Evidence map›Paper›PMID 26700005›Full record

ArticlePloS one2015

Targeting Uric Acid and the Inhibition of Progression to End-Stage Renal Disease--A Propensity Score Analysis.

Shunya Uchida, Wen Xiu Chang, Tatsuru Ota, Yoshifuru Tamura, Takeshi Shiraishi, Takanori Kumagai, Shigeru Shibata, Yoshihide Fujigaki, Makoto Hosoyamada, Kiyoko Kaneko and 2 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed, 1 pooled it
4.3field-weighted citation impact, top 6% 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

40 citing papers in PubMed, 1 synthesis or guideline pooled it, 56 citations in OpenAlex.

  1. Pooled it
  2. Trial
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  6. Review
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  9. Effects of Uric Acid-Lowering Therapy on the Kidney (HTR-2023-0096.R2).Hypertension research : official journal of the Japanese Society of Hypertension · 2023
    Article
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  19. Observational
  20. Renal effects of uric acid: hyperuricemia and hypouricemia.The Korean journal of internal medicine · 2020
    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

12 authors at 3 institutions in 2 countries.

Shunya UchidaDepartment of Internal Medicine, Teikyo University School of Medicine, Tokyo, Japan.
Wen Xiu ChangDepartment of Nephrology, Tianjin First Central Hospital, Tianjin, China.
Tatsuru OtaDepartment of Internal Medicine, Teikyo University School of Medicine, Tokyo, Japan.
Yoshifuru TamuraDepartment of Internal Medicine, Teikyo University School of Medicine, Tokyo, Japan.
Takeshi ShiraishiDepartment of Internal Medicine, Teikyo University School of Medicine, Tokyo, Japan.
Takanori KumagaiDepartment of Internal Medicine, Teikyo University School of Medicine, Tokyo, Japan.
Shigeru ShibataDepartment of Internal Medicine, Teikyo University School of Medicine, Tokyo, Japan.
Yoshihide FujigakiDepartment of Internal Medicine, Teikyo University School of Medicine, Tokyo, Japan.
Makoto HosoyamadaHuman Physiology and Pathology, Faculty of Pharma Sciences, Teikyo University, Tokyo, Japan.
Kiyoko KanekoBiomedical and Analytical Sciences, Faculty of Pharma Sciences, Teikyo University, Tokyo, Japan.
Zhong Yang ShenDepartment of Organ Transplantation, Tianjin First Central Hospital, Tianjin, China.
Shin FujimoriDepartment of Internal Medicine, Teikyo University School of Medicine, Tokyo, Japan.
Teikyo University · JPTianjin First Center Hospital · CNTianjin Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe role of uric acid (UA) in the progression of chronic kidney disease (CKD) remains controversial due to the unavoidable cause and result relationship. This study was aimed to clarify the independent impact of UA on the subsequent risk of end-stage renal disease (ESRD) by a propensity score analysis.

methodsA retrospective CKD cohort was used (n = 803). Baseline 23 covariates were subjected to a multivariate binary logistic regression with the targeted time-averaged UA of 6.0, 6.5 or 7.0 mg/dL. The participants trimmed 2.5 percentile from the extreme ends of the cohort underwent propensity score analyses consisting of matching, stratification on quintile and covariate adjustment. Covariate balances after 1:1 matching without replacement were tested for by paired analysis and standardized differences. A stratified Cox regression and a Cox regression adjusted for logit of propensity scores were examined.

resultsAfter propensity score matching, the higher UA showed elevated hazard ratios (HRs) by Kaplan-Meier analysis (≥ 6.0 mg/dL, HR 4.53, 95%CI 1.79-11.43; ≥ 6.5 mg/dL, HR 3.39, 95%CI 1.55-7.42; ≥ 7.0 mg/dL, HR 2.19, 95%CI 1.28-3.75). The number needed to treat was 8 to 9 over 5 years. A stratified Cox regression likewise showed significant crude HRs (≥ 6.0 mg/dL, HR 3.63, 95%CI 1.25-10.58; ≥ 6.5 mg/dL, HR 3.46, 95%CI 1.56-7.68; ≥ 7.0 mg/dL, HR 2.05, 95%CI 1.21-3.48). Adjusted HR lost its significance at 6.0 mg/dL. The adjustment for the logit of the propensity scores showed the similar results but with worse model fittings than the stratification method. Upon further adjustment for other covariates the significance was attained at 6.5 mg/dL.

conclusionsThree different methods of the propensity score analysis showed consistent results that the higher UA accelerates the progression to the subsequent ESRD. A stratified Cox regression outperforms other methods in generalizability and adjusting for residual bias. Serum UA should be targeted less than 6.5 mg/dL.

Indexed as

Propensity ScoreAdultAgedAged, 80 and overBiomarkersDisease ProgressionFemaleFollow-Up StudiesHumansKidney Failure, ChronicMaleMiddle AgedModels, StatisticalPrognosisProportional Hazards ModelsRetrospective StudiesBiomarkersUric Acid

Identifiers

PMID26700005
PMCPMC4689349
OpenAlexW2211140438

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.