Evidence map›Paper›PMID 40621514›Full record

ReviewPakistan journal of medical sciences2025

Perioperative blood transfusion and the prognosis of ovarian cancer surgery: A meta-analysis.

Qian-Yi Huang, Ya-Xin Huang, Wan-Yang Mu, Peng-Cheng Li

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Pakistan journal of medical sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Qian-Yi HuangQian-Yi Huang, MD Department of Transfusion, Beijing Anzhen Nanchong Hospital, Capital Medical University & Nanchong Central Hospital, 97, South Renmin Road, Shunqing District, Nanchong, Sichuan, China.
Ya-Xin HuangYa-Xin Huang, MD Department of Transfusion, Beijing Anzhen Nanchong Hospital, Capital Medical University & Nanchong Central Hospital, 97, South Renmin Road, Shunqing District, Nanchong, Sichuan, China.
Wan-Yang MuWan-Yang Mu, BA Department of Transfusion, Beijing Anzhen Nanchong Hospital, Capital Medical University & Nanchong Central Hospital, 97, South Renmin Road, Shunqing District, Nanchong, Sichuan, China.
Peng-Cheng LiPeng-Cheng Li, MD Department of Neurosurgery, Beijing Anzhen Nanchong Hospital, Capital Medical University & Nanchong Central Hospital, 97, South Renmin Road, Shunqing District, Nanchong, Sichuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Objective: Perioperative blood transfusion (PBT) is a common procedure in ovarian cancer (OC) surgery, which may be a deleterious prognosis predictor. Therefore, this study aimed to assess the impact of PBT on survival indicators in OC patients using meta-analysis. Methods: This study was performed in adherence to the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines. Relevant articles were collected by searching the PubMed, Embase, Google Scholar, and Cochrane Library databases up to September 30, 2024. A random-effects model was used to calculate pooled hazard ratios (HRs). Sensitivity analysis, sub-analysis, and publication bias were evaluated. Results: This study included nine studies, including 3,727 OC patients. 53.4% of the patients received transfusions. Overall, PBT was associated with shorter overall survival (OS), with pooled HRs of 1.44 (95% CI 1.21-1.71; P < 0.001, I Conclusions: The patients receiving PBT exhibited lower survival after OC surgery, and this impact was more pronounced in early-stage patients.

Indexed as

Meta-analysisOvarian cancerPerioperative blood transfusionPrognosis

Identifiers

PMID40621514
PMCPMC12223746

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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.