Evidence map›Paper›PMID 30887277›Full record

ArticleEndocrine2019

Hyperprolactinemia is associated with a high prevalence of serum autoantibodies, high levels of inflammatory cytokines and an abnormal distribution of peripheral B-cell subsets.

Yaoyang Liu, Zhiguo Zhang, Qianmei Jin, Yang Liu, Zijian Kang, Yongbao Huo, Zhengwen He, Xu Feng, Jian Yin, Xin Wu and 2 more

Abstract read
PubMed Publisher
In one paragraph

Article in Endocrine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.4field-weighted citation impact, top 18% 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

8 citing papers in PubMed, 20 citations in OpenAlex.

  1. Disruption of primary ciliary prostaglandin EJournal of biomedical science · 2026
    Article
  2. Article
  3. Review
  4. Review
  5. Review
  6. Article
  7. Article
  8. Hyperprolactinaemia.Journal of clinical medicine · 2019
    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

12 authors at 1 institution in 2 countries.

Yaoyang LiuDepartment of Rheumatology and Immunology, Shanghai Changzheng Hospital, Second Military Medical University, Shanghai, China.ORCID 0000-0002-0942-9650
Zhiguo ZhangDepartment of Rheumatology and Immunology, Shanghai Changzheng Hospital, Second Military Medical University, Shanghai, China.ORCID 0000-0002-0810-5320
Qianmei JinDepartment of Rheumatology and Immunology, Shanghai Changzheng Hospital, Second Military Medical University, Shanghai, China.ORCID 0000-0002-6516-5207
Yang LiuDepartment of Cardiovascular Surgery, Shanghai Changhai Hospital, Second Military Medical University, Shanghai, China.ORCID 0000-0003-4361-3264
Zijian KangDepartment of Rheumatology and Immunology, Shanghai Changzheng Hospital, Second Military Medical University, Shanghai, China.ORCID 0000-0002-0552-5485
Yongbao HuoDepartment of Rheumatology and Immunology, Shanghai Changzheng Hospital, Second Military Medical University, Shanghai, China.ORCID 0000-0001-9419-2979
Zhengwen HeDepartment of Laboratory Diagnosis, Shanghai Changhai Hospital, Second Military Medical University, Shanghai, China.
Xu FengDepartment of Reproductive Medical Center, Shanghai Changzheng Hospital, Second Military Medical University, Shanghai, China.
Jian YinDepartment of Rheumatology and Immunology, Shanghai Changzheng Hospital, Second Military Medical University, Shanghai, China.ORCID 0000-0003-4314-2175
Xin WuDepartment of Rheumatology and Immunology, Shanghai Changzheng Hospital, Second Military Medical University, Shanghai, China.
Huaizhou WangDepartment of Laboratory Diagnosis, Shanghai Changhai Hospital, Second Military Medical University, Shanghai, China. whz_sh@163.com.ORCID 0000-0003-0948-5772
Huji XuDepartment of Rheumatology and Immunology, Shanghai Changzheng Hospital, Second Military Medical University, Shanghai, China. xuhuji@smmu.edu.cn.
Second Military Medical University · CN

Funding

Major State Basic Research Development Program of China (973 Program) 2014CB541800National Natural Science Foundation of China 81302578National Natural Science Foundation of China 81430031National Natural Science Foundation of China 81501401Pujiang Rheumatologist Training Program SPROG201703
6 · The paper itself

Abstract

purposeHyperprolactinemia (HPRL) has been reported in many autoimmune diseases. However, the serum autoantibody profile and peripheral B-cell subset distribution in women with HPRL are largely unknown. The current study aimed to investigate the autoantibody prevalence and cytokine levels as well as to further explore the B-cell subset distribution in women with HPRL.

methodsSera from 202 women with HPRL and 97 healthy women were included in this study. All sera were examined for prolactin (PRL), anti-nuclear antibody (ANA), rheumatoid factor, anticardiolipin (ACL), immunoglobulin G, immunoglobulin M, complement 3, complement 4, interleukin 4 (IL-4) and interleukin 6 (IL-6). Peripheral blood was collected from 22 women with HPRL and 19 healthy women, and B-cell subsets were measured by flow cytometry.

resultsAt least one autoantibody was found in 47 out of 202 women with HPRL compared with 9 of 97 healthy women (p < 0.001). The levels of IL-4 (p < 0.0001) and IL-6 (p < 0.0001) were significantly higher in women with HPRL than in healthy women. The percentages of naive IgD

conclusionsWomen with HPRL had a higher prevalence of autoantibodies, higher serum levels of IL-4 and IL-6, and more B

Indexed as

AdultAutoantibodiesB-Lymphocyte SubsetsCytokinesFemaleHumansHyperprolactinemiaImmunoglobulinsInflammationMiddle AgedProlactinAutoantibodiesCytokinesImmunoglobulinsProlactinAnti-nuclear antibodiesAutoantibodiesB-cell subsetsHyperprolactinemiaProlactinRheumatoid factor

Identifiers

PMID30887277
OpenAlexW2921057523

What OpenQuestion holds

Textmetadata
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.