Malignant Pleural Effusion: Presentation, Diagnosis, and Management

Minimally Invasive, Maximally Effective: The Power of Precision Cytoanalysis on Effusion Samples-A Comprehensive Exploration from Traditional Methods to Innovative Approaches

Precision medicine translates through molecular assays and in minimally invasive diagnosis, evident in analyses of effusions that serve therapeutic and diagnostic purposes. This cost-effective and low-risk approach provides advantages, playing a pivotal role in late-stage oncology and frequently standing as the primary resource for cancer diagnosis and treatment pathways. This article outlines the workflow for managing serous fluid and explores how cytology effusion analysis extends beyond immunocytological diagnosis. Combined with current molecular tests it showcases the potential to be a skillful tool in precision cytopathology.

Management of malignant pleural effusion and trapped lung: a survey of respiratory physicians and thoracic surgeons in Australasia

BACKGROUND

Malignant pleural effusions (MPEs) are common, and a third of them have underlying trapped lung (TL). Management of MPE and TL is suspected to be heterogeneous. Understanding current practices in Australasia is important in guiding policies and future research.

AIMS

Electronic survey of Australia-New Zealand respiratory physicians, thoracic surgeons and their respective trainees to determine practice of MPE and TL management.

RESULTS

Of the 132 respondents, 56% were respiratory physicians, 23% were surgeons and 20% were trainees. Many respondents defined TL as >25% or any level of incomplete lung expansion; 75% would use large-volume thoracentesis to determine whether TL was present. For patients with TL, indwelling pleural catheters (IPCs) were the preferred treatment irrespective of prognosis. In those without TL, surgical pleurodesis was the most common choice if prognosis was >6 months, whereas IPC was the preferred option if survival was <3 months. Only 5% of respondents considered decortication having a definite role in TL, but 55% would consider it in select cases. Forty-nine per cent of surgeons would not perform decortication when the lung does not fully expand intra-operatively. Perceived advantages of IPCs were minimisation of hospital time, effusion re-intervention and usefulness irrespective of TL status. Perceived disadvantages of IPCs were lack of suitable drainage care, potentially indefinite duration of catheter-in-situ and catheter complications.

CONCLUSION

This survey highlights the lack of definition of TL and heterogeneity of MPE management in Australasia, especially for patients with expandable lungs. This survey also identified the main hurdles of IPC use that should be targeted.

Quantitative proteomics revealed protein biomarkers to distinguish malignant pleural effusion from benign pleural effusion

To identify protein biomarkers capable of early prediction regarding the distinguishing malignant pleural effusion (MPE) from benign pleural effusion (BPE) in patients with lung disease. A four-dimensional data independent acquisition (4D-DIA) proteomic was performed to determine the differentially expressed proteins in samples from 20 lung adenocarcinoma MPE and 30 BPE. The significantly differential expressed proteins were selected for Gene Ontology (GO) enrichment and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analysis. Protein biomarkers with high capability to discriminate MPE from BPE patients were identified by Random Forest (RF) algorithm prediction model, whose diagnostic and prognostic efficacy in primary tumors were further explored in public datasets, and were validated by ELISA experiment. 50 important proteins (30 up-regulated and 20 down-regulated) were selected out as potential markers to distinguish the MPE from BPE group. GO analysis revealed that those proteins involving the most important cell component is extracellular space. KEGG analysis identified the involvement of cellular adhesion molecules pathway. Furthermore, the Area Under Curve (AUC) of these proteins were ranged from 0.717 to 1.000，with excellent diagnostic properties to distinguish the MPE. Finally, significant survival and gene and protein expression analysis demonstrated BPIFB1, DPP4, HPRT1 and ABI3BP had high discriminating values. SIGNIFICANCE: We performed a 4D-DIA proteomics to determine the differentially expressed proteins in pleural effusion samples from MPE and BPE. Some potential protein biomarkers were identified to distinguish the MPE from BPE patients., which may provide helpful diagnostic and therapeutic insights for lung cancer. This is significant because the median survival time of patients with MPE is usually 4-12 months, thus, it is particularly important to diagnose MPE early to start treatments promptly. The most common causes of MPE are lung cancers, while pneumonia and tuberculosis are the main causes of BPE. If more diagnostic markers could be identified periodically, there would be an important significance to clinical diagnose and treatment with drugs in lung cancer patients.

Development of a diagnostic algorithm to ascertain malignant pleural effusion utilizing clinical indicators and serum metal concentrations

Background

Malignant pleural effusion (MPE) is prevalent among cancer patients, indicating pleural metastasis and predicting poor prognosis. However, accurately identifying MPE in clinical settings is challenging. The aim of this study was to establish an innovative nomogram-derived model based on clinical indicators and serum metal ion levels to identify MPE.

Methods

From July 2020 to May 2022, 428 patients diagnosed with pleural effusion (PE) were consecutively recruited. Comprehensive demographic details, clinical symptoms, imaging data, pathological information, and laboratory results, including serum metal ion levels, were systematically collected. The nomogram was created by incorporating the most significant predictors identified through LASSO and multivariate logistic regression analysis. The predictors were assigned weighted points based on their respective regression coefficients, allowing for the calculation of a total score that corresponds to the probability of MPE. Internal validation using bootstrapping techniques assessed the nomogram's performance, including calibration, discrimination, and clinical applicability.

Results

Seven key variables were identified using LASSO regression and multiple regression analysis, including dyspnea, fever, X-ray/CT compatible with malignancy, pleural carcinoembryonic antigen(pCEA), serum neuron-specific enolase(sNSE), serum carcinoembryonic antigen(sCEA), and pleural lactate dehydrogenase(pLDH). Internal validation underscored the superior performance of our model (AUC=0.940). Decision curve analysis (DCA) analysis demonstrated substantial net benefit across a probability threshold range > 1%. Additionally, serum calcium and copper levels were significantly higher, while serum zinc levels were significantly lower in MPE patients compared to benign pleural effusion (BPE) patients.

