Does size matter? -a population-based analysis of malignant pleural mesothelioma

The Incidence of Distant Metastases in Patients with Pleural Mesothelioma Screened for a Multimodal Approach: How Much Staging Do We Really Need?

Pleural mesothelioma (PM) is a very aggressive malignancy with a poor prognosis. Most patients receive systemic treatment only; however, some patients may benefit from multimodality treatment. A precise staging of patients undergoing multimodal treatment is mandatory. We investigated the pattern of metastasis in a cohort of patients screened for multimodal treatment to define the extent of staging examinations. Additionally, we investigated the occurrence of metastasis during follow-up. We investigated a single-center experience of 545 patients newly diagnosed and/or treated with PM between the years 2010 and 2022. Patients who were treated naïvely and had a whole set of imaging of the brain were included and further analyzed. A total of 54% of all patients with cerebral imaging had an available 18FDG-PET CT scan. We also recorded metastasis during treatment follow-up. There were 110 patients who had a whole set of imaging (CT = 89% and MRI = 11%) of the brain, and 54% of all patients with cerebral imaging had an available 18FDG-PET CT scan. We identified four patients with cerebral metastasis at the time of first diagnosis, which means that 5.4% of the cohort had cerebral metastasis and 13.3% of all patients in the subgroup with complete data of 18FDG-PET CT had distant non-cerebral metastasis. During the longitudinal follow-up, we found 11 patients with newly diagnosed metastases after a median time of 1.6 years (range: 2 months to 3.3 years) after first diagnosis without metastases. Distant metastases are more frequent in mesothelioma patients than previously thought. This implies that extensive staging is needed for patients selected for multimodal treatment, including brain imaging and 18FDG-PET CT.

Serum Calretinin and Genetic Variability as a Prognostic and Predictive Factor in Malignant Mesothelioma

Calretinin is a promising diagnostic biomarker for malignant mesothelioma (MM), but less is known about its prognostic role. Our aim was to evaluate the association between serum calretinin concentration or genetic factors and the survival or outcome of cisplatin-based chemotherapy in MM. Our study included 265 MM patients. Serum calretinin concentration was determined using ELISA. Patients were genotyped for seven polymorphisms in CALB2, E2F2, MIR335, NRF1, and SEPTIN7 using competitive allele-specific PCR. Nonparametric tests, logistic regression, and survival analysis were used for statistical analysis. Higher serum calretinin concentration was associated with shorter progression-free (PFS) (HR = 1.18 (1.02-1.37), p = 0.023) and overall survival (OS) (HR = 1.20 (1.03-1.41), p = 0.023), but the association was not significant after adjusting for clinical factors (HR = 1.05 (0.85-1.31), p = 0.653 and HR = 1.06 (0.84-1.34), p = 0.613, respectively). SEPTIN7 rs3801339 and MIR335 rs3807348 were associated with survival even after adjustment (HR = 1.76 (1.17-2.64), p = 0.007 and HR = 0.65 (0.45-0.95), p = 0.028, respectively). Calretinin concentration was higher in patients who progressed after treatment with cisplatin-based chemotherapy (1.68 vs. 0.45 ng/mL, p = 0.001). Calretinin concentration above 0.89 ng/mL was associated with shorter PFS and OS from the start of chemotherapy (HR = 1.88 (1.28-2.77), p = 0.001 and HR = 1.91 (1.22-2.97), p = 0.004, respectively), even after adjusting for clinical factors (p < 0.05). MIR335 rs3807348 was associated with a better response to chemotherapy (OR = 2.69 (1.17-6.18), p = 0.020). We showed that serum calretinin is associated with survival and chemotherapy treatment outcomes in MM and could serve as a predictive biomarker.

Survival analysis and development of a prognostic nomogram for patients with malignant mesothelioma in different anatomic sites

Background

Malignant mesothelioma (MMe) is a rare and fatal cancer with a poor prognosis. Our study aimed to compare the overall survival (OS) of MMe patients across various sites and develop a prognostic model to provide a foundation for individualized management of MMe patients.

Methods

From the Surveillance, Epidemiology, and End Results (SEER) database, 1,772 individuals with malignant mesothelioma (MMe) were identified. The X-tile software was used to identify the optimal cut-off point for continuous variables. The Kaplan–Meier method was employed to compare the survival of MMe across different sites. The Cox proportional hazards model was applied to identify the independent risk factors of overall survival (OS) and a nomogram was constructed.

