Comparison of prone and supine positioning for breast cancer radiotherapy using REQUITE data: dosimetry, acute and two years physician and patient-reported outcomes.

OBJECTIVE: 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. METHODS: 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. RESULTS: 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). CONCLUSIONS: 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.

A Deep Learning Approach Validates Genetic Risk Factors for Late Toxicity After Prostate Cancer Radiotherapy in a REQUITE Multi-National Cohort.

Background: REQUITE (validating pREdictive models and biomarkers of radiotherapy toxicity to reduce side effects and improve QUalITy of lifE in cancer survivors) is an international prospective cohort study. The purpose of this project was to analyse a cohort of patients recruited into REQUITE using a deep learning algorithm to identify patient-specific features associated with the development of toxicity, and test the approach by attempting to validate previously published genetic risk factors. Methods: The study involved REQUITE prostate cancer patients treated with external beam radiotherapy who had complete 2-year follow-up. We used five separate late toxicity endpoints: ≥grade 1 late rectal bleeding, ≥grade 2 urinary frequency, ≥grade 1 haematuria, ≥ grade 2 nocturia, ≥ grade 1 decreased urinary stream. Forty-three single nucleotide polymorphisms (SNPs) already reported in the literature to be associated with the toxicity endpoints were included in the analysis. No SNP had been studied before in the REQUITE cohort. Deep Sparse AutoEncoders (DSAE) were trained to recognize features (SNPs) identifying patients with no toxicity and tested on a different independent mixed population including patients without and with toxicity. Results: One thousand, four hundred and one patients were included, and toxicity rates were: rectal bleeding 11.7%, urinary frequency 4%, haematuria 5.5%, nocturia 7.8%, decreased urinary stream 17.1%. Twenty-four of the 43 SNPs that were associated with the toxicity endpoints were validated as identifying patients with toxicity. Twenty of the 24 SNPs were associated with the same toxicity endpoint as reported in the literature: 9 SNPs for urinary symptoms and 11 SNPs for overall toxicity. The other 4 SNPs were associated with a different endpoint. Conclusion: Deep learning algorithms can validate SNPs associated with toxicity after radiotherapy for prostate cancer. The method should be studied further to identify polygenic SNP risk signatures for radiotherapy toxicity. The signatures could then be included in integrated normal tissue complication probability models and tested for their ability to personalize radiotherapy treatment planning.

Immunohistochemical analysis of prostate apoptosis response-4 (Par-4) in Mexican women with breast cancer: a preliminary study.

BACKGROUND AND AIMS: We undertook this study to compare the expression level of prostate apoptosis response-4 (Par-4) among patient outcome in two groups of women with breast cancer (short and long survival) and two groups without breast cancer (benign lesion and control). METHODS: We included breast specimens with nonhistological abnormalities (eight samples) as a control group. Semiquantitative and quantitative analysis of immunohistochemical staining by image analysis software were used to study the intensity of Par-4 expression. Both methods produced similar results (p>0.05). RESULTS: No significant expression of Par-4 was observed in normal breast tissue. Benign lesions and breast cancer tissue showed strong nuclear expression of Par-4, predominantly on epithelial cells and specifically in ductal cells. Par-4 expression was lower in myoepithelial cells and there was no appreciable stromal staining. Significantly less Par-4 reactivity was detected in tissue from patients with a short survival compared with patients with benign lesions and those with a long survival. CONCLUSIONS: Our findings suggest that a lower expression level of Par-4 is related to an unfavorable prognosis. A larger prospective study of samples of all patient groups with a longer follow-up is needed to validate this finding.