Evidence map›Paper›PMID 42082984›Full record

ArticleBMC pulmonary medicine2026

Derivation and validation of a clinical prediction model incorporating the pleural fluid ADA-to-LDH ratio for differentiating tuberculous from malignant pleural effusions: a multi-center study.

Zhiyu Pan, Sha Tao, Haoyu Sheng, Xiuliang Xu, Zhixin Lin, Fen Huang, Fang Liu, Yajuan Wang, Yihui Sun, Yingchun Sun and 2 more

Abstract readMulticenter StudyValidation Study
In one paragraph

Article in BMC pulmonary medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. A diagnostic nomogram for tuberculous pleural effusion: Methodological considerations.Journal of clinical tuberculosis and other mycobacterial diseases · 2026
    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

12 authors.

Zhiyu Pan *Department of Infectious Diseases, The First Affiliated Hospital of Wannan Medical University (Yijishan Hospital of Wannan Medical University), Wuhu, Anhui, People's Republic of China.
Sha Tao *Department of Infectious Diseases, The First Affiliated Hospital of Wannan Medical University (Yijishan Hospital of Wannan Medical University), Wuhu, Anhui, People's Republic of China.
Haoyu Sheng *Department of Infectious Diseases, The First Affiliated Hospital of Wannan Medical University (Yijishan Hospital of Wannan Medical University), Wuhu, Anhui, People's Republic of China.
Xiuliang Xu *Department of Infectious Diseases, The People's Hospital of Chizhou, Chizhou, Anhui, People's Republic of China.
Zhixin LinDepartment of Infectious Diseases, The Second People's Hospital of Tongling, Tongling, Anhui, People's Republic of China.
Fen HuangDepartment of Infectious Diseases, The Third People's Hospital of Wuhu, Wuhu, Anhui, People's Republic of China.
Fang LiuDepartment of Infectious Diseases, The Fourth People's Hospital of Ma'anshan, Ma'anshan, Anhui, People's Republic of China.
Yajuan WangDepartment of Infectious Diseases, The First Affiliated Hospital of Wannan Medical University (Yijishan Hospital of Wannan Medical University), Wuhu, Anhui, People's Republic of China.
Yihui SunDepartment of Infectious Diseases, The First Affiliated Hospital of Wannan Medical University (Yijishan Hospital of Wannan Medical University), Wuhu, Anhui, People's Republic of China.
Yingchun SunDepartment of Infectious Diseases, The First Affiliated Hospital of Wannan Medical University (Yijishan Hospital of Wannan Medical University), Wuhu, Anhui, People's Republic of China.
Wei QianDepartment of Infectious Diseases, The Second People's Hospital of Tongling, Tongling, Anhui, People's Republic of China.
Jianghua YangDepartment of Infectious Diseases, The First Affiliated Hospital of Wannan Medical University (Yijishan Hospital of Wannan Medical University), Wuhu, Anhui, People's Republic of China. yjhpath@163.com.

Funding

Clinical and Translational Research Special Project of Anhui Province 202527c10020098Key University Science Research Project of Anhui KJ2014A271National Natural Science Foundation of China (Youth Fund) 82204458National Science Foundation of China 30700694project of health soft science and research of Anhui Province 2020WR02013
6 · The paper itself

Abstract

backgroundAccurate discrimination between tuberculous (TPE) and malignant pleural effusion (MPE) is a major clinical challenge. Most existing models rely on non-routine laboratory tests and lack rigorous multicenter external validation.

objectiveTo develop and validate a clinical prediction model integrating the pleural fluid adenosine deaminase to lactate dehydrogenase ratio (ADA/LDH) and routine indicators for TPE vs. MPE differentiation.

methodsIn this multicenter retrospective study conducted between January 2023 and December 2025, patients from five hospitals in Anhui Province, China, were divided into a training cohort (n = 290), an internal validation cohort (n = 72), and an external validation cohort (n = 93). Predictors were screened via univariable analysis and backward stepwise regression based on the Akaike Information Criterion (AIC). The optimal ADA/LDH cutoff was identified as 5.83% using restricted cubic splines (RCS) and simplified to 6.0% for clinical practicability without compromising model performance. A Firth penalized logistic regression model was constructed to mitigate data separation caused by the strong predictive effect of the ADA/LDH ratio.

resultsThe final model included three statistically significant variables: pleural fluid ADA/LDH ratio (≥ 6.0% vs. < 6.0%), age, and sex. An ADA/LDH ratio ≥ 6.0% was the strongest independent predictor (OR = 13.32, 95% CI 6.51-27.28, P < 0.001). The model demonstrated excellent and stable discriminative ability with AUCs of 0.901 (training cohort), 0.893 (internal validation cohort), and 0.916 (external validation cohort). Calibration was good across all cohorts (Brier scores: 0.1235, 0.1249, 0.1159, respectively). Decision curve analysis demonstrated that the model provided numerically higher net benefit than the "treat all" and "treat none" strategies across the clinically relevant threshold range of 0%-90%.

conclusionThis multicenter study developed and validated a robust Firth penalized prediction model centered on the pleural fluid ADA/LDH ratio. The model demonstrates excellent discriminative ability, good calibration, and potential clinical utility for differentiating TPE from MPE in TB-endemic regions of China.

Indexed as

Adenosine DeaminaseL-Lactate DehydrogenasePleural Effusion, MalignantTuberculosis, PleuralAgedChinaDiagnosis, DifferentialFemaleHumansLogistic ModelsMaleMiddle AgedRetrospective StudiesAdenosine DeaminaseL-Lactate DehydrogenaseAdenosine deaminaseDifferential diagnosisLactate dehydrogenaseMalignantMulticenter studyPleural effusionPrediction modelTuberculous

Identifiers

PMID42082984
PMCPMC13285072

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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.