Background Studies have demonstrated worse breast cancer-specific mortality with older age, despite an increasing risk of dying from other causes due to comorbidity (competing mortality). However,... Show moreBackground Studies have demonstrated worse breast cancer-specific mortality with older age, despite an increasing risk of dying from other causes due to comorbidity (competing mortality). However, findings on the association between older age and recurrence risk are inconsistent. The aim of this study was to assess incidences of locoregional and distant recurrence by age, taking competing mortality into account. Materials and Methods Patients surgically treated for nonmetastasized breast cancer between 2003 and 2009 were selected from The Netherlands Cancer Registry. Cumulative incidences of recurrence were calculated considering death without distant recurrence as competing event. Fine and Gray analyses were performed to characterize the impact of age (70-74 [reference group], 75-79, and >= 80 years) on recurrence risk. Results A total of 18,419 patients were included. Nine-year cumulative incidences of locoregional recurrence were 2.5%, 3.1%, and 2.9% in patients aged 70-74, 75-79, and >= 80 years, and 9-year cumulative incidences of distant recurrence were 10.9%, 15.9%, and 12.7%, respectively. After adjustment for tumor and treatment characteristics, age was not associated with locoregional recurrence risk. For distant recurrence, patients aged 75-79 years remained at higher risk after adjustment for tumor and treatment characteristics (75-79 years subdistribution hazard ratio [sHR], 1.25; 95% confidence interval [CI], 1.11-1.41; >= 80 years sHR, 1.03; 95% CI, 0.91-1.17). Conclusion Patients aged 75-79 years had a higher risk of distant recurrence than patients aged 70-74 years, despite the higher competing mortality. Individualizing treatment by using prediction tools that include competing mortality could improve outcome for older patients with breast cancer. Implications for Practice In this population-based study of 18,419 surgically treated patients aged 70 years or older, patients aged 75-79 years were at higher risk of distant recurrence than were patients aged 70-74 years. This finding suggests that patients in this age category are undertreated. In contrast, it was also demonstrated that the risk of dying without a recurrence strongly increases with age, and patients with a high competing mortality risk are easily overtreated. To identify older patients who may benefit from more treatment, clinicians should therefore take competing mortality risk into account. Prediction tools could facilitate this and thereby improve treatment strategy. Show less
Gal, R.; Monninkhof, E.M.; Gils, C.H. van; Groenwold, R.H.H.; Bongard, D.H.J.G. van den; Peeters, P.H.M.; ... ; May, A.M. 2019
Objectives: The Trials within Cohorts (TwiCs) design is an alternative for pragmatic randomized controlled trials (RCTs) and might overcome disadvantages such as difficult recruitment, dropout... Show moreObjectives: The Trials within Cohorts (TwiCs) design is an alternative for pragmatic randomized controlled trials (RCTs) and might overcome disadvantages such as difficult recruitment, dropout after randomization to control, and contamination. We investigated the applicability of the TwiCs design in an exercise oncology study regarding the recruitment process, representativeness of the study sample, contamination, participation, and dropout.Methods: The Utrecht cohort for Multiple BREast cancer intervention studies and Long-term evaLuAtion (UMBRELLA) Fit TwiCs evaluates an exercise intervention in inactive breast cancer patients. Eligible patients participating in the prospective UMBRELLA were identified and randomized. Patients randomized to the intervention (n = 130) were offered the intervention, whereas controls (n = 130) were not informed.Results: Fifty-two percent (n = 68) accepted the intervention. Because this rate was lower than expected, a larger sample size was required than initially estimated (n = 166). However, recruitment of 260 patients was still completed by one researcher within 30 months. Unselective eligibility screening and randomization before invitation improved representativeness. Disadvantage of the design might be inclusion of ineligible patients when cohort information is limited. Furthermore, the design faced higher noncompliance in the intervention group, but prevention of contamination.Conclusion: The TwiCs design improved logistics in recruitment and prevented contamination, but noncompliance due to refusal of the intervention was higher compared with conventional pragmatic exercise oncology RCTs, which may dilute the estimated intervention effect. (C) 2019 The Authors. Published by Elsevier Inc. Show less
