Evidence map›Paper›PMID 19670321›Full record

ReviewMuscle & nerve2009

Applying proteomics to the diagnosis and treatment of ALS and related diseases.

Robert Bowser, David Lacomis

Open access · bronzeAbstract readReview
In one paragraph

Review in Muscle & nerve, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.3field-weighted citation impact, top 12% 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

12 citing papers in PubMed, 29 citations in OpenAlex.

  1. Article
  2. Article
  3. Clinical Trial Designs in Amyotrophic Lateral Sclerosis: Does One Design Fit All?Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2015
    Review
  4. Article
  5. Review
  6. Review
  7. Article
  8. Review
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  10. Article
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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 2 institutions in 1 country.

Robert BowserDepartment of Pathology, University of Pittsburgh School of Medicine, BST S-420, 200 Lothrop Street, Pittsburgh, Pennsylvania 15261, USA. boswerrp@upmc.edu
David Lacomis
University of Pittsburgh · USUniversity of Pittsburgh Medical Center · US

Funding

Transcriptional Responses in Neurodegenerative DiseasesR01NS042724 · NINDS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI BOWSER, ROBERT P · 2004 to 2007
$1.0M
ALS biomarkers in the cerebrospinal fluidR21ES013469 · NIEHS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI BOWSER, ROBERT P · 2004 to 2005
$408k
NIEHS NIH HHS R21 ES013469NINDS NIH HHS NS042724NINDS NIH HHS R01 NS042724
6 · The paper itself

Abstract

Protein-based biomarkers for amyotrophic lateral sclerosis (ALS) and other motor neuron diseases (MNDs) have many potential clinical utilities, including diagnostic, prognostic, and drug development indications. During the past decade a number of potential protein biomarkers have been proposed for MNDs. Further verification studies, followed by large validation and qualification studies, are required to advance these initial discoveries toward clinical use. Study of additional patient populations, including disease mimics, is required during the validation phase of biomarker development. Important regulatory issues are discussed that will affect the timing and strategy for biomarker assay development in ALS and other MNDs. The continued development of protein biomarkers for MNDs requires extensive collaboration between academic clinicians and scientists in conjunction with the biotechnology and pharmaceutical industries.

Indexed as

Amyotrophic Lateral SclerosisAnimalsBiomarkersHumansNervous System DiseasesProteomicsBiomarkers

Identifiers

PMID19670321
PMCPMC2836583
OpenAlexW2035502413

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.