Evidence map›Paper›PMID 30343636›Full record

ArticleTechnology in cancer research & treatment2018

An Assessment of Novel Biomarkers in Bone Metastatic Disease Using Multiplex Measurement and Multivariate Analysis.

Jindra Windrichova, Radek Kucera, Radka Fuchsova, Ondrej Topolcan, Ondrej Fiala, Jana Svobodova, Jindrich Finek, Dagmar Slipkova

Open access · goldAbstract read
In one paragraph

Article in Technology in cancer research & treatment, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact, top 82% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. 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

8 authors at 1 institution in 1 country.

Jindra Windrichova1 Department of Immunochemistry, University Hospital and Faculty of Medicine in Pilsen, Charles University, Plzen, Czech Republic.
Radek Kucera1 Department of Immunochemistry, University Hospital and Faculty of Medicine in Pilsen, Charles University, Plzen, Czech Republic.ORCID 0000-0002-2739-2302
Radka Fuchsova1 Department of Immunochemistry, University Hospital and Faculty of Medicine in Pilsen, Charles University, Plzen, Czech Republic.
Ondrej Topolcan1 Department of Immunochemistry, University Hospital and Faculty of Medicine in Pilsen, Charles University, Plzen, Czech Republic.
Ondrej Fiala2 Department of Oncology and Radiotherapy, University Hospital and Faculty of Medicine in Pilsen, Charles University, Plzen, Czech Republic.
Jana Svobodova4 Osteocenter, Second Internal Clinic, University Hospital Pilsen, Pilsen, Czech Republic.
Jindrich Finek2 Department of Oncology and Radiotherapy, University Hospital and Faculty of Medicine in Pilsen, Charles University, Plzen, Czech Republic.
Dagmar Slipkova1 Department of Immunochemistry, University Hospital and Faculty of Medicine in Pilsen, Charles University, Plzen, Czech Republic.
Charles University · CZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimCurrent diagnostics of bone metastatic disease is not satisfactory for early detection or regular process monitoring. The combination of biomarkers and the multiparametric approach was described as effective in other oncology diagnoses. The aim of the study was to improve the difference diagnostics between bone-metastatic disease and solid tumors using mutivariate logistic regression model.

methodsWe assessed the group of 131 patients with the following diagnoses: prostate cancer, breast cancer, lung cancer, and colorectal cancer. According to the results of scintigraphy, the cohort was divided into 2 groups based on the occurrence of bone metastases. Group 0 was a control group of 75 patients with no signs of bone metastases and group 1 included 56 patients with bone metastases.

resultsWe used stepwise selection multivariate logistic regression for choosing the multimarker formula for calculation of risk score for bone metastases diagnostics. For detection of bone metastasis, it was shown to be most effective measurement of 3 biomarkers: procollagen type 1 N-terminal propeptide, growth differentiation factor-15, and osteonectin and combining with calculation of risk score by designating measured concentrations in mathematical formula: bone risk score = procollagen type 1 N-terminal propeptide × 0.0500 + growth differentiation factor-15 × 1.4179 + osteonectin × 0.00555.

conclusionWe identified growth differentiation factor-15 as the best individual marker for bone metastasis diagnostics. The best formula for risk score includes levels of 3 biomarkers-procollagen type 1 N-terminal propeptide, growth differentiation factor-15, and osteonectin. The new score has better performance described by higher area under the curve than individual biomarkers. A further study is necessary to confirm these findings incorporating a larger number of patients.

Indexed as

AdultAgedAged, 80 and overBiomarkers, TumorBone and BonesBone NeoplasmsCohort StudiesFemaleGrowth Differentiation Factor 15HumansMaleMiddle AgedMultivariate AnalysisOsteonectinRadionuclide ImagingBiomarkers, TumorGrowth Differentiation Factor 15Osteonectinbiomarkersbone metastasiscancermultivariate analysisscintigraphy

Identifiers

PMID30343636
PMCPMC6198393
OpenAlexW2897732623

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.