Evidence map›Paper›PMID 32572372›Full record

ArticleJournal of bone metabolism2020

The Effect of Denosumab on Bone Mass in Super Elderly Patients.

Chaiho Jeong, Jeonghoon Ha

Open access · hybridAbstract read
In one paragraph

Article in Journal of bone metabolism, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
0.4field-weighted citation impact, top 44% 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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. 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

2 authors at 1 institution in 1 country.

Chaiho JeongDivision of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.ORCID https://orcid.org/0000-0002-2914-2278
Jeonghoon HaDivision of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.ORCID https://orcid.org/0000-0001-9219-7135
The Catholic University of Korea Seoul St. Mary's Hospital · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDenosumab is a potent antiresorptive drug leading to significant reduction in the risk of vertebral and non-vertebral fractures in postmenopausal osteoporosis. The effect of denosumab in super-elderly patients lacks data to date and few literature has proven the efficacy to this specific group. The purpose of this study was to determine the effectiveness and safety of denosumab in the super-elderly.

methodsWe retrospectively evaluated 60 patients older than 80 with osteoporosis treated with denosumab. Patients were treated with denosumab every 6 months for 12 months 2017 to 2020. The primary endpoint was defined by the changes in bone mineral density (BMD) of 3 measurement sites: the lumbar spine, femoral neck, and total hip. Changes in bone turnover markers, serum calcium, serum phosphate, and 25-hydroxy-vitamin D were also observed.

resultsAll 60 patients were female, and the mean age was 83.9±3.1, from age 80 to 94. After 12 months of denosumab treatment, significant increases in BMD were observed; 3.02±2.74% for the lumbar spine (

conclusionsDenosumab is thought to be an anti-osteoporotic medication that is sufficiently effective and safe even for the super-elderly.

Indexed as

AgedBone densityDenosumabOsteoporosis

Identifiers

PMID32572372
PMCPMC7297623
OpenAlexW3034033500

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.