Evidence map›Paper›PMID 36018066›Full record

ArticleAsian journal of andrology

Comparison of the predictive value of anthropometric indicators for the risk of benign prostatic hyperplasia in southern China.

Meng-Jun Huang, Yan-Yi Yang, Can Chen, Rui-Xiang Luo, Chu-Qi Wen, Yang Li, Ling-Peng Zeng, Xiang-Yang Li, Zhuo Yin

Open access · goldAbstract read
In one paragraph

Article in Asian journal of andrology. 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
1.1field-weighted citation impact, top 22% 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, 7 citations in OpenAlex.

  1. Pooled it
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  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

9 authors at 2 institutions in 1 country.

Meng-Jun HuangDepartment of Urology, The Second Xiangya Hospital of Central South University, Changsha 410011, China.
Yan-Yi YangHealth Management Center, The Second Xiangya Hospital of Central South University, Changsha 410011, China.
Can ChenDepartment of Urology, The Second Xiangya Hospital of Central South University, Changsha 410011, China.
Rui-Xiang LuoDepartment of Urology, The Second Xiangya Hospital of Central South University, Changsha 410011, China.
Chu-Qi WenDepartment of Urology, The Second Xiangya Hospital of Central South University, Changsha 410011, China.
Yang LiDepartment of Urology, The Second Xiangya Hospital of Central South University, Changsha 410011, China.
Ling-Peng ZengDepartment of Urology, The Second Xiangya Hospital of Central South University, Changsha 410011, China.
Xiang-Yang LiDepartment of Urology, The Second Xiangya Hospital of Central South University, Changsha 410011, China.
Zhuo YinDepartment of Urology, The Second Xiangya Hospital of Central South University, Changsha 410011, China.
Central South University · CNSecond Xiangya Hospital of Central South University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to compare the predictive value of six selected anthropometric indicators for benign prostatic hyperplasia (BPH). Males over 50 years of age who underwent health examinations at the Health Management Center of the Second Xiangya Hospital, Central South University (Changsha, China) from June to December 2020 were enrolled in this study. The characteristic data were collected, including basic anthropometric indices, lipid parameters, six anthropometric indicators, prostate-specific antigen, and total prostate volume. The odds ratios (ORs) with 95% confidence intervals (95% CIs) for all anthropometric parameters and BPH were calculated using binary logistic regression. To assess the diagnostic capability of each indicator for BPH and identify the appropriate cutoff values, receiver operating characteristic (ROC) curves and the related areas under the curves (AUCs) were utilized. All six indicators had diagnostic value for BPH (all P ≤ 0.001). The visceral adiposity index (VAI; AUC: 0.797, 95% CI: 0.759-0.834) had the highest AUC and therefore the highest diagnostic value. This was followed by the cardiometabolic index (CMI; AUC: 0.792, 95% CI: 0.753-0.831), lipid accumulation product (LAP; AUC: 0.766, 95% CI: 0.723-0.809), waist-to-hip ratio (WHR; AUC: 0.660, 95% CI: 0.609-0.712), waist-to-height ratio (WHtR; AUC: 0.639, 95% CI: 0.587-0.691), and body mass index (BMI; AUC: 0.592, 95% CI: 0.540-0.643). The sensitivity of CMI was the highest (92.1%), and WHtR had the highest specificity of 94.1%. CMI consistently showed the highest OR in the binary logistic regression analysis. BMI, WHtR, WHR, VAI, CMI, and LAP all influence the occurrence of BPH in middle-aged and older men (all P ≤ 0.001), and CMI is the best predictor of BPH.

Indexed as

Prostatic HyperplasiaAgedBody Mass IndexChinaHumansMaleMiddle AgedObesityRisk FactorsROC CurveWaist CircumferenceWaist-Height Ratiobenign prostate hyperplasiaobesity indexpredictive valuerisk prediction

Identifiers

PMID36018066
PMCPMC10069681
OpenAlexW4292212536

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
Read underepoch 390

Registered trials

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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.