The effectiveness of personalised surveillance and aftercare in breast cancer follow-up: a systematic review.

PURPOSE: Breast cancer follow-up (surveillance and aftercare) varies from one-size-fits-all to more personalised approaches. A systematic review was performed to get insight in existing evidence on (cost-)effectiveness of personalised follow-up. METHODS: PubMed, Scopus and Cochrane were searched between 01-01-2010 and 10-10-2022 (review registered in PROSPERO:CRD42022375770). The inclusion population comprised nonmetastatic breast cancer patients ≥ 18 years, after completing curative treatment. All intervention-control studies studying personalised surveillance and/or aftercare designed for use during the entire follow-up period were included. All review processes including risk of bias assessment were performed by two reviewers. Characteristics of included studies were described. RESULTS: Overall, 3708 publications were identified, 64 full-text publications were read and 16 were included for data extraction. One study evaluated personalised surveillance. Various personalised aftercare interventions and outcomes were studied. Most common elements included in personalised aftercare plans were treatment summaries (75%), follow-up guidelines (56%), lists of available supportive care resources (38%) and PROs (25%). Control conditions mostly comprised usual care. Four out of seven (57%) studies reported improvements in quality of life following personalisation. Six studies (38%) found no personalisation effect, for multiple outcomes assessed (e.g. distress, satisfaction). One (6.3%) study was judged as low, four (25%) as high risk of bias and 11 (68.8%) as with concerns. CONCLUSION: The included studies varied in interventions, measurement instruments and outcomes, making it impossible to draw conclusions on the effectiveness of personalised follow-up. There is a need for a definition of both personalised surveillance and aftercare, whereafter outcomes can be measured according to uniform standards.

Associations between treatments, comorbidities and multidimensional aspects of quality of life among patients with advanced cancer in the Netherlands-a 2017-2020 multicentre cross-sectional study.

OBJECTIVE: To investigate associations between quality of life (QoL) and 1) immunotherapy and other cancer treatments received three months before QoL measurements, and 2) the comorbidities at the time of completion or in the year prior to QoL measurements, among patients with advanced cancer. METHODS: A cross-sectional study is conducted on patients with advanced cancer in the Netherlands. The data come from the baseline wave of the 2017-2020 eQuiPe study. Participants were surveyed via questionnaires (including EORTC QLQ-C30). Using multivariable linear and logistic regression models, we explored statistical associations between QoL components and immunotherapy and other cancer treatments as well as pre-existing comorbidities while adjusting for age, sex, socio-economic status. RESULTS: Of 1088 participants with median age 67 years, 51% were men. Immunotherapy was not associated with global QoL but was associated with reduced appetite loss (odds ratio (OR) = 0.6, 95%CI = [0.3,0.9]). Reduced global QoL was associated with chemotherapy (adjusted mean difference (ß) = - 4.7, 95% CI [- 8.5,- 0.8]), back pain (ß = - 7.4, 95% CI [- 11.0,- 3.8]), depression (ß = - 13.8, 95% CI [- 21.5,- 6.2]), thyroid diseases (ß = - 8.9, 95% CI [- 14.0,- 3.8]) and diabetes (ß = - 4.5, 95% CI [- 8.9,- 0.5]). Chemotherapy was associated with lower physical (OR = 2.4, 95% CI [1.5,3.9]) and role (OR = 1.8, 95% CI [1.2,2.7]) functioning, and higher pain (OR = 1.9, 95% CI [1.3,2.9]) and fatigue (OR = 1.6, 95% CI [1.1,2.4]). CONCLUSION: Our study identified associations between specific cancer treatments, lower QoL and more symptoms. Monitoring symptoms may improve QoL of patients with advanced cancer. Producing more evidence from real life data would help physicians in better identifying patients who require additional supportive care.

Trends of Axillary Treatment in Sentinel Node-Positive Breast Cancer Patients Undergoing Mastectomy.

