Evidence map›Paper›PMID 36082100›Full record

ArticleGland surgery2022

Correlations between dynamic-enhanced magnetic resonance imaging quantitative parameters and postoperative recurrence or metastasis and clinicopathological features in breast cancer patients-a retrospective cohort study.

Xuelian Chen, Qian Gao, Zhijuan Wu, Hongyan Wang, Jianliang Wang

Abstract read
In one paragraph

Article in Gland surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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

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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 synthesis or guideline pooled it.

  1. Pooled it
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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.

Xuelian ChenDepartment of Radiology, Affiliated Kunshan Hospital of Jiangsu University, Kunshan, China.
Qian GaoDepartment of Radiology, Affiliated Kunshan Hospital of Jiangsu University, Kunshan, China.
Zhijuan WuDepartment of Radiology, Affiliated Kunshan Hospital of Jiangsu University, Kunshan, China.
Hongyan WangDepartment of Radiology, Affiliated Kunshan Hospital of Jiangsu University, Kunshan, China.
Jianliang WangDepartment of Radiology, Affiliated Kunshan Hospital of Jiangsu University, Kunshan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Few related studies focused on the correlations between the quantitative parameters of dynamic-enhanced magnetic resonance imaging (MRI) and the clinical pathological characteristics of patients with invasive breast cancer have been conducted to date. This study sought to explore the value of quantitative parameters of dynamic-enhanced MRI in predicting postoperative recurrence or metastasis in breast cancer patients and their correlations with clinical pathological features, so as to provide clinicians with understanding of MRI in breast cancer. Methods: From January 2016 to June 2017, 214 invasive breast cancer patients admitted to Affiliated Kunshan Hospital of Jiangsu University were retrospectively enrolled in this study. Dynamic-enhanced MRI was performed to analyze the relationship between quantitative parameters of dynamic-enhanced MRI and recurrence or metastasis, and analyze their correlations with clinical pathological features in patients with invasive breast cancer. Results: The apparent diffusion coefficient and peak time had certain diagnostic value for postoperative recurrence or metastasis in breast cancer patients, and the areas under the curve were 0.821 [95% confidence interval (CI): 0.732-0.911; P<0.001] and 0.691 (95% CI: 0.609-0.774; P<0.001), respectively. An apparent diffusion coefficient <0.78×10 Conclusions: The quantitative parameters of MRI were associated with clinical pathological characteristics and recurrence or metastasis in breast cancer after surgery.

Indexed as

apparent diffusion coefficient (ADC)Dynamic-enhanced magnetic resonance imaging (dynamic-enhanced MRI)invasive breast cancerpeak time

Identifiers

PMID36082100
PMCPMC9445722

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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.