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Radiation oncology has the potential to be an excellent option for the frail elderly cancer patients because of its limited systemic toxicities. It can be effective for curative, prophylactic, disease control or palliative purposes. Currently about 60% of all cancer patients undergoing active treatment at some point receive radiation treatment. However, though widely used, there are limited clinical trials strictly designed for the elderly. This paper will review the key points in the assessment and treatment of elderly cancer patient including quality of life, active life expectancy, cognitive performance, frailty, sarcopenia and how the new technologies can help to reach the key goal of maintaining autonomy and independence for the elderly cancer patient.

Purpose: Clinical data collecting is expensive in terms of time and human resources. Data can be collected in different ways; therefore, performing multicentric research based on previously stored data is often difficult. The primary objective of the ENT COBRA (COnsortium for BRachytherapy data Analysis) ontology is to define a specific terminological system to standardized data collection for head and neck (H&N) cancer patients treated with interventional radiotherapy. Material and methods: ENT-COBRA is a consortium for standardized data collection for H&N patients treated with interventional radiotherapy. It is linked to H&N and Skin GEC-ESTRO Working Group and includes 11 centers from 6 countries. Its ontology was firstly defined by a multicentric working group, then evaluated by the consortium followed by a multi-professional technical commission involving a mathematician, an engineer, a physician with experience in data storage, a programmer, and a software expert. Results: Two hundred and forty variables were defined on 13 input forms. There are 3 levels, each offering a specific type of analysis: 1. Registry level (epidemiology analysis); 2. Procedures level (standard oncology analysis); 3. Research level (radiomics analysis). The ontology was approved by the consortium and technical commission; an ad-hoc software architecture (“broker”) remaps the data present in already existing storage systems of the various centers according to the shared terminology system. The first data sharing was successfully performed using COBRA software and the ENT COBRA Ontology, automatically collecting data directly from 3 different hospital databases (Lübeck, Navarra, and Rome) in November 2017. Conclusions: The COBRA Ontology is a good response to the multi-dimensional criticalities of data collection, retrieval, and usability. It allows to create a software for large multicentric databases with implementation of specific remapping functions wherever necessary. Th

The big data approach offers a powerful alternative to Evidence-based medicine. This approach could guide cancer management thanks to machine learning application to large-scale data. Aim of the Thyroid CoBRA (Consortium for Brachytherapy Data Analysis) project is to develop a standardized web data collection system, focused on thyroid cancer. The Metabolic Radiotherapy Working Group of Italian Association of Radiation Oncology (AIRO) endorsed the implementation of a consortium directed to thyroid cancer management and data collection. The agreement conditions, the ontology of the collected data and the related software services were defined by a multicentre ad hoc working-group (WG). Six Italian cancer centres were firstly started the project, defined and signed the Thyroid COBRA consortium agreement. Three data set tiers were identified: Registry, Procedures and Research. The COBRA-Storage System (C-SS) appeared to be not time-consuming and to be privacy respecting, as data can be extracted directly from the single centre's storage platforms through a secured connection that ensures reliable encryption of sensible data. Automatic data archiving could be directly performed from Image Hospital Storage System or the Radiotherapy Treatment Planning Systems. The C-SS architecture will allow “Cloud storage way” or “distributed learning” approaches for predictive model definition and further clinical decision support tools development. The development of the Thyroid COBRA data Storage System C-SS through a multicentre consortium approach appeared to be a feasible tool in the setup of complex and privacy saving data sharing system oriented to the management of thyroid cancer and in the near future every cancer type.

Aim: Identifying the best care for a patient can be extremely challenging. To support the creation of multifactorial Decision Support Systems (DSSs), we propose an Umbrella Protocol, focusing on prostate cancer. Materials & methods: The PRODIGE project consisted of a workflow for standardizing data, and procedures, to create a consistent dataset useful to elaborate DSSs. Techniques from classical statistics and machine learning will be adopted. The general protocol accepted by our Ethical Committee can be downloaded from cancerdata.org. Results: A standardized knowledge sharing process has been implemented by using a semi-formal ontology for the representation of relevant clinical variables. Conclusion: The development of DSSs, based on standardized knowledge, could be a tool to achieve a personalized decision-making.

Aim: Identifying the best care for a patient can be extremely challenging. To support the creation of multifactorial Decision Support Systems (DSSs), we propose an Umbrella Protocol, focusing on prostate cancer. Materials & methods: The PRODIGE project consisted of a workflow for standardizing data, and procedures, to create a consistent dataset useful to elaborate DSSs. Techniques from classical statistics and machine learning will be adopted. The general protocol accepted by our Ethical Committee can be downloaded from cancerdata.org. Results: A standardized knowledge sharing process has been implemented by using a semi-formal ontology for the representation of relevant clinical variables. Conclusion: The development of DSSs, based on standardized knowledge, could be a tool to achieve a personalized decision-making.

From the whole plant of Euphorbia cyparissias, two new diterpenes based on jatrophane skeleton, named cyparissins A and B (1 and 2) were isolated. Their chemical structures were established through a combination of nuclear magnetic resonance spectroscopy and mass spectrometric methods. The new cyparissins A and B were tested to evaluate their ability to inhibit P-glycoprotein-mediated multidrug resistance and their cytotoxic activity against A2780 human ovarian cancer cells, both WT and ADR. Compounds 1 and 2 showed moderate inhibitory effects on P-glycoprotein while showing a significant concentration-depending cytotoxic activity for both cancer cell lines. These isolated compounds are based on a new chemical structure that expands the knowledge base for this class of bioactive metabolites.

Background: The complexity of modern oncology, based on multi-disciplinary management of cancer patients, results in critical amounts of data, leading to problems in managing and sharing information. Methods: Spider is a multi-user system, based on integrated palm technology, created to facilitate data recording, managing and sharing, through Intra-Internet connection. By palms or PCs, data are collected directly at the place where information is generated. Every health professional can edit, modify and display all of the patient's data according to his/her operational level. A powerful engine enables Spider's users to create series of cancer patients' appointments linked to one another by specified time intervals and save them as "Protocols". Applying a protocol to the patient, the system schedules a wave of appointments and alerts keeping the correlation with time intervals previously specified by specialists. XML technology is integrated with traditional RDBMS technology to build the Electronic Patient File (EPF) updated during each patient's admission or consultation, including any new diagnostic/therapeutic events and collective decisions. The system automatically produces all clinical documents routinely in use (discharge letters, exams' requests, etc.). Results: Spider's different archives include 4387 patients (Prostate, n=849; Lung, n=1596; Rectum, n=1541; Head & Neck, n=291; Cervix, n=110). The EPF includes specific modules: staging, surgery, chemotherapy, hormonotherapy, radiotherapy, toxicity, pathology, follow-up and clinical summary. Spider Hospitalization displays the ward map and important details of patients occupying each single bed. Conclusions: Spider makes data capture easier and accurate. The availability of large amounts of information accelerates outcome analysis and improves cancer research.