Evidence map›Paper›PMID 40255560›Full record

ArticleFrontiers in pharmacology2025

Bone loss in young adults with HIV following antiretroviral therapy containing tenofovir disoproxil fumarate regimen using machine learning.

Ling Chen, Jia Tang, Leidan Zhang, Liyuan Zheng, Fada Wang, Fuping Guo, Yang Han, Xiaojing Song, Wei Lv, Wei Cao and 1 more

Abstract read
In one paragraph

Article in Frontiers in pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
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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

11 authors.

Ling ChenDepartment of Infectious Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Jia TangDepartment of Infectious Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Leidan ZhangDepartment of Infectious Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Liyuan ZhengDepartment of Infectious Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Fada WangDepartment of Infectious Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Fuping GuoDepartment of Infectious Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Yang HanDepartment of Infectious Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Xiaojing SongDepartment of Infectious Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Wei LvDepartment of Infectious Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Wei CaoDepartment of Infectious Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Taisheng LiDepartment of Infectious Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Bone mineral density (BMD) monitoring, primarily relying on dual-energy X-ray absorptiometry (DEXA), remains inaccessible in resource-limited regions, making it difficult to promptly address bone loss in people with HIV (PWH) on long-term ART-containing TDF regimens and assess the prevalence of bone loss. Our objective is to identify the frequency of PWH experiencing bone loss after long-term ART with a TDF regimen and to develop a predictive model of HIV-infected high-risk populations containing TDF long-time ART, for providing more appropriate ART regimens for PWH in clinical practice, particularly in resource-limited settings. Methods: Our study retrospectively screened PWH under long-term follow-up at Peking Union Medical College Hospital (PUMCH) from January 2000 to August 2024. These individuals were either treatment-naive or treatment-experienced and had been on containing TDF ART regimen for over 5 years. BMD was assessed using DEXA every 1-2 years in this center. We selected predictive factors utilizing machine learning methods, including Random Forest, XGBoost, LASSO regression, and logistic regression. The results were visualized using a nomogram. Results: Our study enrolled a total of 232 PWH who have contained TDF ART regimens for more than 5 years. Twenty-five percent (58/232) of the patients experienced bone loss, primarily including osteopenia and osteoporosis. Further results showed that the LASSO regression model was the most suitable for the current dataset, based on a comparison of LASSO regression, Random Forest, XGBoost, and logistic regression models including age, gender, LPV/r, baseline CD4+ T count, baseline VL, baseline body weight, treatment-naïve TDF, ART duration, percentage of CD38+CD8+T, percentage of HLA-DR+CD8 Conclusion: Our study quantified the frequency and established a nomogram based on the LASSO regression model to predict bone loss in PWH on long-term containing TDF ART. The nomogram guides identifying individuals at high risk of bone loss due to prolonged TDF exposure. Clinicians can leverage the predicted risk to design personalized ART regimens at the initiation of therapy or to switch from TDF-containing to TDF-free regimens during treatment. This approach aims to reduce the incidence of bone loss, particularly in resource-limited settings.

Indexed as

antiretroviral therapybone lossHIVmachine learningtenofovir disoproxil fumarate

Identifiers

PMID40255560
PMCPMC12006115

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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.