↓ Skip to main content

Blood-Based Biomarker Panel for Personalized Lung Cancer Risk Assessment

Overview of attention for article published in Journal of Clinical Oncology, January 2022
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

news
53 news outlets
blogs
4 blogs
twitter
43 X users
wikipedia
1 Wikipedia page

Citations

dimensions_citation
44 Dimensions

Readers on

mendeley
52 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Blood-Based Biomarker Panel for Personalized Lung Cancer Risk Assessment
Published in
Journal of Clinical Oncology, January 2022
DOI 10.1200/jco.21.01460
Pubmed ID
Authors

Johannes F. Fahrmann, Tracey Marsh, Ehsan Irajizad, Nikul Patel, Eunice Murage, Jody Vykoukal, Jennifer B. Dennison, Kim-Anh Do, Edwin Ostrin, Margaret R. Spitz, Stephen Lam, Sanjay Shete, Rafael Meza, Martin C. Tammemägi, Ziding Feng, Samir M. Hanash

Abstract

To investigate whether a panel of circulating protein biomarkers would improve risk assessment for lung cancer screening in combination with a risk model on the basis of participant characteristics. A blinded validation study was performed using prostate lung colorectal ovarian (PLCO) Cancer Screening Trial data and biospecimens to evaluate the performance of a four-marker protein panel (4MP) consisting of the precursor form of surfactant protein B, cancer antigen 125, carcinoembryonic antigen, and cytokeratin-19 fragment in combination with a lung cancer risk prediction model (PLCOm2012) compared with current US Preventive Services Task Force (USPSTF) screening criteria. The 4MP was assayed in 1,299 sera collected preceding lung cancer diagnosis and 8,709 noncase sera. The 4MP alone yielded an area under the receiver operating characteristic curve of 0.79 (95% CI, 0.77 to 0.82) for case sera collected within 1-year preceding diagnosis and 0.74 (95% CI, 0.72 to 0.76) among the entire specimen set. The combined 4MP + PLCOm2012 model yielded an area under the receiver operating characteristic curve of 0.85 (95% CI, 0.82 to 0.88) for case sera collected within 1 year preceding diagnosis. The benefit of the 4MP in the combined model resulted from improvement in sensitivity at high specificity. Compared with the USPSTF2021 criteria, the combined 4MP + PLCOm2012 model exhibited statistically significant improvements in sensitivity and specificity. Among PLCO participants with ≥ 10 smoking pack-years, the 4MP + PLCOm2012 model would have identified for annual screening 9.2% more lung cancer cases and would have reduced referral by 13.7% among noncases compared with USPSTF2021 criteria. A blood-based biomarker panel in combination with PLCOm2012 significantly improves lung cancer risk assessment for lung cancer screening.

X Demographics

X Demographics

The data shown below were collected from the profiles of 43 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 52 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 8%
Researcher 4 8%
Student > Doctoral Student 3 6%
Other 3 6%
Student > Postgraduate 3 6%
Other 8 15%
Unknown 27 52%
Readers by discipline Count As %
Medicine and Dentistry 16 31%
Biochemistry, Genetics and Molecular Biology 3 6%
Agricultural and Biological Sciences 3 6%
Computer Science 2 4%
Chemical Engineering 1 2%
Other 2 4%
Unknown 25 48%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 424. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 August 2023.
All research outputs
#69,453
of 25,775,807 outputs
Outputs from Journal of Clinical Oncology
#138
of 22,244 outputs
Outputs of similar age
#2,260
of 519,781 outputs
Outputs of similar age from Journal of Clinical Oncology
#8
of 354 outputs
Altmetric has tracked 25,775,807 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 22,244 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 21.2. This one has done particularly well, scoring higher than 99% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 519,781 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 354 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 97% of its contemporaries.