Evidence map›Paper›PMID 39664993›Full record

ArticleClinical kidney journal2024

SUrvey of renal Biopsy registry database and Anticancer dRUg therapy in Japan (SUBARU-J study).

Takashige Kuwabara, Yoshikazu Miyasato, Tomoko Kanki, Teruhiko Mizumoto, Takeshi Matsubara, Naoki Sawa, Hitoshi Sugiyama, Shoichi Maruyama, Hiroshi Sato, Tatsuo Tsukamoto and 8 more

Abstract read
In one paragraph

Article in Clinical kidney journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

18 authors.

Takashige KuwabaraDepartment of Nephrology, Kumamoto University Graduate School of Medical Sciences, Kumamoto, Japan.ORCID https://orcid.org/0000-0003-3507-4328
Yoshikazu MiyasatoDepartment of Nephrology, Kumamoto University Graduate School of Medical Sciences, Kumamoto, Japan.
Tomoko KankiDepartment of Nephrology, Kumamoto University Graduate School of Medical Sciences, Kumamoto, Japan.
Teruhiko MizumotoDepartment of Nephrology, Kumamoto University Graduate School of Medical Sciences, Kumamoto, Japan.
Takeshi MatsubaraDepartment of Nephrology, Kyoto University Graduate School of Medicine, Kyoto, Japan.
Naoki SawaNephrology Center, Toranomon Hospital Kajigaya, Kanagawa, Japan.
Hitoshi SugiyamaDepartment of Medicine, Kawasaki Medical School General Medical Center and Department of Medical Care Work, Kawasaki College of Allied Health Professions, Okayama, Japan.
Shoichi MaruyamaDepartment of Nephrology, Nagoya University Graduate School of Medicine, Nagoya, Japan.ORCID https://orcid.org/0000-0002-8858-632X
Hiroshi SatoDepartment of Nephrology, Rheumatology and Endocrinology, Tohoku University Graduate School of Medicine, Sendai, Miyagi, Japan.
Tatsuo TsukamotoDepartment of Nephrology and Dialysis, Medical Research Institute Kitano Hospital, PIIF Tazuke-Kofukai, Osaka, Japan.
Tomohiro MurataDepartment of Cardiology and Nephrology, Mie University Graduate School of Medicine, Mie, Japan.
Mariko MiyazakiDepartment of Nephrology, Rheumatology and Endocrinology, Tohoku University Graduate School of Medicine, Sendai, Miyagi, Japan.ORCID https://orcid.org/0000-0001-6509-1706
Toshiyuki ImasawaDepartment of Nephrology, National Hospital Organization Chibahigashi National Hospital, Chiba, Japan.
Masashi MukoyamaDepartment of Nephrology, Kumamoto University Graduate School of Medical Sciences, Kumamoto, Japan.
Naoka MurakamiDivision of Nephrology, Washington University in St. Louis, St. Louis, MO, USA.
Kenar D JhaveriGlomerular Center at Northwell Health, Division of Kidney Diseases and Hypertension, Northwell Health, Great Neck, NY, USA.ORCID https://orcid.org/0000-0003-1578-0524
Motoko YanagitaDepartment of Nephrology, Kyoto University Graduate School of Medicine, Kyoto, Japan.ORCID https://orcid.org/0000-0002-0339-9008
JSN Onconephrology working group

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Kidney complications associated with anticancer drug therapy have greatly increased recently. We aimed to investigate the real-world clinical outcomes of anticancer drug therapy-associated renal complications in Japan using the national kidney biopsy database, Japan Renal Biopsy Registry (J-RBR). Methods: From 2018 to 2021, 449 cases from 49 facilities identified as 'drug-induced' histopathology in the J-RBR were screened, of which a total of 135 were confirmed as anticancer drug-related cases and included in the analysis. Overall survival rates were estimated using the Kaplan-Meier method and compared by logrank test. The Cox regression model was used to evaluate the association between variables and deaths. Results: The most common primary sites of malignancies were the lung (33.3%), followed by gastrointestinal (16.3%) and gynaecological (11.1%) cancers. Tubulointerstitial nephritis (TIN; 47.4%) and thrombotic microangiopathy (TMA; 35.6%) were the most frequent diagnoses. All immunoglobulin A nephropathy, minimal change disease and crescentic glomerulonephritis (CrGN) cases were immune checkpoint inhibitor related. All CrGN cases were anti-neutrophil cytoplasmic antibody negative. Antibiotics were most frequently used concomitantly with anticancer drugs in TMA cases among subgroups (TMA versus others: 62.5 versus 27.5%; Conclusions: Our registry analysis highlighted various presentations of biopsy-proven kidney complications associated with anticancer drug therapy. Clinicians should be aware of worse outcomes associated with CTx-TMA and the prognostic role of PPI use.

Indexed as

anticancer drug therapykidney biopsy registry databasePPI usethrombotic microangiopathy

Identifiers

PMID39664993
PMCPMC11630032

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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.