Results

In the survival analysis, MMe originating from the reproductive organs and hollow organs showed a relatively better prognosis than those originating from soft tissue, solid organs, and pleura. Age, gender, location, histological type, grade of differentiation, extent of disease, lymph node status, lymph node ratio (LNR), and chemotherapy were all found to be independent risk variables for the prognosis of MMe patients (P&lt;0.05) in a multivariate Cox analysis and were included in the construction of nomogram. In the training and testing sets, the C-index of the nomogram was 0.701 and 0.665, respectively, and the area under the ROC curve (AUROC) of the 1-, 3-, and 5-year overall survival rate was 0.749, 0.797, 0.833 and 0.730, 0.800, 0.832, respectively. The calibration curve shows that the nomogram is well-calibrated.

Conclusions

This is the first research to examine the prognosis of MMe patients based on the location. However, previous studies often focused on malignant pleural mesothelioma or malignant peritoneal mesothelioma with high incidence. Furthermore, a nomograph with good prediction efficiency was established according to the variables that influence patient survival outcomes, which provides us with a reference for clinical decision-making.

Establishment of predictive nomogram and web-based survival risk calculator for malignant pleural mesothelioma: A SEER database analysis

Background

Malignant pleural mesothelioma (MPM) is an uncommon condition with limited available therapies and dismal prognoses. The purpose of this work was to create a multivariate clinical prognostic nomogram and a web-based survival risk calculator to forecast patients’ prognoses.

Methods

Using a randomization process, training and validation groups were created for a retrospective cohort study that examined the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2015 for individuals diagnosed with MPM (7:3 ratio). Overall survival (OS) and cancer-specific survival (CSS) were the primary endpoints. Clinical traits linked to OS and CSS were identified using Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analysis, which was also utilized to develop nomogram survival models and online survival risk calculators. By charting the receiver operating characteristic (ROC), consistency index (C-index), calibration curve, and decision curve analysis (DCA), the model’s performance was assessed. The nomogram was used to classify patients into various risk categories, and the Kaplan-Meier method was used to examine each risk group’s survival rate.

Results

The prognostic model comprised a total of 1978 patients. For the total group, the median OS and CSS were 10 (9.4-10.5) and 11 (9.4-12.6) months, respectively. As independent factors for OS and CSS, age, gender, insurance, histology, T stage, M stage, surgery, and chemotherapy were chosen. The calibration graphs demonstrated good concordance. In the training and validation groups, the C-indices for OS and CSS were 0.729, 0.717, 0.711, and 0.721, respectively. Our nomogram produced a greater clinical net benefit than the AJCC 7th edition, according to DCA and ROC analysis. According to the cut-off values of 171 for OS and 189 for CSS of the total scores from our nomogram, patients were classified into two risk groups. The P-value &lt; 0.001 on the Kaplan-Meier plot revealed a significant difference in survival between the two patient groups.

Conclusions

Patient survival in MPM was correctly predicted by the risk evaluation model. This will support clinicians in the practice of individualized medicine.

Malignant Pleural Mesothelioma Nodal Status: Where Are We at?

Due to the lack of both prospective trial and high-volume retrospective studies, the management of clinical N+ malignant pleural mesothelioma (MPM) patients remains highly debated. Node positive patients show poor survival compared with node-negative ones; thus, lymph node staging appears crucial in determining treatment strategy. Notwithstanding the improvement in pre-treatment staging and the update on lymph node classification in the 8th edition of TNM, several open controversies remain on N parameter. How should we stage suspected N+ patients? How should we treat node positive patients? Which is the definition of a “resectable patient”? Is the site or the number the main prognostic factor for node positive patients? The aim of our narrative review is to analyse the existing relevant literature on lymph node status in MPM.

