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Optimizing the clinical utility of PCA3 to diagnose prostate cancer in initial prostate biopsy

Overview of attention for article published in BMC Cancer, September 2015
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (72nd percentile)

Mentioned by

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5 tweeters

Citations

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13 Dimensions

Readers on

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26 Mendeley
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Title
Optimizing the clinical utility of PCA3 to diagnose prostate cancer in initial prostate biopsy
Published in
BMC Cancer, September 2015
DOI 10.1186/s12885-015-1623-0
Pubmed ID
Authors

Jose Rubio-Briones, Angel Borque, Luis M. Esteban, Juan Casanova, Antonio Fernandez-Serra, Luis Rubio, Irene Casanova-Salas, Gerardo Sanz, Jose Domínguez-Escrig, Argimiro Collado, Alvaro Gómez-Ferrer, Inmaculada Iborra, Miguel Ramírez-Backhaus, Francisco Martínez, Ana Calatrava, Jose A. Lopez-Guerrero

Abstract

PCA3 has been included in a nomogram outperforming previous clinical models for the prediction of any prostate cancer (PCa) and high grade PCa (HGPCa) at the initial prostate biopsy (IBx). Our objective is to validate such IBx-specific PCA3-based nomogram. We also aim to optimize the use of this nomogram in clinical practice through the definition of risk groups. Independent external validation. Clinical and biopsy data from a contemporary cohort of 401 men with the same inclusion criteria to those used to build up the reference's nomogram in IBx. The predictive value of the nomogram was assessed by means of calibration curves and discrimination ability through the area under the curve (AUC). Clinical utility of the nomogram was analyzed by choosing thresholds points that minimize the overlapping between probability density functions (PDF) in PCa and no PCa and HGPCa and no HGPCa groups, and net benefit was assessed by decision curves. We detect 28 % of PCa and 11 % of HGPCa in IBx, contrasting to the 46 and 20 % at the reference series. Due to this, there is an overestimation of the nomogram probabilities shown in the calibration curve for PCa. The AUC values are 0.736 for PCa (C.I.95 %:0.68-0.79) and 0.786 for HGPCa (C.I.95 %:0.71-0.87) showing an adequate discrimination ability. PDF show differences in the distributions of nomogram probabilities in PCa and not PCa patient groups. A minimization of the overlapping between these curves confirms the threshold probability of harboring PCa >30 % proposed by Hansen is useful to indicate a IBx, but a cut-off > 40 % could be better in series of opportunistic screening like ours. Similar results appear in HGPCa analysis. The decision curve also shows a net benefit of 6.31 % for the threshold probability of 40 %. PCA3 is an useful tool to select patients for IBx. Patients with a calculated probability of having PCa over 40 % should be counseled to undergo an IBx if opportunistic screening is required.

Twitter Demographics

The data shown below were collected from the profiles of 5 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 4%
United States 1 4%
Unknown 24 92%

Demographic breakdown

Readers by professional status Count As %
Student > Master 6 23%
Researcher 2 8%
Professor > Associate Professor 2 8%
Professor 2 8%
Student > Ph. D. Student 2 8%
Other 4 15%
Unknown 8 31%
Readers by discipline Count As %
Medicine and Dentistry 10 38%
Biochemistry, Genetics and Molecular Biology 3 12%
Agricultural and Biological Sciences 1 4%
Computer Science 1 4%
Mathematics 1 4%
Other 1 4%
Unknown 9 35%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 14 September 2015.
All research outputs
#4,402,909
of 15,517,351 outputs
Outputs from BMC Cancer
#1,117
of 5,809 outputs
Outputs of similar age
#67,251
of 242,895 outputs
Outputs of similar age from BMC Cancer
#1
of 1 outputs
Altmetric has tracked 15,517,351 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 5,809 research outputs from this source. They receive a mean Attention Score of 4.1. This one has done well, scoring higher than 80% 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 242,895 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them