Development and external validation of predictive algorithms for six-week mortality in spinal metastasis using 4,304 patients from five institutions Journal Article
| Authors: | Karhade, A. V.; Fenn, B.; Groot, O. Q.; Shah, A. A.; Yen, H. K.; Bilsky, M. H.; Hu, M. H.; Laufer, I.; Park, D. Y.; Sciubba, D. M.; Steyerberg, E. W.; Tobert, D. G.; Bono, C. M.; Harris, M. B.; Schwab, J. H. |
| Article Title: | Development and external validation of predictive algorithms for six-week mortality in spinal metastasis using 4,304 patients from five institutions |
| Abstract: | BACKGROUND CONTEXT: Historically, spine surgeons used expected postoperative survival of 3-months to help select candidates for operative intervention in spinal metastasis. However, this cutoff has been challenged by the development of minimally invasive techniques, novel biologics, and advanced radiotherapy. Recent studies have suggested that a life expectancy of 6 weeks may be enough to achieve significant improvements in postoperative health-related quality of life. PURPOSE: The purpose of this study was to develop a model capable of predicting 6-week mortality in patients with spinal metastases treated with radiation or surgery. STUDY DESIGN/SETTING: A retrospective review was conducted at five large tertiary centers in the United States and Taiwan. PATIENT SAMPLE: The development cohort consisted of 3,001 patients undergoing radiotherapy and/or surgery for spinal metastases from one institution. The validation institutional cohort consisted of 1,303 patients from four independent, external institutions. OUTCOME MEASURES: The primary outcome was 6-week mortality. METHODS: Five models were considered to predict 6-week mortality, and the model with the best performance across discrimination, calibration, decision-curve analysis, and overall performance was integrated into an open access web-based application. RESULTS: The most important variables for prediction of 6-week mortality were albumin, primary tumor histology, absolute lymphocyte, three or more spine metastasis, and ECOG score. The elastic-net penalized logistic model was chosen as the best performing model with AUC 0.84 on evaluation in the independent testing set. On external validation in the 1,303 patients from the four independent institutions, the model retained good discriminative ability with an area under the curve of 0.81. The model is available here: https://sorg-apps.shinyapps.io/spinemetssurvival/. CONCLUSIONS: While this study does not advocate for the use of a 6-week life expectancy as criteria for considering operative management, the algorithm developed and externally validated in this study may be helpful for preoperative planning, multidisciplinary management, and shared decision-making in spinal metastasis patients with shorter life expectancy. © 2022 Elsevier Inc. |
| Keywords: | mortality; quality of life; logistic models; algorithms; algorithm; artificial intelligence; spinal neoplasms; statistical model; spine tumor; spinal metastases; external validation; machine learning; humans; prognosis; human |
| Journal Title: | Spine Journal |
| Volume: | 22 |
| Issue: | 12 |
| ISSN: | 1529-9430 |
| Publisher: | Elsevier Science Inc. |
| Date Published: | 2022-12-01 |
| Start Page: | 2033 |
| End Page: | 2041 |
| Language: | English |
| DOI: | 10.1016/j.spinee.2022.07.089 |
| PUBMED: | 35843533 |
| PROVIDER: | scopus |
| DOI/URL: | |
| Notes: | Article -- Export Date: 1 February 2023 -- Source: Scopus |
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