Survival after resection of malignant peripheral nerve sheath tumors: Introducing and validating a novel type-specific prognostic model

Background This study aimed to assess the performance of currently available risk calculators in a cohort of patients with malignant peripheral nerve sheath tumors (MPNST) and to create an MPNST-specific prognostic model including type-specific predictors for overall survival (OS).Methods This is a retrospective multicenter cohort study of patients with MPNST from 11 secondary or tertiary centers in The Netherlands, Italy and the United States of America. All patients diagnosed with primary MPNST who underwent macroscopically complete surgical resection from 2000 to 2019 were included in this study. A multivariable Cox proportional hazard model for OS was estimated with prespecified predictors (age, grade, size, NF-1 status, triton status, depth, tumor location, and surgical margin). Model performance was assessed for the Sarculator and PERSARC calculators by examining discrimination (C-index) and calibration (calibration plots and observed-expected statistic; O/E-statistic). Internal-external cross-validation by different regions was performed to evaluate the generalizability of the model.Results A total of 507 patients with primary MPNSTs were included from 11 centers in 7 regions. During follow-up (median 8.7 years), 211 patients died. The C-index was 0.60 (95% CI 0.53-0.67) for both Sarculator and PERSARC. The MPNST-specific model had a pooled C-index of 0.69 (95%CI 0.65-0.73) at validation, with adequate discrimination and calibration across regions.Conclusions The MPNST-specific MONACO model can be used to predict 3-, 5-, and 10-year OS in patients with primary MPNST who underwent macroscopically complete surgical resection. Further validation may refine the model to inform patients and physicians on prognosis and support them in shared decision-making.Malignant peripheral nerve sheath tumors (MPNST) are a type of cancer that develops from nerves in the body. It is difficult to know how long someone will live after being diagnosed with MPNST. The authors in this study aimed to find a way to predict survival after diagnosis of MPNST using factors such as age, tumor size, location, depth, NF-1 status, and other relevant information. To do this, they created a computer model that used the above information to predict survival. They tested the model on patients who had surgery for MPNST in the United States, the Netherlands, or Italy between 2000 and 2019. Their results show that these factors can be combined to predict survival at 3-, 5-, and 10- years after surgery with good, but not perfect, accuracy.