Purpose

Surgeons need tools to provide individualised estimates of surgical outcomes and the uncertainty surrounding these, to convey realistic expectations to the patient. This study developed and validated prognostic models for patients undergoing surgical treatment of lumbar disc herniation, to predict outcomes 1 year after surgery, and implemented these models in an online prediction tool.

Methods

Using the data of 1244 patients from a large spine unit, LASSO and linear regression models were fitted with 90% upper prediction limits, to predict scores on the Core Outcome Measures Index, and back and leg pain. Candidate predictors included sociodemographic factors, baseline symptoms, medical history, and surgeon characteristics. Temporal validation was conducted on 364 more recent patients at the same unit, by examining the proportion of observed outcomes exceeding the threshold of the 90% upper prediction limit (UPL), and by calculating mean bias and other calibration measures.

Results

Poorer outcome was predicted by obesity, previous spine surgery, and having basic obligatory (rather than private) insurance. In the validation data, fewer than 12% of outcomes were above the 90% UPL. Calibration plots for the model validation showed values for mean bias < 0.5 score points and regression slopes close to 1.

Conclusion

While the model accuracy was good overall, the prediction intervals indicated considerable predictive uncertainty on the individual level. Implementation studies will assess the clinical usefulness of the online tool. Updating the models with additional predictors may improve the accuracy and precision of outcome predictions.

Graphic abstract

These slides can be retrieved under Electronic Supplementary Material.

中文翻译：

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腰椎间盘突出症减压手术后1年临床预后模型的开发和时间验证。

目的

外科医生需要工具来提供个性化的手术结果估计值和围绕这些结果的不确定性，以向患者传达现实的期望。这项研究开发并验证了接受腰椎间盘突出症手术治疗的患者的预后模型，以预测术后1年的预后，并在在线预测工具中实施这些模型。

方法

利用来自大型脊柱单元的1244例患者的数据，对LASSO和线性回归模型进行了90％的预测上限，以预测核心结果指标和得分以及背部和腿部疼痛的得分。候选预测因子包括社会人口统计学因素，基线症状，病史和外科医生特征。通过检查超过90％预测上限（UPL）阈值的观察到结果的比例，并通过计算平均偏差和其他校准措施，对同一单位的364位新近患者进行了时间验证。

结果

肥胖，先前的脊柱手术以及具有基本的强制性（而非私人）保险可预示结果较差。在验证数据中，只有不到12％的结果高于90％的UPL。用于模型验证的校准图显示了平均值偏差<0.5得分点和回归斜率接近1的值。

结论

虽然模型的总体准确度很高，但预测间隔表明各个级别的预测不确定性很大。实施研究将评估在线工具的临床实用性。使用其他预测变量更新模型可以提高结果预测的准确性和准确性。

图形摘要

这些幻灯片可以在“电子补充材料”下找到。