BACKGROUND: The ACOSOG-Z0011- and the AMAROS-trial obviated the need for axillary surgery in most sentinel node-positive (SLN+) breast cancer patients undergoing breast-conserving surgery (BCS). Data for patients who undergo mastectomy is scarce. The purpose of this study was to investigate patterns of axillary treatment in SLN+ patients treated by mastectomy in the years after the publication of landmark studies regarding axillary treatment in SLN+ breast cancer patients undergoing BCS. METHODS: This was a population-based study in cT1-3N0M0 breast cancer patients treated by mastectomy and staged as SLN+ between 2009 and 2018. The performance of an axillary lymph node dissection (ALND) and/or administration of postmastectomy radiotherapy (PMRT) were primary outcomes and were studied over time. RESULTS: The study included 10,633 patients. The frequency of ALND performance decreased from 78% in 2009 to 10% in 2018, whereas PMRT increased from 4 to 49% (P < 0.001). In ≥N1a patients, ALND performance decreased from 93 to 20%, whereas PMRT increased to 70% (P < 0.001). In N1mi and N0itc patients, ALND was abandoned during the study period, whereas PMRT increased to 38% and 13% respectively (P < 0.001), respectively. Age, tumor subtype, N-stage, and hospital type affected the likelihood that patients underwent ALND. CONCLUSIONS: In this study in SLN+ breast cancer patients undergoing mastectomy, use of ALND decreased drastically over time. By the end of 2018 most ≥N1a patients received PMRT as the only adjuvant axillary treatment, whereas the majority of N1mi and N0itc patients received no additional treatment.

External validation of 87 clinical prediction models supporting clinical decisions for breast cancer patients.

INTRODUCTION: Numerous prediction models have been developed to support treatment-related decisions for breast cancer patients. External validation, a prerequisite for implementation in clinical practice, has been performed for only a few models. This study aims to externally validate published clinical prediction models using population-based Dutch data. METHODS: Patient-, tumor- and treatment-related data were derived from the Netherlands Cancer Registry (NCR). Model performance was assessed using the area under the receiver operating characteristic curve (AUC), scaled Brier score, and model calibration. Net benefit across applicable risk thresholds was evaluated with decision curve analysis. RESULTS: After assessing 922 models, 87 (9%) were included for validation. Models were excluded due to an incomplete model description (n = 262 (28%)), lack of required data (n = 521 (57%)), previously validated or developed with NCR data (n = 45 (5%)), or the associated NCR sample size was insufficient (n = 7 (1%)). The included models predicted survival (33 (38%) overall, 27 (31%) breast cancer-specific, and 3 (3%) other cause-specific), locoregional recurrence (n = 7 (8%)), disease free survival (n = 7 (8%)), metastases (n = 5 (6%)), lymph node involvement (n = 3 (3%)), pathologic complete response (n = 1 (1%)), and surgical margins (n = 1 (1%)). Seven models (8%) showed poor (AUC<0.6), 39 (45%) moderate (AUC:0.6-0.7), 38 (46%) good (AUC:0.7-0.9), and 3 (3%) excellent (AUC≥0.9) discrimination. Using the scaled Brier score, worse performance than an uninformative model was found in 34 (39%) models. CONCLUSION: Comprehensive registry data supports broad validation of published prediction models. Model performance varies considerably in new patient populations, affirming the importance of external validation studies before applying models in clinical practice. Well performing models could be clinically useful in a Dutch setting after careful impact evaluation.

Inequalities in the omission of axillary dissection in sentinel lymph node positive patients in the Netherlands: Innovative hospitals are early adopters of a de-escalating approach.

