frail (G8‐frail). All G8‐fit and 53 G8‐frail were proposed for surgery. GA was performed in 34 patients (9 G8‐fit; 25 G8‐frail) of whom 16 (2 G8‐fit;14 G8‐frail) were considered frail (GA‐frail). 28 out of these 34 patients were considered fit for surgery (including 11 GA‐frail); their impairments were unlikely to interfere with surgery or life expectancy. Reasons for adjusting treatment were physical/cognitive condition and patient preference. Ultimately, 123 patients underwent surgery in accordance with guidelines (81 G8‐fit;42 G8‐frail, p < 0.001). Survival was reduced in G8‐frail compared to G8‐fit (p = 0.001), but G8 lost its association with mortality in multivariable survival analysis. Among patients undergoing surgery, no difference in mortality was seen between G8‐fit and G8‐frail (p = 0.996). Conclusion: The G8 is associated with treatment decisions and did not affect survival in patients undergoing surgery. In the decision‐making process, the G8 may help and estimates the need for adaptive care. [ABSTRACT FROM AUTHOR]

The low incidence of special types of breast cancer hinders adequate clinical research efforts. As such, collecting sufficient data to develop well‐established therapy strategies are difficult. The aim of our study was to obtain more data on these special types in order to better understand the different characteristics and optimize therapy strategies. A single‐institution retrospective cohort study from January 2007 until September 2015. One hundred and five patients remained after excluding the patients with invasive ductal and lobular carcinoma. The percentage of these so called special types in this population was 4%. Tubular carcinoma, cribriform carcinoma, carcinoma with medullary features, carcinoma with apocrine differentiation, secretory carcinoma, mucinous carcinoma, and invasive papillary carcinoma had a good or excellent prognosis, while invasive micropapillary carcinoma, adenoid cystic carcinoma, metaplastic carcinoma, and carcinoma with neuroendocrine features had a worse prognosis. Special types of breast cancer form a heterogeneous group. Submitting them all to the same treatment modality may lead to both over‐ and under‐treatment. We need to combine our data to optimize treatment strategies for the different special types. [ABSTRACT FROM AUTHOR]

Background: In 2013, eribulin was reimbursed under a coverage with evidence development (CED) as third or later chemotherapy line for advanced breast cancer (ABC) patients in the Netherlands because of uncertain cost effectiveness. In 2016, the final decision of reimbursing eribulin was taken without considering the evidence collected during CED research. We analysed the cost effectiveness of eribulin versus non-eribulin chemotherapy, using real-world data. Methods: A three health states (progression-free, progressed disease, dead) partitioned survival model was developed. The SOuth East Netherlands Advanced BREast Cancer (SONABRE) registry informed the effectiveness and costs inputs. Health state utility values were obtained from the literature. Incremental cost-effectiveness ratio (ICER) between the eribulin and matched non-eribulin chemotherapy was estimated. Deterministic and probabilistic sensitivity analyses and scenario analyses were performed. The financial risk (i.e., the expected value of perfect information (EVPI) plus the expected monetary loss (eML) associated with reimbursing eribulin) and budget impact associated with reimbursing eribulin were calculated. Results: Eribulin led to higher health benefits (0.07 quality-adjusted life year (QALY)) and costs (€15,321) compared with non-eribulin chemotherapy. This resulted in an ICER of €220,608. At a €80,000 per QALY threshold, the risk of reimbursing eribulin was €9,791 per patient (EVPI €13, eML €9,778). Scaled up to the Dutch population, the estimated annual budget impact was €1.9 million and the annual risk of reimbursing eribulin was €2.7 million. Conclusion: From a Dutch societal perspective, eribulin is not cost effective when considering its list price as third and later chemotherapy line for ABC patients. [ABSTRACT FROM AUTHOR]

