Evidence map›Paper›PMID 40128016›Full record

ArticleMedicine2025

A case report of giant retroperitoneal liposarcoma.

Zicheng Bao, Nan Jia, Zhidong Zhang, Pingan Ding, Qun Zhao, Xuefeng Zhao, Yong Li

Abstract readCase Reports
In one paragraph

Article in Medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Giant retroperitoneal leiomyosarcoma of massive proportions: a case report.International journal of surgery case reports · 2026
    Article
  2. 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

7 authors.

Zicheng BaoThird Department of Surgery, Fourth Hospital of Hebei Medical University, Shijiazhuang 050011, China.ORCID 0009-0004-3636-7952
Zhidong Zhang
Pingan Ding
Qun Zhao
Xuefeng Zhao
Yong Li

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

rationaleRetroperitoneal liposarcoma (RPLS) is a rare malignancy with a high recurrence rate. Giant RPLS (≥30 cm) poses significant surgical challenges due to its invasive nature and compression of vital organs. Early diagnosis and multidisciplinary management are critical yet underreported in young patients. This case highlights the complexity of managing a 36-year-old male with a 60 cm × 50 cm × 40 cm tumor, emphasizing the importance of surgical precision and collaborative care. PATIENT CONCERNS: The patient is a 36-year-old male who was admitted to the hospital due to abdominal distension presenting for over 7 months, accompanied by a rapid increase in abdominal girth for over the past 2 months. Based on his symptoms, physical examination findings, and imaging studies, the possibility of a giant retroperitoneal liposarcoma was considered. DIAGNOSES: Giant retroperitoneal liposarcoma.

interventionsThe treatment involved the resection of the massive retroperitoneal tumor, along with partial resection of the descending colon, left ureterostomy drainage, and release of intestinal adhesions. OUTCOMES: The patient was discharged 14 days postoperatively with no immediate complications. Albumin levels improved to 35.2 g/L at 1-month follow-up. Telephone follow-ups at 3, 6, 12 months, and 5 years revealed no signs of recurrence on abdominal ultrasound. LESSONS: The tumor had already invaded the surrounding organ tissues at the time of discovery in this case. Comprehensive preoperative evaluation, multidisciplinary collaboration in diagnosis and treatment, precise surgical techniques, and standardized intraoperative and postoperative management are essential to enhance surgical resection rates, minimize complications, and decrease the likelihood of postoperative recurrence.

Indexed as

LiposarcomaRetroperitoneal NeoplasmsAdultHumansMale

Identifiers

PMID40128016
PMCPMC11936651

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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.