Integrating Data from Multidisciplinary Management of Malignant Pleural Mesothelioma: A Cohort Study

Malignant pleural mesothelioma (MPM) is a rare and aggressive malignancy that most commonly affects the pleural layers. MPM has a strong association with asbestos, mainly caused by exposure to its biopersistent fibers in at least 80% of cases. Individuals with a chronic exposure to asbestos might develop disease with a 20–40-year latency with few or no symptoms. Such has been the case in the Italian regions of Piedmont and Lombardy, where industrial production of materials laden with asbestos, mainly cements, has been responsible for the onset of a large epidemic. Since 2018, a multidisciplinary team at San Matteo hospital in Pavia has been collecting data on over 100 patients with MPM. The main goal of this project is to define and describe an integrated profile for each MPM case at diagnosis by using data mining and partition analysis. Here we bring together exhaustive epidemiologic, histologic and radiologic data of 88 MPM patients that came to our observation and draw correlations with predictive and prognostic significance. The median overall survival (OS) was 15.6 months. Most patients presented with pleural effusion, irrespective of disease stage. Quite unexpectedly, no statistically significant association was demonstrated between OS and TNM disease stage at diagnosis. Although average OS is similar in male and female patients, partition analysis of data underlined a significant differential hierarchy of predictor categories based on patient gender. In females with no smoking history, full chemotherapeutic regimens are associated with better outcomes. Moreover, concerning second line treatments, vinorelbine emerged as the most advantageous choice for female patients, whereas in the male subgroup no statistically significant difference resulted between gemcitabine and vinorelbine. A multidisciplinary approach to MPM is mandatory to define better therapeutic approaches, personalize the management and improve patient outcomes.