Conclusion

This study effectively developed a user-friendly and reliable MPE identification model incorporating seven markers, aiding in the classification of PE subtypes in clinical settings. Furthermore, our study highlights the clinical value of serum metal ions in distinguishing malignant pleural effusion from BPE. This significant advancement provides essential tools for physicians to accurately diagnose and treat patients with MPE.

Engineered lactococcus lactis intrapleural therapy promotes regression of malignant pleural effusion by enhancing antitumor immunity

Intrapleural immunotherapies have emerged as a prominent field in treating malignant pleural effusion (MPE). Among these, bacteria-based intrapleural therapy has exerted an anti-MPE effect by immuno-stimulating or cytotoxic properties. We previously engineered a probiotic Lactococcus lactis (FOLactis) expressing a fusion protein of Fms-like tyrosine kinase 3 and co-stimulator OX40 ligands. FOLactis activates tumor antigen-specific immune responses and displays systemic antitumor efficacy via intratumoral delivery. However, no available lesions exist in the pleural cavity of patients with MPE for intratumoral administration. Therefore, we further optimize FOLactis to treat MPE through intrapleural injection. Intrapleural administration of FOLactis (I-Pl FOLactis) not only distinctly suppresses MPE and pleural tumor nodules, but also significantly extends noticeable survival in MPE-bearing murine models. The proportion of CD103+ dendritic cells (DCs) in tumor-draining lymph nodes increases three-fold in FOLactis group, compared to the wild-type bacteria group. The enhanced DCs recruitment promotes the infiltration of effector memory T and CD8+ T cells, as well as the activation of NK cells and the polarization of macrophages to M1. Programmed death 1 blockade antibody combination further enhances the antitumor efficacy of I-Pl FOLactis. In summary, we first develop an innovative intrapleural strategy based on FOLactis, exhibiting remarkable efficacy and favorable biosafety profiles. These findings suggest prospective clinical translation of engineered probiotics for managing MPE through direct administration into the pleural cavity.

Case report: Envafolimab combined with Endostar in the treatment of advanced non-small cell lung cancer with malignant pleural effusion

Malignant pleural effusion (MPE) is one of the common complications of lung cancer. The quality of life and prognoses for MPE patients are significantly compromised. Controlling the production of MPE can relieve patients' symptoms, improve their quality of life, and prolong their survival. This article presents a case of advanced non-small cell lung cancer (NSCLC) with MPE and negative driver genes. The patient received envafolimab and Endostar in combination, resulting in a complete reduction of MPE and durable clinical benefits. The exploratory use of this treatment method improved the quality of life of this patient and has the potential to prolong the survival of this patient.

Single-cell transcriptomics reveal metastatic CLDN4+ cancer cells underlying the recurrence of malignant pleural effusion in patients with advanced non-small-cell lung cancer

BACKGROUND

Recurrent malignant pleural effusion (MPE) resulting from non-small-cell lung cancer (NSCLC) is easily refractory to conventional therapeutics and lacks predictive markers. The cellular or genetic signatures of recurrent MPE still remain largely uncertain.

METHODS

16 NSCLC patients with pleural effusions were recruited, followed by corresponding treatments based on primary tumours. Non-recurrent or recurrent MPE was determined after 3-6 weeks of treatments. The status of MPE was verified by computer tomography (CT) and cytopathology, and the baseline pleural fluids were collected for single-cell RNA sequencing (scRNA-seq). Samples were then integrated and profiled. Cellular communications and trajectories were inferred by bioinformatic algorithms. Comparative analysis was conducted and the results were further validated by quantitative polymerase chain reaction (qPCR) in a larger MPE cohort from the authors' centre (n = 64).

RESULTS

The scRNA-seq revealed that 33 590 cells were annotated as 7 major cell types and further characterized into 14 cell clusters precisely. The cell cluster C1, classified as Epithelial Cell Adhesion Molecule (EpCAM)+ metastatic cancer cell and correlated with activation of tight junction and adherence junction, was significantly enriched in the recurrent MPE group, in which Claudin-4 (CLDN4) was identified. The subset cell cluster C3 of C1, which was enriched in recurrent MPE and demonstrated a phenotype of ameboidal-type cell migration, also showed a markedly higher expression of CLDN4. Meanwhile, the expression of CLDN4 was positively correlated with E74 Like ETS Transcription Factor 3 (ELF3), EpCAM and Tumour Associated Calcium Signal Transducer 2 (TACSTD2), independent of driver-gene status. CLDN4 was also found to be associated with the expression of Hypoxia Inducible Factor 1 Subunit Alpha (HIF1A) and Vascular Endothelial Growth Factor A (VEGFA), and the cell cluster C1 was the major mediator in cellular communication of VEGFA signalling. In the extensive MPE cohort, a notably increased expression of CLDN4 in cells from pleural effusion among patients diagnosed with recurrent MPE was observed, compared with the non-recurrent group, which was also associated with a trend towards worse overall survival (OS).

CONCLUSIONS

CLDN4 could be considered as a predictive marker of recurrent MPE among patients with advanced NSCLC. Further validation for its clinical value in cohorts with larger sample size and in-depth mechanism studies on its biological function are warranted.

TRIAL REGISTRATION

Not applicable.

Risk Factors of Enternal Nutrition Intolerance in Septic Patients: A Case-control Study

OBJECTIVE

This study aimed to investigate the incidence of enteral nutrition intolerance (ENI) in patients with sepsis and explore potential risk factors.

