Evidence map›Paper›PMID 32615705›Full record

ReviewEndocrinology and metabolism (Seoul, Korea)2020

Precision Therapy in Acromegaly Caused by Pituitary Tumors: How Close Is It to Reality?

Cheol Ryong Ku, Vladimir Melnikov, Zhaoyun Zhang, Eun Jig Lee

Abstract readReview
In one paragraph

Review in Endocrinology and metabolism (Seoul, Korea), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Review
  3. The Future of Somatostatin Receptor Ligands in Acromegaly.The Journal of clinical endocrinology and metabolism · 2022
    Review
  4. 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

4 authors.

Cheol Ryong KuDivision of Endocrinology, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Korea.
Vladimir MelnikovDepartment of Endocrinology and Metabolism, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China.
Zhaoyun ZhangDepartment of Endocrinology and Metabolism, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China.
Eun Jig LeeDivision of Endocrinology, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acromegaly presents with an enigmatic range of symptoms and comorbidities caused by chronic and progressive growth hormone elevations, commonly due to endocrinologic hypersecretion from a pituitary gland tumor. Comprehensive national acromegaly databases have been appearing over the years, allowing for international comparisons of data, although still presenting varying prevalence and incidence rates. Lack of large-scale analysis in geographical and ethnic differences in clinical presentation and management requires further research. Assessment of current and novel predictors of responsiveness to distinct therapy can lead to multilevel categorization of patients, allowing integration into new clinical guidelines and reduction of increased morbidity and mortality associated with acromegaly. This review compares current data from epidemiological studies and assesses the present-day application of prognostic factors in medical practice, the reality of precision therapy, as well as its future prospects in acromegaly, with a special focus on its relevance to the South Korean population.

Indexed as

Precision MedicineAcromegalyHuman Growth HormoneHumansPituitary NeoplasmsHuman Growth HormoneAcromegalyGrowth hormonePituitary neoplasmsPrecision medicine

Identifiers

PMID32615705
PMCPMC7386101

What OpenQuestion holds

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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.