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Tamposis I, Tsougos I, Karatzas A, Vassiou K, Vlychou M, Tzortzis V. PCaGuard: A Software Platform to Support Optimal Management of Prostate Cancer. Appl Clin Inform 2022; 13:91-99. [PMID: 35045583 PMCID: PMC8769808 DOI: 10.1055/s-0041-1741481] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
Background and Objective
Prostate cancer (PCa) is a severe public health issue and the most common cancer worldwide in men. Early diagnosis can lead to early treatment and long-term survival. The addition of the multiparametric magnetic resonance imaging in combination with ultrasound (mpMRI-U/S fusion) biopsy to the existing diagnostic tools improved prostate cancer detection. Use of both tools gradually increases in every day urological practice. Furthermore, advances in the area of information technology and artificial intelligence have led to the development of software platforms able to support clinical diagnosis and decision-making using patient data from personalized medicine.
Methods
We investigated the current aspects of implementation, architecture, and design of a health care information system able to handle and store a large number of clinical examination data along with medical images, and produce a risk calculator in a seamless and secure manner complying with data security/accuracy and personal data protection directives and standards simultaneously. Furthermore, we took into account interoperability support and connectivity to legacy and other information management systems. The platform was implemented using open source, modern frameworks, and development tools.
Results
The application showed that software platforms supporting patient follow-up monitoring can be effective, productive, and of extreme value, while at the same time, aiding toward the betterment medicine clinical workflows. Furthermore, it removes access barriers and restrictions to specialized care, especially for rural areas, providing the exchange of medical images and patient data, among hospitals and physicians.
Conclusion
This platform handles data to estimate the risk of prostate cancer detection using current state-of-the-art in eHealth systems and services while fusing emerging multidisciplinary and intersectoral approaches. This work offers the research community an open architecture framework that encourages the broader adoption of more robust and comprehensive systems in standard clinical practice.
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Affiliation(s)
- Ioannis Tamposis
- Department of Computer Science and Biomedical Informatics, University of Thessaly, Lamia, Greece
| | - Ioannis Tsougos
- Department of Medical Physics, Medical School, University of Thessaly, Larisa, Greece
| | - Anastasios Karatzas
- Department of Urology, Medical School, University of Thessaly, Larisa, Greece
| | - Katerina Vassiou
- Radiology and Anatomy Department, Medical School, University of Thessaly, Larisa, Greece
| | - Marianna Vlychou
- Radiology Department, Medical School, University of Thessaly, Larisa, Greece
| | - Vasileios Tzortzis
- Department of Urology, Medical School, University of Thessaly, Larisa, Greece
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Mansmann U, Lindoerfer D. A Comprehensive Assessment Tool for Patient Registry Software Systems: The CIPROS Checklist. Methods Inf Med 2018; 54:447-54. [DOI: 10.3414/me14-02-0026] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2014] [Accepted: 07/24/2015] [Indexed: 12/21/2022]
Abstract
SummaryBackground: Patient registries are an important instrument in medical research. Often their structure is complex and their implementation uses composite software systems to meet the wide spectrum of challenges.Objectives: For the implementation of a registry, there is a wide range of commercial, open source, and self-developed systems available and a minimal standard for the critical appraisal of their architecture is needed.Methods: We performed a systematic review of the literature to define a catalogue of relevant criteria to construct a minimal appraisal standard.Results: The CIPROS list is developed based on 64 papers which were found by our systematic review. The list covers twelve sections and contains 72 items.Conclusions: The CIPROS list supports developers to assess requirements on existing systems and strengthens the reporting of patient registry software system descriptions. It can be a first step to create standards for patient registry software system assessments.
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Shats O, Goldner W, Feng J, Sherman A, Smith RB, Sherman S. Thyroid Cancer and Tumor Collaborative Registry (TCCR). Cancer Inform 2016; 15:73-9. [PMID: 27168721 PMCID: PMC4856228 DOI: 10.4137/cin.s32470] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2015] [Revised: 03/08/2016] [Accepted: 03/20/2016] [Indexed: 12/14/2022] Open
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.
