ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2012
Selecting cases for whom additional tests can improve prognostication.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2012. 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
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
3 citing papers in PubMed.
- Computational advances in cancer informatics (a).Cancer informatics · 2014Article
- EXpectation Propagation LOgistic REgRession (EXPLORER): distributed privacy-preserving online model learning.Journal of biomedical informatics · 2013Article
- A review of approaches to identifying patient phenotype cohorts using electronic health records.Journal of the American Medical Informatics Association : JAMIAReview
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.
Funding
Abstract
Prognostic models are increasingly being used in clinical practice. The benefit of adding variables (e.g., gene expression measurements) to an original set of variables (e.g., phenotypes) when building prognostic models is usually measured on a whole set of cases. In practice, however, including additional information only helps build better models for some subsets of cases. It is important to prioritize who should undergo further testing. We present a method that can help identify those patients might benefit from additional testing. Our experiments based on limited breast cancer data indicate that relatively old patients with large tumors and positive lymph nodes constitute a group for whom prognoses can be more accurate with the addition of gene expression measurements. The same is not true for some other groups.
Indexed as
Identifiers
23304404PMC3540468What 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.