Development and validation a simple model for identify malignant ascites

Guo, Ying; Peng, Xiulan; Zhan, Na; Tian, Shan; Jiao, Li; Dong, Weiguo

doi:10.7150/ijms.53743

Cited by 4 publications

(4 citation statements)

References 49 publications

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“…For example, Chen et al (14) revealed that the combination of FTIR nearinfrared spectroscopy (NIRS) and machine learning is an innovative, rapid, and convenient method for clinical PE classi cation. Wang et al (15,16) reported a classi cation model to identify BPE and MPE using a CT volume and its 3D PE mask as inputs based on arti cial intelligence. However, these models mentioned above may have disadvantages of high cost, the need for additional examinations, and trained personnel.…”

Section: Discussionmentioning

confidence: 99%

Development and validation a Nomogram for identify malignant pleural effusion

Yan

Wang

et al. 2023

Preprint

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Background Malignant pleural effusion (MPE) is a common complication in cancer patients, indicating the presence of pleural metastasis. However, the ability to identify MPE clinically is still limited. The aim of this study was to develop a novel nomogram-based model for predicting MPE. Methods Between July 2020 and May 2022, a total of 428 patients with pleural effusion (PE) were consecutively enrolled. Demographic data, laboratory test results, and pathological parameters were collected. The LASSO regression method was used to select potential variables, and a multivariate logistic regression method was employed to construct a nomogram. Internal validation was performed using a bootstrapping method, and the nomogram's performance was evaluated based on calibration, discrimination, and clinical utility. Results Out of the 428 patients with PE, 217 (50.7%) were diagnosed with MPE. A diagnostic model was established using least absolute shrinkage and selection operator (LASSO) regression and multivariate logistic regression, which identified four variables: serum carcinoembryonic antigen (sCEA), serum neuron-specific enolase (sNSE), pleural carcinoembryonic antigen (pCEA), and pleural lactate dehydrogenase (pLDH). The internal validation of the model showed an area under the curve (AUC) of 0.894 (95% CI: 0.864–0.934). The model was well-calibrated, and decision curve analysis (DCA) indicated that using the proposed nomogram to predict MPE would obtain a net benefit if the threshold probability of MPE was between 5% and 95%. Conclusion This study aimed to construct a nomogram that includes four demographic and clinical characteristics of patients with PE. The nomogram can be highly beneficial in distinguishing between MPE and benign pleural effusion (BPE).

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Section: Discussionmentioning

confidence: 99%

Development and validation a Nomogram for identify malignant pleural effusion

Yan

Wang

et al. 2023

Preprint

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“…The detection and differentiation of malignant ascites are pivotal in the oncological context. Traditional approaches, including cytological testing, have shown varying degrees of accuracy in distinguishing malignant from non-malignant ascite (22,23). For instance, certain tumor markers in ascitic fluid, such as CA15-3, CEA, and CYFRA21.1, have demonstrated high accuracy in identifying malignancy-related ascites.…”

Section: Discussionmentioning

confidence: 99%

Diagnostic Value of Ascitic Fluid Cholesterol Level in Differentiating Malignant Ascites from Non-Malignant Ascites

Rasheed,

Imran,

Parveen

et al. 2023

JHRR

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Background: Ascites, the accumulation of fluid in the peritoneal cavity, poses significant diagnostic challenges, particularly in differentiating between malignancy-related ascites (MRA) and non-malignant ascites (NMA). This differentiation is critical for appropriate clinical management. Objective: The study aimed to evaluate the diagnostic value of ascitic fluid cholesterol levels in distinguishing MRA from NMA. Methods: This cross-sectional study enrolled 48 patients with ascites, divided equally into Group A (MRA) and Group B (NMA). Diagnostic paracentesis was performed, and 20 ml of ascitic fluid was collected for analysis. Cholesterol levels were measured using the Zaks method. Demographic data were recorded, and statistical analysis was conducted using the Mann-Whitney U-test, with a p-value of 0.05 set for statistical significance. Results: Both groups had an equal gender distribution (12 males and 12 females in each), and the mean ages were 60.3 ± 19.1 years for Group A and 60.8 ± 17.9 years for Group B. The mean cholesterol level in ascitic fluid was significantly higher in Group B (189.9 ± 29.9 mg%) compared to Group A (167.73 ± 26.87 mg%), with mean standard deviations of 91.8 ± 12.4 and 20.4 ± 9.1, respectively. The p-values for gender distribution and age differences were <0.001. Conclusion: The study demonstrated that cholesterol levels in ascitic fluid are a reliable biomarker for differentiating between MRA and NMA. Higher cholesterol levels were associated with non-malignant cases, offering a non-invasive, cost-effective diagnostic tool in clinical settings.

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“…Third, in cardiothoracic surgery patients, the odds of postoperative cardiopulmonary complications increased by nearly 2-fold for each 100 U/L increase in preoperative LDH [ 28 ]. Fourth, a study revealed that LDH was considerably higher in patients with malignant ascites than in patients with benign ascites, and it was a risk factor for malignant ascites [ 29 ]. Fifth, a retrospective study of 988 patients with metastatic cancer reported that higher LDH was associated with an increased risk of pleural effusion recurrence [ 30 ].…”

Section: Discussionmentioning

confidence: 99%

Serum Lactate Dehydrogenase Is a Sensitive Predictor of Systemic Complications of Acute Pancreatitis

Huang

Zhong

Yingli

et al. 2022

Gastroenterology Research and Practice

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Background. Acute pancreatitis (AP) is a common and potentially life-threatening inflammatory disease that can cause various complications, including systemic inflammatory response syndrome (SIRS), pleural effusion, ascitic fluid, myocardial infarction, and acute kidney injury (AKI). However, there is still a lack of rapid and effective indicators to assess the disease. The aim of this study was to investigate the associations of high serum lactate dehydrogenase (LDH) levels with AP severity and systemic complications. Methods. AP patients treated from July 2014 to December 2020 were retrospectively enrolled. They were divided into elevated ( n = 93 ) and normal ( n = 143 ) LDH groups. Their demographic data, clinical data, hospital duration, and hospital expenses were analyzed. Linear and binary logistic regression analyses were used to determine whether elevated LDH is a risk factor for AP severity and complications after adjusting for confounders. Results. There were significant differences in AP severity scores (Ranson, MODS, BISAP, APACHE II, and CTSI), hospital duration, hospital expenses, and the incidences of complications (SIRS, pleural effusion, ascitic fluid, myocardial infarction, and AKI) between the elevated and normal LDH groups. After adjusting for confounders, elevated LDH was associated with AP severity scores and hospital duration and expenses (based on linear regression analyses) and was a risk factor for the occurrence of AP complications and interventions, that is, diuretic and vasoactive agent use (based on binary logistic regression analyses). Conclusions. Elevated LDH is associated with high AP severity scores and high incidences of complications (SIRS, pleural effusion, ascitic fluid, myocardial infarction, and AKI).

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Development and validation a simple model for identify malignant ascites

Cited by 4 publications

References 49 publications

Development and validation a Nomogram for identify malignant pleural effusion

Development and validation a Nomogram for identify malignant pleural effusion

Diagnostic Value of Ascitic Fluid Cholesterol Level in Differentiating Malignant Ascites from Non-Malignant Ascites

Serum Lactate Dehydrogenase Is a Sensitive Predictor of Systemic Complications of Acute Pancreatitis

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