External validation of 12 existing survival prediction models for patients with spinal metastases

IF 4.7 1区 医学 Q1 CLINICAL NEUROLOGY Spine Journal Pub Date : 2025-07-01 Epub Date: 2025-01-31 DOI:10.1016/j.spinee.2025.01.014
B.J.J. Bindels MD , R.H. Kuijten BSc , O.Q. Groot MD, PhD , E.H. Huele MD , R. Gal PhD , M.C.H. de Groot PhD , J.M. van der Velden MD, PhD , D. Delawi MD, PhD , J.H. Schwab MD, MS , H.M. Verkooijen MD, PhD , J.J. Verlaan MD, PhD , D. Tobert MD , J.P.H.J. Rutges MD, PhD
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Abstract

BACKGROUND CONTEXT

Survival prediction models for patients with spinal metastases may inform patients and clinicians in shared decision-making.

PURPOSE

To externally validate all existing survival prediction models for patients with spinal metastases.

DESIGN

Prospective cohort study using retrospective data.

PATIENT SAMPLE

A total of 953 patients.

OUTCOME MEASURES

Survival in months, area under the curve (AUC), and calibration intercept and slope.

METHOD

This study included patients with spinal metastases referred to a single tertiary referral center between 2016 and 2021. Twelve models for predicting 3, 6, and 12-month survival were externally validated Bollen, Mizumoto, Modified Bauer, New England Spinal Metastasis Score, Original Bauer, Oswestry Spinal Risk Index (OSRI), PathFx, Revised Katagiri, Revised Tokuhashi, Skeletal Oncology Research Group Machine Learning Algorithm (SORG-MLA), Tomita, and Van der Linden. Discrimination was assessed using (AUC) and calibration using the intercept and slope. Calibration was considered appropriate if calibration measures were close to their ideal values with narrow confidence intervals.

RESULTS

In total, 953 patients were included. Survival was 76.4% at 3 months (728/953), 62.2% at 6 months (593/953), and 50.3% at 12 months (479/953). Revised Katagiri yielded AUCs of 0.79 (95% CI, 0.76–0.82) to 0.81 (95% CI, 0.79–0.84), Bollen yielded AUCs of 0.76 (95% CI, 0.73–0.80) to 0.77 (95% CI, 0.75–0.80), and OSRI yielded AUCs of 0.75 (95% CI, 0.72–0.78) to 0.77 (95% CI, 0.74–0.79). The other 9 prediction models yielded AUCs ranging from 0.59 (95% CI, 0.55–0.63) to 0.76 (95% CI, 0.74–0.79). None of the 12 models yielded appropriate calibration.

CONCLUSIONS

Twelve survival prediction models for patients with spinal metastases yielded poor to fair discrimination and poor calibration. Survival prediction models may inform decision-making in patients with spinal metastases, provided that recalibration using recent patient data is performed.
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12种现有的脊柱转移患者生存预测模型的外部验证。
背景:脊髓转移患者的生存预测模型可以为患者和临床医生共同决策提供信息。目的:从外部验证所有现有的脊柱转移患者的生存预测模型设计:采用回顾性数据的前瞻性队列研究患者样本:953例患者结果测量:月生存率、曲线下面积(AUC)、校准截距和斜率方法:本研究纳入了2016-2021年间在单一三级转诊中心转诊的脊柱转移患者。预测3、6和12个月生存的12个模型是外部验证的Bollen、Mizumoto、Modified Bauer、New England Spinal Metastasis Score、Original Bauer、Oswestry脊柱风险指数(OSRI)、PathFx、Revised Katagiri、Revised Tokuhashi、骨骼肿瘤研究小组机器学习算法(sor - mla)、Tomita和Van der Linden。使用AUC评估鉴别,使用截距和斜率进行校准。如果校准测量值接近理想值且置信区间窄,则认为校准是适当的。结果:共纳入953例患者。3个月生存率为76.4%(728/953),6个月生存率为62.2%(593/953),12个月生存率为50.3%(479/953)。修正后的Katagiri的auc为0.79 (95%CI 0.76;0.82)至0.81 (95%CI 0.79;0.84), Bollen的auc为0.76 (95%CI 0.73;0.80)至0.77 (95%CI 0.75;0.80), OSRI的auc为0.75 (95%CI 0.72;0.78)至0.77 (95%CI 0.74;0.79)。其他9个预测模型的auc范围为0.59 (95%CI 0.55;0.63)至0.76 (95%CI 0.74;0.79)。12个模型均未得到适当的校正。结论:12种脊髓转移患者的生存预测模型具有较差的公平区分和较差的校准。生存预测模型可以为脊柱转移患者的决策提供信息,前提是使用最近的患者数据进行重新校准。资助:本研究由美国国家科学促进会(AOSpine)根据发现与创新奖(aoos - dia -22-012- tum)资助。共收到4万瑞士法郎(4.5万美元)。
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来源期刊
Spine Journal
Spine Journal 医学-临床神经学
CiteScore
8.20
自引率
6.70%
发文量
680
审稿时长
13.1 weeks
期刊介绍: The Spine Journal, the official journal of the North American Spine Society, is an international and multidisciplinary journal that publishes original, peer-reviewed articles on research and treatment related to the spine and spine care, including basic science and clinical investigations. It is a condition of publication that manuscripts submitted to The Spine Journal have not been published, and will not be simultaneously submitted or published elsewhere. The Spine Journal also publishes major reviews of specific topics by acknowledged authorities, technical notes, teaching editorials, and other special features, Letters to the Editor-in-Chief are encouraged.
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