Recommendations on adjuvant chemotherapy in pT1N0M0 triple-negative breast cancer (TNBC) differ among international guidelines owing to lack of randomized trial data. We evaluated associations of adjuvant chemotherapy with a long-term outcome in a population-based cohort of pT1N0M0 TNBC. All patients diagnosed with pT1N0M0 TNBC in the Netherlands between 2005 and 2016 were identified from the Netherlands Cancer Registry. Patient, tumour and treatment characteristics were recorded. The date and cause of death were obtained from Statistics Netherlands. We used multivariable Cox regression models to evaluate associations of adjuvant chemotherapy with breast cancer–specific survival (BCSS) and overall survival (OS), adjusted for baseline characteristics and performed sensitivity analyses using propensity score (PS) weighting. We identified 4366 patients: 284 with pT1a, 923 with pT1b and 3159 with pT1c tumours. Adjuvant chemotherapy was administered in 53% of patients. Patients receiving chemotherapy had more unfavourable baseline characteristics including younger age, larger tumours and higher tumour grade. At 8.2 years median follow-up (interquartile range = 5.8–10.9), 671 patients had died, of whom 311 because of breast cancer. After adjustment for baseline characteristics, chemotherapy was associated with improved BCSS (adjusted hazard ratio [aHR] = 0.65; 95% confidence interval [CI] = 0.48–0.89). The effect of chemotherapy differed by tumour size (pT1a: aHR = 4.28, 95% CI = 1.12–16.44; pT1b: aHR = 1.12, 95% CI = 0.51–2.49; pT1c: aHR = 0.60, 95% CI = 0.43–0.82; p interaction = 0.02). Findings for OS were in line with BCSS results. PS-weighting analysis confirmed the results of the primary analysis. Adjuvant chemotherapy is associated with better BCSS and OS in pT1N0M0 TNBC. Better outcome is most evident in pT1c tumours and may not outweigh harm in pT1a/pT1b tumours. • Recommendations on adjuvant chemotherapy in pT1N0M0 TNBC differ among guidelines. • Adjuvant chemotherapy is associated with better breast cancer–specific survival and overall survival in pT1N0M0 TNBC. • The association of chemotherapy with a better outcome was most pronounced in pT1c tumours (hazard ratio 0.60, 0.43–0.82). [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: 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. [ABSTRACT FROM AUTHOR]

Background The incidence of ductal carcinoma in situ (DCIS) has drastically increased over the past decades. Because DCIS is resected after diagnosis similar to invasive breast cancer, the natural cause and behaviour of DCIS is not well known. We aimed to determine breast cancer–specific survival (BCSS) and overall survival (OS) according to grade in DCIS patients after surgical treatment in the Netherlands. Patients and methods All DCIS patients diagnosed between 1999 and 2012 were selected from the Netherlands Cancer Registry. The cause of death was obtained from ‘Statistics Netherlands’. BCSS and OS were estimated using multivariable Cox regression in the entire cohort and stratified for grades. Results In total, 12,256 patients were included, of whom 1509 (12.3%) presented with grade I, 3675 (30.0%) with grade II, 6064 (49.5%) with grade III and 1008 (8.2%) with an unknown grade. During a median follow-up of 7.8 years, 1138 (9.3%) deaths were observed, and 179 (1.5%) were breast cancer–related. Of these, 10 patients had grade I; 46 grade II; 95 grade III and 28 an unknown grade. After adjustment for confounding, grade II and III were related to worse BCSS than grade I with hazard ratios of 1.92 (95% confidence interval [CI]: 0.97–3.81) and 2.14 (95% CI: 1.11–4.12), respectively. No association between grades and OS was observed. Conclusion BCSS and OS in DCIS patients were excellent. Because superior rates were observed for low-grade DCIS, it seems justified to investigate whether active surveillance may be a balanced alternative for conventional surgical treatment. [ABSTRACT FROM AUTHOR]