Serum Calretinin as a Biomarker in Malignant Mesothelioma

The early diagnosis of malignant mesothelioma (MM) could improve the prognosis of MM patients. To confirm an MM diagnosis, an immunohistochemical analysis of several tumor tissue markers, including calretinin, is currently required. Our aim is to evaluate serum calretinin as a potential biomarker in asbestos-related diseases, especially in MM. Our study includes 549 subjects: 164 MM patients, 117 subjects with asbestosis, 195 subjects with pleural plaques and 73 occupationally asbestos-exposed subjects without asbestos-related diseases. The serum calretinin concentration was determined with a commercially available enzyme immunoassay. Data on the soluble mesothelin-related peptides (SMRP) concentration are available from previous studies. MM patients had a significantly higher calretinin concentration than subjects without disease, subjects with pleural plaques or subjects with asbestosis (all p < 0.001). The histological type was significantly associated with serum calretinin: patients with sarcomatoid MM had lower calretinin than patients with the epithelioid type (p = 0.001). In a ROC curve analysis, the area under the curve for calretinin concentration predicting MM was 0.826 (95% CI = 0.782-0.869; p < 0.001). At the cutoff value of 0.32 ng/mL, sensitivity was 0.683, while specificity was 0.886. The combination of calretinin and SMRP had the highest predictive value. Calretinin is a useful biomarker that can distinguish MM from other asbestos-related diseases and could, therefore, contribute to an earlier non-invasive diagnosis of MM.

Profile of soluble factors in pleural effusions predict prognosis in mesothelioma

BACKGROUND:

Pleural mesothelioma is a deadly asbestos induced cancer. Less than 10% of mesothelioma patients survive 5 years post diagnosis. However survival can range from a few months to a number of years. Accurate prediction of survival is important for patients to plan for their remaining life, and for clinicians to determine appropriate therapy. One unusual feature of mesothelioma is that patients frequently present with tumor-associated pleural effusions early in the course of the disease.

OBJECTIVE:

To study whether cells and molecules present in pleural effusions provide prognostic information for mesothelioma.

METHODS:

We profiled the cellular constituents and concentrations of 40 cytokines, chemokines and cellular factors (collectively “soluble factors”) involved in inflammatory and immune signalling pathways in pleural effusion samples from 50 mesothelioma patients.

Associations with survival were evaluated by Cox proportional hazards regression methods. Results for the two soluble factors most significantly and independently associated with survival were validated in an independent set of samples (n= 51) using a separate assay system.

RESULTS:

Survival analysis revealed that IL8, IL2Ra (CD25) and PF4 were independent determinants of a more negative prognosis in mesothelioma patients, independent of other known prognostic factors. Lipocalin2 and IL4 were associated with better prognosis.

CONCLUSIONS:

This study demonstrates that pleural effusions rich in a range of soluble factors are associated with poor prognosis. These findings will enhance our ability to prognosticate outcomes in mesothelioma patients.

Development of unenhanced CT-based imaging signature for BAP1 mutation status prediction in malignant pleural mesothelioma: Consideration of 2D and 3D segmentation

OBJECTIVES

We aimed to explore the feasibility of 2D and 3D radiomics signature based on the unenhanced computed tomography (CT) images to predict BRCA1-associated protein 1 (BAP1) gene mutation status for malignant pleural mesothelioma (MPM) patients.

MATERIALS AND METHODS

74 patients with MPM were retrospectively enrolled (22 mutant BAP1, 52 wild-type BAP1 demonstrated by Sanger sequencing). The radiomic features were extracted respectively from the 2D and 3D segmentation of unenhanced pre-treatment CT images, and the dataset was randomly divided into training (n = 51) and test (n = 23) sets for radiomics model development and internal validation. The synthetic minority over-sampling technique (SMOTE) was used for data balancing in the training set. 2D or 3D features were sequentially selected by ICC > 0.8, correlation analysis (cut-value 0.7), univariate analysis or univariate logistic regression (LR), which were involved into multivariate LR for LR model construction. Following the comparison of the 2D and 3D models by the ROC analysis and Delong test for AUC, the calibration and clinical utility of 2D and 3D models were evaluated.

RESULTS

3D radiomic features showed better ICCs compared with 2D in both intra- (P < 0.001) and inter-observer (P <  0.001) analysis. 3D radiomic model based on selected features developed from a balanced training dataset presented a favorable predictive performance with AUC of 0.786 and 0.768 in the training and test sets, respectively. The predictive performance of 3D model was superior to 2D model (1 feature) both in the training (AUC 0.786 vs. 0.683, P = 0.036) and the test (AUC 0.768 vs.0.652, P = 0.441) set. The calibration curve and decision curves also indicate a better BAP1 prediction performance and clinical benefit for 3D model than that of 2D model.

CONCLUSION

The developed unenhanced CT-based 3D radiomics signature is potential as a noninvasive marker for predicting BAP1 mutation status.