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Affiliation(s)
- Oleg Shats
- Eppley Institute for Research in Cancer, University of Nebraska Medical Center, Omaha, NE, USA.; Progenomix, Inc., Omaha, NE, USA
| | - Whitney Goldner
- College of Medicine, University of Nebraska Medical Center, Omaha, NE, USA
| | - Jianmin Feng
- Eppley Institute for Research in Cancer, University of Nebraska Medical Center, Omaha, NE, USA
| | - Alexander Sherman
- Eppley Institute for Research in Cancer, University of Nebraska Medical Center, Omaha, NE, USA
| | - Russell B Smith
- College of Medicine, University of Nebraska Medical Center, Omaha, NE, USA.; Nebraska Methodist Hospital, Omaha, NE, USA
| | - Simon Sherman
- Eppley Institute for Research in Cancer, University of Nebraska Medical Center, Omaha, NE, USA.; Progenomix, Inc., Omaha, NE, USA
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Abstract
OBJECTIVE The aim of this paper is to report on the use of the systematised nomenclature of medicine clinical terms (SNOMED CT) by providing an overview of published papers. METHODS Published papers on SNOMED CT between 2001 and 2012 were identified using PubMed and Embase databases using the keywords 'systematised nomenclature of medicine' and 'SNOMED CT'. For each paper the following characteristics were retrieved: SNOMED CT focus category (ie, indeterminate, theoretical, pre-development/design, implementation and evaluation/commodity), usage category (eg, prospective content coverage, used to classify or code in a study), medical domain and country. RESULTS Our search strategy identified 488 papers. A comparison between the papers published between 2001-6 and 2007-12 showed an increase in every SNOMED CT focus category. The number of papers classified as 'theoretical' increased from 46 to 78, 'pre-development/design' increased from 61 to 173 and 'implementation' increased from 10 to 34. Papers classified as 'evaluation/commodity' only started to appear from 2010. CONCLUSIONS The majority of studies focused on 'theoretical' and 'pre-development/design'. This is still encouraging as SNOMED CT is being harmonized with other standardized terminologies and is being evaluated to determine the content coverage of local terms, which is usually one of the first steps towards adoption. Most implementations are not published in the scientific literature, requiring a look beyond the scientific literature to gain insights into SNOMED CT implementations.
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Affiliation(s)
- Dennis Lee
- School of Health Information Science, University of Victoria, Victoria, British Columbia, Canada
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Anderson MA, Zolotarevsky E, Cooper KL, Sherman S, Shats O, Whitcomb DC, Lynch HT, Ghiorzo P, Rubinstein WS, Vogel KJ, Sasson AR, Grizzle WE, Ketcham MA, Lee SY, Normolle D, Plonka CM, Mertens AN, Tripon RC, Brand RE. Alcohol and tobacco lower the age of presentation in sporadic pancreatic cancer in a dose-dependent manner: a multicenter study. Am J Gastroenterol 2012; 107:1730-9. [PMID: 22929760 PMCID: PMC3923585 DOI: 10.1038/ajg.2012.288] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
OBJECTIVES The objective of this study was to examine the association between tobacco and alcohol dose and type and the age of onset of pancreatic adenocarcinoma (PancCa). METHODS Prospective data from the Pancreatic Cancer Collaborative Registry were used to examine the association between age of onset and variables of interest including: gender, race, birth country, educational status, family history of PancCa, diabetes status, and tobacco and alcohol use. Statistical analysis included logistic and linear regression, Cox proportional hazard regression, and time-to-event analysis. RESULTS The median age to diagnosis for PancCa was 66.3 years (95% confidence intervals (CIs), 64.5-68.0). Males were more likely than females to be smokers (77% vs. 69%, P=0.0002) and heavy alcohol and beer consumers (19% vs. 6%, 34% vs. 19%, P<0.0001). In univariate analysis for effects on PancCa presentation age, the following were significant: gender, alcohol and tobacco use (amount, status and type), family history of PancCa, and body mass index. Both alcohol and tobacco had dose-dependent effects. In multivariate analysis, alcohol status and dose were independently associated with increased risk for earlier PancCa onset with greatest risk occurring in heavy drinkers (HR 1.62, 95% CI 1.04-2.54). Smoking status had the highest risk for earlier onset pancreatic cancer with a HR of 2.69 (95% CI, 1.97-3.68) for active smokers and independent effects for dose (P=0.019). The deleterious effects for alcohol and tobacco appear to resolve after 10 years of abstinence. CONCLUSIONS Alcohol and tobacco use are associated with a dose-related increased risk for earlier age of onset of PancCa. Although beer drinkers develop pancreatic cancer at an earlier age than nondrinkers, alcohol type did not have a significant effect after controlling for alcohol dose.
