Evidence map›Paper›PMID 34844553›Full record

ArticleBMC infectious diseases2021

Simple-to-use nomogram for predicting the risk of syphilis among MSM in Guangdong Province: results from a serial cross-sectional study.

Peizhen Zhao, Ziying Yang, Baohui Li, Mingzhou Xiong, Ye Zhang, Jiyuan Zhou, Cheng Wang

Open access · goldAbstract read
In one paragraph

Article in BMC infectious diseases, 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
0.8field-weighted citation impact, top 27% 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, 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

7 authors at 1 institution in 1 country.

Peizhen ZhaoDepartment of Biostatistics, State Key Laboratory of Organ Failure Research, Ministry of Education, and Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, China.
Ziying YangDepartment of Biostatistics, State Key Laboratory of Organ Failure Research, Ministry of Education, and Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, China.
Baohui LiDepartment of Biostatistics, State Key Laboratory of Organ Failure Research, Ministry of Education, and Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, China.
Mingzhou XiongDermatology Hospital, Southern Medical University, Guangzhou, China.
Ye ZhangKirby Institute, New South Wales University, Sydney, Australia.
Jiyuan ZhouDepartment of Biostatistics, State Key Laboratory of Organ Failure Research, Ministry of Education, and Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, China. zhoujiyuan5460@hotmail.com.
Cheng WangDermatology Hospital, Southern Medical University, Guangzhou, China. wangcheng090705@gmail.com.
Southern Medical University · CN

Funding

Medical Scientific Research Foundation of Guangdong Province B2021297National Natural Science Foundation of China 82173619National Nature Science Foundation of China 81773544
6 · The paper itself

Abstract

backgroundThe purpose of this study was to develop and validate a simple-to-use nomogram for the prediction of syphilis infection among men who have sex with men (MSM) in Guangdong Province.

methodsA serial cross-sectional data of 2184 MSM from 2017 to 2019 was used to develop and validate the nomogram risk assessment model. The eligible MSM were randomly assigned to the training and validation dataset. Factors included in the nomogram were determined by multivariate logistic regression analysis based on the training dataset. The receiver operating characteristic (ROC) curves was used to assess its predictive accuracy and discriminative ability.

resultsA total of 2184 MSM were recruited in this study. The prevalence of syphilis was 18.1% (396/2184). Multivariate logistic analysis found that age, the main venue used to find sexual partners, condom use in the past 6 months, commercial sex in the past 6 months, infection with sexually transmitted diseases (STD) in the past year were associated with syphilis infection using the training dataset. All these factors were included in the nomogram model that was well calibrated. The C-index was 0.80 (95% CI 0.76-0.84) in the training dataset, and 0.79 (95% CI 0.75-0.84) in the validation dataset.

conclusionsA simple-to-use nomogram for predicting the risk of syphilis has been developed and validated among MSM in Guangdong Province. The proposed nomogram shows good assessment performance.

Indexed as

HIV InfectionsSexual and Gender MinoritiesSyphilisChinaCross-Sectional StudiesHomosexuality, MaleHumansMaleNomogramsPrevalenceRisk FactorsSexual BehaviorSex WorkMen who have sex with menNomogramSyphilis

Identifiers

PMID34844553
PMCPMC8628378
OpenAlexW3217124762

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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.