Evidence map›Paper›PMID 33842591›Full record

ArticleAnnals of translational medicine2021

Assessing the risk of rapid fibroid growth in patients with asymptomatic solitary uterine myoma using a multivariate prediction model.

Qingxiu Li, Jiehui Zhong, Dongyi Yi, Genqiang Deng, Zezhen Liu, Wei Wang

Open access · diamondAbstract read
In one paragraph

Article in Annals of translational medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.9field-weighted citation impact, top 14% of its field
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

6 citing papers in PubMed, 17 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
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

6 authors at 3 institutions in 1 country.

Qingxiu LiHealth Management Medical Center, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Jiehui ZhongDepartment of Urology, Minimally Invasive Surgery Center, Guangdong Key Laboratory of Urology, Guangzhou Urology Research Institute, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Dongyi YiNetwork and Information Technology Department, Huazhong University of Science and Technology Union Shenzhen Hospital, Shenzhen, China.
Genqiang DengNetwork and Information Technology Department, Huazhong University of Science and Technology Union Shenzhen Hospital, Shenzhen, China.
Zezhen LiuDepartment of Urology, Minimally Invasive Surgery Center, Guangdong Key Laboratory of Urology, Guangzhou Urology Research Institute, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Wei WangDepartment of Obstetrics and Gynecology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Guangzhou Medical University · CNHuazhong University of Science and Technology · CNFirst Affiliated Hospital of Guangzhou Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLong-term conservative approaches are effective management options for asymptomatic uterine fibroids, but not for uterine myomas with excessive growth. In this investigation, a regression model was constructed to evaluate the clinical characteristics related to uterine fibroids' growth.

methodsIn this retrospective study, 19,840 patients with ultrasound-diagnosed uterine fibroids were identified from six centers between 2013 and 2019. In total, 739 patients were followed up for more than 1 year with B-ultrasound test results and clinical test results and had no acute events or surgical treatments. The endpoint was changed in the size of the uterine fibroids. Multivariate stepwise logistic regression analysis was used to identify predictors of uterine fibroid growth, and these were used to build a prediction model. The prediction model's discrimination, calibration, and clinical efficacy were assessed using the area under the curve (AUC)/index of concordance (C-index), calibration plot, decision curve analysis, and clinical impact curve. Internal validation was performed using bootstrapping validation. A linear regression model was constructed to predict uterine fibroids' growth rate without the occurrence of acute events.

resultsA total of 513 patients presented with significant growth of uterine fibroids, with an average follow-up time of 927 days, and 267 patients showed negative growth, with an average follow-up time of 960 days. Age, follicle-stimulating hormone (FSH), low-density lipoprotein (LDL), luteinizing hormone (LH), total cholesterol (TCHO), and neutrophil to lymphocyte ratio (NLR) were the main influential factors that predicted the uterine fibroid growth state, and these were used to develop a nomogram with predictive accuracy (AUC: 0.825). A linear regression prediction model was built based on the following factors: FSH, high-density lipoprotein (HDL), LH, triglyceride (TRIG), TCHO, and lymphocyte to monocyte ratio (LMR). The mean square error (MSE) was 0.32.

conclusionsThis study directly measured the growth rate of uterine fibroids. A prediction model assessing the growth rate of asymptomatic uterine fibroids was established. This model is useful for the early detection of potentially rapidly growing uterine fibroids in patients.

Indexed as

growth ratiolinear regression prediction modelSingle asymptomatic uterine fibroid

Identifiers

PMID33842591
PMCPMC8033343
OpenAlexW3128855402

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.