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Affiliation(s)
- Michelle A. Anderson
- Division of Gastroenterology, Department of Internal
Medicine, University of Michigan Health System, Ann Arbor, Michigan, USA
| | - Eugene Zolotarevsky
- Division of Gastroenterology, Department of Internal
Medicine, University of Michigan Health System, Ann Arbor, Michigan, USA
| | - Kristine L. Cooper
- Department of Biostatistics, University of Pittsburgh,
Pittsburgh, Pennsylvania, USA
| | - Simon Sherman
- Eppley Institute for Research in Cancer, University of
Nebraska Medical Center, Omaha, Nebraska, USA
| | - Oleg Shats
- Eppley Institute for Research in Cancer, University of
Nebraska Medical Center, Omaha, Nebraska, USA
| | - David C. Whitcomb
- Division of Gastroenterology, University of Pittsburgh
Medical Center, Pittsburgh, Pennsylvania, USA
| | - Henry T. Lynch
- Department of Preventive Medicine, Creighton University
School Medicine, Omaha, Nebraska, USA
| | - Paola Ghiorzo
- Department of Internal Medicine and Medical Specialties,
University of Genoa, Genoa, Italy
| | - Wendy S. Rubinstein
- Department of Medicine, Northshore University Health
Systems, Evanston, Illinois, USA,University of Chicago Pritzker School of Medicine, Chicago,
Illinois, USA
| | - Kristen J. Vogel
- Department of Medicine, Northshore University Health
Systems, Evanston, Illinois, USA
| | - Aaron R. Sasson
- Department of Surgery, University of Nebraska Medical
Center, Omaha, Nebraska, USA
| | - William E. Grizzle
- Department of Pathology, University of Alabama at
Birmingham, Birmingham, Alabama, USA
| | - Marsha A. Ketcham
- Eppley Institute for Research in Cancer, University of
Nebraska Medical Center, Omaha, Nebraska, USA
| | - Shih-Yuan Lee
- Department of Biostatistics, University of Michigan
School of Public Health, Ann Arbor, Michigan, USA
| | - Daniel Normolle
- Department of Biostatistics, University of Pittsburgh
Medical Center, Pittsburgh, Pennsylvania, USA
| | - Caitlyn M. Plonka
- Division of Gastroenterology, Department of Internal
Medicine, University of Michigan Health System, Ann Arbor, Michigan, USA
| | - Amy N. Mertens
- Division of Gastroenterology, Department of Internal
Medicine, University of Michigan Health System, Ann Arbor, Michigan, USA
| | - Renee C. Tripon
- Division of Gastroenterology, Department of Internal
Medicine, University of Michigan Health System, Ann Arbor, Michigan, USA
| | - Randall E. Brand
- Division of Gastroenterology, University of Pittsburgh
Medical Center, Pittsburgh, Pennsylvania, USA
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Wang H, Yatawara M, Huang SC, Dudley K, Szekely C, Holden S, Piantadosi S. The integrated proactive surveillance system for prostate cancer. Open Med Inform J 2012; 6:1-8. [PMID: 22505956 PMCID: PMC3322433 DOI: 10.2174/1874431101206010001] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2011] [Revised: 01/31/2012] [Accepted: 02/16/2012] [Indexed: 12/23/2022] Open
Abstract
In this paper, we present the design and implementation of the integrated proactive surveillance system for prostate cancer (PASS-PC). The integrated PASS-PC is a multi-institutional web-based system aimed at collecting a variety of data on prostate cancer patients in a standardized and efficient way. The integrated PASS-PC was commissioned by the Prostate Cancer Foundation (PCF) and built through the joint of efforts by a group of experts in medical oncology, genetics, pathology, nutrition, and cancer research informatics. Their main goal is facilitating the efficient and uniform collection of critical demographic, lifestyle, nutritional, dietary and clinical information to be used in developing new strategies in diagnosing, preventing and treating prostate cancer.The integrated PASS-PC is designed based on common industry standards - a three tiered architecture and a Service- Oriented Architecture (SOA). It utilizes open source software and programming languages such as HTML, PHP, CSS, JQuery, Drupal and MySQL. We also use a commercial