Evidence map›Paper›PMID 39026264›Full record

ArticleBMC cancer2024

Optimizing surgical strategies for retroperitoneal liposarcoma: a comprehensive evaluation of standardized aggressive surgical policies.

Dao-Ning Liu, Liang Yan, Zhong-Wu Li, Hai-Yue Wang, Xiu-Yun Tian, Ang Lv, Chun-Yi Hao

Abstract read
In one paragraph

Article in BMC cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 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

7 authors.

Dao-Ning LiuKey laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Hepato-Pancreato-Biliary Surgery/Sarcoma center, Peking University Cancer Hospital & Institute, No. 52 Fucheng Road, Haidian District, Beijing, People's Republic of China.
Liang YanKey laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Hepato-Pancreato-Biliary Surgery/Sarcoma center, Peking University Cancer Hospital & Institute, No. 52 Fucheng Road, Haidian District, Beijing, People's Republic of China.
Zhong-Wu LiKey laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Pathology, Peking University Cancer Hospital & Institute, Beijing, People's Republic of China.
Hai-Yue WangKey laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Pathology, Peking University Cancer Hospital & Institute, Beijing, People's Republic of China.
Xiu-Yun TianKey laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Hepato-Pancreato-Biliary Surgery/Sarcoma center, Peking University Cancer Hospital & Institute, No. 52 Fucheng Road, Haidian District, Beijing, People's Republic of China.
Ang LvKey laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Hepato-Pancreato-Biliary Surgery/Sarcoma center, Peking University Cancer Hospital & Institute, No. 52 Fucheng Road, Haidian District, Beijing, People's Republic of China.
Chun-Yi HaoKey laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Hepato-Pancreato-Biliary Surgery/Sarcoma center, Peking University Cancer Hospital & Institute, No. 52 Fucheng Road, Haidian District, Beijing, People's Republic of China. haochunyi@bjmu.edu.cn.ORCID http://orcid.org/0000-0002-1233-1689

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRetroperitoneal liposarcoma (RLPS) constitutes the majority of retroperitoneal sarcomas. While surgical resection remains the sole curative approach, determining the optimal surgical strategy for RLPS remains elusive. This study addresses the ongoing debate surrounding the optimal surgical strategy for RLPS.

methodsWe recruited 77 patients with RLPS who underwent aggressive surgical policies. Patients were categorized into three surgical subtypes: suprapancreatic RLPS, pancreatic RLPS, and subpancreatic RLPS. Our standardized surgical strategy involved resecting macroscopically uninvolved adjacent organs according to surgical subtypes. We collected clinical, pathological and prognostic data for analyses.

resultsThe median follow-up was 45.5 months. Overall survival (OS) and recurrence-free survival (RFS) were significantly correlated with multifocal RLPS, pathological subtype, recurrent RLPS and histological grade (P for OS = 0.011, 0.004, 0.010, and < 0.001, P for RFS = 0.004, 0.001, < 0.001, and < 0.001, respectively). The 5-Year Estimate OS of well-differentiated liposarcoma (WDLPS), G1 RLPS, de novo RLPS and unifocal RLPS were 100%, 89.4%, 75.3% and 69.1%, respectively. The distant metastasis rate was 1.4%. The morbidity rates (≥ grade III) for suprapancreatic, pancreatic, and subpancreatic RLPS were 26.7%, 15.6%, and 13.3%, respectively. The perioperative mortality rate is 2.6%.

conclusionsStandardized aggressive surgical policies demonstrated prognostic benefits for RLPS, particularly for G1 RLPS, WDLPS, unifocal RLPS, and de novo RLPS. This approach effectively balanced considerations of adequate exposure, surgical safety, and thorough removal of all fat tissue. G1 RLPS, WDLPS, unifocal RLPS, and de novo RLPS could be potential indications for aggressive surgical policies.

Indexed as

LiposarcomaRetroperitoneal NeoplasmsAdultAgedAged, 80 and overFemaleFollow-Up StudiesHumansMaleMiddle AgedNeoplasm Recurrence, LocalPrognosisRetrospective StudiesLiposarcomaPrognostic factorsRetroperitoneumSurgical indicationsSurgical procedures

Identifiers

PMID39026264
PMCPMC11256468

What OpenQuestion holds

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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.