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Related Concept Videos

Cancer Survival Analysis01:21

Cancer Survival Analysis

Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
Treatment Resistant Cancers02:56

Treatment Resistant Cancers

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Clinical Trials: Overview01:11

Clinical Trials: Overview

Clinical development focuses on how the drug will interact with the human body and encompasses four key phases of clinical trials, each serving a specific purpose in assessing the safety and effectiveness of new drugs. These phases overlap and build upon one another. Phase I involves a small group of healthy volunteers (typically 20-80 individuals) or, in cases where significant toxicity is expected, patients with the targeted disease, such as cancer or AIDS. The volunteers are tested for...
Treatment Resistent Cancers02:56

Treatment Resistent Cancers

Cancer is the second leading cause of death in the United States. A cancer cell is genetically unstable and hence can mutate faster. They can also modify their microenvironment and escape immune surveillance. The difficulties in treating cancer are further compounded by the emergence of rapid resistance to anticancer drugs. The most common ways to attain resistance in cancer cells include alteration in drug transport and metabolism, modification of drug target, elevated DNA damage response, or...
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Related Experiment Video

Updated: May 8, 2026

Generation of Comprehensive Thoracic Oncology Database - Tool for Translational Research
11:18

Generation of Comprehensive Thoracic Oncology Database - Tool for Translational Research

Published on: January 22, 2011

Follow the data: tracking data quality and completeness in oncology real-world data.

Samantha J App1, Anne-Marie Meyer2,3,4, Shannon Silkensen2

  • 1Wake Forest School of Medicine, 9609 Medical Center Drive, Rockville, Maryland, MD, 20850, United States.

JAMIA Open
|May 7, 2026
PubMed
Summary

Electronic Health Record (EHR) biomarker data lose fidelity when transferred to cancer registries and FHIR extracts. This highlights critical gaps in data exchange methods for real-world data (RWD) research.

Keywords:
bioinformaticscancer biomarkersdata qualityelectronic health record

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Last Updated: May 8, 2026

Generation of Comprehensive Thoracic Oncology Database - Tool for Translational Research
11:18

Generation of Comprehensive Thoracic Oncology Database - Tool for Translational Research

Published on: January 22, 2011

Area of Science:

  • Oncology
  • Health Informatics
  • Biomedical Data Science

Background:

  • Electronic Health Record (EHR) data are vital for cancer research.
  • Data fidelity during EHR data exchange between systems is not well understood.
  • Accurate data is crucial for reliable real-world data (RWD) research.

Purpose of the Study:

  • To investigate the agreement of essential biomarker data.
  • To quantify data fidelity when EHR data is transferred to cancer registries and FHIR extracts.
  • To identify potential data loss in RWD extraction and exchange.

Main Methods:

  • Single-institution retrospective study.
  • Compared demographics and 6 biomarkers from 30 lung cancer patients (July 2020-July 2022).
  • Used manual EHR review as the gold standard; tested concordance with Institutional Cancer Registry and FHIR exports.

Main Results:

  • Demographics showed high concordance across databases.
  • Biomarker data from the source EHR were missing in 80%-100% of FHIR extracts.
  • Demographic registry variables were highly concordant.

Conclusions:

  • Significant loss of biomarker data availability across RWD sources.
  • Identified critical gaps in RWD extraction or exchange methods.
  • Emphasized the risks of relying on unvalidated RWD in cancer research.