During the last decade completion axillary lymph node dissection (cALND) was gradually omitted in sentinel lymph node positive (SLN+) breast cancer patients. However, adoption varies among hospitals. We analyzed factors associated with the omission of cALND in all Dutch SLN+ patients. As one of the focus hospital-related factors we defined "innovative" as the percentage of gene-expression profile (GEP) deployment within the indicated group of patients per hospital as a proxy for early adoption of innovations. cT1-2N0M0 SLN+ patients treated between 2011 and 2018 were selected from the Netherlands Cancer Registry. Hospitals were defined to be innovative based on their GEP use. Multivariable logistic regression (MLR) was performed to assess the relationship between innovative capacity, patient-, treatment- and hospital-related characteristics and cALND performance. 14 317 patients were included. Treatment in a hospital with high innovative capacity was associated with a lower probability of receiving cALND (OR 0.69, OR 0.46 and OR 0.35 in modestly, fairly and very innovative, respectively). Other factors associated with a lower probability of receiving a cALND were age 70 and 79 years and ≥79 years (ORs 0.59 [95% CI: 0.50-0.68] and 0.21 [95% CI: 0.17-0.26]) and treatment in an academic hospital (OR 0.41 [95% CI: 0.33-0.51]). Factors associated with an increased probability of undergoing cALND were HR-/HER2- tumors (OR 1.46 [95% CI: 1.19-1.80]), macrometastatic lymph node involvement (OR 6.37 [95% CI: 5.70-7.13]) and mastectomy (OR 4.57 [95% CI: 4.09-5.10]). Patients treated in a hospital that early adopted innovations were less likely to receive cALND. Our findings endorse the need for studies on barriers and facilitators of implementing innovations.

Routine and interval detection of locoregional breast cancer recurrences and risk of subsequent distant metastasis.

PURPOSE: Follow-up for breast cancer survivors consists of after care and surveillance. The benefits of routine surveillance visits remain debatable. In this study we compared the severity of locoregional recurrences (LRRs) and the subsequent risk of a distant metastasis (DM) between LRRs detected at routine and interval visits. METHODS: Women diagnosed with early breast cancer between 2003 and 2008 in one of the 15 participating hospitals, and who developed a LRR as first event after primary treatment, were selected from the Netherlands Cancer Registry (Cohort A). Chi-squared tests were used to compare the severity of routine- and interval-detected local recurrences (LRs) and regional recurrences (RRs), using tumor size, tumor grade, and number of positive lymph nodes. Data on the development of a subsequent DM after a LRR were available for a subset of patients (Cohort B). Cohort B was used to estimate the association between way of LRR-detection and risk of a DM. RESULTS: Cohort A consisted of 109 routine- and 113 interval-LRR patients. The severity of routine-detected LRs or RRs and interval-detected LRs or RRs did not significantly differ. Cohort B consisted of 66 routine- and 61 interval-LRR patients. Sixteen routine- (24%) and 17 (28%) interval-LRR patients developed a DM. After adjustment, way of LRR-detection was not significantly associated with the risk of a DM (hazard ratio: 1.22; 95% confidence interval: 0.49-3.06). CONCLUSION: The current study showed that routine visits did not lead to less severe LRRs and did not decrease the risk of a subsequent DM.

Representativeness of trial participants: linking the EORTC boost-no boost trial to the Netherlands cancer registry.

BACKGROUND AND OBJECTIVES: To evaluate the representativeness of Dutch patients participating in the European Organization for Research and Treatment of Cancer EORTC boost-no-boost trial to the target breast cancer patient population. METHODS: All female breast cancer patients diagnosed between 1989 and 1996, aged ≤70 years, treated with breast-conserving surgery and radiation therapy, were selected from the Netherlands Cancer Registry (NCR) and linked to the EORTC trial database. Baseline characteristics were compared between trial and non-trial participants, for the Dutch population and according to seven participating institutions. Kaplan-Meier curves and multivariable Cox regression were used to explore potential heterogeneity in overall survival between low, medium and high-volume institutes. RESULTS: Overall, 20,880 patients were identified from the NCR: 2,445 of 2,602 (94%) trial participants could be linked, and 18,435 were treated outside the trial. Trial participants had similar age, morphology, topography, laterality and socioeconomic status as non-trial participants, but more often stage I (62.7% vs. 56.4%) tumours and less often adjuvant treatment (22.9% vs. 26.5%). Crude 20-year survival ranged from 52.5% to 57.4%, without significant differences in multivariable analyses. CONCLUSION: This case study showed that participants in the boost-no-boost trial well represented the Dutch target population. Data linkage comes with challenges, but can close the gap between research and clinical practice.

Socioeconomic status and its relation with breast cancer recurrence and survival in young women in the Netherlands.

