Evidence map›Paper›PMID 42764192›Full record

ArticleCancer science2026

Triangulating Evidence on Serum Uric Acid and Cancer Risk: Consistent Inverse Associations With Lung Cancer.

Takashi Matsunaga, Kenji Wakai, Takashi Tamura, Mako Nagayoshi, Rieko Okada, Itsuki Kageyama, Megumi Hara, Takuma Furukawa, Hiroaki Ikezaki, Yuji Matsumoto and 17 more

Abstract read
In one paragraph

Article in Cancer science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

27 authors.

Takashi MatsunagaDepartment of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Kenji WakaiDepartment of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Takashi TamuraDepartment of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan.ORCID https://orcid.org/0000-0002-1057-744X
Mako NagayoshiDepartment of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Rieko OkadaDepartment of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Itsuki KageyamaDepartment of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Megumi HaraDepartment of Preventive Medicine, Faculty of Medicine, Saga University, Saga, Japan.
Takuma FurukawaDepartment of Preventive Medicine, Faculty of Medicine, Saga University, Saga, Japan.
Hiroaki IkezakiDepartment of General Internal Medicine, Kyushu University Hospital, Fukuoka, Japan.
Yuji MatsumotoDepartment of General Internal Medicine, Kyushu University Hospital, Fukuoka, Japan.
Takeshi NishiyamaDepartment of Public Health, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan.
Hiroko Nakagawa-SendaDepartment of Public Health, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan.ORCID https://orcid.org/0000-0003-0845-0279
Chihaya KoriyamaDepartment of Epidemiology and Preventive Medicine, Kagoshima University Graduate School of Medical and Dental Sciences, Kagoshima, Japan.ORCID https://orcid.org/0000-0003-3676-8866
Shiroh TanoueDepartment of Epidemiology and Preventive Medicine, Kagoshima University Graduate School of Medical and Dental Sciences, Kagoshima, Japan.
Naoyuki TakashimaDepartment of Epidemiology for Community Health and Medicine, Kyoto Prefectural University of Medicine, Kyoto, Japan.
Etsuko OzakiDepartment of Epidemiology for Community Health and Medicine, Kyoto Prefectural University of Medicine, Kyoto, Japan.
Katsuyuki MiuraNCD Epidemiology Research Center, Shiga University of Medical Science, Otsu, Japan.
Aya KadotaNCD Epidemiology Research Center, Shiga University of Medical Science, Otsu, Japan.
Takeshi WatanabeDepartment of Preventive Medicine, Tokushima University Graduate School of Biomedical Sciences, Tokushima, Japan.
Masashi IshizuDepartment of Preventive Medicine, Tokushima University Graduate School of Biomedical Sciences, Tokushima, Japan.
Kiyonori KurikiLaboratory of Public Health, Division of Nutritional Sciences, School of Food and Nutritional Sciences, University of Shizuoka, Shizuoka, Japan.
Masahiro NakatochiPublic Health Informatics Unit, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan.ORCID https://orcid.org/0000-0002-1838-4837
Yukihide MomozawaLaboratory for Genotyping Development, RIKEN, Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan.ORCID https://orcid.org/0000-0001-5638-3504
Issei ImotoAichi Cancer Center Research Institute, Nagoya, Japan.
Isao OzeDivision of Cancer Information and Control, Aichi Cancer Center Research Institute, Nagoya, Japan.ORCID https://orcid.org/0000-0002-0762-1147
Keitaro MatsuoDivision of Cancer Epidemiology and Prevention, Aichi Cancer Center Research Institute, Nagoya, Japan.ORCID https://orcid.org/0000-0003-1761-6314
J‐MICC Study Group

Funding

Grants-in-Aid for Scientific Research for Priority Areas of Cancer 17015018Grants-in-Aid for Scientific Research on Innovative Areas 221S0001Japan Agency for Medical Research and Development (AMED)Japan Society for the Promotion of Science (JSPS) KAKENHI Grants 16H06277Japan Society for the Promotion of Science (JSPS) KAKENHI Grants 22H04923Ministry of Education, Culture, Sports, Science and Technology
6 · The paper itself

Abstract

We examined the association between serum uric acid (UA) levels and cancer incidence through a conventional observational and two-sample Mendelian randomization (MR) study in the same population (triangulation). We followed 13,695 individuals aged 35-69 years for cancer incidence (total, gastric, colorectal, lung, prostate, and breast cancers) over a median period of 10.6 years. The conventional observational dataset consisted of two subsets sampled from the full cohort using different sampling procedures. Odds ratios were computed using logistic regression for one type of single-nucleotide polymorphism (SNP) array, and hazard ratios were computed using the Cox proportional hazards model for another type of SNP array, combining them to calculate conventional relative risks (RRs). For two-sample MR, 42 UA-related SNPs were identified from Biobank Japan genome-wide association study data (109,029 participants). Associations between these SNPs and cancer were estimated using J-MICC Study data. MR RRs of cancer incidence per one standard deviation (SD) increase in genetically predicted UA were predicted using the inverse variance weighted (IVW) method and other MR approaches. In the conventional analysis, the highest UA concentration group (≥ 6.4 mg/dL) showed a decreased risk of lung cancer (RR: 0.64, 95% confidence interval [CI]: 0.41-0.98) compared with the lowest UA concentration group (< 4.0 mg/dL). The two-sample MR (IVW method) also suggested that UA was inversely (although marginally) associated with lung cancer risk (RR per one SD: 0.65, 95% CI: 0.40-1.05). In conclusion, lower, rather than higher, UA concentrations may be associated with an increased risk of lung cancer.

Indexed as

cancer incidencelung cancermendelian randomizationtriangulationuric acid

Identifiers

PMID42764192
PMCPMC13590243

What OpenQuestion holds

Textmetadata
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.