Development and validation of a prediction model for tuberculous pleural effusion: a large cohort study and external validation

A scoring model based on the pleural effusion adenosine deaminase-to-serum C-reactive protein ratio for differentiating tuberculous pleural effusion from non-tuberculous benign pleural effusion

BACKGROUND

Differentiating tuberculous pleural effusion (TPE) from non-tuberculous benign pleural effusion (non-TB BPE) can be challenging, especially in patients with low levels of pleural effusion adenosine deaminase (pADA) and negative etiological evidence. This study aimed to evaluate the diagnostic performance of the pADA to serum C-reactive protein ratio (pADA/sCRP) and to develop a scoring model for diagnosing TPE.

METHODS

This retrospective study included 364 patients with pleural effusion, comprising 121 with TPE and 243 with non-TB BPE from Peking Union Medical College Hospital. Clinical, laboratory, and imaging data were collected, and comparisons were made between the two groups. The diagnostic performance of the pADA/sCRP ratio and other statistically significant variables was assessed. Six valuable factors were selected for multivariate regression analysis to establish a predictive model, which was displayed as a nomogram.

RESULTS

The pADA/sCRP ratio demonstrated superior diagnostic performance compared to pADA alone, with an area under the curve (AUC), sensitivity, and specificity for identifying TPE of 0.68, 71%, and 64%, respectively. Six variables were selected to develop a nomogram, including night sweats, calcification on chest computed tomography, pleural effusion lymphocyte ratio, pADA/sCRP, hemoglobin, and neutrophil. With a cutoff value of 20 points, the AUC, sensitivity, and specificity for distinguishing TPE from non-TB BPE were 0.836, 83.4%, and 64.9%, respectively. The validation cohort confirmed the model with the AUC, sensitivity, and specificity of 0.815, 61.1%, and 82.4%, respectively.

CONCLUSION

The pADA/sCRP ratio exhibited improved diagnostic performance compared to pADA alone. The novel scoring system based on a nomogram demonstrated good diagnostic efficacy in differentiating TPE from non-TB BPE.

External Validation and Update of the Risk Prediction Model for Denosumab-Induced Hypocalcemia Developed From a Hospital-Based Administrative Database

PURPOSE

Denosumab is used to treat patients with bone metastasis from solid tumors, but sometimes causes severe hypocalcemia, so careful clinical management is important. This study aims to externally validate our previously developed risk prediction model for denosumab-induced hypocalcemia by using data from two facilities with different characteristics in Japan and to develop an updated model with improved performance and generalizability.

METHODS

In the external validation, retrospective data of Kameda General Hospital (KGH) and Miyagi Cancer Center (MCC) between June 2013 and June 2022 were used and receiver operating characteristic (ROC)-AUC was mainly evaluated. A scoring-based updated model was developed using the same data set from a hospital-based administrative database as previously employed. Selection of variables related to prediction of hypocalcemia was based on the results of external validation.

RESULTS

For the external validation, data from 235 KGH patients and 224 MCC patients were collected. ROC-AUC values in the original model were 0.879 and 0.774, respectively. The updated model consisting of clinical laboratory tests (calcium, albumin, and alkaline phosphatase) afforded similar ROC-AUC values in the two facilities (KGH, 0.837; MCC, 0.856).

CONCLUSION

We developed an updated risk prediction model for denosumab-induced hypocalcemia with small interfacility differences. Our results indicate the importance of using data from plural facilities with different characteristics in the external validation of generalized prediction models and may be generally relevant to the clinical application of risk prediction models. Our findings are expected to contribute to improved management of bone metastasis treatment.

Performance verification of a biochemical detection system for hydrothorax and ascites and clinical diagnostic accuracy evaluation of exudate and tuberculous effusion

Background

Lactate dehydrogenase (LDH), total protein (TP) and glucose (Glu) in pleural hydrothorax and ascites can be used in the diagnosis of exudate, and adenosine deaminase (ADA) can be used in the diagnosis of tuberculous effusion. However, the manufacturers do not claim that their biochemical reagents can be used to detect hydrothorax and ascites samples. Therefore, medical laboratories must conduct suitability studies on biochemical reagents for hydrothorax and ascites samples to comply with regulatory requirements for humor detection. This study aimed to verify the analytical performance and clinical diagnostic accuracy of the Mindray biochemical reagents, including LDH, TP, Glu and ADA, for hydrothorax and ascites.

