Benefit of respiratory gating in the Danish Breast Cancer Group partial breast irradiation trial.

BACKGROUND AND PURPOSE: Partial breast irradiation (PBI)has beenthe Danish Breast Cancer Group(DBCG) standard for selected breast cancer patients since 2016 based onearlyresults from the DBCG PBI trial.During trial accrual, respiratory-gated radiotherapy was introduced in Denmark. This study aims to investigate the effect of respiratory-gating on mean heart dose (MHD). PATIENTS AND METHODS: From 2009 to 2016 the DBCG PBI trial included 230 patientswith left-sided breast cancer receiving external beam PBI, 40 Gy/15 fractions/3 weeks.Localization of the tumor bed on the planning CT scan, the use of respiratory-gating, coverage of the clinical target volume (CTV), and doses to organs at risk were collected. RESULTS: Respiratory-gating was used in 123 patients (53 %). In 176 patients (77 %) the tumor bed was in the upper and in 54 patients (23 %) in the lower breast quadrants. The median MHD was 0.37 Gy (interquartile range 0.26-0.57 Gy), 0.33 Gy (0.23-0.49 Gy) for respiratory-gating, and 0.49 Gy (0.31-0.70 Gy) for free breathing, p < 0.0001. MHD was < 1 Gy in 206 patients (90 %) and < 2 Gy in 221 patients (96 %). Respiratory-gating led to significantly lower MHD for upper-located, but not for lower-located tumor beds, however, all MHD were low irrespective of respiratory-gating. Respiratory-gating did not improve CTV coverage or lower lung doses. CONCLUSIONS: PBI ensured a low MHD for most patients. Adding respiratory-gating further reduced MHD for upper-located but not for lower-located tumor beds but did not influence target coverage or lung doses. Respiratory-gating is no longer DBCG standard for left-sided PBI.

Shared decision making with breast cancer patients - does it work? Results of the cluster-randomized, multicenter DBCG RT SDM trial.

BACKGROUND AND PURPOSE: Shared decision making (SDM) is a patient engaging process advocated especially for preference-sensitive decisions, such as adjuvant treatment after breast cancer. An increasing call for patient engagement in decision making highlights the need for a systematic SDM approach. The objective of this trial was to investigate whether the Decision Helper (DH), an in-consultation patient decision aid, increases patient engagement in decisions regarding adjuvant whole breast irradiation. MATERIAL AND METHODS: Oncologists at four radiotherapy units were randomized to practice SDM using the DH versus usual practice. Patient candidates for adjuvant whole breast irradiation after breast conserving surgery for node-negative breast cancer were eligible. The primary endpoint was patient-reported engagement in the decision process assessed with the Shared Decision Making Questionnaire (SDM-Q-9) (range 0-100, 4 points difference considered clinical relevant). Other endpoints included oncologist-reported patient engagement, decisional conflict, fear of cancer recurrence, and decision regret after 6 months. RESULTS: Of the 674 included patients, 635 (94.2%) completed the SDM-Q-9. Patients in the intervention group reported higher level of engagement (median 80; IQR 68.9 to 94.4) than the control group (71.1; IQR 55.6 to 82.2; p < 0.0001). Oncologist-reported patient engagement was higher in the invention group (93.3; IQR 82.2 to 100) compared to control group (73.3; IQR 60.0 to 84.4) (p < 0.0001). CONCLUSION: Patient engagement in medical decision making was significantly improved with the use of an in-consultation patient decision aid compared to standard. The DH on adjuvant whole breast irradiation is now recommended as standard of care in the Danish guideline.

Development of a national deep learning-based auto-segmentation model for the heart on clinical delineations from the DBCG RT nation cohort.

