Evidence map›Paper›PMID 39649259›Full record

ReviewArchives of medical science : AMS2024

A meta-analysis of the association between preoperative magnetic resonance imaging and surgical outcomes in newly diagnosed breast cancer.

Li-Li Xie, Zhi-Hong Xu, Deng-Hui Wei, Chun-Sen Xu

Abstract readReview
In one paragraph

Review in Archives of medical science : AMS, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  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

4 authors.

Li-Li XieFujian Medical University Union Hospital, Fuzhou, Fujian Province, China.
Zhi-Hong XuFujian Medical University Union Hospital, Fuzhou, Fujian Province, China.
Deng-Hui WeiFujian Medical University Union Hospital, Fuzhou, Fujian Province, China.
Chun-Sen XuFujian Medical University Union Hospital, Fuzhou, Fujian Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The use of preoperative magnetic resonance imaging (MRI) in newly diagnosed breast cancer has been increasing. However, the value of MRI applied to women with newly diagnosed breast cancer remains controversial. Therefore, this study focused on the association between preoperative MRI and surgical outcomes, which include mastectomy rate, breast conservation rate, and re-excision rate. Material and methods: A systematic literature search was performed by the Wanfang, VIP (Chinese biomedical databases), PubMed, Cochrane Library, and Embase, databases. The keywords were "breast cancer", "magnetic resonance imaging", "mastectomy rate", "re-excision rate", and "breast conservation rate". A random-effects model was used to estimate the proportion of women with various outcomes in the MRI group versus the non-MRI group. The odds ratio (OR) for each surgical outcome was calculated. Results: 4 RCTs (randomized controlled trials) met the eligibility criteria that included a total of 2312 patients with breast cancer. The analysis results of the MRI group versus the non-MRI group were as follows: mastectomy rate of 15% versus 10%, OR = 2.01, 95% CI: 0.79-5.11, Conclusions: There was no significant association between preoperative MRI and surgical outcomes. This study suggested that the use of preoperative MRI should be selective. The results showed that the application of preoperative MRI did not improve the prognosis of breast cancer patients. More randomized trials are needed for further study due to limited randomized trials.

Indexed as

breast cancerbreast conservation ratemagnetic resonance imagingmastectomy ratemeta-analysisre-excision rate

Identifiers

PMID39649259
PMCPMC11623173

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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.