Methods

The repeatability, detection limits and reference intervals of Mindray biochemical reagents (LDH, TP, Glu, ADA) in detecting hydrothorax and ascites were determined. The comparison of different measurement procedures was performed. Meanwhile, the diagnostic accuracy of LDH, TP, Glu and ADA were assessed.

Results

The quality control results of LDH, TP, Glu, and ADA were all under control. The repeatability coefficient of variation (%) of LDH, TP, Glu, and ADA were all less than 1%. The limits of blank of LDH, TP, Glu, and ADA were 0.33 U/L, 0.45 g/L, 0.00 mmol/L, and 0.04 U/L, respectively; the limits of detection were 1.57 U/L, 1.85 g/L, 0.05 mmol/L, and 0.12 U/L, respectively. Compared with the reference measurement program, the correlation coefficients of LDH, TP, Glu and ADA were 0.9931, 0.9983, 0.9996 and 0.9966, respectively; the regression equations were y=1.0082x-10.06, y=0.9965x-0.4732, y=0.9903x+0.0522 and y=1.0051x-0.0232, respectively. The reference intervals of LDH, TP, Glu, and ADA in hydrothorax and ascites were ≤198.39 U/L, ≤32.97 g/L, ≥5.03 mmol/L. and ≤11.00 U/L respectively. For differentiating between exudates and transudates, the area under the curve (AUC) of LDH, TP, and Glu were 0.913, 0.875, and 0.767, respectively; the AUC of ADA for the differential diagnosis of tuberculous and nontuberculous effusions was 0.876.

Conclusions

The LDH, TP, Glu, and ADA assays were validated for use with the Mindray BS-2800 analyzer for hydrothorax and ascites evaluation. LDH, TP, and Glu in hydrothorax and ascites are applicable to the differential diagnosis of exudates and transudates; ADA in hydrothorax and ascites can be employed to differentiate and diagnose tuberculous and nontuberculous effusions.

Clinical significance of pleural fluid lactate dehydrogenase/adenosine deaminase ratio in the diagnosis of tuberculous pleural effusion

BACKGROUND

Pleural fluid is one of the common complications of thoracic diseases, and tuberculous pleural effusion (TPE) is the most common cause of pleural effusion in TB-endemic areas and the most common type of exudative pleural effusion in China. In clinical practice, distinguishing TPE from pleural effusion caused by other reasons remains a relatively challenging issue. The objective of present study was to explore the clinical significance of the pleural fluid lactate dehydrogenase/adenosine deaminase ratio (pfLDH/pfADA) in the diagnosis of TPE.

METHODS

The clinical data of 618 patients with pleural effusion were retrospectively collected, and the patients were divided into 3 groups: the TPE group (412 patients), the parapneumonic pleural effusion (PPE) group (106 patients), and the malignant pleural effusion (MPE) group (100 patients). The differences in the ratios of pleural effusion-related and serology-related indicators were compared among the three groups, and receiver operating characteristic curves were drawn to analyze the sensitivity and specificity of the parameter ratios of different indicators for the diagnosis of TPE.

RESULTS

The median serum ADA level was higher in the TPE group (13 U/L) than in the PPE group (10 U/L, P < 0.01) and MPE group (10 U/L, P < 0.001). The median pfADA level in the TPE group was 41 (32, 52) U/L; it was lowest in the MPE group at 9 (7, 12) U/L and highest in the PPE group at 43 (23, 145) U/L. The pfLDH level in the PPE group was 2542 (1109, 6219) U/L, which was significantly higher than that in the TPE group 449 (293, 664) U/L. In the differential diagnosis between TPE and non-TPE, the AUC of pfLDH/pfADA for diagnosing TPE was the highest at 0.946 (0.925, 0.966), with an optimal cutoff value of 23.20, sensitivity of 93.9%, specificity of 87.0%, and Youden index of 0.809. In the differential diagnosis of TPE and PPE, the AUC of pfLDH/pfADA was the highest at 0.964 (0.939, 0.989), with an optimal cutoff value of 24.32, sensitivity of 94.6%, and specificity of 94.4%; this indicated significantly better diagnostic efficacy than that of the single index of pfLDH. In the differential diagnosis between TPE and MPE, the AUC of pfLDH/pfADA was 0.926 (0.896, 0.956), with a sensitivity of 93.4% and specificity of 80.0%; this was not significantly different from the diagnostic efficacy of pfADA.