Background: In addition to the established association between general obesity and breast cancer risk, central obesity and circulating fasting insulin and glucose have been linked to the... Show moreBackground: In addition to the established association between general obesity and breast cancer risk, central obesity and circulating fasting insulin and glucose have been linked to the development of this common malignancy. Findings from previous studies, however, have been inconsistent, and the nature of the associations is unclear.Methods: We conducted Mendelian randomization analyses to evaluate the association of breast cancer risk, using genetic instruments, with fasting insulin, fasting glucose, 2-h glucose, body mass index (BMI) and BMI-adjusted waist-hip-ratio (WHRadj BMI). We first confirmed the association of these instruments with type 2 diabetes risk in a large diabetes genome-wide association study consortium. We then investigated their associations with breast cancer risk using individual-level data obtained from 98 842 cases and 83 464 controls of European descent in the Breast Cancer Association Consortium.Results: All sets of instruments were associated with risk of type 2 diabetes. Associations with breast cancer risk were found for genetically predicted fasting insulin [odds ratio (OR) = 1.71 per standard deviation (SD) increase, 95% confidence interval (CI) = 1.26-2.31, p = 5.09 x 10(-4)], 2-h glucose (OR = 1.80 per SD increase, 95% CI = 1.3 0-2.49, p = 4.02 x 10(-4)), BMI (OR = 0.70 per 5-unit increase, 95% CI = 0.65-0.76, p = 5.05 x 10(-19)) and WHRadj BMI (OR = 0.85, 95% CI = 0.79-0.91, p = 9.22 x 10(-6)). Stratified analyses showed that genetically predicted fasting insulin was more closely related to risk of estrogen-receptor [ER]-positive cancer, whereas the associations with instruments of 2h glucose, BMI and WHRadj BMI were consistent regardless of age, menopausal status, estrogen receptor status and family history of breast cancer.Conclusions: We confirmed the previously reported inverse association of genetically predicted BMI with breast cancer risk, and showed a positive association of genetically predicted fasting insulin and 2-h glucose and an inverse association of WHRadj BMI with breast cancer risk. Our study suggests that genetically determined obesity and glucose/insulin-related traits have an important role in the aetiology of breast cancer. Show less
Lakeman, I.M.M.; Schmidt, M.K.; Asperen, C.J. van; Devilee, P. 2019
Purpose of ReviewBreast cancer is the most common cancer among females in developed countries. Strategies such as early detection by breast cancer screening can reduce the burden of disease but... Show morePurpose of ReviewBreast cancer is the most common cancer among females in developed countries. Strategies such as early detection by breast cancer screening can reduce the burden of disease but have disadvantages including overdiagnosis and increased cost. Stratification of women according to the risk of developing breast cancer, based on genetic and lifestyle risk factors, could improve risk-reduction and screening strategies by targeting those most likely to benefit.Recent FindingsBreast cancer risk is partly determined by genetic factors including rare pathogenic variants in susceptibility genes and common low-risk variants. Other risk factors include alcohol use, smoking, reproductive factors, hormonal factors, family history, mammographic density, BMI, and body height. Ideally, all risk factors are combined into an individual breast cancer lifetime risk score, but this requires knowledge about their interactions as well as accurate effect sizes. A few risk models seem to be sufficiently developed to inform clinical risk management to minimise cancer risk of those at increased risk and avoid overtreatment of those at decreased risk.SummaryIn this review, we briefly summarise the breast cancer susceptibility factors and discuss avenues towards combining all these factors to create individual risk scores. Show less
This thesis is about clinical quality audits, used to measure and improve the quality of health care; focusing on the quality of breast cancer care (see: the NBCA) and on the quality of breast... Show moreThis thesis is about clinical quality audits, used to measure and improve the quality of health care; focusing on the quality of breast cancer care (see: the NBCA) and on the quality of breast implant surgery (see: the DBIR) in the Netherlands. Show less