METHODS

A case-control study was conducted in patients with sepsis who were receiving enteral nutrition (EN) at a tertiary hospital in China. The included patients were divided into the ENI group and the non-ENI group. Univariate and multivariate analyses were performed to identify the risk factors for ENI.

RESULTS

A total of 859 patients were included in the study. Among them, 288 (33.53%) patients experienced symptoms of ENI, including diarrhea, vomiting, bloating, and gastric retention. Logistic regression analysis revealed that the Acute Physiology and Chronic Health Evaluation H (APACHE H) score, thoracocentesis, and usage of cardiotonic drugs (namely, inotropes) were independent predictors of the ENI.

CONCLUSION

The incidence of ENI is relatively high in patients with sepsis, especially in those who have higher APACHE H scores, have undergone thoracocentesis, and have received inotropes.

Clinical application of the Lung Cancer Compact PanelTM using various types of cytological specimens in patients with lung cancer

BACKGROUND

The Lung Cancer Compact PanelTM (compact panel) is a gene panel that can detect driver alterations with high sensitivity in liquid samples, including tumor cells. This study examined the ability of a compact panel to detect genetic mutations in liquid specimens used in clinical practice.

METHODS

Three cohorts, bronchoscopic biopsy forceps washing (washing cohort), pleural effusion (pleural cohort), and spinal fluid (spinal cohort), were analyzed using the compact panel. Liquid samples were added into the GM (Genemetrics) tubes and analyzed. The washing cohort assessed the concordance rate of gene panel analysis outcomes in tissue specimens derived from the primary tumor. Meanwhile, the pleural cohort investigated the impact of storing specimens for 8 weeks and more on nucleic acid and mutation detection rates.

RESULTS

In the washing cohort (n = 79), the concordance rate with mutations detected in tissues was 75/79 (94.9 %). This rate reached 100 % when focusing solely on driver alterations for treatment. The pleural cohort (n = 8) showed no deterioration in nucleic acid quality or quantity after 8 weeks of storage in GM tubes. Similarly, in the spinal cohort (n = 9), spinal fluid with malignant cells exhibited driver alterations similar to those in the primary tumor. These findings underscore the efficacy of the compact panel in accurately identifying genetic mutations in different liquid specimens.

CONCLUSIONS

The compact panel is a reliable tool for detecting driver alterations in various cytological specimens. Its consistent performance across diverse sample types emphasizes its potential for guiding targeted therapies for patients with lung cancer and enhancing precision medicine approaches.

Home Ultrasound: A Contemporary and Valuable Tool for Palliative Medicine

This narrative review explores the application of point-of-care ultrasound (POCUS) in palliative care and its feasibility in home care settings. POCUS has the potential to streamline diagnostic strategies without patient transfer to the hospital, expedite timely symptomatic relief, and reduce complications from specific palliative interventions. The advent of handheld ultrasound devices has made it an attractive diagnostic and interventional adjunct in acute palliative care. POCUS has gained widespread acceptance as part of routine care in emergency medicine and intensive care, guiding certain procedures and increasing their safety. The modernization and miniaturization of ultrasound equipment have made ultra-portable devices available, allowing for better-quality images at affordable prices. Handheld devices have the potential to revolutionize everyday clinical practice in home-based palliative care, contributing to important bedside clinical decisions. Palliative care patients often require diagnostic examinations in the last months of their lives, with CT being the most frequently performed imaging procedure. However, CT imaging is associated with high costs and burdens, leading to increased suffering and impaired quality of life. Clinical ultrasound, a dialogic imaging modality, offers a safer and more efficient approach to palliative care. POCUS applications, which are cost-effective, non-invasive, and well-tolerated, can be used to improve patient satisfaction and diagnostic understanding. POCUS is a valuable tool in palliative care, improving diagnostic accuracy and reducing the time to diagnosis for various pathologies. It is a standard of care for many procedures and improves patient safety. However, there are limitations to POCUS in palliative care, such as operator-dependent examination variability and limited availability of trained professionals. To overcome these limitations, palliative care physicians should receive mandatory training in POCUS, which can be incorporated into the core curriculum. Additionally, ultrasound teleconsulting can assist less experienced examiners in real-time examinations. The literature on POCUS in palliative care is limited, but research on patient-oriented outcomes is crucial. POCUS should be considered a supplement to good clinical reasoning and regulated radiological evaluations.

An Integrated Clinical and Computerized Tomography-Based Radiomic Feature Model to Separate Benign from Malignant Pleural Effusion

INTRODUCTION

Distinguishing between malignant pleural effusion (MPE) and benign pleural effusion (BPE) poses a challenge in clinical practice. We aimed to construct and validate a combined model integrating radiomic features and clinical factors using computerized tomography (CT) images to differentiate between MPE and BPE.

METHODS

A retrospective inclusion of 315 patients with pleural effusion (PE) was conducted in this study (training cohort: n = 220; test cohort: n = 95). Radiomic features were extracted from CT images, and the dimensionality reduction and selection processes were carried out to obtain the optimal radiomic features. Logistic regression (LR), support vector machine (SVM), and random forest were employed to construct radiomic models. LR analyses were utilized to identify independent clinical risk factors to develop a clinical model. The combined model was created by integrating the optimal radiomic features with the independent clinical predictive factors. The discriminative ability of each model was assessed by receiver operating characteristic curves, calibration curves, and decision curve analysis (DCA).

RESULTS

Out of the total 1,834 radiomic features extracted, 15 optimal radiomic features explicitly related to MPE were picked to develop the radiomic model. Among the radiomic models, the SVM model demonstrated the highest predictive performance [area under the curve (AUC), training cohort: 0.876, test cohort: 0.774]. Six clinically independent predictive factors, including age, effusion laterality, procalcitonin, carcinoembryonic antigen, carbohydrate antigen 125 (CA125), and neuron-specific enolase (NSE), were selected for constructing the clinical model. The combined model (AUC: 0.932, 0.870) exhibited superior discriminative performance in the training and test cohorts compared to the clinical model (AUC: 0.850, 0.820) and the radiomic model (AUC: 0.876, 0.774). The calibration curves and DCA further confirmed the practicality of the combined model.

