Evidence map›Paper›PMID 39210338›Full record

ReviewBMC nephrology2024

Giant retroperitoneal liposarcoma with multiple organ involvement: a case report and literature review.

Jia-Ning Sun, Rui Yang, Xiao-Lu Jiang, Feng Zhang, Hong-Wei Zhao

Abstract readCase ReportsReview
In one paragraph

Review in BMC nephrology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
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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.

Jia-Ning Sun *School of Clinical Medicine, Shandong Second Medical University, Weifang, China.
Rui Yang *School of Clinical Medicine, Shandong Second Medical University, Weifang, China.
Xiao-Lu JiangAffiliated Yantai Yuhuangding Hospital of Qingdao University, No. 20 East Yuhuangding Road, Yantai, 264000, Shandong, China.
Feng ZhangSecond Clinical Medical College, Binzhou Medical University, Yantai, China.
Hong-Wei ZhaoAffiliated Yantai Yuhuangding Hospital of Qingdao University, No. 20 East Yuhuangding Road, Yantai, 264000, Shandong, China. 15153578806@126.com.

Funding

Taishan Scholars Program of Shandong Province tsqn202211379the National Natural Science Foundation of China 81972376
6 · The paper itself

Abstract

backgroundRetroperitoneal liposarcoma (RPLPS) is a relatively rare disease. Liposarcomas vary in size, but sizeable RPLPS larger than 30 cm in diameter are very rare, and their diagnosis and treatment present significant challenges. CASE PRESENTATION: We report a 58-year-old male patient who was admitted to the hospital with an increased abdominal circumference and was later diagnosed with a giant RPLPS. The liposarcoma was found to adhere to the right kidney and the entire ureter, invading the ascending colon. The patient underwent complete combined surgical resection. The tumor was removed intact, measured 55.0 cm × 30.0 cm × 18.0 cm, and weighed 19.8 kg. Histopathologic analysis revealed well-differentiated liposarcoma (WDLPS). The patient was successfully discharged from the hospital and followed up for 6 months with no signs of recurrence.

conclusionRPLPS is a rare tumor with atypical clinical presentation. Surgery remains the most effective method of treatment for retroperitoneal sarcomas, with complete removal if there is local invasion. Preoperative examination, including three-dimensional (3D) reconstruction, is essential for surgical success. The role of adjuvant radiotherapy or chemotherapy remains controversial. However, clinicians should not rule them out as viable options.

Indexed as

LiposarcomaRetroperitoneal NeoplasmsHumansMaleMiddle AgedCase reportCombined organ resectionDiagnosisGiant sizeRetroperitoneal liposarcoma

Identifiers

PMID39210338
PMCPMC11363381

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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.