BACKGROUND: Associations between socioeconomic status (SES) and breast cancer survival are most pronounced in young patients. We further investigated the relation between SES, subsequent recurrent events and mortality in breast cancer patients < 40 years. Using detailed data on all recurrences that occur between date of diagnosis of the primary tumor and last observation, we provide a unique insight in the prognosis of young breast cancer patients according to SES. METHODS: All women < 40 years diagnosed with primary operated stage I-III breast cancer in 2005 were selected from the nationwide population-based Netherlands Cancer Registry. Data on all recurrences within 10 years from primary tumor diagnosis were collected directly from patient files. Recurrence patterns and absolute risks of recurrence, contralateral breast cancer (CBC) and mortality - accounting for competing risks - were analysed according to SES. Relationships between SES, recurrence patterns and excess mortality were estimated using a multivariable joint model, wherein the association between recurrent events and excess mortality (expected mortality derived from the general population) was included. RESULTS: We included 525 patients. The 10-year recurrence risk was lowest in high SES (18.1%), highest in low SES (29.8%). Death and CBC as first events were rare. In high, medium and low SES 13.2%, 15.3% and 19.1% died following a recurrence. Low SES patients had shorter median time intervals between diagnosis, first recurrence and 10-year mortality (2.6 and 2.7 years, respectively) compared to high SES (3.5 and 3.3 years, respectively). In multivariable joint modeling, high SES was significantly related to lower recurrence rates over 10-year follow-up, compared to low SES. A strong association between the recurrent event process and excess mortality was found. CONCLUSIONS: High SES is associated with lower recurrence risks, less subsequent events and better prognosis after recurrence over 10 years than low SES. Breast cancer risk factors, adjuvant treatment adherence and treatment of recurrence may possibly play a role in this association.

The majority of 922 prediction models supporting breast cancer decision-making are at high risk of bias.

OBJECTIVES: To systematically review the currently available prediction models that may support treatment decision-making in breast cancer. STUDY DESIGN AND SETTING: Literature was systematically searched to identify studies reporting on development of prediction models aiming to support breast cancer treatment decision-making, published between January 2010 and December 2020. Quality and risk of bias were assessed using the Prediction model Risk Of Bias (ROB) Assessment Tool (PROBAST). RESULTS: After screening 20,460 studies, 534 studies were included, reporting on 922 models. The 922 models predicted: mortality (n = 417 45%), recurrence (n = 217, 24%), lymph node involvement (n = 141, 15%), adverse events (n = 58, 6%), treatment response (n = 56, 6%), or other outcomes (n = 33, 4%). In total, 285 models (31%) lacked a complete description of the final model and could not be applied to new patients. Most models (n = 878, 95%) were considered to contain high ROB. CONCLUSION: A substantial overlap in predictor variables and outcomes between the models was observed. Most models were not reported according to established reporting guidelines or showed methodological flaws during the development and/or validation of the model. Further development of prediction models with thorough quality and validity assessment is an essential first step for future clinical application.

Trends in incidence, treatment, survival and subsequent breast cancer in lobular carcinoma in situ in the Netherlands: A population-based analysis.

PURPOSE: We analysed incidence, treatment, survival, occurrence of ductal carcinoma in situ (DCIS) and invasive breast cancer (IBC) after lobular carcinoma in situ (LCIS) in the Netherlands. METHODS: All women diagnosed with classic LCIS between 1989 and 2017 were identified from the Netherlands Cancer Registry. We calculated overall (OS), relative survival (RS) and cumulative incidence functions (CIF, accounting for competing risks) of mortality, DCIS and IBC. For IBC, standardised incidence ratios (SIR) of IBC were calculated. Analyses were stratified for surgical treatment. RESULTS: We included 1890 patients. Median age was 51 years. Median follow-up was 8.5 years. In 1989-2017, LCIS incidence increased from 41 to 124, surgical treatment decreased from 100% to 41.1 % - mostly BCS. 10-year OS and 20-year RS exceeded 90 % in all subgroups. Overall, 48 (2.5 %) and 270 (14.3 %) patients were diagnosed with DCIS and IBC. IBCs were mostly early-stage. After mastectomy, 13 of 14 IBCs presented contralaterally. In the other groups, 64.8-70.9 % of IBCs presented ipsilaterally, 34.5-53.9 % of these were lobular. The SIR of ipsilateral IBC was highest after no surgery (6.9, 95%CI:4.9-9.4), lowest after mastectomy (0.2, 95%CI:0.4-0.8). CONCLUSION: LCIS incidence increased, surgical treatment decreased. The low mortality risks support consideration of active surveillance. However, the increased IBC incidence suggests careful monitoring.

