VATE: VAlidation of high TEchnology based on large database analysis by learning machine

Abstract

SummaryThe interaction between implementation of new technologies and different outcomes can allow a broad range of researches to be expanded. The purpose of this paper is to introduce the VAlidation of high TEchnology based on large database analysis by learning machine (VATE) project that aims to combine new technologies with outcomes related to rectal cancer in terms of tumor control and normal tissue sparing. Using automated computer bots and the knowledge for screening data it is possible to identify the factors that can mostly influence those outcomes. Population-based observational studies resulting from the linkage of different datasets will be conducted in order to develop predictive models that allow physicians to share decision with patients into a wider concept of tailored treatment. KeywordSOver the past decade, remarkable advances in cancer care with the adoption of newest diagnostic and treatment technologies has created new challenges [1].The use and role of medical imaging technologies in clinical oncology has greatly expanded from a primarily diagnostic tool to award a central role in the context of individualized medicine. Multiple imaging features involving descriptors of intensity distribution, spatial relationships between the various intensity levels, texture heterogeneity patterns, descriptors of shape and the relations of the tumor with the surrounding tissues have been analyzed for their relationship with treatment outcomes or Practice points• Progress in individualized medicine has created new challenges.• New technology implementation.• Necessity to develop systems that allow shared decision making by the physicians and the patients and chose a tailored treatment.• Standardization of the data collection -ontology.• Sharing data: Semantic Web and Resource Description Framework.• Statistical analysis.• Privacy protection of individual patients.• Development of predictive models based on individual patients features which complement existing consensus or guidelines.For reprint orders, please contact: reprints@futuremedicine.com

Prospective validation of pathologic complete response models in rectal cancer: Transferability and reproducibility

“…We would advise to validate prediction models on trial and routine clinical cohorts as also suggested by Booth and Tannock and proposed in the VATE project . The quality of cohorts from clinical trials are needed to identify which variables need to be reported in clinical practice.…”

Personalized Medicine in Prostate Cancer: Future Perspectives for Tailored Treatments

“…In fact, more advanced technologies have been adopted in clinical use in the last decade, such as image guided radiation therapy, different advanced dose modulation and delivery techniques, particle therapy, with a increasing attention to address resources in a reliable and cost-effective technologies [4]. Furthermore, radiotherapy is actually more a biological intervention rather than a physical, because of its effects on cellular and molecular level [7][8]; the heterogeneity of dose distribution in the irradiated and normal tissue should be considered [1]. In the past, in order to analyse the treatment effects in radiation oncology, several models were elaborated, to show the correlation between radiotherapy dose and outcomes, through different dose-reduction methods; the probit-based one (or the Lyman--Kutcher-Burman model) [9] and the logit-based one [10] are the most used dose-response models.…”

“…Collecting data, without knowing beforehand what the relevant features will be, implies a standardization of any variable to collect to universally define data and procedures allowing automatic and consistent upload from any data sources [1]. This process will take advantage of an ontology definition to describe data, both for being sure to share the same meanings between researchers and to allow automatic inference/reasoning from computers.…”

“…The key value of randomized clinical trials and consequent meta-analyses and reviews cannot be ignored, but some of their limits are the long follow up needed to obtain the established outcomes, the accrual of only homogeneous subgroups of population with determinate characteristics and also the lack of standardized assessments among the different studies, in terms of methodology, patients' characteristics, outcomes, data collection systems, etc. Emerging observational studies are crucial to confirm the trials results in the general population, more heterogeneous and with different characteristics, and also to identify whether practice has changed appropriately (Booth 2014); moreover, they could facilitate the identification of risks groups and, consequently, the choice of a better treatment for each patient; they could, also, stimulate research focused on specific risk groups [1].…”

“…Advances in Radiation Oncology and, in general, in modern medicine made more complex the "personalized medicine" process [1] "Personalized medicine" is defined by the National Cancer Institute as a "form of medicine that uses information about a person's genes, proteins, and environment to prevent, diagnose, and treat disease. In cancer, personalized medicine uses specific information about a person's tumour to help diagnose, plan treatment, find out how well treatment is working, or make a prognosis" [2].…”