Evidence map›Paper›PMID 37153061›Full record

ArticleOncology letters2023

Well‑differentiated neuroendocrine tumor of the right kidney: A case report.

Denghao Yang, Wen Tang, Tao Wu, Zeju Zhao, Guobiao Liang

Open access · diamondAbstract readCase Reports
In one paragraph

Article in Oncology letters, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
0.6field-weighted citation impact, top 30% 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

3 citing papers in PubMed, 1 synthesis or guideline pooled it, 3 citations in OpenAlex.

  1. Pooled it
  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

5 authors at 1 institution in 1 country.

Denghao YangDepartment of Urology, The Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China.
Wen TangDepartment of Urology, The Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China.
Tao WuDepartment of Urology, The Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China.
Zeju ZhaoDepartment of Urology, The Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China.
Guobiao LiangDepartment of Urology, The Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China.
Zunyi Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Neuroendocrine tumors (NETs) are tumors originating from neuroendocrine cells and peptidergic neurons. Primary renal well-differentiated NETs (WDNETs) are rare and only sporadic cases have been reported worldwide. In November 2021, a 45-year-old female patient was admitted to The Affiliated Hospital of Zunyi Medical University (Zunyi, China) with right-sided lumbago. Abdominal computed tomography revealed a 44×34×70-mm mass in the right kidney. Following a complete examination, a laparoscopic partial nephrectomy of the right kidney was performed under general anesthesia. The postoperative pathology indicated a well-differentiated NET of the right kidney. There was no tumor recurrence or metastasis during the 1-year follow-up period. WDNETs are rare, their clinical and imaging findings are not specific, and their diagnosis depends on immunohistochemical analysis. The degree of malignancy is low and the prognosis is positive. Surgical resection is often the first choice, and long-term follow-up is required.

Indexed as

case reportprimary renal carcinoid tumorsrenal neoplasmsrenal neuroendocrine neoplasmswell-differentiated neuroendocrine tumor of the kidney

Identifiers

PMID37153061
PMCPMC10161357
OpenAlexW4366596333

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.