Survival after Resection of Malignant Peripheral Nerve Sheath Tumors: Introducing and Validating a Novel Subtype-specific Prognostic Model
Ibtissam Acem, BSc1, Ewout Steyerberg, PhD2, Marta Spreafico, PhD3, Dirk J Grunhagen, MD, PhD4, Dario Callegaro, MD, PhD5, Robert J. Spinner, MD6, Courtney Pendleton, MD7, J. Henk Coert, MD PhD8, Rosalba Miceli, PhD5, Giulia Abruzzese, MD5, Michiel A.J. van de Sande, MD, PhD9, Alessandro Gronchi, MD, PhD5, Cornelis Verhoef, MD, PhD10 and Enrico Martin, MD, PhD11, 1Erasmus MC Cancer Institute, Rotterdam, Zuid-Holland, Netherlands, 2Leiden University Medical Center, Leiden, Zuid-Holland, Netherlands, 3Leiden University, Leiden, Zuid-Holland, Netherlands, 4Erasmus Medical Center, Rotterdam, Netherlands, 5Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Milano, Italy, 6Neurologic Surgery, Mayo Clinic, Department of Neurologic Surgery, Rochester, MN, 7Mayo Clinic, Rochester, MN, 8University Medical Center Utrecht, Utrecht, Utrecht, Netherlands, 9Leiden University Medical Center, Leiden, Netherlands, 10Erasmus Medical Center, Rotterdam, Zuid-Holland, Netherlands, 11Utrecht University Medical Center, Utrecht, Utrecht, Netherlands
Introduction
Sarculator and PERSARC are two well performing prediction tools for survival in patients with soft tissue sarcoma (STS). These tools, however, do not include subtype specific predictors, such as neurofibromatosis type 1 (NF1) and triton status for malignant peripheral nerve sheath tumors (MPNSTs). This study aimed to assess the performance of currently available risk calculators in a cohort of patients with MPNST and to create an MPNST-specific prediction model including subtype-specific predictors for overall survival (OS).
Materials & Methods
This is a retrospective multicenter cohort study of patients with MPNST from eleven sarcoma centers. All patients diagnosed with primary MPNST who underwent macroscopically complete surgical resection from 2000-2019 were included in this study. A multivariable Cox proportional hazard model for OS was estimated with pre-specified predictors (age, grade, size, NF1 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 is the first model to incorporate MPNST-specific predictors in a prediction tool for OS. This 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.
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