CONCLUSION

This study presented the development and validation of a combined model for distinguishing MPE and BPE. The combined model was a powerful tool for assisting in the clinical diagnosis of PE patients.

Treatment and Management of the Clinical Manifestations of Advanced Breast Cancer

OBJECTIVES

People with advanced breast cancer (ABC) experience complex and debilitating physical symptoms of their disease that can have a profound effect on quality of life. This report provides an overview of the clinical manifestations related to different metastatic sites in ABC and potential oncologic emergencies.

DATA SOURCES

Date sources include peer-reviewed papers sourced in electronic databases (CINAHL, MEDLINE, Google Scholar) and national and international best practice guidelines.

CONCLUSION

People living with ABC experience multiple symptoms of disease that can impact on quality of life and physical functioning. The most common sites of metastatic disease are bone, lung, liver and brain. Clinical manifestations of ABC include pain, pathologic fractures, pleural effusions, and ascites. Potential oncologic emergencies related to these metastatic sites include hypercalcemia, malignant spinal cord compression, superior vena cava obstruction, and raised intracranial pressure.

IMPLICATIONS FOR NURSING PRACTICE

It is important for nurses to have informed knowledge and understanding of these clinical manifestations. This will enable them to be vigilant and perform targeted patient evaluation to assess signs and symptoms with a view to identifying potentially life-threatening emergencies and initiating interventions or appropriate referral or follow-up accordingly.

Study on the application of percutaneous closed pleural brushing combined with cell block technique in the diagnosis of malignant pleural effusion

INTRODUCTION

This study was to investigate the diagnostic value of percutaneous closed pleural brushing (CPBR) followed by cell block technique for malignant pleural effusion (MPE) and the predictive efficacy of pleural fluid carcinoembryonic antigen (CEA) for epidermal growth factor receptor (EGFR) mutations in lung adenocarcinoma patients with MPE.

METHODS

All patients underwent closed pleural biopsy (CPB) and CPBR followed by cell block examination. MPE-positive diagnostic rates between the two methods were compared. Univariate and multivariate analyses were performed to determine factors influencing the EGFR mutations. Receiver operating characteristic (ROC) curve was used to analyze the predictive efficacy of pleural fluid CEA for EGFR mutations.

RESULTS

The cumulative positive diagnostic rates for MPE after single and twice CPBR followed by cell block examination were 80.5% and 89.0%, higher than CPB (45.7%, 54.3%) (P < 0.001). Univariate analysis showed that EGFR mutation was associated with pleural fluid and serum CEA (P < 0.05). Multivariate analysis showed that pleural fluid CEA was an independent risk factor for predicting EGFR mutation (P < 0.001). The area under the curve (AUC) of pleural fluid CEA for EGFR mutation prediction was 0.774, higher than serum CEA (P = 0.043), but no difference with the combined test (P > 0.05).

CONCLUSION

Compared with CPB, CPBR followed by the cell block technique can significantly increase the positive diagnostic rate of suspected MPE. CEA testing of pleural fluid after CPBR has a high predictive efficacy for EGFR mutation in lung adenocarcinoma patients with MPE, implying pleural fluid extracted for cell block after CPBR may be an ideal specimen for genetic testing.

Pleural Uptake Patterns in F18Fluorodeoxyglucose-Positron Emission Tomography (FDG-PET) Scans Improve the Identification of Malignant Pleural Effusions

BACKGROUND

The confirmation of malignant pleural effusions (MPE) requires an invasive procedure. Diagnosis can be difficult and may require repeated thoracentesis or biopsies. F18Fluorodeoxyglucose-Positron Emission Tomography (FDG-PET) can characterize the extent of malignant involvement in areas of increased uptake. Patterns of uptake in the pleura may be sufficient to obviate the need for further invasive procedures.

METHODS

This is a retrospective review of patients with confirmed malignancy and suspected MPE. Patients who underwent diagnostic thoracentesis with cytology and contemporaneous FDG-PET were identified for analysis. Some underwent confirmatory pleural biopsy. The uptake pattern on FDG-PET underwent blinded review and was categorized based on the pattern of uptake.

RESULTS

One hundred consecutive patients with confirmed malignancy, suspected MPE and corresponding FDG-PET scans were reviewed. MPE was confirmed in 70 patients with positive pleural fluid cytology or tissue pathology. Of the remaining patients, 15 had negative cytopathology, 14 had atypical cells and 1 had reactive cells. Positive uptake on FDG-PET was noted in 76 patients. The concordance of malignant histology and positive FDG-PET occurred in 58 of 76 patients (76%). Combining histologically confirmed MPE with atypical cytology, positive pleural FDG-PET uptake had a positive predictive value of 91% for MPE. An encasement pattern had a 100% PPV for malignancy.

CONCLUSION

Positive FDG-PET pleural uptake represents an excellent method to identify MPE, especially in patients with an encasement pattern. This may eliminate the need for additional invasive procedures in some patients, even when initial pleural cytology is negative.

Role of cytoblock on pleural effusion for diagnosis of malignant disease

BACKGROUND

Thoracocentesis of pleural effusion is a simple technique for pleural fluid examination through cytology. In addition to cytological examination to assess the nature of pleural fluid content, we can also perform more detailed examinations through cytoblocks of residual fluid. These paraffin-embedded cytoblock samples are important because we can perform examinations as in other bioptic samples. In these samples, immunohistochemical and molecular analyses can be performed.

