Search

Fatigue is common in breast‐cancer survivors. Our study assessed fatigue longitudinally in breast cancer patients receiving adjuvant radiotherapy (RT) and aimed to identify risk factors associated with long‐term fatigue and underlying fatigue trajectories. Fatigue was measured in a prospective multicenter cohort (REQUITE) using the Multidimensional Fatigue Inventory (MFI‐20) and analyzed using mixed models. Multivariable logistic models identified factors associated with fatigue dimensions at 2 years post‐RT and latent class growth analysis identified individual fatigue trajectories. A total of 1443, 1302, 1203 and 1098 patients completed the MFI‐20 at baseline, end of RT, after 1 and 2 years. Overall, levels of fatigue significantly increased from baseline to end of RT for all fatigue dimensions (P <.05) and returned to baseline levels after 2 years. A quarter of patients were assigned to latent trajectory high (23.7%) and moderate (24.8%) fatigue classes, while 46.3% and 5.2% to the low and decreasing fatigue classes, respectively. Factors associated with multiple fatigue dimensions at 2 years include age, BMI, global health status, insomnia, pain, dyspnea and depression. Fatigue present at baseline was consistently associated with all five MFI‐20 fatigue dimensions (ORGeneralFatigue = 3.81, P <.001). From latent trajectory analysis, patients with a combination of factors such as pain, insomnia, depression, younger age and endocrine therapy had a particularly high risk of developing early and persistent high fatigue years after treatment. Our results confirmed the multidimensional nature of fatigue and will help clinicians identify breast cancer patients at higher risk of having persistent/late fatigue so that tailored interventions can be delivered. [ABSTRACT FROM AUTHOR]

This document is a reply to comments on a previously published paper about the risk factors for fatigue in breast cancer patients who have undergone radiotherapy. The authors explain that they focused on late fatigue because there is a lack of understanding about this aspect of fatigue in breast cancer patients. They also address concerns about missing data and attrition rates in their study, stating that mortality did not substantially influence the attrition rate. The authors express gratitude for the opportunity to discuss their research and express interest in future collaborations to further understand fatigue in breast cancer patients. [Extracted from the article]

Most patients receive whole breast radiotherapy in a supine position. However, two randomised trials showed lower acute toxicity in prone position. Furthermore, in most patients, prone positioning reduced doses to the organs at risk. To confirm these findings, we compared toxicity outcomes, photographic assessment, and dosimetry between both positions using REQUITE data. REQUITE is an international multi-centre prospective observational study that recruited 2069 breast cancer patients receiving radiotherapy. Data on toxicity, health-related quality of life (HRQoL), and dosimetry were collected, as well as a photographic assessment. A matched case control analysis compared patients treated prone (n = 268) versus supine (n = 493). Exact matching was performed for the use of intensity-modulated radiotherapy, boost, lymph node irradiation, chemotherapy and fractionation, and the nearest neighbour for breast volume. Primary endpoints were dermatitis at the end of radiotherapy, and atrophy and cosmetic outcome by photographic assessment at two years. At the last treatment fraction, there was no significant difference in dermatitis (p =.28) or any HRQoL domain, but prone positioning increased the risk of breast oedema (p <.001). At 2 years, patients treated in prone position had less atrophy (p =.01), and higher body image (p <.001), and social functioning (p <.001) scores. The photographic assessment showed no difference in cosmesis at 2 years (p =.22). In prone position, mean heart dose (MHD) was significantly lower for left-sided patients (1.29 Gy vs 2.10 Gy, p <.001) and ipsilateral mean lung dose (MLD) was significantly lower for all patients (2.77 Gy vs 5.89 Gy, p <.001). Prone radiotherapy showed lower MLD and MHD compared to supine position, although the risk of developing breast oedema during radiotherapy was higher. At 2 years the photographic assessment showed no difference in the cosmetic outcome, but less atrophy was seen in prone-treated patients and this seems to have a positive influence on the HRQoL domain of body image. [ABSTRACT FROM AUTHOR]

Background: Acute skin toxicity is a common and usually transient side-effect of breast radiotherapy although, if sufficiently severe, it can affect breast cosmesis, aftercare costs and the patient's quality-of-life. The aim of this study was to develop predictive models for acute skin toxicity using published risk factors and externally validate the models in patients recruited into the prospective multi-center REQUITE (validating pREdictive models and biomarkers of radiotherapy toxicity to reduce side-effects and improve QUalITy of lifE in cancer survivors) study. Methods: Patient and treatment-related risk factors significantly associated with acute breast radiation toxicity on multivariate analysis were identified in the literature. These predictors were used to develop risk models for acute erythema and acute desquamation (skin loss) in three Radiogenomics Consortium cohorts of patients treated by breast-conserving surgery and whole breast external beam radiotherapy (n = 2,031). The models were externally validated in the REQUITE breast cancer cohort (n = 2,057). Results: The final risk model for acute erythema included BMI, breast size, hypo-fractionation, boost, tamoxifen use and smoking status. This model was validated in REQUITE with moderate discrimination (AUC 0.65), calibration and agreement between predicted and observed toxicity (Brier score 0.17). The risk model for acute desquamation, excluding the predictor tamoxifen use, failed to validate in the REQUITE cohort. Conclusions: While most published prediction research in the field has focused on model development, this study reports successful external validation of a predictive model using clinical risk factors for acute erythema following radiotherapy after breast-conserving surgery. This model retained discriminatory power but will benefit from further re-calibration. A similar model to predict acute desquamation failed to validate in the REQUITE cohort. Future improvements and more accurate predictions are expected through the addition of genetic markers and application of other modeling and machine learning techniques. [ABSTRACT FROM AUTHOR]

