ReviewProceedings (Baylor University. Medical Center)2020
Clinical entities, phenotypes, causation, and endotypes based on selected asthma publications.
Review in Proceedings (Baylor University. Medical Center), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed, 6 citations in OpenAlex.
- Modeling the enigma of complex disease etiology.Journal of translational medicine · 2023Article
- Clinical implications of asthma endotypes and phenotypes.Allergy and asthma proceedings · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Patients with complex chronic disorders, such as asthma, present clinicians with important management problems. The identification of a clinical syndrome usually leads to the diagnosis of the disease entity. The next concern involves classification and a choice as to whether to use a few inclusive categories or multiple exclusive categories. Patients with asthma have multiple clinical syndromes, and these can be described as phenotypes. The use of cluster analysis allows investigators to identify phenotypes with less clinical bias. However, the identification of a particular phenotype does not necessarily provide much insight into the underlying pathogenesis. In asthma, the pathogenetic events are complex and multiple and require a classification based on endotypes. This difficulty introduces the idea of causation and models for causation. Asthma probably does not have a single universal necessary cause. However, it does have multiple sufficient component causes. Understanding these components and their interactions potentially leads to better treatment trials and more focused drug therapy. Clinicians need to identify asthmatic patients and classify them into particular phenotypes; they should also wonder about causation. Clinical investigators need to use these phenotypes to identify more homogenous groups of patients to study the underlying pathogenesis and establish endotypes. Focusing on causation can improve our understanding of disease entities, disease classification, and disease causation. This review outlines ideas relevant to causation in nearly all diseases.
Indexed as
Identifiers
What 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.