TY - JOUR
T1 - To operate, or not to operate? Narrative review of the role of survival predictors in patient selection for operative management of patients with metastatic spine disease
AU - Pennington, Zach
AU - Ehresman, Jeff
AU - Cottrill, Ethan
AU - Lubelski, Daniel
AU - Lehner, Kurt
AU - Feghali, James
AU - Ahmed, A. Karim
AU - Schilling, Andrew
AU - Sciubba, Daniel M.
N1 - Funding Information:
Mr. Cottrill: F30 grant from National Institutes on Aging. Dr. Sciubba: consultant for Baxter, DePuy-Synthes, Globus Medical, K2M, Medtronic, NuVasive, and Stryker; unrelated grant support
Publisher Copyright:
© AANS 2021, except where prohibited by US copyright law
PY - 2021/1
Y1 - 2021/1
N2 - Accurate prediction of patient survival is an essential component of the preoperative evaluation of patients with spinal metastases. Over the past quarter of a century, a number of predictors have been developed, although none have been accurate enough to be instituted as a staple of clinical practice. However, recently more comprehensive survival calculators have been published that make use of larger data sets and machine learning to predict postoperative survival among patients with spine metastases. Given the glut of calculators that have been published, the authors sought to perform a narrative review of the current literature, highlighting existing calculators along with the strengths and weaknesses of each. In doing so, they identify two “generations” of scoring systems—a first generation based on a priori factor weighting and a second generation comprising predictive tools that are developed using advanced statistical modeling and are focused on clinical deployment. In spite of recent advances, the authors found that most predictors have only a moderate ability to explain variation in patient survival. Second-generation models have a greater prognostic accuracy relative to first-generation scoring systems, but most still require external validation. Given this, it seems that there are two outstanding goals for these survival predictors, foremost being external validation of current calculators in multicenter prospective cohorts, as the majority have been developed from, and internally validated within, the same single-institution data sets. Lastly, current predictors should be modified to incorporate advances in targeted systemic therapy and radiotherapy, which have been heretofore largely ignored.
AB - Accurate prediction of patient survival is an essential component of the preoperative evaluation of patients with spinal metastases. Over the past quarter of a century, a number of predictors have been developed, although none have been accurate enough to be instituted as a staple of clinical practice. However, recently more comprehensive survival calculators have been published that make use of larger data sets and machine learning to predict postoperative survival among patients with spine metastases. Given the glut of calculators that have been published, the authors sought to perform a narrative review of the current literature, highlighting existing calculators along with the strengths and weaknesses of each. In doing so, they identify two “generations” of scoring systems—a first generation based on a priori factor weighting and a second generation comprising predictive tools that are developed using advanced statistical modeling and are focused on clinical deployment. In spite of recent advances, the authors found that most predictors have only a moderate ability to explain variation in patient survival. Second-generation models have a greater prognostic accuracy relative to first-generation scoring systems, but most still require external validation. Given this, it seems that there are two outstanding goals for these survival predictors, foremost being external validation of current calculators in multicenter prospective cohorts, as the majority have been developed from, and internally validated within, the same single-institution data sets. Lastly, current predictors should be modified to incorporate advances in targeted systemic therapy and radiotherapy, which have been heretofore largely ignored.
KW - Minimally invasive surgery
KW - Oncology
KW - Patient selection
KW - Predictive analytics
KW - Quality of life
KW - Spinal metastases
KW - Survival prediction
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U2 - 10.3171/2020.6.SPINE20707
DO - 10.3171/2020.6.SPINE20707
M3 - Review article
C2 - 32916652
AN - SCOPUS:85098873149
SN - 1547-5654
VL - 34
SP - 135
EP - 149
JO - Journal of Neurosurgery: Spine
JF - Journal of Neurosurgery: Spine
IS - 1
ER -