ArticleThe Permanente journal2020
CRcoder: An Interactive Web Application and SAS Macro to Support Personalized Clinical Decisions.
Article in The Permanente journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Article
- A Joint Model for Disability, Self-Rated Health, and Mortality Among Medicare Beneficiaries-Differences by Chronic Disease and Race/Ethnicity.Journal of aging and health · 2024Article
- Importance of customized (task oriented) software tools for biomedical applications.Bioinformation · 2020Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
introductionElectronic health care data offer an opportunity to improve clinical decision making through advanced statistical analyses of longitudinal observations.
objectiveTo describe a Web application and SAS/STAT macro (SAS Institute Inc, Cary, NC) for computing joint models to estimate the typical and personalized risk of 2 concurrent binary outcomes.
methodsFeatures of the Web application design include uploading longitudinal files formatted with constant or time-varying covariates, specification of 2 binary outcomes, specification of a propensity model for treatment, and joint and separate models of the outcomes. In addition we designed an SAS macro for conducting the analysis. Fitting of joint and separate statistical models was implemented using a model specified in the Web application, with subsequent processing by the SAS macro. To illustrate the fitting of models, a sample of older adults with comorbid hypertension and chronic obstructive pulmonary disease from the Medical Expenditure Panel Survey was created to examine the association between polypharmacy (use of ≥ 5 medication classes) and limitations in social activities and mobility.
resultsRelative to separate models, the joint models typically estimated attenuated associations between explanatory variables and the 2 outcomes with smaller standard errors. These joint models yielded estimates of personalized concurrent risk and typical concurrent risk. DISCUSSION: Clinical decision making based on electronic health data can be improved using joint modeling to generate an individual's probability of concurrent risk.
conclusionThis user-friendly software performs the advanced statistical analyses needed to estimate typical and personalized concurrent risks.
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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.