ArticleCancer informatics2016
Thyroid Cancer and Tumor Collaborative Registry (TCCR).
Article in Cancer informatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Use of Natural Language Processing to Extract and Classify Papillary Thyroid Cancer Features From Surgical Pathology Reports.Endocrine practice : official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists · 2024Article
- Characterization of Immune Infiltrate Along the Leading Edge of Differentiated Thyroid Cancer.Thyroid : official journal of the American Thyroid Association · 2024Article
- Relaxin-2 is a novel biomarker for differentiated thyroid carcinoma in humans.Biochemical pharmacology · 2024Article
- The Korea Cancer Big Data Platform (K-CBP) for Cancer Research.International journal of environmental research and public health · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
A multicenter, web-based Thyroid Cancer and Tumor Collaborative Registry (TCCR, http://tccr.unmc.edu) allows for the collection and management of various data on thyroid cancer (TC) and thyroid nodule (TN) patients. The TCCR is coupled with OpenSpecimen, an open-source biobank management system, to annotate biospecimens obtained from the TCCR subjects. The demographic, lifestyle, physical activity, dietary habits, family history, medical history, and quality of life data are provided and may be entered into the registry by subjects. Information on diagnosis, treatment, and outcome is entered by the clinical personnel. The TCCR uses advanced technical and organizational practices, such as (i) metadata-driven software architecture (design); (ii) modern standards and best practices for data sharing and interoperability (standardization); (iii) Agile methodology (project management); (iv) Software as a Service (SaaS) as a software distribution model (operation); and (v) the confederation principle as a business model (governance). This allowed us to create a secure, reliable, user-friendly, and self-sustainable system for TC and TN data collection and management that is compatible with various end-user devices and easily adaptable to a rapidly changing environment. Currently, the TCCR contains data on 2,261 subjects and data on more than 28,000 biospecimens. Data and biological samples collected by the TCCR are used in developing diagnostic, prevention, treatment, and survivorship strategies against TC.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.