METHODS

Two hundred fifty-five cytological samples from patients with pleural effusion were examined. In cases in which the presence of malignant cells was identified in the cytological examination, as well as cases that were suspicious but not definitive for the presence of a malignant effusion, a cytoblock was prepared. Histological examination and immunohistochemical analysis were performed.

RESULTS

Among 255 cases with pleural effusion, 152 had the presence of malignant cells and 6 cases were suspicious, but uncertain for the presence of malignant cells, while 86 cases had inflammatory pleural effusion or other pathologies but were not malignant. After histological analysis of the cytoblock and immunohistochemical analysis, we identified 82 malignant tumors of the lung, 8 malignant tumors of the gastrointestinal tract, 15 malignant tumors of the breast, and 6 malignant tumors of the female genital tract, as well as 24 tumors of undetermined origin.

CONCLUSIONS

Cytoblocks are important for the diagnosis of the primary nature of malignant pleural effusions. The highest importance is primary lung tumors, as well as those tumors in which the primary site of the tumor cannot be determined clinically.

Logic gate-driven dual-index balanced visualization strategy for tumor metastasis diagnosis

Exfoliated tumor cells are integral to malignant tumors diagnosis. The process of clinical cytology of exfoliation involves several complex steps that require at least two days of preparation. Here, we develop a balanced-etching visual kit based on concentration differences of Glutathione/Glucose (GSH/Glu) to distinguish normal from exfoliated tumor cells rapidly and accurately. The balanced-etching visualization kit can be used to obtain color cards and screen exfoliated tumor cells initially (within 10 min). Furthermore, by utilizing logic gates and machine learning algorithms for RGB extraction of the color card obtained from the kit, accurate screening of exfoliated tumor cells is achieved. Finally, a series of clinical tumor samples, such as urine, pleural fluids, ascites, and gastric fluids, have been validated. With effective experimental methods, accurate disease information, and appropriate therapeutic programs, the novel diagnostic strategy is expected to promote precision medicine.

Establishment of Patient-Derived Organoids Using Ascitic or Pleural Fluid from Cancer Patients

PURPOSE

Patient-derived tumor cells can be a powerful resource for studying pathophysiological mechanisms and developing robust strategies for precision medicine. However, establishing organoids from patient-derived cells is challenging because of limited access to tissue specimens. Therefore, we aimed to establish organoids from malignant ascites and pleural effusions.

MATERIALS AND METHODS

Ascitic or pleural fluid from pancreatic, gastric, and breast cancer patients was collected and concentrated to culture tumor cells ex vivo. Organoids were considered to be successfully cultured when maintained for five or more passages. Immunohistochemical staining was performed to compare the molecular features, and drug sensitivity was assayed to analyze the clinical responses of original patients.

RESULTS

We collected 70 fluid samples from 58 patients (pancreatic cancer, n=39; gastric cancer, n=21; and breast cancer, n=10). The overall success rate was 40%; however, it differed with types of malignancy, with pancreatic, gastric, and breast cancers showing 48.7%, 33.3%, and 20%, respectively. Cytopathological results significantly differed between successful and failed cases (p=0.014). Immunohistochemical staining of breast cancer organoids showed molecular features identical to those of tumor tissues. In drug sensitivity assays, pancreatic cancer organoids recapitulated the clinical responses of the original patients.

CONCLUSION

Tumor organoids established from malignant ascites or pleural effusion of pancreatic, gastric, and breast cancers reflect the molecular characteristics and drug sensitivity profiles. Our organoid platform could be used as a testbed for patients with pleural and peritoneal metastases to guide precision oncology and drug discovery.

Construction of a multi-classified decision tree model for identifying malignant pleural effusion and tuberculous pleural effusion

OBJECTIVE

Pleural effusion (PE) is a common clinical complication associated with various disorders. We aimed to utilize laboratory variables and their corresponding ratios in serum and PE for the differential diagnosis of multiple types of PE based on a decision tree (DT) algorithm.

METHODS

A total of 1435 untreated patients with PE admitted to The First Affiliated Hospital of Ningbo University were enrolled. The demographic and laboratory variables were collected and compared. The receiver operating characteristic curve was used to select important variables for diagnosing malignant pleural effusion (MPE) or tuberculous pleural effusion (TPE) and included in the DT model. The data were divided into the training set and the test set at a ratio of 7:3. The training data was used to develop the DT model, and the test data was for evaluating the model. Independent data was collected as external validation.

RESULTS

Three PE indicators (carcinoembryonic antigen, adenosine deaminase [ADA], and total protein), two serum indicators (neuron-specific enolase and cytokeratin 19 fragments), and two ratios [high-sensitivity C-reactive protein (hsCRP)/ PE lymphocyte and hsCRP/PE ADA] were used to construct the DT model. The area under the curve (AUC), sensitivity, and specificity for diagnosing MPE were 0.963, 84.0%, 91.6% in the training set, 0.976, 84.1%, 88.6% in the test set, and 0.955,83.3%, 86.7% in the external validation set. The AUC, sensitivity, and specificity of diagnosing TPE were 0.898, 86.8%, 92.3% in the training set, 0.888, 88.8%, 92.7% in the test set, and 0.778, 84.8%, 94.3% in the external validation set.

CONCLUSION

The DT model showed good diagnostic efficacy and could be applied for the differential diagnosis of MPE and TPE in clinical settings.