CONCLUSIONS

Compared with single biomarkers, pfLDH/pfADA has higher diagnostic value for TPE and can identify patients with TPE early, easily, and economically.

Diagnostic scoring systems for tuberculous pleural effusion in patients with lymphocyte-predominant exudative pleural profile: A development study

Background

Diagnosing tuberculous pleural effusion (TPE) in patients presenting with Lymphocyte-Predominant Exudative pleural effusion (LPE) is challenging, due to the poor clinical utility of TB culture. Adenosine deaminase (ADA) has been recommended for diagnosis, but its high cost and limited availability hinder its clinical utility. We aim to develop diagnostic prediction tools for Thai patients with LPE in scenarios where pleural fluid ADA is available but yields negative results and in situations where pleural fluid ADA is not available.

Methods

Two diagnostic prediction tools were developed using retrospective data from patients with LPE at Surin Hospital. Model 1 is for ADA-negative results, and Model 2 is for situations where pleural fluid ADA testing is unavailable. The models were derived using multivariable logistic regression and presented as two clinical scoring systems: round-up and count scoring. The score cut-point that achieves a positive predictive value (PPV) comparable to the post-test probability of a pleural fluid ADA at a cut-point of 40 U/L was used as a threshold for initiating anti-TB treatment.

Results

A total of 359 patients were eligible for analysis, with 166 diagnosed with TPE and 193 diagnosed with non-TPE. Age <40 years, fever, pleural fluid protein ≥5 g/dL, male gender, pleural fluid color, and pleural fluid ADA ≥20 U/L were identified as final predictors. Both models demonstrated excellent discriminative ability (AuROC: 0.85 to 0.89). The round-up scoring demonstrated PPV above 90% at cut-off points of 4 and 4.5, while the count scoring achieved cut-off points of 3 and 4 for Model 1 (Lex-2P2A) and Model 2 (Lex-2P-MAC), respectively.

Conclusion

These diagnostic tools offer valuable assistance in differentiating between TPE and non-TPE in LPE patients with negative pleural fluid ADA (Lex-2P2A) and in settings where pleural fluid ADA testing is not available (Lex-2P-MAC). Implementing these diagnostic scores may have the potential to improve TPE diagnosis and facilitate prompt initiation of treatment.

Diagnostic flowchart for tuberculous pleurisy, pleural infection, and malignant pleural effusion

BACKGROUND

Several markers for the diagnosis of pleural effusion have been reported; however, a comprehensive evaluation using those markers has not been performed. Therefore, this study aimed to develop a diagnostic flowchart for tuberculous pleurisy, pleural infection, malignant pleural effusion, and other diseases by using these markers.

METHODS

We retrospectively collected data from 174 patients with tuberculous pleurisy, 215 patients with pleural infection other than tuberculous pleurisy, 360 patients with malignant pleural effusion, and 209 patients with other diseases at Fukujuji Hospital from January 2012 to October 2022. The diagnostic flowchart for four diseases was developed by using several previously reported markers.

RESULTS

The flowchart was developed by including seven markers: pleural ADA ≥40 IU/L, pleural fluid LDH <825 IU/L, pleural fluid ADA/TP < 14, neutrophil predominance or cell degeneration, peripheral blood WBC ≥9200/μL or serum CRP ≥12 mg/dL, pleural amylase ≥75 U/L, and the presence of pneumothorax according to the algorithm of a decision tree. The accuracy ratio of the flowchart was 71.7 % for the diagnosis of the four diseases, with 79.3 % sensitivity and 75.4 % positive predictive value (PPV) for tuberculosis pleurisy, 75.8 % sensitivity and 83.2 % PPV for pleural infection, 88.6 % sensitivity and 68.8 % PPV for malignant pleural effusion, and 33.0 % sensitivity and 60.0 % PPV for other diseases in the flowchart. The misdiagnosis ratios were 4.6 % for tuberculosis pleurisy, 6.8 % for pleural infection, and 8.3 % for malignant pleural effusion.

CONCLUSION

This study developed a useful diagnostic flowchart for tuberculous pleurisy, pleural infection, malignant pleural effusion, and other diseases.