Background Resection of breast cancer liver metastases (BCLM) combined with systemic treatment is increasingly accepted but not offered as therapeutic option. New evidence of the additional value of surgery in these patients is scarce while prognoses without surgery remains poor. Patients and methods For this case matched analysis, all nationally registered patients with BCLM confined to the liver in the Netherlands (systemic group; N = 523) were selected and compared with patients who received systemic treatment and underwent hepatectomy (resection group; N = 139) at a hepatobiliary centre in France. Matching was based on age, decade when diagnosed, interval to metastases, maximum metastases size, single or multiple tumours, chemotherapy, hormonal or targeted therapy after diagnosis. Based on published guidelines, palliative systemic treatment strategies are similar in both European countries. Results Between 1983 and 2013, 3894 patients were screened for inclusion. Overall median follow-up was 80 months (95% CI 70–90 months). The median, 3- and 5-year overall survival of the whole population was 19 months, 29% and 19%, respectively. The resection and systemic group had median survival of 73 vs. 13 months (P < 0.001), respectively. Three and 5-year survival was 18% and 10% for the systemic group and 75% and 54% for the resection group, respectively. After matching, the resection group had a median overall survival of 82 months with a 3- and 5-year overall survival of 81% and 69%, respectively, compared with a median overall survival of 31 months in the systemic group with a 3- and 5-year overall survival of 32% and 24%, respectively (HR 0.28, 95% CI 0.15–0.52; P < 0.001). Conclusions For patients with BCLM, liver resection combined with systemic treatment results in improved overall survival compared to systemic treatment alone. Liver resection should be considered in selected cases. [ABSTRACT FROM AUTHOR]

Background: Whole brain radiotherapy (WBRT) is considered standard of care for patients with multiple brain metastases or unfit for radical treatment modalities. Recent studies raised discussion about the expected survival after WBRT. Therefore, we analysed survival after WBRT for brain metastases 'in daily practice' in a large nationwide multicentre retrospective cohort. Methods: Between 2000 and 2014, 6325 patients had WBRT (20 Gy in 4Gy fractions) for brain metastases from non-small cell lung cancer (NSCLC; 4363 patients) or breast cancer (BC; 1962 patients); patients were treated in 15 out of 21 Dutch radiotherapy centres. Survival was calculated by the Kaplan-Meier method from the first day of WBRT until death as recorded in local hospital data registration or the Dutch Municipal Personal Records Database. Findings: The median survival was 2.7 months for NSCLC and 3.7 months for BC patients (p<.001). For NSCLC patients aged <50, 50-60, 60-70 and >70 years, survival was 4.0, 3.0, 2.8 and 2.1 months, respectively (p<.001). For BC patients, survival was 4.5, 3.8, 3.2 and 2.9 months, respectively (p=.047). In multivariable analyses, higher age was related to poorer survival with hazard ratios (HR) for patients aged 50-60, 60-70 and >70 years being 1.05, 1.19 and 1.34, respectively. Primary BC (HR: 0.83) and female sex (HR: 0.85) were related to better survival (p<.001). Interpretation: The survival of patients after WBRT for brain metastases from NSCLC treated in Dutch 'common radiotherapy practice' is poor, in breast cancer and younger patients it is disappointingly little better. These results are in line with the results presented in the QUARTZ trial and we advocate a much more restrictive use of WBRT. In patients with a more favourable prognosis the optimal treatment strategy remains to be determined. Prospective randomized trials and individualized prognostic models are needed to identify these patients and to tailor treatment. [ABSTRACT FROM AUTHOR]

