Evidence map›Paper›PMID 22917154›Full record

ReviewBiomarkers in medicine2012

Personalized medicine: applying 'omics' to lung fibrosis.

Jose D Herazo-Maya, Naftali Kaminski

Open access · greenAbstract readReview
In one paragraph

Review in Biomarkers in medicine, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.4field-weighted citation impact, top 11% of its field
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

11 citing papers in PubMed, 23 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Mouse Models of Lung Fibrosis.Methods in molecular biology (Clifton, N.J.) · 2021
    Article
  5. Article
  6. Systems medicine advances in interstitial lung disease.European respiratory review : an official journal of the European Respiratory Society · 2017
    Review
  7. Article
  8. Molecular biomarkers in interstitial lung diseases.Molecular diagnosis & therapy · 2014
    Review
  9. Article
  10. Article
  11. 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

2 authors at 1 institution in 1 country.

Jose D Herazo-MayaDorothy P & Richard P Simmons Center for Interstitial Lung Disease, Pulmonary, Allergy & Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine, 3459 5th Avenue, Pittsburgh, PA 15261, USA.
Naftali Kaminski
University of Pittsburgh · US

Funding

Lung Genomics Research ConsortiumRC2HL101715 · NHLBI · UNIVERSITY OF COLORADO DENVER · PI GERACI, MARK W, KAMINSKI, NAFTALI · 2009 to 2010
$11.4M
Molecular Phenotypes within and across disease boundaries in IPF and COPDR01HL095397 · NHLBI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI KAMINSKI, NAFTALI, SHAPIRO, STEVEN D · 2008 to 2011
$3.0M
Modeling in vivo Protein-DNA Interactions from High-Throughput Data MP1/1R01LM009657 · NLM · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI BENOS, PANAGIOTIS V, KAMINSKI, NAFTALI · 2007 to 2011
$2.5M
Gene networks beyond organ boundaries; heart, lung and pulmonary vascular diseaseU01HL108642 · NHLBI · YALE UNIVERSITY · PI AHMAD, FERHAAN, BENOS, PANAGIOTIS V · 2011 to 2014
$2.2M
NHLBI NIH HHS R01 HL095397NHLBI NIH HHS R01HL095397NHLBI NIH HHS RC2 HL101715NHLBI NIH HHS RC2HL101715NHLBI NIH HHS U01 HL108642NHLBI NIH HHS U01HL108642NLM NIH HHS R01 LM009657NLM NIH HHS R01LM009657
6 · The paper itself

Abstract

Idiopathic pulmonary fibrosis (IPF), the most common fibrotic lung disease, is a chronic disease of unknown etiology with a very high mortality. Personalized medicine focuses on the use of the individual's molecular and 'omic' (i.e., genomic, epigenomic and proteomic) information to direct more efficient and cost-effective strategies for prevention, diagnosis, outcome prediction and treatment of diseases. In this review, we describe the use and promise of applying 'omic' technologies to the familial and sporadic forms of IPF as a means to personalize diagnosis and outcome prediction in IPF. The validation and implementation of such approaches will be crucial to personalize IPF patient care, prioritize lung transplant and stratify patients for drug studies, as well as, in the future, predict response to therapies as they emerge.

Indexed as

Precision MedicineBlood ProteinsDisease SusceptibilityGenomicsHumansMatrix Metalloproteinase 7Polymorphism, Single NucleotidePulmonary FibrosisTomography Scanners, X-Ray ComputedTumor Suppressor ProteinsBlood ProteinsMatrix Metalloproteinase 7Tumor Suppressor Proteins

Identifiers

PMID22917154
PMCPMC3517740
OpenAlexW2083963813

What OpenQuestion holds

Textmetadata
LicenceTDM
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.