EP-1374: Contouring guideline optimisation for prostate pts undergoing carbon ions/photons combined treatment

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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

Primary breast lymphoma: Patient profile, outcome and prognostic factors. A multicentre Rare Cancer Network study

BACKGROUND: To asses the clinical profile, treatment outcome and prognostic factors in primary breast lymphoma (PBL). METHODS: Between 1970 and 2000, 84 consecutive patients with PBL were treated in 20 institutions of the Rare Cancer Network. Forty-six patients had Ann Arbor stage IE, 33 stage IIE, 1 stage IIIE, 2 stage IVE and 2 an unknown stage. Twenty-one underwent a mastectomy, 39 conservative surgery and 23 biopsy; 51 received radiotherapy (RT) with (n = 37) or without (n = 14) chemotherapy. Median RT dose was 40 Gy (range 12-55 Gy). RESULTS: Ten (12%) patients progressed locally and 43 (55%) had a systemic relapse. Central nervous system (CNS) was the site of relapse in 12 (14%) cases. The 5-yr overall survival, lymphoma-specific survival, disease-free survival and local control rates were 53%, 59%, 41% and 87% respectively. In the univariate analyses, favorable prognostic factors were early stage, conservative surgery, RT administration and combined modality treatment. Multivariate analysis showed that early stage and the use of RT were favorable prognostic factors. CONCLUSION: The outcome of PBL is fair. Local control is excellent with RT or combined modality treatment but systemic relapses, including that in the CNS, occurs frequently

Pengaruh Arsitektur Informasi terhadap USAbilitas Situs Web Perpustakaan Universitas Diponegoro

Penelitian ini berjudul pengaruh arsitektur informasi terhadap USAbilitas situs web Perpustakaan Universitas Diponegoro. Tujuan dari penelitian ini adalah untuk mengetahui seberapa pengaruh arsitektur informasi terhadap USAbilitas situs web Perpustakaan Universitas Diponegoro. Penelitian ini menggunakan desain penelitian kuantitatif deskriptif bentuk korelasi. Populasi pada penelitian ini adalah pengguna situs web PerpustakaanUniversitas Diponegoro. Penelitian ini mengambil sampel 100mahasiswa yang sedang atau pernah membuka situs web Perpustakaan Universitas Diponegoro. Teori yang digunakan yakni delapan prinsip arsitektur informasi menurut Brown dan karakteristik USAbilitas menurut Jeng. Teknik pengumpulan data yang digunakan pada penelitian ini yaitu dengan menggunakan kuesioner, wawancara, observasi dan dokumentasi. Penelitian ini menggunakan teknik analisis koefisien korelasi Spearman. Pengujian hipotesis didapat dari membandingkan nilai signifikan korelasi dengan signifikansi 0,05. Hasil analisis menunjukkan bahwa arsitektur informasi berpengaruh positif terhadap USAbilitas situs web PerpustakaanUniversitas Diponegoro dengan tingkat keeratan cukup berarti atau sedang dengan nilai koefisien 0,510

Understanding Refinement and Specialization in the UML

The old technique of "abstraction and refinement" makes it possible to understand complex systems by describing them in successive levels of detail. On the other hand the more modern technique of "generalization and specialization" (or Inheritance) facilitates the construction of systems by enabling reuse of specifications. Both techniques enable developers to specify a taxonomic relationship between a more general element and a more specific one

Evaluación y Aplicación de Procesos Ágiles para la Producción de Software en Ambientes de Desarrollo Dirigido por Modelos

El uso de modelos para construir distintos tipos de sistemas software es actualmente una de las claves para la producción de nuevas tecnologías. El Desarrollo de Software Dirigido por Modelos conocido por sus siglas en inglés “MDD” (Model Driven Development) se ha convertido actualmente en un importante paradigma de la Ingeniería de Software, proponiendo sustituir - como artefacto principal en el proceso de producción del software - al código fuente de lenguajes de programación por modelos. De este modo, tales modelos son considerados como entidades de primera línea, permitiendo nuevas posibilidades de crear, analizar y manipular grandes sistemas a través de diversos lenguajes de modelado y herramientas automáticas. En este ámbito, los aspectos de evolución y trazabilidad son un importante desafío teórico-práctico, necesarios tanto en actividades de modelado manual como en procesos de transformación automática entre modelos (que van desde el refinamiento de un modelo de negocio hasta llegar al código fuente compilable en una plataforma de implementación concreta). El motor productivo del MDD es utilizar herramientas automáticas dedicadas y establecer mecanismos de transformación estrictos para los distintos modelos (que van de los más abstractos a los más específicos) involucrados en el proceso de producción de software: CIM (Computational Independent Model), PIM (Platform Independment Model), PSM (Platform Specific Model) e IM (Implementation Model). En este trabajo presentaremos los resultados obtenidos sobre el estudio comparativo y aplicación de procesos ágiles en el campo sistémico aplicable al enfoque automatizado MDD para la producción de software, destacando aspectos evolutivos de productos intermedios durante el curso de transformación de los modelos hasta llegar al producto software resultante, subrayando la importancia del uso combinado de lenguajes de modelado y el apoyo de potentes herramientas CASE (Computer Aided Software Engineering) de soporte a la edición y transformación automatizada de modelo