Department of Health Professions, Macquarie University, Sydney, Australia.
Faculty of Medicine and Health, Sydney School of Public Health, University of Sydney, Sydney, Australia.
Eur J Pain. 2019 Feb;23(2):341-353. doi: 10.1002/ejp.1308. Epub 2018 Sep 24.
The prognosis of acute low back pain (LBP) is typically good; however, there is substantial variation in individual patient's outcomes. We recently developed a prediction model that was able to predict the likelihood of pain recovery in patients with acute LBP who continue to have pain approximately 1 week after initially seeking care. The aims of the current study were to (a) re-categorize the variables in the developmental dataset to be able to validate the model in the validation dataset; (b) refit the existing model in the developmental dataset; and (c) validate the model in the validation dataset.
The validation study sample comprised 737 patients with acute LBP, with a pain score of ≥2/10, 1 week after initially seeking care and with duration of current episode of ≤4 weeks. The primary outcome measure was days to pain recovery. Some of the variables from the development dataset were re-categorized prior to refitting the existing model in the developmental dataset using Cox regression. The performance (calibration and discrimination) of the prediction model was then tested in the validation dataset.
Three variables of the development dataset were re-categorized. The performance of the prediction model with re-categorized variables in the development dataset was good (C-statistic = 0.76, 95% CI 0.70-0.82). The discrimination of the model using the validation dataset resulted in a C-statistic of 0.71 (95% CI 0.63-0.78). The calibration for the validation sample was acceptable at 1 month. However, at 1 week the predicted proportions within quintiles tended to overestimate the observed recovery proportions, and at 3 months, the predicted proportions tended to underestimate the observed recovery proportions.
The updated prediction model demonstrated reasonably good external validity and may be useful in practice, but further validation and impact studies in relevant populations should be conducted.
A clinical prediction model based on five easily collected variables demonstrated reasonable external validity. The prediction model has the potential to inform patients and clinicians of the likely prognosis of individuals with acute LBP but requires impact studies to assess its clinical usefulness.
急性腰痛（LBP）的预后通常良好；然而，个体患者的结果存在很大差异。我们最近开发了一种预测模型，能够预测在最初就诊后约 1 周仍持续疼痛的急性 LBP 患者疼痛恢复的可能性。本研究的目的是：（a）重新分类发展数据集的变量，以便在验证数据集中验证模型；（b）在发展数据集中重新拟合现有模型；（c）在验证数据集中验证模型。
验证研究样本包括 737 例急性 LBP 患者，就诊后 1 周时疼痛评分≥2/10，且当前发作持续时间≤4 周。主要结局测量为疼痛恢复的天数。在使用 Cox 回归重新拟合发展数据集中的现有模型之前，对发展数据集中的某些变量进行了重新分类。然后在验证数据集中测试预测模型的性能（校准和区分）。
对发展数据集中的三个变量进行了重新分类。在发展数据集中使用重新分类变量的预测模型的性能良好（C 统计量=0.76，95%CI 0.70-0.82）。使用验证数据集的模型的区分度导致 C 统计量为 0.71（95%CI 0.63-0.78）。验证样本的校准在 1 个月时可接受。然而，在 1 周时，五分位数内的预测比例倾向于高估观察到的恢复比例，而在 3 个月时，预测比例倾向于低估观察到的恢复比例。
更新后的预测模型显示出相当好的外部有效性，在实践中可能有用，但应在相关人群中进行进一步的验证和影响研究。
基于五个易于收集的变量的临床预测模型显示出了相当好的外部有效性。该预测模型有可能为急性 LBP 患者的个体预后提供信息，但需要影响研究来评估其临床实用性。