Background PREDICT version 2.0 is increasingly used to estimate prognosis in breast cancer. This study aimed to validate this tool in specific prognostic subgroups in the Netherlands. Methods All operated women with non-metastatic primary invasive breast cancer, diagnosed in 2005, were selected from the nationwide Netherlands Cancer Registry (NCR). Predicted and observed 5- and 10-year overall survival (OS) were compared for the overall cohort, separated by oestrogen receptor (ER) status, and predefined subgroups. A >5% difference was considered as clinically relevant. Discriminatory accuracy and goodness-of-fit were determined using the area under the receiver operating characteristic curve (AUC) and the Chi-squared-test. Results We included 8834 patients. Discriminatory accuracy for 5-year OS was good (AUC 0.80). For ER-positive and ER-negative patients, AUCs were 0.79 and 0.75, respectively. Predicted 5-year OS differed from observed by −1.4% in the entire cohort, −0.7% in ER-positive and −4.9% in ER-negative patients. Five-year OS was accurately predicted in all subgroups. Discriminatory accuracy for 10-year OS was good (AUC 0.78). For ER-positive and ER-negative patients AUCs were 0.78 and 0.76, respectively. Predicted 10-year OS differed from observed by −1.0% in the entire cohort, −0.1% in ER-positive and −5.3 in ER-negative patients. Ten-year OS was overestimated (6.3%) in patients ≥75 years and underestimated (−13.%) in T3 tumours and patients treated with both endocrine therapy and chemotherapy (−6.6%). Conclusions PREDICT predicts OS reliably in most Dutch breast cancer patients, although results for both 5-year and 10-year OS should be interpreted carefully in ER-negative patients. Furthermore, 10-year OS should be interpreted cautiously in patients ≥75 years, T3 tumours and in patients considering endocrine therapy and chemotherapy. [ABSTRACT FROM AUTHOR]

Background Reproductive and lifestyle factors influence both breast cancer risk and prognosis; this might be through breast cancer subtype. Subtypes defined by immunohistochemical hormone receptor markers and gene expression signatures are used to predict prognosis of breast cancer patients based on their tumour biology. We investigated the association between established breast cancer risk factors and the 70-gene prognostication signature in breast cancer patients. Patients and methods Standardised questionnaires were used to obtain information on established risk factors of breast cancer from the Dutch patients of the MINDACT trial. Clinical-pathological and genomic information were obtained from the trial database. Logistic regression analyses were used to estimate the associations between lifestyle risk factors and tumour prognostic subtypes, measured by the 70-gene MammaPrint ® signature (i.e. low-risk or high-risk tumours). Results Of the 1555 breast cancer patients included, 910 had low-risk and 645 had high-risk tumours. Current body mass index (BMI), age at menarche, age at first birth, age at menopause, hormonal contraceptive use and hormone replacement therapy use were not associated with MammaPrint ® . In parous women, higher parity was associated with a lower risk (OR: 0.75, [95% confidence interval {CI}: 0.59–0.95] P = 0.018) and longer breastfeeding duration with a higher risk (OR: 1.03, [95% CI: 1.01–1.05] P = 0.005) of developing high-risk tumours; risk estimates were similar within oestrogen receptor–positive disease. After stratifying by menopausal status, the associations remained present in post-menopausal women. Conclusion Using prognostic gene expression profiles, we have indications that specific reproductive factors may be associated with prognostic tumour subtypes beyond hormone receptor status. [ABSTRACT FROM AUTHOR]

Purpose. Risk prediction models (RPM) in breast cancer quantify survival benefit from adjuvant systemic treatment. These models [e.g. Adjuvant! Online (AO)] are increasingly used during consultations, despite their not being designed for such use. As still little is known about oncologists' views on and use of RPM to communicate prognosis to patients, we investigated if, why, and how they use RPM. Methods. We disseminated an online questionnaire that was based on the literature and individual and group interviews with oncologists. Results. Fifty-one oncologists (partially) completed the questionnaire. AO is the best known (95%) and most frequently used RPM (96%). It is used to help oncologists decide whether or not to recommend chemotherapy (> 85%), to inform (86%) and help patients decide about treatment (> 80%), or to persuade them to follow the proposed course of treatment (74%). Most oncologists (74%) believe that using AO helps patients understand their prognosis. Conclusion. RPM have found a place in daily practice, especially AO. Oncologists think that using AO helps patients understand their prognosis, yet studies suggest that this is not always the case. Our findings highlight the importance of exploring whether patients understand the information that RPM provide. [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]