BACKGROUND: This study aimed at investigating the feasibility of developing a deep learning-based auto-segmentation model for the heart trained on clinical delineations. MATERIAL AND METHODS: This study included two different datasets. The first dataset contained clinical heart delineations from the DBCG RT Nation study (1,561 patients). The second dataset was smaller (114 patients), but with corrected heart delineations. Before training the model on the clinical delineations an outlier-detection was performed, to remove cases with gross deviations from the delineation guideline. No outlier detection was performed for the dataset with corrected heart delineations. Both models were trained with a 3D full resolution nnUNet. The models were evaluated with the dice similarity coefficient (DSC), 95% Hausdorff distance (HD95) and Mean Surface Distance (MSD). The difference between the models were tested with the Mann-Whitney U-test. The balance of dataset quantity versus quality was investigated, by stepwise reducing the cohort size for the model trained on clinical delineations. RESULTS: During the outlier-detection 137 patients were excluded from the clinical cohort due to non-compliance with delineation guidelines. The model trained on the curated clinical cohort performed with a median DSC of 0.96 (IQR 0.94-0.96), median HD95 of 4.00 mm (IQR 3.00 mm-6.00 mm) and a median MSD of 1.49 mm (IQR 1.12 mm-2.02 mm). The model trained on the dedicated and corrected cohort performed with a median DSC of 0.95 (IQR 0.93-0.96), median HD95 of 5.65 mm (IQR 3.37 mm-8.62 mm) and median MSD of 1.63 mm (IQR 1.35 mm-2.11 mm). The difference between the two models were found non-significant for all metrics (p > 0.05). Reduction of cohort size showed no significant difference for all metrics (p > 0.05). However, with the smallest cohort size, a few outlier structures were found. CONCLUSIONS: This study demonstrated a deep learning-based auto-segmentation model trained on curated clinical delineations which performs on par with a model trained on dedicated delineations, making it easier to develop multi-institutional auto-segmentation models.

Adjuvant Cyclophosphamide and Docetaxel With or Without Epirubicin for Early TOP2A-Normal Breast Cancer: DBCG 07-READ, an Open-Label, Phase III, Randomized Trial.

Purpose Administration of anthracycline and taxane therapy in the adjuvant setting is considered a standard for breast cancer. We evaluated a non-anthracycline-based regimen in TOP2A-normal patients. Patients and Methods In this multicenter, open-label, phase III trial, 2,012 women with early TOP2A-normal breast cancer and at least one high-risk factor were randomly assigned to receive six cycles of docetaxel (75 mg/m2) and cyclophosphamide (600 mg/m2) every 3 weeks (DC) or three cycles of epirubicin (90 mg/m2) and cyclophosphamide (600 mg/m2) followed by three cycles of docetaxel (100 mg/m2; EC-D). The primary end point was disease-free survival (DFS) after a median of 5 years of follow-up. Secondary end points were patient-reported toxicity, overall survival (OS), and distant disease-free survival. Results At a median estimated potential follow-up of 69 months, 5-year DFS was 87.9% (95% CI, 85.6% to 89.8%) in the EC-D arm and 88.3% (95% CI, 86.1% to 90.1%) in the DC arm. There was no significant difference in the risk of DFS events (hazard ratio [HR], 1.00; 95% CI, 0.78 to 1.28; P = 1.00), distant disease-free survival (HR, 1.12; 95% CI, 0.86 to 1.47; P = .40), or mortality (HR, 1.15; 95% CI, 0.83 to 1.59; P = .41) in the intent-to-treat analysis. A significant interaction between menopausal status and treatment group was observed for DFS ( P = .04) but not for OS ( P = .07). Patients with grade 3 tumors derived most benefit from DC, and patients with grade 1 to 2 tumors derived most benefit from EC-D (DFS: interaction P = .02; and OS: interaction P = .03). Patients receiving EC-D reported significantly more stomatitis, myalgia or arthralgia, vomiting, nausea, fatigue, and peripheral neuropathy, whereas edema was more frequent after DC. Conclusion This study provides evidence to support no overall outcome benefit from adjuvant anthracyclines in patients with early TOP2A-normal breast cancer.

Plasma HER2 amplification in cell-free DNA during neoadjuvant chemotherapy in breast cancer.

PURPOSE: Measurement of human epidermal growth factor receptor 2 (HER2) gene amplification in cell-free DNA (cfDNA) is an evolving technique in breast cancer, enabling liquid biopsies and treatment monitoring. The present study investigated the dynamics of plasma HER2 gene copy number and amplification in cfDNA during neoadjuvant chemotherapy. PATIENTS AND METHODS: The study included 50 patients from a prospective cohort analyzed during neoadjuvant chemotherapy. Fifty healthy women with no history of cancer served as control group and 15 patients with metastatic breast cancer were used to validate the assay. Total cfDNA and HER2 gene amplification were measured by quantitative real-time polymerase chain reaction. RESULTS: Plasma HER2 gene copy number (p = 0.794), HER2 gene amplification (p = 0.127) and total cfDNA (p = 0.440) did not differ significantly from the levels in the control group. Eighteen patients (36 %) obtained pathological complete response (pCR). HER2 gene copy number before the operation was significantly higher than the baseline level (p < 0.0001), but there was no difference between patients with and without pCR (p = 0.569). Likewise, there was no difference in plasma HER2 gene amplification between tissue HER2-positive and -negative patients (p = 0.754). CONCLUSIONS: The results indicate that neither total cfDNA nor HER2 gene copy number is elevated in primary breast cancer patients compared to healthy controls. The level of both parameters increased during neoadjuvant chemotherapy, but without any relation to treatment effect. There was no indication of plasma HER2 gene amplification in the HER2-positive patients in the neoadjuvant setting.

