Moddicom: a Complete and Easily Accessible Library for Prognostic Evaluations Relying on Image Features

Decision Support Systems (DSSs) are increasingly exploited in the area of prognostic evaluations. For predicting the effect of therapies on patients, the trend is now to use image features, i.e. information that can be automatically computed by considering images resulting by analysis. The DSSs application as predictive tools is particularly suitable for cancer treatment, given the peculiarities of the disease –which is highly localised and lead to significant social costs– and the large number of images that are available for each patient. At the state of the art, there exists tools that allow to handle image features for prognostic evaluations, but they are not designed for medical experts. They require either a strong engineering or computer science background since they do not integrate all the required functions, such as image retrieval and storage. In this paper we fill this gap by proposing Moddicom, a user-friendly complete library specifically designed to be exploited by physicians. A preliminary experimental analysis, performed by a medical expert that used the tool, demonstrates the efficiency and the effectiveness of Moddicom

RadioBio data: a Moddicom Module to Predict Tumor Control Probability and Normal Tissue Complication Probability in Radiotherapy

In this work a system for analysing radiotherapy treatment planning dose-volume data is proposed. The work starts from the definition of a framework inside a statistical scripting environment (R) used for creating a software package. The analysis of dose-volume data in radiotherapy of malignant tumours is mandatory for evaluating the prescribed treatment and for feedback analysis of outcome, both in the direction of tumour control and in detection of parameters for estimating and predicting toxicity outcome. The statistical analysis of large amount of clinical data can be slowed by the lack of practice in statistical tools needed, by clinicians, to perform such kind of analysis. This is the reason that lead our working group in the creation of such a tool. Finally an example of clinical application of our software is given for the analysis of the outcome of patients undergoing to radiotherapy for prostate cancer

Intensified Adjuvant Treatment of Prostate Carcinoma: Feasibility Analysis of a Phase I/II Trial

PURPOSE: To perform a preliminary feasibility acute and late toxicity evaluation of an intensified and modulated adjuvant treatment in prostate cancer (PCa) patients after radical prostatectomy. MATERIAL AND METHODS: A phase I/II has been designed. Eligible patients were 79 years old or younger, with an ECOG of 0-2, previously untreated, histologically proven prostate adenocarcinoma with no distant metastases, pT2-4 N0-1, and with at least one of the following risk factors: capsular perforation, positive surgical margins, and seminal vesicle invasion. All patients received a minimum dose on tumor bed of 64.8 Gy, or higher dose (70.2 Gy; 85.4%), according to the pathological stage, pelvic lymph nodes irradiation (57.7%), and/or hormonal therapy (69.1%). RESULTS: 123 patients were enrolled and completed the planned treatment, with good tolerance. Median follow-up was 50.6 months. Grade 3 acute toxicity was only 2.4% and 3.3% for genitourinary (GU) and gastrointestinal (GI) tract, respectively. No patient had late grade 3 GI toxicity, and the GU grade 3 toxicity incidence was 5.8% at 5 years. 5-year BDSF was 90.2%. CONCLUSIONS: A modulated and intensified adjuvant treatment in PCa was feasible in this trial. A further period of observation can provide a complete assessment of late toxicity and confirm the BDSF positive results

Standardized data collection to build prediction models in oncology: A prototype for rectal cancer

The advances in diagnostic and treatment technology are responsible for a remarkable transformation in the internal medicine concept with the establishment of a new idea of personalized medicine. Inter- and intra-patient tumor heterogeneity and the clinical outcome and/or treatment's toxicity's complexity, justify the effort to develop predictive models from decision support systems. However, the number of evaluated variables coming from multiple disciplines: oncology, computer science, bioinformatics, statistics, genomics, imaging, among others could be very large thus making traditional statistical analysis difficult to exploit. Automated data-mining processes and machine learning approaches can be a solution to organize the massive amount of data, trying to unravel important interaction. The purpose of this paper is to describe the strategy to collect and analyze data properly for decision support and introduce the concept of an 'umbrella protocol' within the framework of 'rapid learning healthcare'

Radiation therapy for prostate cancer: What's the best in 2021

Radiotherapy is highly involved in the management of prostate cancer. Its features and potential applications experienced a radical evolution over last decades, as they are associated to the continuous evolution of available technology and current oncological innovations. Some application of radiotherapy like brachytherapy have been recently enriched by innovative features and multidisciplinary dedications. In this report we aim to put some questions regarding the following issues regarding multiple aspects of modern application of radiation oncology: the current application of radiation oncology; the modern role of stereotactic body radiotherapy (SBRT) for both the management of primary lesions and for lymph-nodal recurrence; the management of the oligometastatic presentations; the role of brachytherapy; the aid played by the application of the organ at risk spacer (spacer OAR), fiducial markers, electromagnetic tracking systems and on-line Magnetic Resonance guided radiotherapy (MRgRT), and the role of the new opportunity represented by radiomic analysis

