Evidence map›Paper›PMID 20859284›Full record

ArticleBritish journal of cancer2010

A multi-analyte serum test for the detection of non-small cell lung cancer.

E C Farlow, M S Vercillo, J S Coon, S Basu, A W Kim, L P Faber, W H Warren, P Bonomi, M J Liptay, J A Borgia

Abstract readValidation Study
In one paragraph

Article in British journal of cancer, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–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

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Observational
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Elevated serum apolipoprotein E is associated with metastasis and poor prognosis of non-small cell lung cancer.Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine · 2016
    Article
  10. Urinary protein biomarkers in the early detection of lung cancer.Cancer prevention research (Philadelphia, Pa.) · 2015
    Article
  11. Article
  12. Article
  13. The state of molecular biomarkers for the early detection of lung cancer.Cancer prevention research (Philadelphia, Pa.) · 2012
    Review
  14. 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

10 authors.

E C FarlowDepartment of General Surgery, Rush University Medical Center, 785 Jelke-Southcenter, 1750 W. Harrison Street, Chicago, IL 60612, USA.
M S Vercillo
J S Coon
S Basu
A W Kim
L P Faber
W H Warren
P Bonomi
M J Liptay
J A Borgia

Funding

SPECIALIZED CENTER OF RESEARCH IN OSTEOARTHRITISP50AR039239 · NIAMS · RUSH UNIVERSITY MEDICAL CENTER · PI OEGEMA, THEODORE RICHARD · 1987 to 2007
$8.5M
NIAMS NIH HHS 2-P50-AR39239NIAMS NIH HHS P50 AR039239
6 · The paper itself

Abstract

backgroundIn this study, we appraised a wide assortment of biomarkers previously shown to have diagnostic or prognostic value for non-small cell lung cancer (NSCLC) with the intent of establishing a multi-analyte serum test capable of identifying patients with lung cancer.

methodsCirculating levels of 47 biomarkers were evaluated against patient cohorts consisting of 90 NSCLC and 43 non-cancer controls using commercial immunoassays. Multivariate statistical methods were used on all biomarkers achieving statistical relevance to define an optimised panel of diagnostic biomarkers for NSCLC. The resulting biomarkers were fashioned into a classification algorithm and validated against serum from a second patient cohort.

resultsA total of 14 analytes achieved statistical relevance upon evaluation. Multivariate statistical methods then identified a panel of six biomarkers (tumour necrosis factor-α, CYFRA 21-1, interleukin-1ra, matrix metalloproteinase-2, monocyte chemotactic protein-1 and sE-selectin) as being the most efficacious for diagnosing early stage NSCLC. When tested against a second patient cohort, the panel successfully classified 75 of 88 patients.

conclusionsHere, we report the development of a serum algorithm with high specificity for classifying patients with NSCLC against cohorts of various 'high-risk' individuals. A high rate of false positives was observed within the cohort in which patients had non-neoplastic lung nodules, possibly as a consequence of the inflammatory nature of these conditions.

Indexed as

AdultAgedAged, 80 and overAlgorithmsBiomarkers, TumorBlood Chemical AnalysisCarcinoma, Non-Small-Cell LungCase-Control StudiesCohort StudiesEarly Detection of CancerFemaleHumansLung NeoplasmsMaleMiddle AgedSerumBiomarkers, Tumor

Identifiers

PMID20859284
PMCPMC2967050

What OpenQuestion holds

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Registered trials

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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.