Normal tissue complication probability (NTCP) models can be useful to estimate the risk of fibrosis after breast-conserving surgery (BCS) and radiotherapy (RT) to the breast. However, they are subject to uncertainties. We present the impact of contouring variation on the prediction of fibrosis. 280 breast cancer patients treated BCS-RT were included. Nine Clinical Target Volume (CTV) contours were created for each patient: i) CTV_crop (reference), cropped 5 mm from the skin and ii) CTV_skin, uncropped and including the skin, iii) segmenting the 95% isodose (Iso 95%) and iv) 3 different auto-contouring atlases generating uncropped and cropped contours (Atlas_skin/Atlas_crop). To illustrate the impact of contour variation on NTCP estimates, we applied two equations predicting fibrosis grade ≥ 2 at 5 years, based on Lyman-Kutcher-Burman (LKB) and Relative Seriality (RS) models, respectively, to each contour. Differences were evaluated using repeated-measures ANOVA. For completeness, the association between observed fibrosis events and NTCP estimates was also evaluated using logistic regression. There were minimal differences between contours when the same contouring approach was followed (cropped and uncropped). CTV_skin and Atlas_skin contours had lower NTCP estimates (−3.92%, IQR 4.00, p < 0.05) compared to CTV_crop. No significant difference was observed for Atlas_crop and Iso 95% contours compared to CTV_crop. For the whole cohort, NTCP estimates varied between 5.3% and 49.5% (LKB) or 2.2% and 49.6% (RS) depending on the choice of contours. NTCP estimates for individual patients varied by up to a factor of 4. Estimates from "skin" contours showed higher agreement with observed events. Contour variations can lead to significantly different NTCP estimates for breast fibrosis, highlighting the importance of standardising breast contours before developing and/or applying NTCP models. • Differences in breast radiotherapy contouring after breast-conserving surgery influence the estimated probability of normal tissue complications. • For individual patients, the estimated risk of grade ≥ 1 breast fibrosis at five years after radiotherapy varies by up to factor of 4. • It is essential to define and standardise contours when developing/applying NTCP models. [ABSTRACT FROM AUTHOR]

Abstract: Objective: To fit four different NTCP (Normal Tissue Complication Probability) models to prospectively collected data on short-term pulmonary complications following breast cancer radiotherapy (RT). Materials/methods: Four hundred and seventy-five breast cancer patients, referred to the Radiotherapy Department at Stockholm Söder Hospital (1994–1998) for adjuvant post-operative RT were prospectively followed for pulmonary complications 1, 4 and 7 months after the completion of RT. Eighty-seven patients with complete dose–volume histogram (DVH) of the ipsilateral lung were selected for the present analysis. Mean dose to the ipsilateral lateral lung ranged from 2.5 to 18Gy (median 12Gy). Three different endpoints were considered: (1) clinical pneumonitis scored according to CTC-NCIC criteria: asymptomatic (grade 0) vs grade 1 and grade 2; (2) radiological changes assessed with diagnostic chest X-ray: no/slight radiological changes vs moderate/severe; (3) radiological changes assessed with CT: no/slight vs moderate/severe. Four NTCP models were used: the Lyman model with DVH reduced to the equivalent uniform dose (LEUD), the Logit model with DVH reduced to EUD, the Mean Lung Dose (MLD) model and the Relative Seriality (RS) model. The data fitting procedure was done using the maximum likelihood analysis. The analysis was done on the entire population (n =87) and on a subgroup of patients treated with loco-regional RT (n =44). Results: 24/87 patients (28%) developed clinical pneumonitis; 28/81 patients (35%) had radiological side effects on chest X-rays and 11/75 patients (15%) showed radiological density changes on Computed Tomography (CT). The analysis showed that the risk of clinical pneumonitis was a smooth function of EUD (calculated from DVH using n =0.86±0.10, best fit result). With LEUD, the relationship between EUD and NTCP could be described with a D 50 of 16.4Gy±1.1Gy and a steepness parameter m of 0.36±0.7. The results found in the overall population were substantially confirmed in the subgroup of patients treated with loco-regional RT. Conclusions: A large group of prospective patient data (87 pts), including grade 1 pneumonitis, were analysed. The four NTCP models fit quite accurately the considered endpoints. EUD or the mean lung dose are robust and simple parameters correlated with the risk of pneumonitis. For all endpoints the D 50 values ranged in an interval between 10 and 20Gy. [Copyright &y& Elsevier]

