(Pre)treatment risk factors for late fatigue and fatigue trajectories following radiotherapy for breast cancer

Breast cancer; Fatigue; RadiotherapyCáncer de mama; Fatiga; RadioterapiaCàncer de mama; Fatiga; RadioteràpiaFatigue 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.We thank all patients who participated in the REQUITE study and all the REQUITE staff involved in this project. Belgium: Ghent University Hospital; KU Leuven. France: ICM Montpellier, CHU Nîmes (Department of Radiation Oncology, CHU Nîmes, Nîmes, France). Germany: Zentrum für Strahlentherapie Freiburg (Dr. Petra Stegmaier); Städtisches Klinikum Karlsruhe (Dr. Bernhard Neu); ViDia Christliche Kliniken Karlsruhe (Prof. Johannes Claßen); Klinikum der Stadt Ludwigshafen GmbH (PD Dr. Thomas Schnabel); Universitätsklinikum Mannheim: Anette Kipke and Christiane Zimmermann; Strahlentherapie Speyer (Dr. Jörg Schäfer). The researchers at DKFZ also thank Anusha Müller, Irmgard Helmbold, Thomas Heger, Sabine Behrens, Axel Benner, Nicholas Schreck. Petra Seibold is supported by ERA PerMed 2018 funding (BMBF #01KU1912) and BfS funding (#3619S42261). Italy: Fondazione IRCCS Istituto Nazionale dei Tumori, Milano; Candiolo Cancer Institute – FPO, IRCCS. Tiziana Rancati was partially funded by Fondazione Italo Monzino. The Netherlands: Sylvie Canisius at Maastro Clinics, Maastricht. Spain: Barcelona: Vall d'Hebron Hospital Universitari, Vall d'Hebron Barcelona Hospital Campus; VHIO acknowledge the Cellex Foundation for providing research facilities and thank CERCA Programme/Generalitat de Catalunya for institutional support. Sara Gutiérrez-Enríquez is supported by ERAPerMed JTC2018 funding (ERAPERMED2018-244 and SLT011/18/00005). Santiago: Complexo Hospitalario Universitario de Santiago. Ana Vega: supported by Spanish Instituto de Salud Carlos III (ISCIII) funding, an initiative of the Spanish Ministry of Economy and Innovation partially supported by European Regional Development FEDER Funds (PI22/00589, PI19/01424; INT20/00071); the ERAPerMed JTC2018 funding (AC18/00117); the Autonomous Government of Galicia (Consolidation and structuring program: IN607B), by the Fundación Mutua Madrileña (call 2018) and by the AECC (PRYES211091VEGA); UK: University Hospitals of Leicester NHS Trust; Theresa Beaver, Kaitlin Walker and Sara Barrows. Dr Tim Rattay was funded by a National Institute of Health Research (NIHR) Clinical Lectureship (CL 2017-11-002) and is currently supported by the NIHR Leicester Biomedical Research Centre. He was previously funded by a National Institute of Health Research (NIHR) Doctoral Research Fellowship (DRF 2014-07-079). This publication presents independent research funded by the NIHR. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. Manchester: Catharine West and Rebecca Elliott are supported by NIHR Manchester Biomedical Research Centre and Catharine West is supported by Cancer Research UK (C1094/A18504, C147/A25254). USA: Mount Sinai Hospital, New York. Open Access funding enabled and organized by Projekt DEAL

High weekly integral dose and larger fraction size increase risk of fatigue and worsening of functional outcomes following radiotherapy for localized prostate cancer

