Patel, Naresh

OBJECTIVE Chordomas are slow-growing tumors derived from notochord remnants. Despite margin-negative excision and postoperative radiation therapy, spinal chordomas (SCs) often progress. The potential of immunohistochemical (IHC) markers, such as epithelial membrane antigen (EMA), combined with machine learning algorithms to predict long-term (≥ 12 months) postoperative tumor progression, has been understudied. The authors aimed to identify IHC markers using trained tree-based algorithms to predict long-term (≥ 12 months) postoperative tumor progression. METHODS The authors reviewed the records of patients who underwent resection of SCs between January 2017 and June 2021 across the Mayo Clinic enterprise. Demographics, type of treatment, histopathology, and other relevant clinical factors were abstracted from each patient’s record. Low tumor progression was defined as more than a 94.3-mm3 decrease in the tumor size at the latest radiographic follow-up. Decision trees and random forest classifiers were trained and tested to predict the long-term volumetric progression after an 80/20 data split. RESULTS Sixty-two patients diagnosed with and surgically treated for SC were identified, of whom 31 were found to have a more advanced tumor progression based on the tumor volume change cutoff of 94.3 mm3. The mean age was 54.3 ± 13.8 years, and most patients were male (62.9%) and White (98.4%). The most common treatment modality was subtotal resection with radiation therapy (35.5%), with proton beam therapy being the most common (71%). Most SCs were sacrococcygeal (41.9%), followed by cervical (32.3%). EMA-positive SCs had a postoperative progression risk of 67%. Pancytokeratin-positive SCs had a progression rate of 67%; however, patients with S100 protein–positive SCs had a 54% risk of progression. The accuracy of this model in predicting the progression of unseen test data was 66%. Pancytokeratin (mean minimal depth = 1.57), EMA (mean minimal depth = 1.58), cytokeratin A1/A3 (mean minimal depth = 1.59), and S100 protein (mean minimal depth = 1.6) predicted the long-term volumetric progression. Multiway variable importance plots show the relative importance of the top 10 variables based on three measures of varying significance and their predictive role. CONCLUSIONS These IHC variables with tree-based machine learning tools successfully demonstrate a high capacity to identify a patient’s tumor progression pattern with an accuracy of 66%. Pancytokeratin, EMA, cytokeratin A1/A3, and S100 protein were the IHC drivers of a low tumor progression. This shows the power of machine learning algorithms in analyzing and predicting outcomes of rare conditions in a small sample size.

AbstractBackgroundSpinal cord stimulation (SCS) has been shown to provide pain relief for chronic back and leg pain due to failed back surgery syndrome. But many patients with chronic back pain have not had major back surgery or are not good candidates for surgery, and conventional medical management (CMM) provides limited relief. We have termed this condition nonsurgical refractory back pain (NSRBP). Level 1 evidence does not yet exist showing the therapeutic benefit of SCS for NSRBP.ObjectiveTo compare 10‐kHz SCS plus CMM (10‐kHz SCS + CMM) to CMM alone for treatment of NSRBP in terms of clinical and cost effectiveness.Study DesignMulticenter, randomized controlled trial (RCT), with subjects randomized 1:1 to either 10‐kHz SCS + CMM or CMM alone. Optional crossover occurs at 6 months if treatment does not achieve ≥50% pain relief.MethodsPatients with NSRBP as defined above may be enrolled if they are ineligible for surgery based on surgical consultation. Subjects randomized to 10‐kHz SCS + CMM will receive a permanent implant if sufficient pain relief is achieved in a temporary trial. Both groups will receive CMM per standard of care and will undergo assessments at baseline and at follow‐ups to 12 months. Self‐report outcomes include pain, disability, sleep, mental health, satisfaction, healthcare utilization, and quality of life.ResultsEnrollment was initiated on September 10, 2018. Prespecified independent interim analysis at 40% of the enrollment target indicated the sample size was sufficient to show superiority of treatment at the primary endpoint; therefore, enrollment was stopped at 211.ConclusionsThis large multicenter RCT will provide valuable evidence to guide clinical decisions in NSRBP.