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Does the SORG Algorithm Predict 5-year Survival in Patients with Chondrosarcoma? An External Validation

Bongers, Michiel E. R. MD; Thio, Quirina C. B. S. MD; Karhade, Aditya V. BE; Stor, Merel L. BS; Raskin, Kevin A. MD; Lozano Calderon, Santiago A. MD, PhD; DeLaney, Thomas F. MD; Ferrone, Marco L. MD; Schwab, Joseph H. MD, MS

Clinical Orthopaedics and Related Research®: October 2019 - Volume 477 - Issue 10 - p 2296–2303
doi: 10.1097/CORR.0000000000000748
CLINICAL RESEARCH
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Background We developed a machine learning algorithm to predict the survival of patients with chondrosarcoma. The algorithm demonstrated excellent discrimination and calibration on internal validation in a derivation cohort based on data from the Surveillance, Epidemiology, and End Results (SEER) registry. However, the algorithm has not been validated in an independent external dataset.

Questions/purposes Does the Skeletal Oncology Research Group (SORG) algorithm accurately predict 5-year survival in an independent patient population surgically treated for chondrosarcoma?

Methods The SORG algorithm was developed using the SEER registry, which contains demographic data, tumor characteristics, treatment, and outcome values; and includes approximately 30% of the cancer patients in the United States. The SEER registry was ideal for creating the derivation cohort, and consequently the SORG algorithm, because of the high number of eligible patients and the availability of most (explanatory) variables of interest. Between 1992 to 2013, 326 patients were treated surgically for extracranial chondrosarcoma of the bone at two tertiary care referral centers. Of those, 179 were accounted for at a minimum of 5 years after diagnosis in a clinical note at one of the two institutions, unless they died earlier, and were included in the validation cohort. In all, 147 (45%) did not meet the minimum 5 years of followup at the institution and were not included in the validation of the SORG algorithm. The outcome (survival at 5 years) was checked for all 326 patients in the Social Security death index and were included in the supplemental validation cohort, to also ascertain validity for patients with less than 5 years of institutional followup. Variables used in the SORG algorithm to predict 5-year survival including sex, age, histologic subtype, tumor grade, tumor size, tumor extension, and tumor location were collected manually from medical records. The tumor characteristics were collected from the postoperative musculoskeletal pathology report. Predicted probabilities of 5-year survival were calculated for each patient in the validation cohort using the SORG algorithm, followed by an assessment of performance using the same metrics as used for internal validation, namely: discrimination, calibration, and overall performance. Discrimination was calculated using the concordance statistic (or the area under the Receiver Operating Characteristic (ROC) curve) to determine how well the algorithm discriminates between the outcome, which ranges from 0.5 (no better than a coin-toss) to 1.0 (perfect discrimination). Calibration was assessed using the calibration slope and intercept from a calibration plot to measure the agreement between predicted and observed outcomes. A perfect calibration plot should show a 45° upwards line. Overall performance was determined using the Brier score, ranging from 0 (excellent prediction) to 1 (worst prediction). The Brier score was compared with the null-model Brier score, which showed the performance of a model that ignored all the covariates. A Brier score lower than the null model Brier score indicated greater performance of the algorithm. For the external validation an F1-score was added to measure the overall accuracy of the algorithm, which ranges between 0 (total failure of an algorithm) and 1 (perfect algorithm).

The 5-year survival was lower in the validation cohort than it was in the derivation cohort from SEER (61.5% [110 of 179] versus 76% [1131 of 1544] ; p < 0.001). This difference was driven by higher proportion of dedifferentiated chondrosarcoma in the institutional population than in the derivation cohort (27% [49 of 179] versus 9% [131 of 1544]; p < 0.001). Patients in the validation cohort also had larger tumor sizes, higher grades, and nonextremity tumor locations than did those in the derivation cohort. These differences between the study groups emphasize that the external validation is performed not only in a different patient cohort, but also in terms of disease characteristics. Five-year survival was not different for both patient groups between subpopulations of patients with conventional chondrosarcomas and those with dedifferentiated chondrosarcomas.

Results The concordance statistic for the validation cohort was 0.87 (95% CI, 0.80–0.91). Evaluation of the algorithm’s calibration in the institutional population resulted in a calibration slope of 0.97 (95% CI, 0.68–1.3) and calibration intercept of -0.58 (95% CI, -0.20 to -0.97). Finally, on overall performance, the algorithm had a Brier score of 0.152 compared with a null-model Brier score of 0.237 for a high level of overall performance. The F1-score was 0.836. For the supplementary validation in the total of 326 patients, the SORG algorithm had a validation of 0.89 (95% CI, 0.85–0.93). The calibration slope was 1.13 (95% CI, 0.87–1.39) and the calibration intercept was -0.26 (95% CI, -0.57 to 0.06). The Brier score was 0.11, with a null-model Brier score of 0.19. The F1-score was 0.901.

Conclusions On external validation, the SORG algorithm retained good discriminative ability and overall performance but overestimated 5-year survival in patients surgically treated for chondrosarcoma. This internet-based tool can help guide patient counseling and shared decision making.

Level of Evidence Level III, prognostic study.

M. E. R. Bongers, Q. C. B. S. Thio, A.V. Karhade, M. L. Stor, K. A. Raskin, S. A. Lozano-Calderon, Department of Orthopaedic Surgery, Division of Orthopaedic Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA

T. F. DeLaney, Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA, USA

M. L. Ferrone, Department of Orthopaedic Surgery, Orthopaedic Oncology Service, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA

J. H. Schwab, Department of Orthopaedic Surgery, Division of Orthopaedic Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA

M. E. R. Bongers, Department of Orthopaedic Surgery, Division of Orthopaedic Oncology, Massachusetts General Hospital, Harvard Medical School, Room 3.550, Yawkey Building, Massachusetts General Hospital, 55 Fruit Street, Boston, MA, 02114, USA, Email: michielbongers@gmail.com

All ICMJE Conflict of Interest Forms for authors and Clinical Orthopaedics and Related Research® editors and board members are on file with the publication and can be viewed on request.

Each author certifies that neither he, nor any member of his immediate family, has funding or commercial associations (consultancies, stock ownership, equity interest, patent/licensing arrangements, etc) that might pose a conflict of interest in connection with the submitted article.

Each author certifies that his or her institution approved the human protocol for this investigation and that all investigations were conducted in conformity with ethical principles of research.

This work was performed at Massachusetts General Hospital, Boston, MA, USA.

Received November 21, 2018

Accepted March 08, 2019

Online date: April 27, 2019

© 2019 Lippincott Williams & Wilkins LWW
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