Immunoassay with Novel Paired Antibodies for Detection of Lipoarabinomannan in the Pleural Fluid and Plasma of Patients with Tuberculous Pleurisy

Tuberculous pleurisy (TP) is one of the most common forms of extrapulmonary tuberculosis, but its diagnosis is challenging. Lipoarabinomannan (LAM) antigen is a biomarker for Mycobacterium tuberculosis (Mtb) infection. LAM detection has potential as an auxiliary diagnostic method for TP. We have successfully generated five rabbit anti-LAM monoclonal antibodies (BJRbL01, BJRbL03, BJRbL20, BJRbL52, and BJRbL76). Here, anti-LAM antibodies were tested to detect LAM in the pleural fluid and plasma of patients with TP by sandwich enzyme-linked immunosorbent assays (ELISAs). The results revealed that all of the anti-LAM antibodies were successfully used as capture and detection antibodies in sandwich ELISAs. The BJRbL01/BJRbL01-Bio pair showed better performance than the other antibody pairs for detecting mycobacterial clinical isolates and had a limit of detection of 62.5 pg/mL for purified LAM. LAM levels were significantly higher in the pleural fluid and plasma of patients with TP than in those of patients with malignant pleural effusion or the plasma of non-TB, and LAM levels in the pleural fluid and plasma were positively correlated. Moreover, LAM levels in the pleural fluid sample were significantly higher in confirmed TP patients than in clinically diagnosed TP patients. Our studies provide novel LAM detection choices in the pleural fluid and plasma of TP patients and indicate that LAM detection assay has an auxiliary diagnostic value for TP, which may help to improve the diagnosis of TP.

Acute Oncologic Complications: Clinical-Therapeutic Management in Critical Care and Emergency Departments

Introduction. It is now known that cancer is a major public health problem; on the other hand, it is less known, or rather, often underestimated, that a significant percentage of cancer patients will experience a cancer-related emergency. These conditions, depending on the severity, may require treatment in intensive care or in the emergency departments. In addition, it is not uncommon for a tumor pathology to manifest itself directly, in the first instance, with a related emergency. The emergency unit proves to be a fundamental and central unit in the management of cancer patients. Many cancer cases are diagnosed in the first instance as a result of symptoms that lead the patient's admittance into the emergency room. Materials and Methods. This narrative review aims to analyze the impact of acute oncological cases in the emergency setting and the role of the emergency physician in their management. A search was conducted over the period January 1981-April 2023 using the main scientific platforms, including PubMed, Scopus, Medline, Embase and Google scholar, and 156 papers were analyzed. Results. To probe into the main oncological emergencies and their management in increasingly overcrowded emergency departments, we analyzed the following acute pathologies: neurological emergencies, metabolic and endocrinological emergencies, vascular emergencies, malignant effusions, neutropenic fever and anemia. Discussion/Conclusions. Our analysis found that a redefinition of the emergency department connected with the treatment of oncology patients is necessary, considering not only the treatment of the oncological disease in the strict sense, but also the comorbidities, the oncological emergencies and the palliative care setting. The need to redesign an emergency department that is able to manage acute oncological cases and end of life appears clear, especially when this turns out to be related to severe effects that cannot be managed at home with integrated home care. In conclusion, a redefinition of the paradigm appears mandatory, such as the integration between the various specialists belonging to oncological medicine and the emergency department. Therefore, our work aims to provide what can be a handbook to detect, diagnose and treat oncological emergencies, hoping for patient management in a multidisciplinary perspective, which could also lead to the regular presence of an oncologist in the emergency room.

Comparison between different treatment regimens of vascular targeting drug to malignant pleural effusion in patients with lung cancer: A Bayesian network meta-analysis

BACKGROUND

The presence of malignant pleural effusion in lung cancer patients often suggests a poor prognosis. We plan to investigate which regimen of vascular targeting drug is preferable to control the malignant pleural effusion in such patients.

METHODS

Two investigators dependently searched and screened for randomized controlled trials in PubMed, Embase, Web of Science and China National Knowledge Infrastructure from the database inception to August 2022. R software was applied to build a network model in Bayesian method. Objective response rate of malignant pleural effusion is the primary outcome measure. Besides, the incidence of 3 adverse events were compared, including gastrointestinal reaction, leukopenia and hypertension. Due to the disconnection of network, we analysis and discuss the short-term treatment (3-4 weeks) and long-term treatment (6-12 weeks) respectively.

RESULTS

31 studies with 2093 patients were identified. Four targeting drugs contain bevacizumab (Bev), anlotinib, apatinib and Endostar. Two administration routes include intracavity perfusion (icp) and intravenous injection. Based on the current evidence, for short-term treatments, compared with single-agent chemotherapy (CT), Bev_icp + CT, anlotinib + CT, Bev_icp and anlotinib + endorstar_icp present better objective response, and no statistical significance was found in objective response between Bev_icp + CT, anlotinib + CT and Bev_icp. For long-term treatments, compared with doublet or triplet chemotherapy (2CT or 3CT), Bev_icp + 2CT, apatinib + 2CT, Bev_icp + 3CT, and Bev_intravenous injection + 2CT are more effective option, but no statistical significance was found in objective response between the 4 combination regimens with chemotherapy.

CONCLUSION

Our findings suggest that no statistical significance between above vascular targeting regimens. Pathological type of lung cancer may affect the effect of bevacizumab intracavity infusion plus chemotherapy. The influence of different administration routes of vascular targeting drugs on efficacy remains to be investigated. There are some concerns with the quality of the studies, and some limitations should be considered when interpreting these results, which includes limited geographical region and sample size of studies. Despite these limitations, this study may inform vascular targeting therapy choice in such a patient population.

