Development and validation of a novel scoring system developed from a nomogram to identify malignant pleural effusion

Wang, Sufei; Tian, Shan; Li, Yuan; Zhan, Na; Guo, Ying; Liu, Yu; Xu, Jing; Ma, Yanling; Zhang, Shujing; Song, Siwei; Wang, Geng; Xia, Hui; Ma, Pei; Wang, Xuan; Liao, Tingting; Duan, Yanran; Jin, Yang; Dong, Weiguo

doi:10.1016/j.ebiom.2020.102924

Cited by 31 publications

(33 citation statements)

References 33 publications

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“…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.…”

Section: Discussionmentioning

confidence: 99%

Development and Validation of A Prediction Model for Tuberculous Pleural Effusion: A Large Cohort Study and External Validation

Liu

Liang

Yuan

et al. 2022

Preprint

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Background: Distinguishing tuberculous pleural effusion (TPE) from non-tuberculosis (TB) benign pleural effusion (BPE) remains to be a challenge in clinical practice. The aim of the present study was to develop and validate a novel nomogram for diagnosing TPE.Methods: In this retrospective analysis, a total of 744 consecutive patients with TPE and non-TB BPE from Ningbo First Hospital were divided into the training set and the internal validation set at a ratio of 7:3, respectively. The clinical and laboratory features were collected and analyzed by logistic regression analysis. A diagnostic model incorporating selected variables was developed and was externally validated in a cohort of 110 patients from another hospital.Results: Six variables including age, effusion lymphocyte, effusion adenosine deaminase (ADA), effusion lactatedehy drogenase (LDH), effusion LDH/effusion ADA, and serum white blood cell (WBC) were identified as valuable parameters used for developing a nomogram. The nomogram showed a good diagnostic performance in the training set. A novel scoring system was then established based on the nomogram to distinguish TPE from non-TB BPE. The scoring system showed good diagnostic performance in the training set (area under the curve (AUC), 0.932, sensitivity, 93.7%, and specificity, 85.4%), the internal validation set (AUC, 0.934, sensitivity, 93.5%, and specificity, 82.9%), and the external validation set (AUC, 0.938, sensitivity, 93.0%, and specificity, 83.1%), respectively.Conclusions: The study developed and validated a novel scoring system based on a nomogram originated from six clinical parameters. The novel scoring system showed a good diagnostic performance in distinguishing TPE from non-TB BPE and can be conveniently used in clinical settings.

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Section: Discussionmentioning

confidence: 99%

Development and Validation of A Prediction Model for Tuberculous Pleural Effusion: A Large Cohort Study and External Validation

Liu

Liang

Yuan

et al. 2022

Preprint

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“…The scoring system comprehensively integrated clinical and laboratory indicators, which might be better than any single parameter alone. A previous study reported a scoring system based on a nomogram that incorporated six factors (fever, ESR, ADA, effusion CEA, serum CEA, and CEA ratio) and obtained a favorable diagnostic performance in distinguishing lung cancer-associated MPE from TPE ( 19 ). Also, other tumor markers have been reported to be useful in lung cancer (such as CYFRA 21-1, NSE, or CR), which were not evaluated in this study.…”

Section: Discussionmentioning

confidence: 99%

“…However, no single marker from blood or PE could obtain both high sensitivity and specificity. Many studies have indicated that a combination of two or more biomarkers could improve the diagnostic performance in patients with MPE ( 19 , 20 ). Reportedly, several studies have revealed that the PE/serum ratio of several tumor markers has higher diagnostic accuracy than a single index for MPE and BPE ( 17 , 21 ).…”

Section: Introductionmentioning

confidence: 99%

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

Liang

Yuan

et al. 2021

Front. Oncol.

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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.

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“…Nomogram, an easy-to-use predictive model, is widely applied in the diagnosis of cancer and prediction of survival. 15 However, most of them focused on overall survival, [16][17][18][19] and no nomogram is specifically created for the prediction of early recurrence in patients with CRC. As far as we know, this is the first clinical study to explore the affecting features of early recurrence among CRC patients.…”

Section: Discussionmentioning

confidence: 99%

Predictive Nomogram for the Prediction of Early Recurrence of Colorectal Cancer

Tang¹,

Chen²,

Tian³

et al. 2021

IJGM

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Aim The prognosis of colorectal cancer (CRC) individuals after curative resection is not satisfactory due to the early recurrence. We sought to identify the affecting features of early recurrence in CRC patients. Methods A total of 3500 CRC patients underwent curative resection were retrospectively incorporated into our study. Among them, 246 patients exhibited tumor recurrence: 121 had early recurrence (≤1 year after operation) and 125 had late recurrence (>1 year after operation). A total of 246 CRC patients with recurrence were randomly assigned into the training group (N=177) or validation group (N=69) based on the ratio of 7:3. LASSO COX regression and support vector machine (SVM) were utilized to screen for the significant clinical indexes associated with the presence of early recurrence. Recurrent nomogram was created based on the above informative parameters to predict the probability of early recurrence. Results Proportion of advanced TNM stage, platelet count, systemic immune-inflammation index (SII), mean corpuscular hemoglobin concentration (MCHC), CA-199, CA-125, lactate dehydrogenase, total bile acid (TBA), urea nitrogen were significantly higher in early recurrence group compared with that in late recurrence group. Results from LASSO COX regression and support vector machine (SVM) revealed that TNM stage, CA-199, CA125, SII and TBA were strong predictors for the presence of early recurrence among postoperative CRC patients in the training group. The recurrent nomogram based on the five predictors exhibited good predictive performance as calculated by C-index (0.846, 95% CI 0.789–0.902 in the training group and 0.799, 95% CI 0.697–0.902 in the validation group) for the prediction of early recurrence. Moreover, the recurrent nomogram exhibited not only encouraging calibration ability, but also great clinical utility both in the training group and validation group. Conclusion TNM stage, CA-199, CA125, SII and TBA were closely correlated with the presence of early recurrence of CRC patients. The recurrent nomogram held well predictive ability for the identification of CRC patients with early recurrence.

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Development and validation of a novel scoring system developed from a nomogram to identify malignant pleural effusion

Cited by 31 publications

References 33 publications

Development and Validation of A Prediction Model for Tuberculous Pleural Effusion: A Large Cohort Study and External Validation

Development and Validation of A Prediction Model for Tuberculous Pleural Effusion: A Large Cohort Study and External Validation

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

Predictive Nomogram for the Prediction of Early Recurrence of Colorectal Cancer

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