Evidence map›Paper›PMID 38411285›Full record

ArticleCancer science2024

Scoring system for diagnosis and pretreatment risk assessment of neuroblastoma using urinary biomarker combinations.

Hizuru Amano, Hiroo Uchida, Kazuharu Harada, Atsushi Narita, Shigehisa Fumino, Yuji Yamada, Shun Kumano, Mayumi Abe, Takashi Ishigaki, Minoru Sakairi and 19 more

Open access · goldAbstract read
In one paragraph

Article in Cancer science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
3.0field-weighted citation impact, top 9% 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

7 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Review
  6. Article
  7. 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

29 authors at 10 institutions in 1 country.

Hizuru AmanoDepartment of Rare/Intractable Cancer Analysis Research, Nagoya University Graduate School of Medicine, Nagoya, Japan.ORCID https://orcid.org/0000-0001-5373-9069
Hiroo UchidaDepartment of Pediatric Surgery, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Kazuharu HaradaDepartment of Health Data Science, Tokyo Medical University, Tokyo, Japan.
Atsushi NaritaDepartment of Pediatrics, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Shigehisa FuminoDepartment of Pediatric Surgery, Kyoto Prefectural University of Medicine, Kyoto, Japan.
Yuji YamadaChildren's Cancer Center, National Center for Child Health and Development, Tokyo, Japan.
Shun KumanoDepartment of Rare/Intractable Cancer Analysis Research, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Mayumi AbeDepartment of Rare/Intractable Cancer Analysis Research, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Takashi IshigakiDepartment of Rare/Intractable Cancer Analysis Research, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Minoru SakairiDepartment of Rare/Intractable Cancer Analysis Research, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Chiyoe ShirotaDepartment of Pediatric Surgery, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Takahisa TainakaDepartment of Pediatric Surgery, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Wataru SumidaDepartment of Pediatric Surgery, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Kazuki YokotaDepartment of Pediatric Surgery, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Satoshi MakitaDepartment of Pediatric Surgery, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Shuhei KarakawaDepartment of Pediatrics, Hiroshima University, Graduate School of Biomedical and Health Sciences, Hiroshima, Japan.
Yuichi MitaniDepartment of Hematology/Oncology, Saitama Children's Medical Center, Saitama, Japan.
Shojiro MatsumotoDepartment of Complex Systems Science, Graduate School of Information Science, Nagoya University, Nagoya, Japan.
Yutaka TomiokaDepartment for the Promotion of Medical Device Innovation, National Cancer Center Hospital East, Chiba, Japan.
Hideki MuramatsuDepartment of Pediatrics, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Nobuhiro NishioDepartment of Pediatrics, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Tsuyoshi OsawaDivision of Integrative Nutriomics and Oncology, RCAST, The University of Tokyo, Tokyo, Japan.ORCID https://orcid.org/0000-0002-9479-6665
Masataka TaguriDepartment of Health Data Science, Tokyo Medical University, Tokyo, Japan.
Katsuyoshi KohDepartment of Hematology/Oncology, Saitama Children's Medical Center, Saitama, Japan.
Tatsuro TajiriDepartment of Pediatric Surgery, Kyoto Prefectural University of Medicine, Kyoto, Japan.
Motohiro KatoDepartment of Pediatrics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Kimikazu MatsumotoChildren's Cancer Center, National Center for Child Health and Development, Tokyo, Japan.
Yoshiyuki TakahashiDepartment of Pediatrics, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Akinari HinokiDepartment of Rare/Intractable Cancer Analysis Research, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Nagoya University · JPNational Center For Child Health and Development · JPSaitama Children's Medical Center · JPTokyo Medical University · JPHiroshima University · JPKyoto Prefectural University of Medicine · JPKyushu University · JPNational Cancer Center Hospital East · JPThe University of Tokyo · JPTokyo City University · JP

Funding

Hitachi, Ltd. 2617Dm-08bJapan Agency for Medical Research and Development JP22cm0106481
6 · The paper itself

Abstract

The urinary catecholamine metabolites, homovanillic acid (HVA) and vanillylmandelic acid (VMA), are used for the adjunctive diagnosis of neuroblastomas. We aimed to develop a scoring system for the diagnosis and pretreatment risk assessment of neuroblastoma, incorporating age and other urinary catecholamine metabolite combinations. Urine samples from 227 controls (227 samples) and 68 patients with neuroblastoma (228 samples) were evaluated. First, the catecholamine metabolites vanillactic acid (VLA) and 3-methoxytyramine sulfate (MTS) were identified as urinary marker candidates through comprehensive analysis using liquid chromatography-mass spectrometry. The concentrations of these marker candidates and conventional markers were then compared among controls, patients, and numerous risk groups to develop a scoring system. Participants were classified into four groups: control, low risk, intermediate risk, and high risk, and the proportional odds model was fitted using the L2-penalized maximum likelihood method, incorporating age on a monthly scale for adjustment. This scoring model using the novel urine catecholamine metabolite combinations, VLA and MTS, had greater area under the curve values than the model using HVA and VMA for diagnosis (0.978 vs. 0.964), pretreatment risk assessment (low and intermediate risk vs. high risk: 0.866 vs. 0.724; low risk vs. intermediate and high risk: 0.871 vs. 0.680), and prognostic factors (MYCN status: 0.741 vs. 0.369, histology: 0.932 vs. 0.747). The new system also had greater accuracy in detecting missing high-risk neuroblastomas, and in predicting the pretreatment risk at the time of screening. The new scoring system employing VLA and MTS has the potential to replace the conventional adjunctive diagnostic method using HVA and VMA.

Indexed as

Biomarkers, TumorHomovanillic AcidNeuroblastomaVanilmandelic AcidCase-Control StudiesCatecholaminesChildChild, PreschoolChromatography, LiquidDopamineFemaleHumansInfantMaleRisk AssessmentBiomarkers, TumorCatecholaminesDopamineHomovanillic AcidVanilmandelic Acid3‐methoxytyramine sulfatediagnosisliquid chromatography–mass spectrometryneuroblastomavanillactic acid

Identifiers

PMID38411285
PMCPMC11093204
OpenAlexW4392192625

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.