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Spinal Instability Neoplastic Score: An Analysis of Reliability and Validity From the Spine Oncology Study Group
Open accessAbstract
Purpose: Standardized indications for treatment of tumor-related spinal instability are hampered by the lack of a valid and reliable classification system. The objective of this study was to determine the interobserver reliability, intraobserver reliability, and predictive validity of the Spinal Instability Neoplastic Score (SINS). Methods: Clinical and radiographic data from 30 patients with spinal tumors were classified as stable, potentially unstable, and unstable by members of the Spine Oncology Study Group. The median category for each patient case (consensus opinion) was used as the gold standard for predictive validity testing. On two occasions at least 6 weeks apart, each rater also scored each patient using SINS. Each total score was converted into a three-category data field, with 0 to 6 as stable, 7 to 12 as potentially unstable, and 13 to 18 as unstable. Results: The κ statistics for interobserver reliability were 0.790, 0.841, 0.244, 0.456, 0.462, and 0.492 for the fields of location, pain, bone quality, alignment, vertebral body collapse, and posterolateral involvement, respectively. The κ statistics for intraobserver reliability were 0.806, 0.859, 0.528, 0.614, 0.590, and 0.662 for the same respective fields. Intraclass correlation coefficients for inter- and intraobserver reliability of total SINS score were 0.846 (95% CI, 0.773 to 0.911) and 0.886 (95% CI, 0.868 to 0.902), respectively. The κ statistic for predictive validity was 0.712 (95% CI, 0.676 to 0.766). Conclusion: SINS demonstrated near-perfect inter- and intraobserver reliability in determining three clinically relevant categories of stability. The sensitivity and specificity of SINS for potentially unstable or unstable lesions were 95.7% and 79.5%, respectively.
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The Measurement of Observer Agreement for Categorical Data
Landis, J. R., & Koch, G. G. (1977) · Biometrics · doi:10.2307/2529310 · Cited by 81,148
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Shrout, P. E., & Fleiss, J. L. (1979) · Psychological Bulletin · doi:10.1037/0033-2909.86.2.420 · Cited by 24,532
Measuring nominal scale agreement among many raters.
Fleiss, J. L. (1971) · Psychological Bulletin · doi:10.1037/h0031619 · Cited by 8,733
Statistics Notes: Diagnostic tests 2: predictive values
Altman, D. G., & Bland, J. M. (1994) · BMJ · doi:10.1136/bmj.309.6947.102 · Cited by 1,711
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Decision curve analysis to evaluate the clinical benefit of prediction models
Vickers, A. J., & Holland, F. (2021) · The Spine Journal · doi:10.1016/j.spinee.2021.02.024 · Cited by 394
Spratt, D. E., Beeler, W. H., de Moraes, F. Y., Rhines, L. D., Gemmete, J. J., Chaudhary, N., Shultz, D. B., Smith, S. R., Berlin, A., Dahele, M., et al. (2017) · The Lancet Oncology · doi:10.1016/s1470-2045(17)30612-5 · Cited by 363
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- Authors
- Fourney, D. R., Frangou, E. M., Ryken, T. C., DiPaola, C. P., Shaffrey, C. I., Berven, S. H., Bilsky, M. H., Harrop, J. S., Fehlings, M. G., Boriani, S., Chou, D., Schmidt, M. H., Polly, D. W., Biagini, R., Burch, S., Dekutoski, M. B., Ganju, A., Gerszten, P. C., Gokaslan, Z. L., Groff, M. W., Liebsch, N. J., Mendel, E., Okuno, S. H., Patel, S., Rhines, L. D., Rose, P. S., Sciubba, D. M., Sundaresan, N., Tomita, K., Varga, P. P., Vialle, L. R., Vrionis, F. D., Yamada, Y., & Fisher, C. G.
- Venue
- Journal of Clinical Oncology
- Published
- 2011-08-01
- Volume
- 29
- Issue
- 22
- Pages
- 3072-3077
- ISSN
- 0732-183X (ISSN-L)
- 1527-7755
- OpenAlex
- W2160698388
- Cited by
- 551
- References
- 4
- FWCI
- 17.48
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Fourney, D. R., Frangou, E. M., Ryken, T. C., DiPaola, C. P., Shaffrey, C. I., Berven, S. H., Bilsky, M. H., Harrop, J. S., Fehlings, M. G., Boriani, S., Chou, D., Schmidt, M. H., Polly, D. W., Biagini, R., Burch, S., Dekutoski, M. B., Ganju, A., Gerszten, P. C., Gokaslan, Z. L., . . . Fisher, C. G. (2011). Spinal Instability Neoplastic Score: An Analysis of Reliability and Validity From the Spine Oncology Study Group. Journal of Clinical Oncology. https://doi.org/10.1200/jco.2010.34.3897
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.