ESTRO 2022 - Abstract Book

S724

Abstract book

ESTRO 2022

The aims of this study were to assess fatigue levels over time in breast cancer patients receiving radiotherapy (RT), and to identify demographic and treatment factors associated with multiple dimensions of long-term fatigue. Materials and Methods Data from breast cancer patients undergoing adjuvant RT after breast-conserving surgery was collected in a prospective international multicentre cohort study (www.requite.eu), including treatment/disease factors, baseline sociodemographic data and patient-reported outcomes. 31% of patients also received chemotherapy. Fatigue was measured at four time points (pre-RT, end of RT, 12 months and 24 months after RT) using the Multidimensional Fatigue Inventory (MFI-20) to assess general fatigue, physical fatigue, mental fatigue, reduced activity, and reduced motivation. The prevalence of moderate-severe fatigue was calculated using a cut-point of >12 (scale range 4-20). The change in fatigue levels over time was analyzed using Friedman test followed by pairwise Wilcoxon signed-rank test. Multivariable logistic regression models (including chemotherapy) were used to identify factors associated with the occurrence of fatigue two years after RT for every MFI-20 dimension. Results A total of 1443, 1302, and 1098 patients completed the MFI-20 at baseline, end of RT and two years after RT. The prevalence of moderate-severe general fatigue in our sample was 37%, 50%, and 34%, respectively. Patients with chemotherapy had higher baseline fatigue levels (Fig. 1). From baseline to the end of RT, levels of fatigue significantly increased for all MFI- 20 dimensions ( p-values <0.05) . Fatigue levels had their peak at the end of RT and returned to baseline levels after two years for mental fatigue. For the other four MFI-20 dimensions, there was a statistically significant decrease in fatigue levels when comparing the baseline and two-year measurements ( p-values <0.05). Baseline fatigue, depression, sleeping disorders, and dyspnea were significantly associated with the occurrence of general fatigue 2 years after RT (e.g., depression OR = 1.75, 95% CI 1.04-2.92 ), whereas overall quality of life was inversely associated ( OR = 0.85, 95% CI 0.77- 0.94). In addition to the previously mentioned variables, other factors such as obesity or pain were associated with other fatigue domains. Conclusion Fatigue is a prevalent symptom in long-term breast cancer survivors receiving RT. Fatigue levels peaked by the end of RT and declined to baseline levels afterwards. Despite this overall decline, still a third of patients reported moderate-severe fatigue two years after RT. Several patient demographic factors and quality of life at baseline were associated with different dimensions of long-term fatigue. Screening for fatigue should be implemented in routine care to identify patients at a higher risk of developing long-term fatigue so that tailored interventions (e.g., psychological, exercise) can be offered in early phases.

Poster Discussion: 19: Dosimetry

PD-0805 3D Portal Dosimetry for extreme hypofraction: pre-treatment and in vivo verification

M. Pereira 1 , J. Stroom 1 , A. Rocha 1 , C. Greco 1 , S. Nijsten 2

1 Champalimaud Centre for the Unknown, Department of Radiation Oncology, Lisbon, Portugal; 2 Maastricht University Medical Centre, Department of Radiation Oncology (MAASTRO Clinic), Maastricht, The Netherlands Purpose or Objective Standard gamma-analysis for individual plan QA can be difficult to interpret and its clinical relevance is doubtful. Deviations from clinical objectives are readily understandable by DVH-based portal transit dosimetry. We aim to demonstrate the feasibility of our in-house developed portal dosimetry solution for 3D dosimetric verification of extreme hypofractionated VMAT treatments, using DVH metrics. Materials and Methods Energy fluency measured with an aS1200 Varian EPID is used by our EPICoreMedPhys (ECMP) software to perform 3D dose verification without ( pre-treatment ) and with a phantom ( in phantom ) or patient in the beam ( in vivo). ECMP reconstructs 3D dose using a Monte Carlo code (XVMC) and compares it to the 3D TPS dose (AAA, Eclipse v15.6). The in phantom tests were performed using the ArcCheck cylindrical phantom. 30 hypofractionated (D fx >4Gy) VMAT plans (13 Prostate, 5 Bone, 4 Brain, 4 Lymph Nodes, 2 Gyneacologic, 1 Pancreas and 1 Lung) with 6 and 10 FFF beams were included. To study the influence of plan complexity, the mean distance between opposing MLC leaves (mdMLC) was calculated for each plan and correlated with median dose differences ( Δ D50) between planned and reconstructed dose distributions for the VOI defined