Evidence map›Paper›PMID 24676019›Full record

ArticlePloS one2014

Quantitative stratification of diffuse parenchymal lung diseases.

Sushravya Raghunath, Srinivasan Rajagopalan, Ronald A Karwoski, Fabien Maldonado, Tobias Peikert, Teng Moua, Jay H Ryu, Brian J Bartholmai, Richard A Robb

Abstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Article
  6. Advances in imaging for lung emphysema.Annals of translational medicine · 2020
    Review
  7. Review
  8. Article
  9. Review
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Unsupervised Discovery of Emphysema Subtypes in a Large Clinical Cohort.Machine learning in medical imaging. MLMI (Workshop) · 2016
    Article
  17. Article
  18. Review
  19. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Sushravya RaghunathDepartment of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, Minnesota, United States of America.
Srinivasan RajagopalanDepartment of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, Minnesota, United States of America.
Ronald A KarwoskiDepartment of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, Minnesota, United States of America.
Fabien MaldonadoDivision of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, Minnesota, United States of America.
Tobias PeikertDivision of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, Minnesota, United States of America.
Teng MouaDivision of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, Minnesota, United States of America.
Jay H RyuDivision of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, Minnesota, United States of America.
Brian J BartholmaiDepartment of Radiology, Mayo Clinic, Rochester, Minnesota, United States of America.
Richard A RobbDepartment of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, Minnesota, United States of America.

Funding

Anti-Tumor Immunity in Response to a Modified Vaccine Strain Measles VirusK23CA159391 · NCI · MAYO CLINIC ROCHESTER · PI PEIKERT, TOBIAS · 2012 to 2015
$657k
NCI NIH HHS K23 CA159391NHLBI NIH HHS HHSN268201100022C
6 · The paper itself

Abstract

Diffuse parenchymal lung diseases (DPLDs) are characterized by widespread pathological changes within the pulmonary tissue that impair the elasticity and gas exchange properties of the lungs. Clinical-radiological diagnosis of these diseases remains challenging and their clinical course is characterized by variable disease progression. These challenges have hindered the introduction of robust objective biomarkers for patient-specific prediction based on specific phenotypes in clinical practice for patients with DPLD. Therefore, strategies facilitating individualized clinical management, staging and identification of specific phenotypes linked to clinical disease outcomes or therapeutic responses are urgently needed. A classification schema consistently reflecting the radiological, clinical (lung function and clinical outcomes) and pathological features of a disease represents a critical need in modern pulmonary medicine. Herein, we report a quantitative stratification paradigm to identify subsets of DPLD patients with characteristic radiologic patterns in an unsupervised manner and demonstrate significant correlation of these self-organized disease groups with clinically accepted surrogate endpoints. The proposed consistent and reproducible technique could potentially transform diagnostic staging, clinical management and prognostication of DPLD patients as well as facilitate patient selection for clinical trials beyond the ability of current radiological tools. In addition, the sequential quantitative stratification of the type and extent of parenchymal process may allow standardized and objective monitoring of disease, early assessment of treatment response and mortality prediction for DPLD patients.

Indexed as

Diagnosis, DifferentialHumansImage Interpretation, Computer-AssistedImage Processing, Computer-AssistedLungLung Diseases, InterstitialRespiratory Function TestsTomography, X-Ray Computed

Identifiers

PMID24676019
PMCPMC3968138

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.