Improved risk estimation of locoregional recurrence, secondary contralateral tumors and distant metastases in early breast cancer: the INFLUENCE 2.0 model.

PURPOSE: To extend the functionality of the existing INFLUENCE nomogram for locoregional recurrence (LRR) of breast cancer toward the prediction of secondary primary tumors (SP) and distant metastases (DM) using updated follow-up data and the best suitable statistical approaches. METHODS: Data on women diagnosed with non-metastatic invasive breast cancer were derived from the Netherlands Cancer Registry (n = 13,494). To provide flexible time-dependent individual risk predictions for LRR, SP, and DM, three statistical approaches were assessed; a Cox proportional hazard approach (COX), a parametric spline approach (PAR), and a random survival forest (RSF). These approaches were evaluated on their discrimination using the Area Under the Curve (AUC) statistic and on calibration using the Integrated Calibration Index (ICI). To correct for optimism, the performance measures were assessed by drawing 200 bootstrap samples. RESULTS: Age, tumor grade, pT, pN, multifocality, type of surgery, hormonal receptor status, HER2-status, and adjuvant therapy were included as predictors. While all three approaches showed adequate calibration, the RSF approach offers the best optimism-corrected 5-year AUC for LRR (0.75, 95%CI: 0.74-0.76) and SP (0.67, 95%CI: 0.65-0.68). For the prediction of DM, all three approaches showed equivalent discrimination (5-year AUC: 0.77-0.78), while COX seems to have an advantage concerning calibration (ICI < 0.01). Finally, an online calculator of INFLUENCE 2.0 was created. CONCLUSIONS: INFLUENCE 2.0 is a flexible model to predict time-dependent individual risks of LRR, SP and DM at a 5-year scale; it can support clinical decision-making regarding personalized follow-up strategies for curatively treated non-metastatic breast cancer patients.

Explainable machine learning can outperform Cox regression predictions and provide insights in breast cancer survival.

Cox Proportional Hazards (CPH) analysis is the standard for survival analysis in oncology. Recently, several machine learning (ML) techniques have been adapted for this task. Although they have shown to yield results at least as good as classical methods, they are often disregarded because of their lack of transparency and little to no explainability, which are key for their adoption in clinical settings. In this paper, we used data from the Netherlands Cancer Registry of 36,658 non-metastatic breast cancer patients to compare the performance of CPH with ML techniques (Random Survival Forests, Survival Support Vector Machines, and Extreme Gradient Boosting [XGB]) in predicting survival using the [Formula: see text]-index. We demonstrated that in our dataset, ML-based models can perform at least as good as the classical CPH regression ([Formula: see text]-index [Formula: see text]), and in the case of XGB even better ([Formula: see text]-index [Formula: see text]). Furthermore, we used Shapley Additive Explanation (SHAP) values to explain the models' predictions. We concluded that the difference in performance can be attributed to XGB's ability to model nonlinearities and complex interactions. We also investigated the impact of specific features on the models' predictions as well as their corresponding insights. Lastly, we showed that explainable ML can generate explicit knowledge of how models make their predictions, which is crucial in increasing the trust and adoption of innovative ML techniques in oncology and healthcare overall.

Comprehensive trends in incidence, treatment, survival and mortality of first primary invasive breast cancer stratified by age, stage and receptor subtype in the Netherlands between 1989 and 2017.