Since 2001, 50 breast cancer patients, for whom extensive lung/heart involvement was expected from the use of conventional tangential 2-field technique (2F) owing to complex anatomies, were irradiated using a 3-field conformal technique (3F). Dose plans were designed for both 3F and 2F and a dose volume histogram analysis on ipsilateral lung, heart, and target was conducted. The 3F technique allowed a significant reduction in ipsilateral lung irradiation: mean dose dropped from 16.0±3.8 (2F) to 12.0±2.7 Gy (3F) and V 45Gy from 20.7±6.8 (2F) to 3.2±2.9% (3F). Similarly, in patients irradiated to the left breast, heart mean dose was reduced from 8.1 Gy (2F) to 6.8 Gy (3F) and D 15% from 19.0 Gy to 14.0 Gy. All differences reached a high degree of significance. The target coverage was not clinically compromised since the slight reduction using 3F compared with 2F is limited to V 95% while V 90% difference, even if statistically significant, is small: 98.2±1.8% (3F) and 98.8±1.6 (2F). A preliminary report on clinical follow up is also included; with a mean follow up of 15.8 months, no pulmonary or cardiac complications were observed. [ABSTRACT FROM AUTHOR]

• Ten institutes set KB models for tangential fields of right-breast irradiation. • Inter-institute variability was quantified by SD of predicted DVHs and PCs. • The inter-institute variability of DVH ipsilateral lung prediction was around 2%. • High inter-institute interchangeability for 9 out of 10 models was found. • Results suggest the feasibility of multi-centric KB-model plan optimization. To quantify inter-institute variability of Knowledge-Based (KB) models for right breast cancer patients treated with tangential fields whole breast irradiation (WBI). Ten institutions set KB models by using RapidPlan (Varian Inc.), following previously shared methodologies. Models were tested on 20 new patients from the same institutes, exporting DVH predictions of heart, ipsilateral lung, contralateral lung, and contralateral breast. Inter-institute variability was quantified by the inter-institute SD int of predicted DVHs/Dmean. Association between lung sparing vs PTV coverage strategy was also investigated. The transferability of models was evaluated by the overlap of each model's geometric Principal Component (PC1) when applied to the test patients of the other 9 institutes. The overall inter-institute variability of DVH/Dmean ipsilateral lung dose prediction, was less than 2% (20%-80% dose range) and 0.55 Gy respectively (1SD) for a 40 Gy in 15 fraction schedule; it was < 0.2 Gy for other OARs. Institute 6 showed the lowest mean dose prediction value and no overlap between PTV and ipsilateral lung. Once excluded, the predicted ipsilateral lung Dmean was correlated with median PTV D99% (R2 = 0.78). PC1 values were always within the range of applicability (90th percentile) for 7 models: for 2 models they were outside in 1/18 cases. For the model of institute 6, it failed in 7/18 cases. The impact of inter-institute variability of dose calculation was tested and found to be almost negligible. Results show limited inter-institute variability of plan prediction models translating in high inter-institute interchangeability, except for one of ten institutes. These results encourage future investigations in generating benchmarks for plan prediction incorporating inter-institute variability. [ABSTRACT FROM AUTHOR]

• A dosimetric model for late reactions has been developed on a large cohort of breast cancer patients. • We considered for the first time the dose distribution of a 3D skin structure in association with late effects in breast cancer RT. • Quantitative associations between skin DVH and late effects were assessed. • Few clinical parameters (poor cosmesis, aromatase inhibitors (protective)) significantly modulate the risk. Toxicity after whole breast Radiotherapy is a relevant issue, impacting the quality-of-life of a not negligible number of patients. We aimed to develop a Normal Tissue Complication Probability (NTCP) model predicting late toxicities by combining dosimetric parameters of the breast dermis and clinical factors. The skin structure was defined as the outer CT body contour's 5 mm inner isotropic expansion. It was retrospectively segmented on a large mono-institutional cohort of early-stage breast cancer patients enrolled between 2009 and 2017 (n = 1066). Patients were treated with tangential-field RT, delivering 40 Gy in 15 fractions to the whole breast. Toxicity was reported during Follow-Up (FU) using SOMA/LENT scoring. The study endpoint was moderate-severe late side effects consisting of Fibrosis-Atrophy-Telangiectasia-Pain (FATP G ≥ 2) developed within 42 months after RT completion. A machine learning pipeline was designed with a logistic model combining clinical factors and absolute skin DVH (cc) parameters as output. The FATP G2 + rate was 3.8 %, with 40/1066 patients experiencing side effects. After the preprocessing of variables, a cross-validation was applied to define the best-performing model. We selected a 4-variable model with Post-Surgery Cosmetic alterations (Odds Ratio, OR = 7.3), Aromatase Inhibitors (as a protective factor with OR = 0.45), V20 Gy (50 % of the prescribed dose, OR = 1.02), and V42 Gy (105 %, OR = 1.09). Factors were also converted into an adjusted V20Gy. The association between late reactions and skin DVH when delivering 40 Gy/15 fr was quantified, suggesting an independent role of V20 and V42. Few clinical factors heavily modulate the risk. [ABSTRACT FROM AUTHOR]