database management system - Oracle 11g. The integrated PASS-PC project uses a "confederation model" that encourages participation of any interested center, irrespective of its size or location. The integrated PASS-PC utilizes a standardized approach to data collection and reporting, and uses extensive validation procedures to prevent entering erroneous data. The integrated PASS-PC controlled vocabulary is harmonized with the National Cancer Institute (NCI) Thesaurus. Currently, two cancer centers in the USA are participating in the integrated PASS-PC project.THE FINAL SYSTEM HAS THREE MAIN COMPONENTS: 1. National Prostate Surveillance Network (NPSN) website; 2. NPSN myConnect portal; 3. Proactive Surveillance System for Prostate Cancer (PASS-PC). PASS-PC is a cancer Biomedical Informatics Grid (caBIG) compatible product. The integrated PASS-PC provides a foundation for collaborative prostate cancer research. It has been built to meet the short term goal of gathering prostate cancer related data, but also with the prerequisites in place for future evolution into a cancer research informatics platform. In the future this will be vital for successful prostate cancer studies, care and treatment.
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Affiliation(s)
- Haibin Wang
- Research Informatics Core, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los
Angeles, CA 90048, USA
| | - Mahendra Yatawara
- Research Informatics Core, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los
Angeles, CA 90048, USA
| | - Shao-Chi Huang
- Research Informatics Core, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los
Angeles, CA 90048, USA
| | - Kevin Dudley
- Research Informatics Core, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los
Angeles, CA 90048, USA
| | - Christine Szekely
- Clinical Research Office, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles,
CA 90048, USA
| | - Stuart Holden
- Louis Warschaw Prostate Cancer Center, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Steven Piantadosi
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
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Sherman S, Shats O, Fleissner E, Bascom G, Yiee K, Copur M, Crow K, Rooney J, Mateen Z, Ketcham MA, Feng J, Sherman A, Gleason M, Kinarsky L, Silva-Lopez E, Edney J, Reed E, Berger A, Cowan K. Multicenter breast cancer collaborative registry. Cancer Inform 2011; 10:217-26. [PMID: 21918596 PMCID: PMC3169352 DOI: 10.4137/cin.s7845] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
The Breast Cancer Collaborative Registry (BCCR) is a multicenter web-based system that efficiently collects and manages a variety of data on breast cancer (BC) patients and BC survivors. This registry is designed as a multi-tier web application that utilizes Java Servlet/JSP technology and has an Oracle 11g database as a back-end. The BCCR questionnaire has accommodated standards accepted in breast cancer research and healthcare. By harmonizing the controlled vocabulary with the NCI Thesaurus (NCIt) or Systematized Nomenclature of Medicine-Clinical Terms (SNOMED-CT), the BCCR provides a standardized approach to data collection and reporting. The BCCR has been recently certified by the National Cancer Institute’s Center for Biomedical Informatics and Information Technology (NCI CBIIT) as a cancer Biomedical Informatics Grid (caBIG®) Bronze Compatible product. The BCCR is aimed at facilitating rapid and uniform collection of critical information and biological samples to be used in developing diagnostic, prevention, treatment, and survivorship strategies against breast cancer. Currently, seven cancer institutions are participating in the BCCR that contains data on almost 900 subjects (BC patients and survivors, as well as individuals at high risk of getting BC).
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Affiliation(s)
- Simon Sherman
- Eppley Institute for Research in Cancer, University of Nebraska Medical Center, Omaha, NE, USA
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