| Autor: |
Ricciardi S; Unit of Thoracic Surgery, Azienda Ospedaliera San Camillo-Forlanini, Carlo Forlanini Hospital, 00151 Rome, Italy.; PhD Program, Alma Mater Studiorum, University of Bologna, 40126 Bologna, Italy., Giovanniello D; Department of Cardio-Thoraco-Vascular Surgery, Sapienza University of Rome, Piazzale Aldo Moro 5, 00185 Rome, Italy., Carbone L; Unit of Thoracic Surgery, Azienda Ospedaliera San Camillo-Forlanini, Carlo Forlanini Hospital, 00151 Rome, Italy., Carleo F; Unit of Thoracic Surgery, Azienda Ospedaliera San Camillo-Forlanini, Carlo Forlanini Hospital, 00151 Rome, Italy., Di Martino M; Unit of Thoracic Surgery, Azienda Ospedaliera San Camillo-Forlanini, Carlo Forlanini Hospital, 00151 Rome, Italy., Jaus MO; Unit of Thoracic Surgery, Azienda Ospedaliera San Camillo-Forlanini, Carlo Forlanini Hospital, 00151 Rome, Italy., Mantovani S; Unit of Thoracic Surgery, Azienda Ospedaliera San Camillo-Forlanini, Carlo Forlanini Hospital, 00151 Rome, Italy.; Department of Cardio-Thoraco-Vascular Surgery, Sapienza University of Rome, Piazzale Aldo Moro 5, 00185 Rome, Italy., Treggiari S; Unit of Thoracic Surgery, Azienda Ospedaliera San Camillo-Forlanini, Carlo Forlanini Hospital, 00151 Rome, Italy., Tornese A; Unit of Anatomy and Pathological Histology, Azienda Ospedaliera San Camillo-Forlanini, Carlo Forlanini Hospital, 00151 Rome, Italy., Cardillo G; Unit of Thoracic Surgery, Azienda Ospedaliera San Camillo-Forlanini, Carlo Forlanini Hospital, 00151 Rome, Italy.; Unicamillus-Saint Camillus University of Health Sciences, 00131 Rome, Italy. |
| Abstrakt: |
Introduction: Malignant solitary fibrous tumours of the pleura (mSFTP) are extremely rare diseases (<5% of all pleural neoplasms) with unpredictable behaviour. Surgery remains the standard of care for these tumours; however, estimating patient prognosis and planning follow-up remain challenging. Several risk stratification models have been proposed, but a classification with diagnostic and prognostic potential has not been well standardised yet. The aim of this study was to analyse the clinicopathological data of mSFTP to investigate their prognostic features and to compare the performance of three risk stratification models proposed in the literature. Methods: Observational retrospective cohort study on all proven cases of mSFTP surgically resected with radical intent between 2000 and 2019 in a single centre. Demographic, surgical and pathological data were examined. All patients were risk-stratified by using three prediction models: modified Demicco, De Perrot and Tapias. Overall survival (OS) and disease-free survival (DFS) were analysed. Results: There were 21 men and 13 women (median age, 67 years, range, 23-83 years). Twenty-one patients (62%) were symptomatic. The median follow-up was 111 months (range, 6-258 months). The 5-year OS and DFS were 81.2% and 77.4%, respectively. Nine patients (26.5%) experimented recurrences. At univariate analysis, the presence of necrosis ( p = 0.019), nuclear atypia ( p = 0.006), dimension greater than 11.5 cm (median value of our cohort) ( p = 0.037) and relapse/disease progression ( p = 0.001) were independent prognostic factor of worse OS. The administration of adjuvant treatment was a protective independent factor for survival ( p = 0.001). Radicality of resection ( p = 0.005); tumour dimension ( p = 0.013), presence of necrosis ( p = 0.041) and nuclear atypia ( p = 0.007) and pleural pattern ( p = 0.011) were independent prognostic factors of worse DFS. Analysing the three risk stratification models, the Tapias score was revealed as the best index to predict both OS ( p = 0.002) and DFS ( p = 0.047) in patients with mSFTP. Conclusions: Using the risk stratification model proposed by Tapias, patients with the highest risk of recurrence could be identified at the time of surgery to establish a more frequent imaging surveillance and longer follow-up. The role of adjuvant treatment in mSFTP therapy has not been established yet, but further analysis on patients with a high risk of recurrence, stratified according to risk models, along with biomolecular panels may tailor future post-surgical therapies. |
