ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2014
A method for analyzing commonalities in clinical trial target populations.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 2 of them syntheses that pooled it.
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
16 citing papers in PubMed, 2 syntheses or guidelines pooled it, 19 citations in OpenAlex.
- Natural language processing systems for capturing and standardizing unstructured clinical information: A systematic review.Journal of biomedical informatics · 2017Pooled it
- Comparative Analysis of Geriatric and Adult Drug Clinical Trials on ClinicalTrials.gov.Studies in health technology and informatics · 2017Pooled it
- Automated classification of clinical trial eligibility criteria text based on ensemble learning and metric learning.BMC medical informatics and decision making · 2021Article
- A knowledge base of clinical trial eligibility criteria.Journal of biomedical informatics · 2021Article
- An Ensemble Learning Strategy for Eligibility Criteria Text Classification for Clinical Trial Recruitment: Algorithm Development and Validation.JMIR medical informatics · 2020Article
- Comparing the Study Populations in Dietary Supplement and Drug Clinical Trials for Metabolic Syndrome and Related Disorders.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2019Article
- Learning disease relationships from clinical drug trials.Journal of the American Medical Informatics Association : JAMIA · 2017Article
- Comparing and Contrasting A Priori and A Posteriori Generalizability Assessment of Clinical Trials on Type 2 Diabetes Mellitus.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2017Article
- Analysis of Temporal Constraints in Qualitative Eligibility Criteria of Cancer Clinical Studies.Proceedings. IEEE International Conference on Bioinformatics and Biomedicine · 2016Article
- Automatic classification of registered clinical trials towards the Global Burden of Diseases taxonomy of diseases and injuries.BMC bioinformatics · 2016Article
- Assessing the population representativeness of colorectal cancer treatment clinical trials.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2016Article
- Multivariate analysis of the population representativeness of related clinical studies.Journal of biomedical informatics · 2016Article
- Visual aggregate analysis of eligibility features of clinical trials.Journal of biomedical informatics · 2015Article
- Simulation-based Evaluation of the Generalizability Index for Study Traits.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2015Article
- Assessing the Collective Population Representativeness of Related Type 2 Diabetes Trials by Combining Public Data from ClinicalTrials.gov and NHANES.Studies in health technology and informatics · 2015Article
- Predicting New Target Conditions for Drug Retesting Using Temporal Patterns in Clinical Trials: A Proof of Concept.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
ClinicalTrials.gov presents great opportunities for analyzing commonalities in clinical trial target populations to facilitate knowledge reuse when designing eligibility criteria of future trials or to reveal potential systematic biases in selecting population subgroups for clinical research. Towards this goal, this paper presents a novel data resource for enabling such analyses. Our method includes two parts: (1) parsing and indexing eligibility criteria text; and (2) mining common eligibility features and attributes of common numeric features (e.g., A1c). We designed and built a database called "Commonalities in Target Populations of Clinical Trials" (COMPACT), which stores structured eligibility criteria and trial metadata in a readily computable format. We illustrate its use in an example analytic module called CONECT using COMPACT as the backend. Type 2 diabetes is used as an example to analyze commonalities in the target populations of 4,493 clinical trials on this disease.
Indexed as
Identifiers
25954450PMC4419878W2395308602What OpenQuestion holds
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.