Purpose: Patients may transfer of hospital for clinical reasons but this may delay time to treatment. The purpose of this study is to provide insight in the extent of hospital transfer in breast... Show morePurpose: Patients may transfer of hospital for clinical reasons but this may delay time to treatment. The purpose of this study is to provide insight in the extent of hospital transfer in breast cancer care; which type of patients transfer and what is the impact on time to treatment.Methods: We included 41,413 breast cancer patients registered in the Netherlands Cancer Registry between 2014 and 2016. We investigated transfer of hospital between diagnosis and first treatment being surgery or neoadjuvant chemotherapy (NAC). Co-variate adjusted characteristics predictive for hospital transfer were determined. To adjust for possible treatment by indication bias we used propensity score matching (PSM). Time to treatment in patients with and without hospital transfer was compared.Results: Among 41,413 patients, 8.5% of all patients transferred to another hospital between diagnosis and first treatment; 4.9% before primary surgery and 24.8% before NAC. Especially young (aged <40 years) patients and those who underwent a mastectomy with immediate breast reconstruction (IBR) were more likely to transfer. The association of mastectomy with IBR with hospital transfer remained when using PSM. Hospital transfer after diagnosis significantly prolonged time to treatment; breast conserving surgery by 5 days, mastectomy by 7 days, mastectomy with IBR by 9 days and NAC by 1 day.Conclusions: While almost 5% of Dutch patients treated with primary surgery transfer hospital after diagnosis and up to 25% for patients treated with NAC, our findings suggest that especially those treated with primary surgery are at risk for additional treatment delay by hospital transfer. (C) 2018 Published by Elsevier Ltd. Show less
Early-onset breast cancer may be due to Li-Fraumeni Syndrome (LFS). Current national and international guidelines recommend that TP53 genetic testing should be considered for women with breast... Show moreEarly-onset breast cancer may be due to Li-Fraumeni Syndrome (LFS). Current national and international guidelines recommend that TP53 genetic testing should be considered for women with breast cancer diagnosed before the age of 31years. However, large studies investigating TP53 mutation prevalence in this population are scarce. We collected nationwide laboratory records for all young breast cancer patients tested for TP53 mutations in the Netherlands. Between 2005 and 2016, 370 women diagnosed with breast cancer younger than 30years of age were tested for TP53 germline mutations, and eight (2.2%) were found to carry a (likely) pathogenic TP53 sequence variant. Among BRCA1/BRCA2 mutation negative women without a family history suggestive of LFS or a personal history of multiple LFS-related tumours, the TP53 mutation frequency was <1% (2/233). Taking into consideration that TP53 mutation prevalence was comparable or even higher in some studies selecting patients with breast cancer onset at older ages or HER2-positive breast cancers, raises the question of whether a very early age of onset is an appropriate single TP53 genetic testing criterion. Show less
This thesis describes the preferences of both older patients with breast cancer and clinicians to optimize the current care of this patient group. The significant increase in the number of breast... Show moreThis thesis describes the preferences of both older patients with breast cancer and clinicians to optimize the current care of this patient group. The significant increase in the number of breast cancer patients above the age of 65 years necessitates insight into their preferences. Decision-making regarding treatment of early breast cancer is often difficult as decisions need to be made between two surgical options and about the addition of systemic therapy. Like younger patients, older patients are faced with these difficult decisions (together with their clinician). However, treatments for early breast cancer differ substantially between younger and older patients, which possibly can be explained by the preferences of older patients or their clinicians. Currently, little is known about the preferences of older patients, while this knowledge is particularly of great value. To assess how the current care of older patients and the treatment-decision-making process with this patient group can be optimised, we explore the preferences and motivations of older patients with early breast cancer; if and how their preferences for treatment and participation in decision-making differ from those of younger patients; and the treatment preferences of breast cancer specialists with regard to treatment of older patients. Show less
