Development and Validation of a Scoring System for Early Diagnosis of Malignant Pleural Effusion Based on a Nomogram

Abstract

BackgroundThe diagnostic value of clinical and laboratory features to differentiate between malignant pleural effusion (MPE) and benign pleural effusion (BPE) has not yet been established.ObjectivesThe present study aimed to develop and validate the diagnostic accuracy of a scoring system based on a nomogram to distinguish MPE from BPE.MethodsA total of 1,239 eligible patients with PE were recruited in this study and randomly divided into a training set and an internal validation set at a ratio of 7:3. Logistic regression analysis was performed in the training set, and a nomogram was developed using selected predictors. The diagnostic accuracy of an innovative scoring system based on the nomogram was established and validated in the training, internal validation, and external validation sets (n = 217). The discriminatory power and the calibration and clinical values of the prediction model were evaluated.ResultsSeven variables [effusion carcinoembryonic antigen (CEA), effusion adenosine deaminase (ADA), erythrocyte sedimentation rate (ESR), PE/serum CEA ratio (CEA ratio), effusion carbohydrate antigen 19-9 (CA19-9), effusion cytokeratin 19 fragment (CYFRA 21-1), and serum lactate dehydrogenase (LDH)/effusion ADA ratio (cancer ratio, CR)] were validated and used to develop a nomogram. The prediction model showed both good discrimination and calibration capabilities for all sets. A scoring system was established based on the nomogram scores to distinguish MPE from BPE. The scoring system showed favorable diagnostic performance in the training set [area under the curve (AUC) = 0.955, 95% confidence interval (CI) = 0.942–0.968], the internal validation set (AUC = 0.952, 95% CI = 0.932–0.973), and the external validation set (AUC = 0.973, 95% CI = 0.956–0.990). In addition, the scoring system achieved satisfactory discriminative abilities at separating lung cancer-associated MPE from tuberculous pleurisy effusion (TPE) in the combined training and validation sets.ConclusionsThe present study developed and validated a scoring system based on seven parameters. The scoring system exhibited a reliable diagnostic performance in distinguishing MPE from BPE and might guide clinical decision-making.

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

“…Nomograms are a graphical representation of a complex mathematical formula, which are widely used to estimate diagnosis and prognosis for a variety of diseases by integrating clinical, biologic, and/or genetic variables in medicine [22]. Previously, we and other investigators had reported the application of nomogram in differentiating MPE from BPE [23,24]. In the present study, we developed a scoring system based on a nomogram to distinguish TPE from non-TB BPE.…”

A simple and efficient clinical prediction scoring system to identify malignant pleural effusion

“… 6 – 11 Therefore, scholars pay more attention to build prediction models that combine at least two blood or PE indicators with the advantages of less invasion, cheaper, easy acquirement, and simpler based on current reliable medical diagnosis resources. 12 – 15 , 17 – 21 …”

“…The reported good sensitivity, specificity, and area under the curve (AUC) of these prediction models to distinguish MPE from BPE were about 85–89%, 82–92%, and 91–98%, respectively, which showed greatly improved diagnostic efficiency of MPE. 12 – 15 However, these clinical prediction models contain at least six markers and they are not simple enough to be widely used in heavy clinical work.…”

Diagnostic Value of Six Tumor Markers for Malignant Pleural Effusion in 1,230 Patients: A Single-Center Retrospective Study

“…The sensitivity, specificity, PPV, and PLR were 67.7%, 91.0%, 61.5%, and 9.55, respectively. Previously, we also developed and validated a scoring system based on a nomogram for distinguishing MPE and BPE, which performed well for differentiating lung cancer and tuberculosis [ 31 ]. However, the diagnosis of MPE was according to the presence of malignant cells in PE cytology in our previous study [ 31 ].…”

“…Previously, we also developed and validated a scoring system based on a nomogram for distinguishing MPE and BPE, which performed well for differentiating lung cancer and tuberculosis [ 31 ]. However, the diagnosis of MPE was according to the presence of malignant cells in PE cytology in our previous study [ 31 ]. At present, many clinicians still regard positive cytology as the gold standard for MPE diagnosis, but the accuracy rate of this method is only about 60% [ 3 , 7 ].…”