Deep Learning-Based Computational Cytopathologic Diagnosis of Metastatic Breast Carcinoma in Pleural Fluid

A Pleural effusion cytology is vital for treating metastatic breast cancer; however, concerns have arisen regarding the low accuracy and inter-observer variability in cytologic diagnosis. Although artificial intelligence-based image analysis has shown promise in cytopathology research, its application in diagnosing breast cancer in pleural fluid remains unexplored. To overcome these limitations, we evaluate the diagnostic accuracy of an artificial intelligence-based model using a large collection of cytopathological slides, to detect the malignant pleural effusion cytology associated with breast cancer. This study includes a total of 569 cytological slides of malignant pleural effusion of metastatic breast cancer from various institutions. We extracted 34,221 augmented image patches from whole-slide images and trained and validated a deep convolutional neural network model (DCNN) (Inception-ResNet-V2) with the images. Using this model, we classified 845 randomly selected patches, which were reviewed by three pathologists to compare their accuracy. The DCNN model outperforms the pathologists by demonstrating higher accuracy, sensitivity, and specificity compared to the pathologists (81.1% vs. 68.7%, 95.0% vs. 72.5%, and 98.6% vs. 88.9%, respectively). The pathologists reviewed the discordant cases of DCNN. After re-examination, the average accuracy, sensitivity, and specificity of the pathologists improved to 87.9, 80.2, and 95.7%, respectively. This study shows that DCNN can accurately diagnose malignant pleural effusion cytology in breast cancer and has the potential to support pathologists.

Main applications of point-of care ultrasound in palliative care

Combined with a physical examination, clinical ultrasound offers a valuable complement that can help guide clinical decision-making. In various medical and surgical specialties, it is increasingly used for diagnostic and therapeutic purposes. Due to recent technological advances, smaller and more affordable ultrasound machines are now being developed for use in home hospice care. The purpose of this paper is to describe how clinical ultrasound may be applied in Palliative Care, where it can be a valuable tool to assist the clinician in making better clinical decisions and to assist in accurately guiding palliative procedures. Furthermore, it can be used to identify unnecessary hospitalizations and prevent them from occurring. Training programs with specific objectives are necessary to implement clinical ultrasound in Palliative Care, as well as defining learning curves and promoting alliances with scientific societies that recognize the teaching, care and research trajectory for accreditation of competencies.

A Microfluidic System for Detecting Tumor Cells Based on Biomarker Hexaminolevulinate (HAL): Applications in Pleural Effusion

Malignant pleural effusion is a common clinical problem, which often occurs in cases of malignant tumors, especially in lung cancer. In this paper, a pleural effusion detection system based on a microfluidic chip, combined with specific tumor biomarker, hexaminolevulinate (HAL), used to concentrate and identify tumor cells in pleural effusion was reported. The lung adenocarcinoma cell line A549 and mesothelial cell line Met-5A were cultured as the tumor cells and non-tumor cells, respectively. The optimum enrichment effect was achieved in the microfluidic chip when the flow rates of cell suspension and phosphate-buffered saline achieved 2 mL/h and 4 mL/h, respectively. At the optimal flow rate, the proportion of A549 increased from 28.04% to 70.01% due to the concentration effect of the chip, indicating that tumor cells could be enriched by a factor of 2.5 times. In addition, HAL staining results revealed that HAL can be used to identify tumor cells and non-tumor cells in chip and clinical samples. Additionally, the tumor cells obtained from the patients diagnosed with lung cancer were confirmed to be captured in the microfluidic chip, proving the validity of the microfluidic detection system. This study preliminarily demonstrates the microfluidic system is a promising method with which to assist clinical detection in pleural effusion.

Point of care ultrasonography in onco-nephrology: A stride toward better physical examination

Onco-Nephrology is an emerging subspecialty of Nephrology that focuses on a broad spectrum of renal disorders that can arise in patients with cancer. It encompasses acute kidney injury (AKI), complex fluid, electrolyte, and acid-base disorders, as well as chronic kidney disease caused or exacerbated by cancer and/or its treatment. In many such scenarios including AKI and hyponatremia, objective evaluation of hemodynamics is vital for appropriate management. Point of care ultrasonography (POCUS) is a limited ultrasound exam performed at the bedside and interpreted by the treating physician intended to answer focused clinical questions and guide therapy. Compared to conventional physical examination, POCUS offers substantially higher diagnostic accuracy for various structural and hemodynamic derangements. In this narrative review, we provide an overview of the utility of POCUS enhanced physical examination for the Onconephrologist supported by the current evidence and our experience-based opinion.

Diagnosis of malignant pleural effusion with combinations of multiple tumor markers: A comparison study of five machine learning models

BACKGROUND

To evaluate the diagnostic value of combinations of tumor markers carcinoembryonic antigen (CEA), carbohydrate antigen (CA) 125, CA153, and CA19-9 in identifying malignant pleural effusion (MPE) from non-malignant pleural effusion (non-MPE) using machine learning, and compare the performance of popular machine learning methods.

METHODS

A total of 319 samples were collected from patients with pleural effusion in Beijing and Wuhan, China, from January 2018 to June 2020. Five machine learning methods including Logistic regression, extreme gradient boosting (XGBoost), Bayesian additive regression tree, random forest, and support vector machine were applied to evaluate the diagnostic performance. Sensitivity, specificity, Youden's index, and the area under the receiver operating characteristic curve (AUC) were used to evaluate the performance of different diagnostic models.

RESULTS

For diagnostic models with a single tumor marker, the model using CEA, constructed by XGBoost, performed best (AUC = 0.895, sensitivity = 0.80), and the model with CA153, also by XGBoost, showed the largest specificity 0.98. Among all combinations of tumor markers, the combination of CEA and CA153 achieved the best performance (AUC = 0.921, sensitivity = 0.85) in identifying MPE under the diagnostic model constructed by XGBoost.

CONCLUSIONS

Diagnostic models for MPE with a combination of multiple tumor markers outperformed the models with a single tumor marker, particularly in sensitivity. Using machine learning methods, especially XGBoost, could comprehensively improve the diagnostic accuracy of MPE.

