Evidence map›Paper›PMID 25866164›Full record

ReviewAnnals of the New York Academy of Sciences2015

Personalized health care beyond oncology: new indications for immunoassay-based companion diagnostics.

Richard Batrla, Bruce W M Jordan

Open access · hybridAbstract readReview
In one paragraph

Review in Annals of the New York Academy of Sciences, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
11.2field-weighted citation impact, top 2% 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

3 citing papers in PubMed, 18 citations in OpenAlex.

  1. Article
  2. Review
  3. 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.

Richard BatrlaRoche Diagnostics International Ltd, Rotkreuz, Switzerland.
Bruce W M JordanRoche Diagnostics International Ltd, Rotkreuz, Switzerland.
Roche (Switzerland) · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Personalized health care (PHC) is an evolving field of medicine aimed at providing the right therapy to the right patient at the right time. This approach often incorporates the use of companion diagnostics (CDx) assays that provide information essential for the safe and effective use of the corresponding drug. In addition to oncology, many other therapy areas, such as cardiovascular, neurological, and infectious and inflammatory diseases, may benefit from PHC, owing to disease complexity and heterogeneity. Furthermore, although most U.S. Food and Drug Administration-approved CDx are based on molecular-based technologies, immunoassays can provide a significant contribution to the evolution of CDx in patient management. In this review we discuss how the incorporation of biomarker immunoassays into routine diagnostic testing may allow early and definitive detection of Alzheimer's disease and enable population enrichment in clinical trials. In addition, we will describe how biomarker-based CDx immunoassays have potential utility for stratifying patients with asthma based on their potential response to therapy and for selecting treatment according to phenotypic profile. Continued research into the underlying disease pathology and development of accurate and reliable diagnostic assays may ensure that PHC becomes the future standard for many indications.

Indexed as

Diagnostic Techniques and ProceduresBiomarkersCardiovascular DiseasesCommunicable DiseasesDelivery of Health CareHumansImmunoassayInflammationNeoplasmsNervous System DiseasesPrecision MedicineBiomarkersAlzheimer's diseaseasthmabiomarkercompanion diagnosticsperiostinpersonalized health care

Identifiers

PMID25866164
PMCPMC4744740
OpenAlexW1527265275

What OpenQuestion holds

Textmetadata
LicenceCC BY-ND
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.