Real-world study for identifying the predictive factors of surgical intervention and the value of magnetic resonance imaging in patients with low back pain

Quantitative Imaging in Medicine and Surgery

article

Hui Wang¹  Chang Liu²  Zhou Meng³  Wenxian Zhou¹  Tao Chen¹  Kai Zhang⁴  Aimin Wu¹ 

[1] Department of Orthopedics, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University , Zhejiang Provincial Key Laboratory of Orthopedics;Institute for Musculoskeletal Health , The University of Sydney and Sydney Local Health District;Department of Medicine , University of Maryland Medical Center Midtown Campus;Department of Orthopedics, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine , Shanghai Key Laboratory of Orthopedic Implants

关键词: Low back pain (LBP);    magnetic resonance imaging (MRI);    nomogram;    prediction;   

DOI  :  10.21037/qims-21-584

学科分类：外科医学

来源: AME Publications

【 摘 要 】

Background: Low back pain (LBP) is a prevalent disease and can be disabling. Currently, many patients with LBP with or without radiculopathy commonly undergo magnetic resonance imaging (MRI) for diagnosis and therapeutic assessment, yet the final intervention is mainly centered around nonoperative treatment. This study’s aim was to identify the predictive factors of surgical treatment and the value of MRI in patients with LBP with or without radiculopathy. Methods: The study included a training cohort that consisted of 461 patients with MRI from January 2014 to December 2018. Demographic characteristics and MRI findings were collected from our medical records. We developed and validated 2 nomograms to predict the possibility of receiving surgical treatment in LBP patients, based on multivariable logistic regression analysis. The performance of the 2 nomograms was assessed in terms of their calibration, discrimination, and clinical usefulness. An independent validation cohort containing 163 patients was comparatively analyzed. Results: The baseline model incorporated 6 clinicopathological variables, while the MRI model consisted of 9 variables including several MRI findings. Internal validation revealed the good performance of the 2 nomograms in discrimination and calibration, with a concordance index (C-index) of 0.799 (95% CI: 0.743–0.855) for the baseline model and 0.834 (95% CI: 0.783–0.884) for the MRI model, which showed that the addition of MRI findings to the nomogram failed to achieve better prognostic value (Z statistic =−1.509; P=0.131). Application of the 2 models in the validation cohort also showed good discrimination (baseline model: C-index 0.75, 95% CI: 0.671–0.829; MRI model: C-index 0.777, 95% CI: 0.696–0.857) and calibration. No significant predictive benefit was found in the MRI model in the validation cohort (Z statistic =−0.588; P=0.557). Conclusions: This study showed that clinical demographic characteristics provide good prognostic value to determine whether LBP patients with or without radiculopathy require surgical treatment. The addition of MRI findings yielded no significantly incremental prognostic value.

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