ArticlePloS one2015
Merging Children's Oncology Group Data with an External Administrative Database Using Indirect Patient Identifiers: A Report from the Children's Oncology Group.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed, 18 citations in OpenAlex.
- Late health outcomes after dexrazoxane treatment: A report from the Children's Oncology Group.Cancer · 2022Trial
- Changes in Gut Microbial Diversity and Correlation with Clinical Outcome in Children with Acute Myeloid Leukemia Receiving Induction Chemotherapy.Children (Basel, Switzerland) · 2025Article
- Article
- Leveraging machine learning to identify acute myeloid leukemia patients and their chemotherapy regimens in an administrative database.Pediatric blood & cancer · 2023Article
- Leveraging Clinical Trial Populations and Data from the Children's Oncology Group for Cancer Survivorship Research.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2022Article
- The Impact of Donor Type on Outcomes and Cost of Allogeneic Hematopoietic Cell Transplantation for Pediatric Leukemia: A Merged Center for International Blood and Marrow Transplant Research and Pediatric Health Information System Analysis.Biology of blood and marrow transplantation : journal of the American Society for Blood and Marrow Transplantation · 2020Article
- Assessing data linkage quality in cohort studies.Annals of human biology · 2020Article
- Expanding analytic possibilities in pediatric solid organ transplantation through linkage of administrative and clinical registry databases.Pediatric transplantation · 2019Article
- Resource Utilization in Pediatric Patients Supported With Ventricular Assist Devices in the United States: A Multicenter Study From the Pediatric Interagency Registry for Mechanically Assisted Circulatory Support and the Pediatric Health Information System.Journal of the American Heart Association · 2018Article
- An overview of disparities in childhood cancer: Report on the Inaugural Symposium on Childhood Cancer Health Disparities, Houston, Texas, 2016.Pediatric hematology and oncology · 2018Article
- A unique linkage of administrative and clinical registry databases to expand analytic possibilities in pediatric heart transplantation research.American heart journal · 2017Article
- Clinical risks and healthcare utilization of hematopoietic cell transplantation for sickle cell disease in the USA using merged databases.Haematologica · 2017Article
Corrections and comments
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Authors and funding
13 authors at 6 institutions in 2 countries.
Funding
Abstract
purposeClinical trials data from National Cancer Institute (NCI)-funded cooperative oncology group trials could be enhanced by merging with external data sources. Merging without direct patient identifiers would provide additional patient privacy protections. We sought to develop and validate a matching algorithm that uses only indirect patient identifiers.
methodsWe merged the data from two Phase III Children's Oncology Group (COG) trials for de novo acute myeloid leukemia (AML) with the Pediatric Health Information Systems (PHIS). We developed a stepwise matching algorithm that used indirect identifiers including treatment site, gender, birth year, birth month, enrollment year and enrollment month. Results from the stepwise algorithm were compared against the direct merge method that used date of birth, treatment site, and gender. The indirect merge algorithm was developed on AAML0531 and validated on AAML1031.
resultsOf 415 patients enrolled on the AAML0531 trial at PHIS centers, we successfully matched 378 (91.1%) patients using the indirect stepwise algorithm. Comparison to the direct merge result suggested that 362 (95.7%) matches identified by the indirect merge algorithm were concordant with the direct merge result. When validating the indirect stepwise algorithm using the AAML1031 trial, we successfully matched 157 out of 165 patients (95.2%) and 150 (95.5%) of the indirectly merged matches were concordant with the directly merged matches.
conclusionsThese data demonstrate that patients enrolled on COG clinical trials can be successfully merged with PHIS administrative data using a stepwise algorithm based on indirect patient identifiers. The merged data sets can be used as a platform for comparative effectiveness and cost effectiveness studies.
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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.