Department of Epidemiology and Biostatistics, Amsterdam Public health research Institute, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
Physical Therapy Practice Panken, Roermond, The Netherlands.
BMC Musculoskelet Disord. 2020 Mar 12;21(1):163. doi: 10.1186/s12891-020-3186-8.
Currently used performance measures for discrimination were not informative to determine the clinical benefit of predictor variables. The purpose was to evaluate if a former relevant predictor, kinesiophobia, remained clinically relevant to predict chronic occupational low back pain (LBP) in the light of a novel discriminative performance measure, Decision Curve Analysis (DCA), using the Net Benefit (NB).
Prospective cohort data (n = 170) of two merged randomized trials with workers with LBP on sickleave, treated with Usual Care (UC) were used for the analyses. An existing prediction model for chronic LBP with the variables 'a clinically relevant change in pain intensity and disability status in the first 3 months', 'baseline measured pain intensity' and 'kinesiophobia' was compared with the same model without the variable 'kinesiophobia' using the NB and DCA.
Both prediction models showed an equal performance according to the DCA and NB. Between 10 and 95% probability thresholds of chronic LBP risk, both models were of clinically benefit. There were virtually no differences between both models in the improved classification of true positive (TP) patients.
This study showed that the variable kinesiophobia, which was originally included in a prediction model for chronic LBP, was not informative to predict chronic LBP by using DCA. DCA and NB have to be used more often to develop clinically beneficial prediction models in workers because they are more sensitive to evaluate the discriminate ability of prediction models.
目前用于判别能力的绩效衡量指标并不能提供信息来确定预测变量的临床获益。本研究旨在评估一种先前相关的预测因子——运动恐惧，在使用新的判别性能测量方法——决策曲线分析（DCA）和净获益（NB）的情况下，是否仍然对预测慢性职业性下腰痛（LBP）具有临床相关性。
使用两项合并的随机试验中患有 LBP 的休病假工人的前瞻性队列数据（n=170）进行分析。使用“前 3 个月内疼痛强度和残疾状态的临床相关变化”、“基线测量的疼痛强度”和“运动恐惧”这三个变量的现有慢性 LBP 预测模型，与不包含“运动恐惧”变量的相同模型进行比较，使用 NB 和 DCA 进行比较。
根据 DCA 和 NB，两个预测模型的性能均相当。在慢性 LBP 风险的 10%至 95%概率阈值之间，两个模型都具有临床获益。在真正阳性（TP）患者的分类改善方面，两个模型之间几乎没有差异。
这项研究表明，原本包含在慢性 LBP 预测模型中的运动恐惧变量，通过 DCA 预测慢性 LBP 时没有提供信息。在工人中开发具有临床获益的预测模型时，应更频繁地使用 DCA 和 NB，因为它们更能敏感地评估预测模型的判别能力。