Our study aimed to provide a comprehensive overview of trends in incidence, survival, mortality and treatment of first primary invasive breast cancer (BC), according to age, stage and receptor subtype in the Netherlands between 1989 and 2017. Data from all women diagnosed with first primary stage I to IV BC (N = 320 249) were obtained from the Netherlands Cancer Registry. BC mortality and general population data were retrieved from Statistics Netherlands. Age-standardised incidence and mortality rates were calculated with annual percentage change (APC) and average annual percentage change (AAPC) statistics. The relative survival (RS) was used as estimator for disease-specific survival. The BC incidence for all BC patients combined significantly increased until 2013 from 126 to 158 per 100 000 person-years, after which a declining trend was observed. Surgery became less extensive, but (neo-)adjuvant systemic treatments and their combinations were given more frequently. The RS improved for all age groups and for most stages and receptor subtypes, but remained stable for all subtypes since 2012 to 2013 and since 2000 to 2009 for Stage IV BC at 15 years of follow-up. Overall, the 5- and 10-year RS increased from 76.8% (95% confidence interval [CI]: 76.1, 77.4) and 55.9% (95% CI: 54.7, 57.1) in 1989 to 1999 to 91.0% (95% CI: 90.5, 91.5) and 82.9% (95% CI: 82.2, 83.5), respectively, in 2010 to 2016. BC mortality improved regardless of age and overall decreased from 57 to 35 per 100 000 person-years between 1989 and 2017. In conclusion, the BC incidence in the Netherlands has steadily increased since 1989, but the latest trends show promising declines. Survival improved markedly for most patients and the mortality decreased regardless of age.

Conditional regional recurrence risk: The effect of event-free years in different subtypes of breast cancer.

BACKGROUND: Regional recurrence (RR), also known as lymph node recurrence, is an endpoint in several trials concerning reducing axillary treatment in cT1-2N0 breast cancer patients. The risk of RR may decrease with each subsequent event-free year, affecting the yield and consequently usefulness of long (er) follow-up. The aim of this study is to determine the risk of RR as a first event within five years after diagnosis in subtypes of breast cancer, conditional to being event-free for one, two, three and four years. METHODS: From the Netherlands Cancer Registry, cT1-2N0 breast cancer patients diagnosed from 2005 to 2008 were analyzed. Subgroup analysis was performed for pT1-2N+(sn) patients. RR risk was calculated with Kaplan-Meier analysis. Conditional RR (assuming x event-free years) was determined by selecting patients without an event at x years, and calculating the remaining risk for RR within five years after diagnosis. RESULTS: A total of 18,009 cT1-2N0 (all pN stages) breast cancer patients were included. RR occurred in 1.3% of cT1-2N0 and 1.5% of pT1-2N+(sn) patients. The risk of RR varied between subtypes; it was highest for triple negative tumors and lowest for ER + PR + Her2-and ER + Her2+ tumors. After event-free years, the risk of RR decreased subsequently in both groups and in all subtypes. After two event-free years, the risk of RR was 0.8%. CONCLUSION: The absolute yield of follow-up to detect RR beyond two years is low; for every 125 event-free patients, one RR can be expected until five years. This suggests that follow-up longer than two years is of limited value for detecting RR in both clinical and research setting.

Heart failure medication after a first hospital admission and risk of heart failure readmission, focus on beta-blockers and renin-angiotensin-aldosterone system medication: A retrospective cohort study in linked databases.

BACKGROUND: This study assessed the association between heart failure (HF) medication (angiotensin-converting-enzyme inhibitors (ACEI)/angiotensin-receptor blockers (ARB), beta-blockers (BB), mineralocorticoid-receptor antagonists (MRA) and diuretics) and HF readmissions in a real-world unselected group of patients after a first hospital admission for HF. Furthermore we analysed readmission rates for ACEI versus ARB and for carvedilol versus ß1-selective BB and we investigated the effect of HF medication in relation to time since discharge. METHODS AND FINDINGS: Medication at discharge was determined with dispensing data from the Dutch PHARMO Database Network including 22,476 patients with HF between 2001 and 2015. After adjustment for age, gender, number of medications and year of admission no associations were found for users versus non-users of ACEI/ARB (hazard ratio, HR = 1.01; 95%CI 0.96-1.06), BB (HR = 1.00; 95%CI 0.95-1.05) and readmissions. The risk of readmission for patients prescribed MRA (HR = 1.11; 95%CI 1.05-1.16) or diuretics (HR = 1.17; 95%CI 1.09-1.25) was higher than for non-users. The HR for ARB relative to ACEI was 1.04 (95%CI 0.97-1.12) and for carvedilol relative to ß1-selective BB 1.33 (95%CI 1.20-1.46). Post-hoc analyses showed a protective effect shortly after discharge for most medications. For example one month post discharge the HR for ACEI/ARB was 0.77 (95%CI 0.69-0.86). Although we did try to adjust for confounding by indication, probably residual confounding is still present. CONCLUSIONS: Patients who were prescribed carvedilol have a higher or at least a similar risk of HF readmission compared to ß1-selective BB. This study showed that all groups of HF medication -some more pronounced than others- were more effective immediately following discharge.