Concurrent and adjuvant temozolomide-based chemoradiotherapy schedules for glioblastoma. Hypotheses based on two prospective phase II trials

To investigate the impact of nonstandard concomitant temozolomide (TMZ) administration in two prospective phase\ua0II studies for glioblastoma (GBM)

Disease-specific and general health-related quality of life in newly diagnosed prostate cancer patients: The Pros-IT CNR study

BACKGROUND: The National Research Council (CNR) prostate cancer monitoring project in Italy (Pros-IT CNR) is an observational, prospective, ongoing, multicentre study aiming to monitor a sample of Italian males diagnosed as new cases of prostate cancer. The present study aims to present data on the quality of life at time prostate cancer is diagnosed. METHODS: One thousand seven hundred five patients were enrolled. Quality of life is evaluated at the time cancer was diagnosed and at subsequent assessments via the Italian version of the University of California Los Angeles-Prostate Cancer Index (UCLA-PCI) and the Short Form Health Survey (SF-12). RESULTS: At diagnosis, lower scores on the physical component of the SF-12 were associated to older ages, obesity and the presence of 3+ moderate/severe comorbidities. Lower scores on the mental component were associated to younger ages, the presence of 3+ moderate/severe comorbidities and a T-score higher than one. Urinary and bowel functions according to UCLA-PCI were generally good. Almost 5% of the sample reported using at least one safety pad daily to control urinary loss; less than 3% reported moderate/severe problems attributable to bowel functions, and sexual function was a moderate/severe problem for 26.7%. Diabetes, 3+ moderate/severe comorbidities, T2 or T3-T4 categories and a Gleason score of eight or more were significantly associated with lower sexual function scores at diagnosis. CONCLUSIONS: Data collected by the Pros-IT CNR study have clarified the baseline status of newly diagnosed prostate cancer patients. A comprehensive assessment of quality of life will allow to objectively evaluate outcomes of different profile of care

Disease-specific and general health-related quality of life in newly diagnosed prostate cancer patients: the Pros-IT CNR study

Background: The National Research Council (CNR) prostate cancer monitoring project in Italy (Pros-IT CNR) is an observational, prospective, ongoing, multicentre study aiming to monitor a sample of Italian males diagnosed as new cases of prostate cancer. The present study aims to present data on the quality of life at time prostate cancer is diagnosed. Methods: One thousand seven hundred five patients were enrolled. Quality of life is evaluated at the time cancer was diagnosed and at subsequent assessments via the Italian version of the University of California Los Angeles-Prostate Cancer Index (UCLA-PCI) and the Short Form Health Survey (SF-12). Results: At diagnosis, lower scores on the physical component of the SF-12 were associated to older ages, obesity and the presence of 3+ moderate/severe comorbidities. Lower scores on the mental component were associated to younger ages, the presence of 3+ moderate/severe comorbidities and a T-score higher than one. Urinary and bowel functions according to UCLA-PCI were generally good. Almost 5% of the sample reported using at least one safety pad daily to control urinary loss; less than 3% reported moderate/severe problems attributable to bowel functions, and sexual function was a moderate/severe problem for 26.7%. Diabetes, 3+ moderate/severe comorbidities, T2 or T3-T4 categories and a Gleason score of eight or more were significantly associated with lower sexual function scores at diagnosis. Conclusions: Data collected by the Pros-IT CNR study have clarified the baseline status of newly diagnosed prostate cancer patients. A comprehensive assessment of quality of life will allow to objectively evaluate outcomes of different profile of care

Pros-IT CNR: an Italian prostate cancer monitoring project

Aims: The Pros-IT CNR project aims to monitor a sample of Italian males \ue2\u89\ua518\uc2 years of age who have been diagnosed in the participating centers with incident prostate cancer, by analyzing their clinical features, treatment protocols and outcome results in relation to quality of life. Methods: Pros-IT CNR is an observational, prospective, multicenter study. The National Research Council (CNR), Neuroscience Institute, Aging Branch (Padua) is the promoting center. Ninety-seven Italian centers located throughout Italy were involved. The field study began in September 1, 2014. Subjects eligible were diagnosed with biopsy-verified prostate cancer, na\uc3\uafve. A sample size of 1500 patients was contemplated. A baseline assessment including anamnestic data, clinical history, risk factors, the initial diagnosis, cancer staging information and quality of life (Italian UCLA Prostate Cancer Index; SF-12 Scale) was completed. Six months after the initial diagnosis, a second assessment evaluating the patient\ue2\u80\u99s health status, the treatment carried out, and the quality of life will be made. A third assessment, evaluating the treatment follow-up and the quality of life, will be made 12\uc2 months after the initial diagnosis. The 4th, 5th, 6th and 7th assessments, similar to the third, will be completed 24, 36, 48 and 60\uc2 months after the initial diagnosis, respectively, and will include also a Food Frequency Questionnaire and the Physical Activity Scale for the Elderly. Discussion: The study will provide information on patients\ue2\u80\u99 quality of life and its variations over time in relation to the treatments received for the prostate cancer