Ent cobra ontology: the covariates classification system proposed by the Head & Neck and Skin GEC-ESTRO Working Group for interdisciplinary standardized data collection in head and neck patient cohorts treated with interventional radiotherapy (brachytherapy)

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 (\u201cbroker\u201d) 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 (L\ufcbeck, 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. This approach is well-received by all involved parties, primarily because it does not change a single center\u2019s storing technologies, procedures, and habits

Dynamic Contrast-Enhanced MRI Parameters as Biomarkers in Assessing Head and Neck Lesions After Chemoradiotherapy Using a Wide-Bore 3 Tesla Scanner

Pilot studies have shown promising results in characterizing head and neck tumors (HNT) using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), differentiating between malignant and benign lesions and evaluating changes in response to chemoradiotherapy (CRT). Our aim was to find DCE-MRI parameters, biomarkers in evaluating the post-CRT status. Two hundred and five patients with head and neck lesions were examined with DCE-MRI sequences. The time intensity curves (TIC) were extracted and processed to acquire time-to-peak (TTP), relative maximum enhancement (RME), relative wash-out (RWO), and two new parameters attack and decay. These parameters were analyzed using univariate tests in SPSS (Statistical Package for the Social Sciences, version 17, SPSS Inc. Chicago, USA) to identify parameters that could be used to infer tumor malignancy and post-CRT changes. Multiple parameters of curve characteristics were significantly different between malignant tumors after CRT (MACRT) and changes caused by CRT. The best-performing biomarkers were the attack and the decay. We also found multiple significant (p < 0.05) parameters for both the benign and malignant status as well as pre- and post-CRT status. Our large cohort of data supports the increasing role of DCE-MRI in HNT differentiation, particularly for the assessment of post-CRT status along with accurate morphological imaging

Effect of low-dose and standard-dose aspirin on PGE2 biosynthesis among individuals with colorectal adenomas: A randomized clinical trial

Low-dose aspirin is recommended by the U.S. Preventive Services Task Force for primary prevention of colorectal cancer in certain individuals. However, broader implementation will require improved precision prevention approaches to identify those most likely to benefit. The major urinary metabolite of PGE2, 11a-hydroxy-9,15-dioxo-2,3,4,5-tetranor-prostane-1,20-dioic acid (PGE-M), is a biomarker for colorectal cancer risk, but it is unknown whether PGE-M is modifiable by aspirin in individuals at risk for colorectal cancer. Adults (N \ubc 180) who recently underwent adenoma resection and did not regularly use aspirin or NSAIDs were recruited to a double-blind, placebo-controlled, randomized trial of aspirin at 81 or 325 mg/day for 8\u201312 weeks. The primary outcome was postintervention change in urinary PGE-M as measured by LC/MS. A total of 169 participants provided paired urine samples for analysis. Baseline PGE-M excretion was 15.9 = 14.6 (mean = S.D, ng/mg creatinine). Aspirin significantly reduced PGE-M excretion (=4.7 = 14.8) compared with no decrease (0.8 = 11.8) in the placebo group (P \ubc 0.015; mean duration of treatment \ubc 68.9 days). Aspirin significantly reduced PGE-M levels in participants receiving either 81 (-15%; P \ubc 0.018) or 325 mg/day (-28%; P &lt; 0.0001) compared with placebo. In 40% and 50% of the individuals randomized to 81 or 325 mg/day aspirin, respectively, PGE-M reduction reached a threshold expected to prevent recurrence in 10% of individuals. These results support that aspirin significantly reduces elevated levels of PGE-M in those at increased colorectal cancer risk to levels consistent with lower risk for recurrent neoplasia and underscore the potential utility of PGE-M as a precision chemoprevention biomarker. The ASPIRED trial is registered as NCT02394769