ArticleJCO clinical cancer informatics2022
Cancer Registry Data Linkage of Electronic Health Record Data From ASCO's CancerLinQ: Evaluation of Advantages, Limitations, and Lessons Learned.
Article in JCO clinical cancer informatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed.
- Establishing cancer registries in Africa - focus on hepatopancreatobiliary cancers.Nature reviews. Gastroenterology & hepatology · 2026Review
- "Assessment of an EMR-integrated Onco-Insight hospital-based cancer registry system for data completeness and data entry turnaround time at a tertiary care cancer center in India".Frontiers in oncology · 2026Article
- Novel Electronic Health Record-Based Data Commons for Pancreatic Cancer.JCO clinical cancer informatics · 2026Article
- Challenges in analyzing real-world evidence: analysis of androgen deprivation therapy use for prostate cancer in the REASSURE study.ESMO real world data and digital oncology · 2025Review
- Implementing Cancer Registry Data With the PCORnet Common Data Model: The Greater Plains Collaborative Experience.JCO clinical cancer informatics · 2024Article
- Extracting Electronic Health Record Neuroblastoma Treatment Data With High Fidelity Using the REDCap Clinical Data Interoperability Services Module.JCO clinical cancer informatics · 2024Article
- Machine learning to predict distant metastasis and prognostic analysis of moderately differentiated gastric adenocarcinoma patients: a novel focus on lymph node indicators.Frontiers in immunology · 2024Article
- Engaging European society at the forefront of cancer research and care: How discussions at the 5Molecular oncology · 2023Article
- Assessing Completeness of Cancer Treatment Data from an Academic Medical Center's Tumor Registry Through Comparison to the Central Registry.Journal of registry management · 2023Article
- Enhancing Administrative Claims Data: Feasibility, Validation and Application of Linking Medicare Claims Data and National Marrow Donor Program Search Data.JCO clinical cancer informatics · 2022Article
- Cardiovascular adverse events in oncology trials: understanding and appreciating the differences between clinical trial data and real-world reports.Cardio-oncology (London, England) · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
purposeTo evaluate the completeness of information for research and quality assessment through a linkage between cancer registry data and electronic health record (EHR) data refined by ASCO's health technology platform CancerLinQ.
methodsA probabilistic data linkage between Iowa Cancer Registry (ICR) and an Iowa oncology clinic through CancerLinQ data was conducted for cases diagnosed between 2009 and 2018. Demographic, cancer, and treatment variables were compared between data sources for the same patients, all of whom were diagnosed with one primary cancer. Treatment data and compliance with quality measures were compared among those with breast or prostate cancer; SEER-Medicare data served as a comparison. Variables captured only in CancerLinQ data (smoking, pain, and height/weight) were evaluated for completeness.
resultsThere were 6,175 patients whose data were linked between ICR and CancerLinQ data sets. Of those, 4,291 (70%) were diagnosed with one primary cancer and were included in analyses. Demographic variables were comparable between data sets. Proportions of people receiving hormone therapy (30%
conclusionLinking CancerLinQ EHR data with cancer registry data led to more complete data for each source respectively, as registry data provides definitive diagnosis and more complete stage information and laboratory results, whereas EHR data provide more detailed treatment data and additional variables not captured by registries.
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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.