Abstract: Aim: To evaluate trends in the risk of local recurrences after breast-conserving treatment (BCT) and to examine the impact of local recurrence (LR) on distant relapse-free survival in a large, population-based cohort of women aged ⩽40years with early-stage breast cancer. Methods: All women (n =1143) aged ⩽40years with early-stage (pT1-2/cT1-2, N0-2, M0) breast cancer who underwent BCT in the south of the Netherlands between 1988 and 2010 were included. BCT consisted of local excision of the tumour followed by irradiation of the breast. Results: After a median follow-up of 8.5 (0.1–24.6)years, 176 patients had developed an isolated LR. The 5-year LR-rate for the subgroups treated in the periods 1988–1998, 1999–2005 and 2006–2010 were 9.8% (95% confidence interval (CI) 7.1–12.5), 5.9% (95% CI 3.2–8.6) and 3.3% (95% CI 0.6–6.0), respectively (p =0.006). In a multivariate analysis, adjuvant systemic treatment was associated with a reduced risk of LR of almost 60% (hazard ratio (HR) 0.42; 95%CI 0.28–0.60; p <0.0001). Patients who experienced an early isolated LR (⩽5years after BCT) had a worse distant relapse-free survival compared to patients without an early LR (HR 1.83; 95% CI 1.27–2.64; p =0.001). Late local recurrences did not negatively affect distant relapse-free survival (HR 1.24; 95% CI 0.74–2.08; p =0.407). Conclusion: Local control after BCT improved significantly over time and appeared to be closely related to the increased use and effectiveness of systemic therapy. These recent results underline the safety of BCT for young women with early-stage breast cancer. [Copyright &y& Elsevier]

Summary: Background: Adjuvant! is a web-based program that calculates individualised 10-year survival probabilities and predicted benefit of adjuvant systemic therapy. The Adjuvant! model has not been validated in any large European series. The aim of our study was to validate Adjuvant! in Dutch patients, investigating both its calibration and discriminatory accuracy. Methods: Patients who were at least partly treated at the Netherlands Cancer Institute for breast cancer between 1987 and 1998 were included if they met the following criteria: tumour size T1 (≤2 cm), T2 (2–5 cm), or T3 (>5 cm), invasive breast carcinoma, with information about involvement of axillary lymph nodes available, no distant metastases, primary surgery, axillary staging, and radiotherapy according to national guidelines. Clinicopathological characteristics and adjuvant treatment data were retrieved from hospital records and medical registries and were entered into the Adjuvant! (version 8.0) batch processor with blinding to outcome. Endpoints were overall survival and the proportion of patients that did not die from breast cancer (breast-cancer-specific survival [BCSS]). Findings: 5380 patients were included with median follow-up of 11·7 years (range 0·03–21·8). The 10-year observed overall survival (69·0%) and BCSS (78·6%) and Adjuvant! predicted overall survival (69·1%) and BCSS (77·8%) were not statistically different (p=0·87 and p=0·18, respectively). Moreover, differences between predicted and observed outcomes were within 2% for most relevant clinicopathological subgroups. In patients younger than 40 years, Adjuvant! overestimated overall survival by 4·2% (p=0·04) and BCSS by 4·7% (p=0·01). The concordance index, which indicates discriminatory accuracy at the individual level, was 0·71 for BCSS in the entire cohort. Interpretation: Adjuvant! accurately predicted 10-year outcomes in this large-scale Dutch validation study and is of use for adjuvant treatment decision making, although the results may be less reliable in some subgroups. Funding: Dutch National Genomics Initiative-Cancer Genomics Center, Dutch Cancer Society-KWF. [Copyright &y& Elsevier]