IntroductionWe hypothesized that increasing the pelvic integral dose (ID) and a higher dose per fraction correlate with worsening fatigue and functional outcomes in localized prostate cancer (PCa) patients treated with external beam radiotherapy (EBRT). MethodsThe study design was a retrospective analysis of two prospective observational cohorts, REQUITE (development, n=543) and DUE-01 (validation, n=228). Data were available for comorbidities, medication, androgen deprivation therapy, previous surgeries, smoking, age, and body mass index. The ID was calculated as the product of the mean body dose and body volume. The weekly ID accounted for differences in fractionation. The worsening (end of radiotherapy versus baseline) of European Organisation for Research and Treatment of Cancer EORTC) Quality of Life Questionnaire (QLQ)-C30 scores in physical/role/social functioning and fatigue symptom scales were evaluated, and two outcome measures were defined as worsening in >= 2 (WS2) or >= 3 (WS3) scales, respectively. The weekly ID and clinical risk factors were tested in multivariable logistic regression analysis. ResultsIn REQUITE, WS2 was seen in 28% and WS3 in 16% of patients. The median weekly ID was 13.1 L center dot Gy/week [interquartile (IQ) range 10.2-19.3]. The weekly ID, diabetes, the use of intensity-modulated radiotherapy, and the dose per fraction were significantly associated with WS2 [AUC (area under the receiver operating characteristics curve) =0.59; 95% CI 0.55-0.63] and WS3 (AUC=0.60; 95% CI 0.55-0.64). The prevalence of WS2 (15.3%) and WS3 (6.1%) was lower in DUE-01, but the median weekly ID was higher (15.8 L center dot Gy/week; IQ range 13.2-19.3). The model for WS2 was validated with reduced discrimination (AUC=0.52 95% CI 0.47-0.61), The AUC for WS3 was 0.58, ConclusionIncreasing the weekly ID and the dose per fraction lead to the worsening of fatigue and functional outcomes in patients with localized PCa treated with EBRT

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

Large-Scale Meta-GWAS Reveals Common Genetic Factors Linked to Radiation-Induced Acute Toxicities across Cancers

BACKGROUND: This study was designed to identify common genetic susceptibility and shared genetic variants associated with acute radiation-induced toxicity (RIT) across four cancer types (prostate, head and neck, breast, and lung).METHODS: A GWAS meta-analysis was performed using 19 cohorts including 12,042 patients. Acute standardized total average toxicity (rSTATacute) was modelled using a generalized linear regression model for additive effect of genetic variants adjusted for demographic and clinical covariates. LD score regression estimated shared SNP-based heritability of rSTATacute in all patients and for each cancer type.RESULTS: Shared SNP-based heritability of STATacute among all cancer types was estimated at 10% (se = 0.02), and was higher for prostate (17%, se = 0.07), head and neck (27%, se = 0.09), and breast (16%, se = 0.09) cancers. We identified 130 suggestive associated SNPs with rSTATacute (5.0x10-8&lt;P-value&lt;1.0x10-5) across 25 genomic regions. rs142667902 showed the strongest association (effect allele A; effect size -0.17; P-value=1.7x10-7), which is located near DPPA4, encoding a protein involved in pluripotency in stem cells, which are essential for repair of radiation-induced tissue injury. Gene-set enrichment analysis identified 'RNA splicing via endonucleolytic cleavage and ligation' (P = 5.1 x10-6, Pcorrected =0.079) as the top gene set associated with rSTATacute among all patients. In-silico gene expression analysis showed the genes associated with rSTATacute were statistically significantly up-regulated in skin (not sun exposed Pcorrected=0.004; sun exposed Pcorrected=0.026).CONCLUSIONS: There is shared SNP-based heritability for acute RIT across and within individual cancer sites. Future meta-GWAS among large radiotherapy patient cohorts are worthwhile to identify the common causal variants for acute radiotoxicity across cancer types.</p

REQUITE: A prospective multicentre cohort study of patients undergoing radiotherapy for breast, lung or prostate cancer

