Evidence map›Paper›PMID 34414899›Full record

ArticleEndocrine connections2021

Novel nomogram for predicting the 3-year incidence risk of osteoporosis in a Chinese male population.

Yaqian Mao, Lizhen Xu, Ting Xue, Jixing Liang, Wei Lin, Junping Wen, Huibin Huang, Liantao Li, Gang Chen

Open access · goldAbstract read
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Article in Endocrine connections, 2021. 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
1.2field-weighted citation impact, top 23% 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

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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

4 citing papers in PubMed, 7 citations in OpenAlex.

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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

9 authors at 3 institutions in 1 country.

Yaqian MaoShengli Clinical Medical College of Fujian Medical University, Fujian, China.
Lizhen XuShengli Clinical Medical College of Fujian Medical University, Fujian, China.
Ting XueShengli Clinical Medical College of Fujian Medical University, Fujian, China.
Jixing LiangDepartment of Endocrinology, Fujian Provincial Hospital, Fujian, China.
Wei LinDepartment of Endocrinology, Fujian Provincial Hospital, Fujian, China.
Junping WenDepartment of Endocrinology, Fujian Provincial Hospital, Fujian, China.
Huibin HuangDepartment of Endocrinology, Fujian Provincial Hospital, Fujian, China.
Liantao LiDepartment of Endocrinology, Fujian Provincial Hospital, Fujian, China.
Gang ChenShengli Clinical Medical College of Fujian Medical University, Fujian, China.
Fujian Provincial Hospital · CNFujian Medical University · CNFujian Academy of Medical Sciences · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo establish a rapid, cost-effective, accurate, and acceptable osteoporosis (OP) screening model for the Chinese male population (age ≥ 40 years) based on data mining technology. MATERIALS AND

methodsThis was a 3-year retrospective cohort study, which belonged to the sub-cohort of the Chinese Reaction Study. The research period was from March 2011 to December 2014. A total of 1834 subjects who did not have OP at the baseline and completed a 3-year follow-up were included in this study. All subjects underwent quantitative ultrasound examinations for calcaneus at the baseline and follow-ups that lasted for 3 years. We utilized the least absolute shrinkage and selection operator (LASSO) regression model to select feature variables. The characteristic variables selected in the LASSO regression were analyzed by multivariable logistic regression (MLR) to construct the predictive model. This predictive model was displayed through a nomogram. We used the receiver operating characteristic (ROC) curve, C-index, calibration curve, and clinical decision curve analysis (DCA) to evaluate model performance and the bootstrapping validation to internally validate the model.

resultsThe predictive factors included in the prediction model were age, neck circumference, waist-to-height ratio, BMI, triglyceride, impaired fasting glucose, dyslipidemia, osteopenia, smoking history, and strenuous exercise. The area under the ROC (AUC) curve of the risk nomogram was 0.882 (95% CI, 0.858-0.907), exhibiting good predictive ability and performance. The C-index for the risk nomogram was 0.882 in the prediction model, which presented good refinement. In addition, the nomogram calibration curve indicated that the prediction model was consistent. The DCA showed that when the threshold probability was between 1 and 100%, the nomogram had a good clinical application value. More importantly, the internally verified C-index of the nomogram was still very high, at 0.870.

conclusionsThis novel nomogram can effectively predict the 3-year incidence risk of OP in the male population. It also helps clinicians to identify groups at high risk of OP early and formulate personalized intervention measures.

Indexed as

data miningmale patientsnomogramosteoporosisrisk factors

Identifiers

PMID34414899
PMCPMC8494413
OpenAlexW3193904928

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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.