Evidence map›Paper›PMID 30065622›Full record

ArticleClinical proteomics2018

MALDI-TOF peptidomic analysis of serum and post-prostatic massage urine specimens to identify prostate cancer biomarkers.

Andrea Padoan, Daniela Basso, Carlo-Federico Zambon, Tommaso Prayer-Galetti, Giorgio Arrigoni, Dania Bozzato, Stefania Moz, Filiberto Zattoni, Rino Bellocco, Mario Plebani

Open access · goldAbstract read
In one paragraph

Article in Clinical proteomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
0.7field-weighted citation impact, top 35% 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

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

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Article
  6. Review
  7. Review
  8. Urinary Peptidomic Biomarkers in Kidney Diseases.International journal of molecular sciences · 2019
    Review
  9. Review
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 at 2 institutions in 1 country.

Andrea Padoan1Department of Medicine-DIMED, University of Padova, Via Giustiniani 2, 35128 Padua, Italy.
Daniela Basso1Department of Medicine-DIMED, University of Padova, Via Giustiniani 2, 35128 Padua, Italy.
Carlo-Federico Zambon2Department of Biomedical Sciences, University of Padova, Padua, Italy.
Tommaso Prayer-Galetti3Department of Surgical, Oncological and Gastroenterological Sciences, University of Padova, Padua, Italy.
Giorgio Arrigoni2Department of Biomedical Sciences, University of Padova, Padua, Italy.
Dania Bozzato1Department of Medicine-DIMED, University of Padova, Via Giustiniani 2, 35128 Padua, Italy.
Stefania Moz1Department of Medicine-DIMED, University of Padova, Via Giustiniani 2, 35128 Padua, Italy.
Filiberto Zattoni3Department of Surgical, Oncological and Gastroenterological Sciences, University of Padova, Padua, Italy.
Rino Bellocco5Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Milan, Italy.
Mario Plebani1Department of Medicine-DIMED, University of Padova, Via Giustiniani 2, 35128 Padua, Italy.
University of Padua · ITUniversity of Milano-Bicocca · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLower urinary tract symptoms (LUTS) and prostate specific antigen-based parameters seem to have only a limited utility for the differential diagnosis of prostate cancer (PCa). MALDI-TOF/MS peptidomic profiling could be a useful diagnostic tool for biomarker discovery, although reproducibility issues have limited its applicability until now. The current study aimed to evaluate a new MALDI-TOF/MS candidate biomarker.

methodsWithin- and between-subject variability of MALDI-TOF/MS-based peptidomic urine and serum analyses were evaluated in 20 and 15 healthy donors, respectively. Normalizations and approaches for accounting below limit of detection (LOD) values were utilized to enhance reproducibility, while Monte Carlo experiments were performed to verify whether measurement error can be dealt with LOD data. Post-prostatic massage urine and serum samples from 148 LUTS patients were analysed using MALDI-TOF/MS. Regression-calibration and simulation and extrapolation methods were used to derive the unbiased association between peptidomic features and PCa.

resultsAlthough the median normalized peptidomic variability was 24.9%, the within- and between-subject variability showed that median normalization, LOD adjustment, and log

conclusionsMALDI-TOF/MS serum peptidome profiling was more efficacious with respect to post-prostatic massage urine analysis in discriminating PCa.

Indexed as

Analytical variabilityBiomarkersData normalizationMALDI-TOF/MSMeasurement errorPeptidomic profilingProstate cancerRegression calibrationSerumSIMEXUrine

Identifiers

PMID30065622
PMCPMC6060548
OpenAlexW2883932710

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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.