Evidence map›Paper›PMID 29046289›Full record

ArticleEndocrine-related cancer2018

A novel model to predict positive prostate biopsy based on serum androgen level.

Takeshi Ujike, Motohide Uemura, Atsunari Kawashima, Akira Nagahara, Kazutoshi Fujita, Yasushi Miyagawa, Norio Nonomura

Open access · hybridAbstract read
In one paragraph

Article in Endocrine-related cancer, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
0.6field-weighted citation impact, top 27% 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

10 citing papers in PubMed, 11 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Diagnosis of Prostate Cancer in Patients with Prostate-Specific Antigen (PSA) in the Gray Area: Construction of 2 Predictive Models.Medical science monitor : international medical journal of experimental and clinical research · 2021
    Article
  8. Obesity, Inflammation, and Prostate Cancer.Journal of clinical medicine · 2019
    Review
  9. Article
  10. 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

7 authors at 1 institution in 1 country.

Takeshi UjikeDepartment of UrologyOsaka University Graduate School of Medicine, Suita, Osaka, Japan.
Motohide UemuraDepartment of UrologyOsaka University Graduate School of Medicine, Suita, Osaka, Japan uemura@uro.med.osaka-u.ac.jp.
Atsunari KawashimaDepartment of UrologyOsaka University Graduate School of Medicine, Suita, Osaka, Japan.
Akira NagaharaDepartment of UrologyOsaka University Graduate School of Medicine, Suita, Osaka, Japan.
Kazutoshi FujitaDepartment of UrologyOsaka University Graduate School of Medicine, Suita, Osaka, Japan.
Yasushi MiyagawaDepartment of UrologyOsaka University Graduate School of Medicine, Suita, Osaka, Japan.
Norio NonomuraDepartment of UrologyOsaka University Graduate School of Medicine, Suita, Osaka, Japan.
Osaka University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Circulating levels of prostate-specific antigen (PSA) and testosterone are widely used for the detection of prostate cancer prior to prostate biopsy; however, both remain controversial. Effective screening strategies based on quantitative factors could help avoid unnecessary biopsies. Here, we sought to clarify the predictive value of free testosterone (FT) vs total testosterone (TT) in identifying patients likely to have positive biopsies. This study aims to develop a novel model for predicting positive prostate biopsy based on serum androgen levels. This study included 253 Japanese patients who underwent prostate biopsy at our institution. TT and FT, %FT (=FT/TT), age, PSA, prostate volume (PV) and PSA density (PSAD = PSA/PV) were assessed for association with prostate biopsy findings. The following results were obtained. Of 253 patients, 145 (57.3%) had positive biopsies. Compared to the negative biopsy group, the positive biopsy group demonstrated higher age, PSA and PSAD but lower PV, FT and %FT by univariate analysis. Multivariate logistic regression analysis indicated PSA, PSAD and %FT were independent predictors of cancer detection. We developed a predictive model based on PSAD and %FT, for which the area under the curve was significantly greater than that of PSA (0.82 vs 0.66), a well-known predictor. Applying this analysis to the subset of patients with PSA <10 ng/mL yielded similar results. We confirmed the utility of this model in another independent cohort of 88 patients. In conclusion, lower %FT predicted a positive prostate biopsy. We constructed a predictive model based on %FT and PSAD, which are easily obtained prior to biopsy.

Indexed as

Models, StatisticalAdultAgedAged, 80 and overBiomarkers, TumorBiopsyCohort StudiesFemaleFollow-Up StudiesHumansMaleMiddle AgedPredictive Value of TestsProstate-Specific AntigenProstatic NeoplasmsROC CurveBiomarkers, TumorProstate-Specific AntigenTestosteronefree testosteronepercent free testosteroneprostate biopsyprostate cancertotal testosterone

Identifiers

PMID29046289
PMCPMC5744473
OpenAlexW2766959904

What OpenQuestion holds

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LicenceCC BY
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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.