Prognostic impact of VEGFA germline polymorphisms in patients with HER2-positive primary breast cancer.

BACKGROUND: Vascular endothelial growth factor A (VEGFA) is essential in tumour angiogenesis, and polymorphisms in the VEGFA gene have been associated with breast cancer prognosis. The human epidermal growth factor receptor 2 (HER2) is overexpressed in breast tumours and is also associated with angiogenesis. We investigated the possible prognostic impact of VEGFA single nucleotide polymorphisms (SNPs) in patients with HER2-positive primary breast cancer. PATIENTS AND METHODS: DNA was isolated from venous blood samples from 116 HER2-positive patients and genotyped for VEGFA -2578C>A, -1498T>C, -1154G>A, -634G>C, -7C>T and +936C>T SNPs using the TaqMan® SNP Genotyping Assay. RESULTS: The -2578C>A and -634G>C genotypes were associated with tumour size, p ≤ 0.014. In univariate analysis -2578CC, -634CC and -7CC genotypes were associated with inferior recurrence-free survival (p ≤ 0.028) but in cox multivariate analysis, only the -634CC genotype remained an independent prognostic factor (p=0.008). CONCLUSION: The VEGFA -634CC genotype was found to be associated with an inferior prognosis for patients with HER2-positive breast cancer.

Prognostic impact of placenta growth factor and vascular endothelial growth factor A in patients with breast cancer.

Placenta growth factor (PlGF) and vascular endothelial growth factor A (VEGF-A) are angiogenic growth factors interacting competitively with the same receptors. VEGF-A is essential in both normal and pathologic conditions, but the functions of PlGF seem to be restricted to pathologic conditions such as ischemic heart disease, arthritis and tumor growth. Angiogenesis is a complex process with several growth factors involved. Because PlGF modulates VEGF-A responses, we investigated their mutual relationship and impact on breast cancer prognosis. Quantitative PlGF and VEGF-A levels were measured in 229 tumor tissue specimen from primarily operated patients with unilateral breast cancer. Non-malignant breast tissue was also dissected near the tumor and quantitative measurements were available for 211 patients. PlGF and VEGF-A protein levels in homogenized tissue lysates were analyzed using the Luminex system. We found significantly higher median levels of PlGF and VEGF-A in tumor tissue compared to non-malignant tissue (PlGF: 69.8 vs. 31.4 pg/mg, p < 0.001 and VEGF-A: 1148.2 vs. 163.5 pg/mg, p < 0.001). PlGF and VEGF-A were correlated in both malignant tissue (r = 0.41, p < 0.001) and in non-malignant tissue (r = 0.69, p < 0.001). The proportion of node positive patients was higher with high PlGF expression (61.4%) than with low PlGF expression (45.6%) in tumor tissue, p = 0.024. High levels of PlGF and VEGF-A in tumor tissue were associated with significant shorter recurrence-free survival (RFS) in both univariate analysis (PlGF: p = 0.023; VEGF-A: p = 0.047) and in multivariate analysis (PlGF: p = 0.026; VEGF-A: p = 0.036). Neither PlGF nor VEGF-A expression in non-malignant tissue were predictors for RFS. In conclusion, our results support the mutual relationship between PlGF and VEGF-A and encourage further investigations as prognostic markers in breast cancer patients.

Estimation of immunohistochemical expression of VEGF in ductal carcinomas of the breast.

Vascular endothelial growth factor A (VEGF-A) is a very important growth factor in angiogenesis and holds potential as both a predictive marker for anti-angiogenic cancer treatment and a prognostic variable. Consequently, reliable estimation of VEGF expression is crucial. Investigators immunostained whole tumor sections for VEGF-A, VEGF-B, and VEGFR-1 of invasive ductal carcinomas of the breast and scored the tumors manually with staining intensity as the only parameter and by a combination of qualitative and quantitative information. The investigators also introduce an automated method for analyzing VEGF expression (so-called AI score) using the same tumor sections. Analysis of 100% of the tumor area was performed and the results were compared with the reduced analysis of 25% of the tumor area. These analyses were performed at ×5 and ×10 magnification, and each analysis was repeated in a second run with a new delineation of the tumor area. The AI scores were correlated to the manual scoring of VEGF intensity, but reproducibility of manual IHC scores was rather poor. The AI scores were reproducible, and the restricted analysis of 25% of the tumor area at ×5 magnifications was the most efficient considering time consumption and data load.