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The ferritin-heavy chain (FTH1) is the catalytic subunit of the ferroxidase ferritin, which prevents oxidative DNA damage via intracellular iron storage. FTH1 was shown to be a prognostic marker for triple-negative breast cancer (BC) patients and associated with an enrichment of CD8+ effector T cells. However, whether the expression and localization of FTH1 are also associated with clinical outcome in other BC subtypes is unknown. Here, we investigated the association of FTH1 with time to survival in BCs from 222 BRCA1/2 mutation carriers by immunohistochemistry on tissue microarrays. In addition, for 51 of these patients, the association between FTH1 and specific subsets of T cells was evaluated on whole slides using automatic scoring algorithms. We revealed that nuclear FTH1 (nFTH1) expression, in multivariable analyses, was associated with a shorter disease-free (HR = 2.71, 95% CI = 1.49–4.92, p = 0.001) and metastasis-free survival (HR = 3.54, 95% CI = 1.45–8.66, p = 0.006) in patients carrying a BRCA1/2 mutation. However, we found no relation between cytoplasmic FTH1 expression and survival of BRCA1/2 mutation carriers. Moreover, we did not detect an association between FTH1 expression and the amount of CD45+ (p = 0.13), CD8+ (p = 0.18), CD4+ (p = 0.20) or FOXP3+ cells (p = 0.17). Consequently, the mechanism underlying the worse recurrence-free survival of nFTH1 expression in BRCA1/2 mutation carriers needs further investigation.

Background:This study aimed to validate the DCIS-upstage model, a previously developed model to predict the risk of upstaging to invasive breast cancer in patients with biopsy-proven ductal carcinoma in situ (DCIS) in a more recent cohort and to assess the model’s clinical utility.Methods: The model was validated in a registry cohort (n = 2269) and in an institution cohort (n = 302). A calibration plot was made, followed by a decision curve analysis (DCA). The model’s area under the curve (AUC) was compared with the AUC of another published model and with the AUCs of new models using the risk factors of the DCIS-upstage model and additional risk factors. Results: The DCIS-upstage model had an AUC of 0.67 at development; in the validation, the AUC was 0.65 in the registry cohort and 0.73 in the institution cohort. The DCA showed that the model has clinical utility. The other published model had an AUC of 0.66 in the institution cohort. Adding risk factors to the DCIS-upstage model slightly increased the AUC. Conclusions: The DCIS-upstage prediction model is valid in other cohorts. The model has clinical utility and may be used to select patients with biopsy-proven DCIS for sentinel lymph node biopsy.

Background:: Previously published studies report up to 30% recurrence rates after DCIS, so it would be desirable to identify those women at risk for recurrence and adapt adjuvant management. This study aimed to identify the locoregional recurrence rate after breast conserving surgery (BCS) for DCIS, and to evaluate the possible role of immunohistochemical (IHC) staining in predicting the risk of recurrence. Patients and methods:: In a retrospective cohort study, patients who underwent BCS for pure DCIS were identified. Data on well-established clinical-pathological risk factors and development of locoregional recurrence was gathered from patient files. In addition, IHC stains of ER, PR, HER2, p53, and ki67 were performed on original tumor samples. Univariable Cox regression analyses were performed to identify possible risk factors for locoregional recurrence. Results:: 190 patients were included. At a median follow-up time of 12.8 years fifteen (8%) patients developed locoregional recurrence: 7 invasive cancer and 8 DCIS. These recurrences were diagnosed within a range of 1.7 to 19.6 years after the initial diagnosis. Univariable Cox regression analysis did only show a significant association between p53 and locoregional recurrence. Our re-excision rate to obtain free margins was 30.5%, and 90% received radiotherapy. Endocrine treatment was not used. Conclusions:: At 12.8 years follow-up, patients with DCIS treated with BCS have a very low locoregional recurrence of 8%. Although we could demonstrate that increased p53 expression is a risk factor for locoregional recurrence, we think this is of little clinical value in our population with such a low recurrence rate.: With a published recurrence rate up to 30% after DCIS, it would be desirable to identify those at risk to adapt treatment and follow-up. We aimed to evaluate the role of immunohistochemical staining to determine the risk of locoregional recurrence, in addition to established clinical and pathological