Purpose: REQUITE aimed to establish a resource for multi-national validation of models and biomarkers that predict risk of late toxicity following radiotherapy. The purpose of this article is to provide summary descriptive data. Methods: An international, prospective cohort study recruited cancer patients in 26 hospitals in eight countries between April 2014 and March 2017. Target recruitment was 5300 patients. Eligible patients had breast, prostate or lung cancer and planned potentially curable radiotherapy. Radiotherapy was prescribed according to local regimens, but centres used standardised data collection forms. Pre-treatment blood samples were collected. Patients were followed for a minimum of 12 (lung) or 24 (breast/prostate) months and summary descriptive statistics were generated. Results: The study recruited 2069 breast (99% of target), 1808 prostate (86%) and 561 lung (51%) cancer patients. The centralised, accessible database includes: physician-(47,025 forms) and patient-(54,901) reported outcomes; 11,563 breast photos; 17,107 DICOMs and 12,684 DVHs. Imputed genotype data are available for 4223 patients with European ancestry (1948 breast, 1728 prostate, 547 lung). Radiation-induced lymphocyte apoptosis (RILA) assay data are available for 1319 patients. DNA (n = 4409) and PAXgene tubes (n = 3039) are stored in the centralised biobank. Example prevalences of 2-year (1-year for lung) grade >= 2 CTCAE toxicities are 13% atrophy (breast), 3% rectal bleeding (prostate) and 27% dyspnoea (lung). Conclusion: The comprehensive centralised database and linked biobank is a valuable resource for the radiotherapy community for validating predictive models and biomarkers. Patient summary: Up to half of cancer patients undergo radiation therapy and irradiation of surrounding healthy tissue is unavoidable. Damage to healthy tissue can affect short-and long-term quality-of-life. Not all patients are equally sensitive to radiation "damage" but it is not possible at the moment to identify those who are. REQUITE was established with the aim of trying to understand more about how we could predict radiation sensitivity. The purpose of this paper is to provide an overview and summary of the data and material available. In the REQUITE study 4400 breast, prostate and lung cancer patients filled out questionnaires and donated blood. A large amount of data was collected in the same way. With all these data and samples a database and biobank were created that showed it is possible to collect this kind of information in a standardised way across countries. In the future, our database and linked biobank will be a resource for research and validation of clinical predictors and models of radiation sensitivity. REQUITE will also enable a better understanding of how many people suffer with radiotherapy toxicity

Magnetic Resonance-Guided Reirradiation for Local Recurrence within the Prostate or in the Prostate Bed: One-Year Clinical Results of a Prospective Registry Study

Around 33% of patients treated by EBRT or brachytherapy will present a biochemical recurrence. SBRT is a new option for the treatment of patients with local-only recurrence. MRgRT seems to be interesting for the treatment of these recurrences. This article presents the one-year late tolerance and biochemical recurrence-free survival results of a prospective registry study. Patients with intraprostatic (or in the prostate bed) recurrence were treated with 5 to 9 fractions (median dose of 30 Gy in 5 fractions) with the MRIdian® system. PSA level and toxicities were evaluated before treatment and at three, six and 12 months after treatment. Thirty-seven patients with a median age of 74.5 years old were treated between 21 October 2019 and 7 December 2020. Acute tolerance was excellent with no grade >2 toxicities. Twelve months after treatment, we observed an increase of grade 1–2 dysuria (46% vs. 13% before treatment) and grade 1 polyuria (73% vs. 7%). The six, nine and 12-months biochemical-recurrence free survival were 97.3%, 86.5% and 65.0%. Fifteen patients (40%) presented a biochemical recurrence. Nine of these 15 patients (60%) had a persistent disease within the treated volume. In conclusion, MRgRT is safe and has promising survival results

Stereotactic MR-Guided Radiotherapy for Adrenal Gland Metastases: First Clinical Results

Stereotactic MR-guided Radiotherapy (MRgRT) is an interesting treatment option for adrenal gland metastases (AGM). We reviewed data from 12 consecutive patients treated with MRgRT for an AGM in our center between 14 November 2019 and 17 August 2021. Endpoints were tolerance assessment, the impact of adaptive treatment on target volume coverage and organs at risk (OAR) sparing, local control (LC), and overall survival (OS). The majority of patients were oligometastatic (58.3%), with 6 right AGM, 5 left AGM and 1 left and right AGM. The prescribed dose was 35 to 50 Gy in 3 to 5 fractions. The median PTV V95% on the initial plan was 95.74%. The median V95% of the PTVoptimized (PTVopt) on the initial plan was 95.26%. Thirty-eight (69%) fractions were adapted. The PTV coverage was significantly improved for adapted plans compared to predicted plans (median PTV V95% increased from 89.85% to 91.17%, p = 0.0478). The plan adaptation also significantly reduced Dmax for the stomach and small intestine. The treatment was well tolerated with no grade > 2 toxicities. With a median follow-up of 15.5 months, the 1–year LC and OS rate were 100% and 91.7%. Six patients (50%) presented a metastatic progression, and one patient (8.3%) died of metastatic evolution during the follow-up. Adaptation of the treatment plan improved the overall dosimetric quality of MRI-guided radiotherapy. A longer follow-up is required to assess late toxicities and clinical results

(Pre)treatment risk factors for late fatigue and fatigue trajectories following radiotherapy for breast cancer

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 &lt; .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 &lt; .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