Deep Learning-Based Classification and Targeted Gene Alteration Prediction from Pleural Effusion Cell Block Whole-Slide Images

Cytopathological examination is one of the main examinations for pleural effusion, and especially for many patients with advanced cancer, pleural effusion is the only accessible specimen for establishing a pathological diagnosis. The lack of cytopathologists and the high cost of gene detection present opportunities for the application of deep learning. In this retrospective analysis, data representing 1321 consecutive cases of pleural effusion were collected. We trained and evaluated our deep learning model based on several tasks, including the diagnosis of benign and malignant pleural effusion, the identification of the primary location of common metastatic cancer from pleural effusion, and the prediction of genetic alterations associated with targeted therapy. We achieved good results in identifying benign and malignant pleural effusions (0.932 AUC (area under the ROC curve)) and the primary location of common metastatic cancer (0.910 AUC). In addition, we analyzed ten genes related to targeted therapy in specimens and used them to train the model regarding four alteration statuses, which also yielded reasonable results (0.869 AUC for ALK fusion, 0.804 AUC for KRAS mutation, 0.644 AUC for EGFR mutation and 0.774 AUC for NONE alteration). Our research shows the feasibility and benefits of deep learning to assist in cytopathological diagnosis in clinical settings.

Hyperthermic intrathoracic/intraperitoneal chemotherapy versus conventional intrapleural/intraperitoneal chemotherapy for the malignant effusion: a multi-center randomized clinical trial

OBJECTIVE

To compare the efficacy and safety of hyperthermic intrathoracic/intraperitoneal chemotherapy versus conventional intrapleural/intraperitoneal chemotherapy in the treatment of malignant pleural or peritoneal effusion.

METHODS

A randomized clinical trial was carried out in 8 cancer centers across China. Patients with malignant pleural or peritoneal effusion were randomly assigned to the study group or control group. Patients in the study group were treated with cisplatin-based hyperthermic intrathoracic chemotherapy (HITHOC) or hyperthermic intraperitoneal chemotherapy (HIPEC), while the control group was treated with conventional intrapleural or intraperitoneal chemotherapy using same chemotherapeutic regime as the study group. The objective response rate (ORR) was analyzed as primary outcome. Quality-of-life (QOL) score was recorded as secondary outcome using the questionnaire 30 (QLQ-C30) of the European Organization for Research and Treatment of Cancer (EORTC). The efficacy and safety of the two treatments were compared.

RESULTS

Total 135 patients were recruited and randomized in this study, with 67 patients in the study group and 68 patients in the control group. The ORR in the study group (80.70%) was significantly higher than that in the control group (31.03%, p < 0.001). However, neither changes of QOL scores, nor incidence rates of adverse events were significantly different between the two groups (p = 0.076 and 0.197, respectively).

CONCLUSION

Efficacy of HITHOC or HIPEC is superior to that of conventional modality for the treatment of malignant effusion with comparable side effects.

Development and validation of a machine learning model for differential diagnosis of malignant pleural effusion using routine laboratory data

BACKGROUND

The differential diagnosis of malignant pleural effusion (MPE) and benign pleural effusion (BPE) presents a clinical challenge. In recent years, the use of artificial intelligence (AI) machine learning models for disease diagnosis has increased.

OBJECTIVE

This study aimed to develop and validate a diagnostic model for early differentiation between MPE and BPE based on routine laboratory data.

DESIGN

This was a retrospective observational cohort study.

METHODS

A total of 2352 newly diagnosed patients with pleural effusion (PE), between January 2008 and March 2021, were eventually enrolled. Among them, 1435, 466, and 451 participants were randomly assigned to the training, validation, and testing cohorts in a ratio of 3:1:1. Clinical parameters, including age, sex, and laboratory parameters of PE patients, were abstracted for analysis. Based on 81 candidate laboratory variables, five machine learning models, namely extreme gradient boosting (XGBoost) model, logistic regression (LR) model, random forest (RF) model, support vector machine (SVM) model, and multilayer perceptron (MLP) model were developed. Their respective diagnostic performances for MPE were evaluated by receiver operating characteristic (ROC) curves.

RESULTS

Among the five models, the XGBoost model exhibited the best diagnostic performance for MPE (area under the curve (AUC): 0.903, 0.918, and 0.886 in the training, validation, and testing cohorts, respectively). Additionally, the XGBoost model outperformed carcinoembryonic antigen (CEA) levels in pleural fluid (PF), serum, and the PF/serum ratio (AUC: 0.726, 0.699, and 0.692 in the training cohort; 0.763, 0.695, and 0.731 in the validation cohort; and 0.722, 0.729, and 0.693 in the testing cohort, respectively). Furthermore, compared with CEA, the XGBoost model demonstrated greater diagnostic power and sensitivity in diagnosing lung cancer-induced MPE.

CONCLUSION

The development of a machine learning model utilizing routine laboratory biomarkers significantly enhances the diagnostic capability for distinguishing between MPE and BPE. The XGBoost model emerges as a valuable tool for the diagnosis of MPE.

A Rare Case of Metastatic Gastric Signet Ring Cell Adenocarcinoma in a 23-Year-Old Female Presenting as Malignant Pleural Effusion

Signet ring cell carcinoma (SRCC) is a poorly differentiated mucin-producing adenocarcinoma with greater than 50% signet ring cells. It commonly arises from the gastrointestinal (GI) tract and rarely from extraintestinal organs. This is a rare case of a young African American female who presented with metastatic spread of signet ring cell gastric cancer (pleural and lymph nodal involvement) as the initial presentation of SRCC. Knowledge of the various clinical manifestations of SRCC can help with its early diagnosis, and there is a high need for detailed physical examination, early referral, and prompt treatment in patients with SRCC.