Quantifying the Mitigating Effects of Whole-Breast Radiotherapy and Systemic Treatments on Regional Recurrence Incidence Among Breast Cancer Patients.

BACKGROUND: Despite the potential for residual lymph node metastases after a negative or positive sentinel lymph node biopsy (SLNB), breast cancer patients rarely experience regional recurrences (RRs). This study aimed to quantify the effects of nonsurgical treatments on RR incidence among SLNB-negative (SLNB N0) breast cancer patients. METHODS: All primary SLNB N0-staged breast cancer patients with a diagnosis between 2005 and 2008 and 5-year follow-up data on recurrences were selected from the Netherlands Cancer Registry. The cumulative incidence function (CIF) for RR was calculated as the first event at 5 years, taking into account any other first-event (local or distant recurrence, contralateral breast cancer, or death) as competing risk. Cox regression analysis was used to model the cause-specific hazard of RR developing as the first event to quantify the effect of adjuvant systemic therapy and whole-breast radiotherapy (RT) on RR incidence at 5 years. RESULTS: The study included 13,512 patients. Of these patients, 162 experienced an RR. The CIF of RR at 5 years was 1.3% (95% confidence interval [CI], 1.1-1.5%), whereas the CIFs for death and other events were 4.4% and 9.5%, respectively. Cox regression analysis showed hazard ratios (HRs) of 0.46 (95% CI 0.33-0.64), 0.31 (95% CI 0.18-0.55), and 0.40 (95% CI 0.24-0.67) respectively for patients treated by RT as a routine part of breast-conserving therapy (BCT), chemotherapy, and hormonal therapy. CONCLUSION: RT as routine part of BCT, chemotherapy, and hormonal therapy independently exerted a mitigating effect on the risk for the development of RR. The three methods at least halved the risk.

Association between initiation of adjuvant chemotherapy beyond 30 days after surgery and overall survival among patients with triple-negative breast cancer.

Delayed time to chemotherapy (TTC) is associated with decreased outcomes of breast cancer patients. Recently, studies suggested that the association might be subtype-dependent and that TTC within 30 days should be warranted in patients with triple-negative breast cancer (TNBC). The aim of the current study is to determine if TTC beyond 30 days is associated with reduced 10-year overall survival in TNBC patients. We identified all TNBC patients diagnosed between 2006 and 2014 who received adjuvant chemotherapy in the Netherlands. We distinguished between breast-conserving surgery (BCS) vs. mastectomy given the difference in preoperative characteristics and outcomes. The association was estimated with hazard ratios (HRs) using propensity-score matched Cox proportional hazard analyses. In total, 3,016 patients were included. In matched patients who underwent BCS (n = 904), 10-year overall survival was favorable for patients with TTC within 30 days (84.4% vs. 76.9%, p = 0.001). Patients with TTC beyond 30 days were more likely than those with TTC within 30 days to die within 10 years after surgery (HR 1.69 (95% CI 1.22-2.34), p = 0.002). In matched patients who underwent mastectomy (n = 1,568), there was no difference in 10 years overall survival between those with TTC within or beyond 30 days (74.5% vs. 74.7%, p = 0.716), nor an increased risk of death for those with TTC beyond 30 days (HR 1.04 (95% CI 0.84-1.28), p = 0.716). Initiation of adjuvant chemotherapy beyond 30 days is associated with decreased 10 years overall survival in TNBC patients who underwent BCS. Therefore, timelier initiation of chemotherapy in TNBC patients undergoing BCS seems warranted.