Purpose: In patients with a biopsy-proven ductal carcinoma in situ (DCIS), axillary staging is frequently performed, but in hindsight often turns out to be superfluous. The aim of this observational study was to develop a prediction model for risk of lymph node metastasis in patients with a biopsy-proven DCIS. Methods: Data were received from the Dutch Pathology Databank and the Netherlands Cancer Registry. The population-based cohort consisted of all biopsy-proven DCIS patients diagnosed in the Netherlands in 2011 and 2012. The prediction model was evaluated with the area under the curve (AUC) of the receiver operating characteristic, and a calibration plot and a decision curve analysis and was validated in a Dutch cohort of patients diagnosed in the period 2016–2019. Results: Of 2892 biopsy-proven DCIS patients, 127 had metastasis (4.4%). Risk factors were younger age (OR = 0.97, 95% CI 0.95–0.99), DCIS not detected by screening (OR = 1.55, 95% CI 1.01–2.38), suspected invasive component at biopsy (OR = 1.86, 95% CI 1.01–3.41), palpable tumour (OR = 2.06, 95% CI 1.34–3.18), BI-RADS score 5 (OR = 2.41, 95% CI 1.53–3.78), intermediate-grade DCIS (OR = 3.01, 95% CI 1.27–7.15) and high-grade DCIS (OR = 3.20, 95% CI 1.36–7.54). For 24% (n = 708) of the patients, the predicted risk of lymph node metastasis was above 5%. Based on the decision curve analysis, the model had a net benefit for a predicted risk below 25%. The AUC was 0.745. Of the 2269 patients in the validation cohort, 53 (2.2%) had metastasis and the AUC was 0.741. Conclusions: This DCIS-met model can support clinical decisions on axillary staging in patients with biopsy-proven DCIS.

Lobular primary breast cancer (PBC) histology has been proposed as a risk factor for contralateral breast cancer (CBC), but results have been inconsistent. We investigated CBC risk and the impact of systemic therapy in lobular versus ductal PBC. Further, CBC characteristics following these histologic subtypes were explored. We selected 74,373 women diagnosed between 2003 and 2010 with stage I-III invasive PBC from the nationwide Netherlands Cancer Registry. We assessed absolute risk of CBC taking into account competing risks among those with lobular (n = 8903), lobular mixed with other types (n = 3512), versus ductal (n = 62,230) histology. Hazard ratios (HR) for CBC were estimated in a cause-specific Cox model, adjusting for age at PBC diagnosis, radiotherapy, chemotherapy and/or endocrine therapy. Multivariable HRs for CBC were 1.18 (95% CI: 1.04-1.33) for lobular and 1.37 (95% CI: 1.16-1.63) for lobular mixed versus ductal PBC. Ten-year cumulative CBC incidences in patients with lobular, lobular mixed versus ductal PBC were 3.2%, 3.6% versus 2.8% when treated with systemic therapy and 6.6%, 7.7% versus 5.6% in patients without systemic therapy, respectively. Metachronous CBCs were diagnosed in a less favourable stage in 19%, 26% and 23% and less favourable differentiation grade in 22%, 33% and 27% than the PBCs of patients with lobular, lobular mixed and ductal PBC, respectively. In conclusion, lobular and lobular mixed PBC histology are associated with modestly increased CBC risk. Personalised CBC risk assessment needs to consider PBC histology, including systemic treatment administration. The impact on prognosis of CBCs with unfavourable characteristics warrants further evaluation.

Purpose: We aimed to compare (1) treatments and time intervals between treatments of breast cancer patients diagnosed during and before the COVID-19 pandemic, and (2) the number of treatments started during and before the pandemic. Methods: Women were selected from the Netherlands Cancer Registry. For aim one, odds ratios (OR) and 95% confidence intervals (95%CI) were calculated to compare the treatment of women diagnosed within four periods of 2020: pre-COVID (weeks 1–8), transition (weeks 9–12), lockdown (weeks 13–17), and care restart (weeks 18–26), with data from 2018/2019 as reference. Wilcoxon rank-sums test was used to compare treatment intervals, using a two-sided p-value < 0.05. For aim two, number of treatments started per week in 2020 was compared with 2018/2019. Results: We selected 34,097 women for aim one. Compared to 2018/2019, neo-adjuvant chemotherapy was less likely for stage I (OR 0.24, 95%CI 0.11–0.53), stage II (OR 0.63, 95%CI 0.47–0.86), and hormone receptor+/HER2− tumors (OR 0.55, 95%CI 0.41–0.75) diagnosed during transition. Time between diagnosis and first treatment decreased for patients diagnosed during lockdown with a stage I (p < 0.01), II (p < 0.01) or III tumor (p = 0.01). We selected 30,002 women for aim two. The number of neo-adjuvant endocrine therapies and surgeries starting in week 14, 2020, increased by 339% and 18%, respectively. The number of adjuvant chemotherapies decreased by 42% in week 15 and increased by 44% in week 22. Conclusion: The pandemic and subsequently altered treatment recommendations affected multiple aspects of the breast cancer treatment strategy and the number of treatments started per week.