Differentiating tuberculous pleurisy from pulmonary tuberculosis using mNGS: a multicenter cohort analysis

Tuberculous pleurisy (TBP), a major extrapulmonary form of tuberculosis, is characterized by a paucibacillary state that makes diagnosis challenging. Metagenomic next-generation sequencing (mNGS) has emerged as a promising approach for MTB detection; however, its discriminatory value between TBP and pulmonary tuberculosis (PTB) among mNGS-confirmed cases, and its integration with clinical features for differential diagnosis, remain insufficiently defined.

This multicenter retrospective cohort included hospitalized patients with MTB-positive mNGS results from January 2020 to January 2025. As only mNGS-positive cases were included, overall mNGS diagnostic sensitivity cannot be estimated. Twelve TBP patients were matched 1:2 with twenty-four PTB patients by age and sex; patients with immunosuppressive conditions were excluded prior to matching. Clinical, laboratory, mNGS, and conventional TB test data were collected. Logistic regression and ROC analyses were performed.

Conventional tests showed limited sensitivity in TBP despite universal mNGS positivity. MTB read counts were similar between groups (median 1976.5 vs. 990.0, P = 0.920). Pleural-derived specimens predominated in TBP (41.7% vs. 4.2%, P = 0.007). CRP demonstrated the highest individual discriminatory value (AUC = 0.658, P = 0.131), though no single predictor reached significance. A combined model (cough, fever, CRP, WBC) showed modest non-significant improvement (AUC = 0.722, overall P = 0.359; sensitivity 66.7%, specificity 83.3%). Given EPV ≈ 3, all findings are exploratory only. No significant prognostic predictors were identified in TBP; a non-significant trend toward lower lymphocyte counts was observed in patients with unfavorable outcomes (0.60 vs. 1.10 ×10⁹/L, P = 0.115).

Among mNGS-confirmed cases, MTB read counts were comparable between TBP and PTB. No single parameter reliably distinguished the two; a combined clinical model showed modest improvement but requires prospective validation in larger cohorts. Integrating mNGS with systematic clinical evaluation remains essential for accurate TB diagnosis.