ArticlePragmatic and observational research2017
A validation of clinical data captured from a novel Cancer Care Quality Program directly integrated with administrative claims data.
Article in Pragmatic and observational research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
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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
14 citing papers in PubMed, 19 citations in OpenAlex.
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- A real-world study on characteristics, treatments and outcomes in US patients with advanced stage ovarian cancer.Journal of ovarian research · 2020Article
- Common data elements of breast cancer for research databases: A systematic review.Journal of family medicine and primary care · 2020Review
- Cancer care and public health policy evaluations in France: Usefulness of the national cancer cohort.PloS one · 2018Article
- Real-World Treatment Sequences and Outcomes Among Patients With Non-Small Cell Lung Cancer (RESOUNDS) in the United States: Study Protocol.JMIR research protocols · 2017Article
- Validation of a Case-Finding Algorithm for Identifying Patients with Non-small Cell Lung Cancer (NSCLC) in Administrative Claims Databases.Frontiers in pharmacology · 2017Article
- Comparative Analysis of First-Line FOLFOX Treatment With and Without Anti-VEGF Therapy in Metastatic Colorectal Carcinoma: A Real-World Data Study.Cancer control : journal of the Moffitt Cancer CenterArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 5 institutions in 2 countries.
Funding
Abstract
backgroundData from a Cancer Care Quality Program are directly integrated with administrative claims data to provide a level of clinical detail not available in claims-based studies, and referred to as the HealthCore Integrated Research Environment (HIRE)-Oncology data. This study evaluated the validity of the HIRE-Oncology data compared with medical records of breast, lung, and colorectal cancer patients.
methodsData elements included cancer type, stage, histology (lung only), and biomarkers. A sample of 300 breast, 200 lung, and 200 colorectal cancer patients within the HIRE-Oncology data were identified for medical record review. Statistical measures of validity (agreement, positive predictive value [PPV], negative predictive value [NPV], sensitivity, specificity) were used to compare clinical information between data sources, with medical record data considered the gold standard.
resultsAll 300 breast cancer records reviewed were confirmed breast cancer, while 197 lung and 197 colorectal records were confirmed (PPV =0.99 for each). The agreement of disease stage was 85% for breast, 90% for lung, and 94% for colorectal cancer. The agreement of lung cancer histology (small cell vs non-small cell) was 97%. Agreement of progesterone receptor, estrogen receptor, and human epidermal growth factor receptor 2 status biomarkers in breast cancer was 92%, 97%, and 92%, respectively; epidermal growth factor receptor and anaplastic lymphoma kinase agreement in lung was 97% and 92%, respectively; and agreement of KRAS status in colorectal cancer was 95%. Measures of PPV, NPV, sensitivity, and specificity showed similarly strong evidence of validity.
conclusionGood agreement between the HIRE-Oncology data and medical records supports the validity of these data for research.
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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.