Objective Osteoporotic vertebral compression fractures (OVCFs) are a major public health concern. While percutaneous vertebral augmentation (PVA) is an effective treatment for OVCF, adjacent vertebral fractures (AVF) often occur post-PVA, adversely affecting treatment outcomes. This study aims to develop a nomogram for predicting AVF risk using multicenter data to aid clinical decision-making for OVCF patients.
Methods We retrospectively analyzed patients who underwent PVA at 3 hospitals between 2017 and 2022. The cohort was divided into a training set (80%) and a validation set (20%). Independent risk factors for AVF were identified using LASSO (least absolute shrinkage and selection operator) and logistic regression. Seven significant factors were: bone mineral density, diabetes, total fractured vertebrae, intravertebral vacuum cleft sign, recovery of local kyphosis angle, regular aerobic exercise, and lumbar brace use.
Results Among the 483 patients, 52 (10.76%) developed adjacent vertebral refractures within 2 years. The nomogram demonstrated high predictive accuracy, with area under the curves of 89.21% in the training set and 98.33% in the validation set.
Conclusion This pioneering nomogram, incorporating baseline, surgical, and postoperative factors, provides valuable guidance for spine surgeons in preoperative planning and postoperative management, enabling personalized prognosis and rehabilitation for OVCF patients.
Citations
Citations to this article as recorded by
Risk Factors for Osteoporotic Vertebral Compression Fracture and Evaluation of Clinical Outcomes of Minimally Invasive Vertebral Augmentation Zhuang Zhu, Ying Li, Jixiang Chen, Shuang Su, Ru Tao, Defeng Wang Global Spine Journal.2026;[Epub] CrossRef
Prediction models for subsequent vertebral fractures after percutaneous vertebroplasty or kyphoplasty: a systematic review and critical appraisal Linlin Zhang, Shuqiu Lin, Wenping Xue, Wei Wang, Yanling Zhou BMC Musculoskeletal Disorders.2026;[Epub] CrossRef
Functional recovery and pain reduction following surgical and non-surgical management of osteoporosis-related bone, joint, and spine disorders Dr. Utkarsh Mahera, Dr. Saurabh Sahu, Mahesh Kumar Navadaya, Dr. Longjam Darendrajit Singh, Dr. Bhagyesh Darji, Dr. Veenakirthika.S PAIN, JOINTS, SPINE.2026; : 106. CrossRef
The osteoporosis-fracture cascade: new insights into vertebral fracture prevalence and financial costs in China Guoliang Ma, He Yin, Liguo Zhu International Journal of Surgery.2025; 111(7): 4921. CrossRef
Objective Primary spinal cord glioblastoma (PSCGBM) is a rare malignancy with a poor prognosis. To date, no prognostic nomogram for this rare disease was established. Hence, we aimed to develop a nomogram to predict overall survival (OS) of PSCGBM.
Methods Clinical data of patients with PSCGBM was retrospectively collected from the neurosurgery department of Soochow University Affiliated Second Hospital and the Surveillance Epidemiology and End Results database. Information including age, sex, race, tumor extension, extent of resection, adjuvant treatment, marital status, income, year of diagnosis and months from diagnosis to treatment were recorded. Univariate and multivariate Cox regression analyses were used to identify independent prognostic factors for PSCGBM. A nomogram was constructed to predict 1-year, 1.5-year, and 2-year OS of PSCGBM.
Results A total of 132 patients were included. The 1-year, 1.5-year, and 2-year OS were 45.5%, 29.5%, and 18.9%, respectively. Four variables: age groups, tumor extension, extent of resection, and adjuvant therapy, were identified as independent prognostic factors. The nomogram showed robust discrimination with a C-index value for the prediction of 1-year OS, 1.5-year OS, and 2-year of 0.71 (95% confidence interval [CI], 0.61–0.70), 0.72 (95% CI, 0.62–0.70), and 0.70 (95% CI, 0.61–0.70), respectively. The calibration curves exhibited high consistencies between the predicted and observed survival probability in this cohort.
Conclusion We have developed and internally validated a nomogram for predicting the survival outcome of PSCGBM for the first time. The nomogram has the potential to assist clinicians in making individualized predictions of survival outcome of PSCGBM.
Citations
Citations to this article as recorded by
Influence of treatment modalities on survival and progression free survival in primary spinal cord glioblastoma: a systematic review and individual participant data meta-analysis Pedro Lucas Negromonte Guerra, Inaê Carolline Silveira Silva, Deoclides Lima, Mateus Rodrigues Souza, Tomoo Inoue, Toshiki Endo, Eduardo Vieira Carvalho Júnior European Spine Journal.2026; 35(5): 2566. CrossRef
Disease characteristics and clinical specific survival prediction of spinal ependymoma: a genetic and population-based study Tengyue Fu, Chuxiao Mao, Zhuming Chen, Yuxiang Huang, Houlin Li, Chunhua Wang, Jie Liu, Shenyu Li, Famu Lin Frontiers in Neurology.2024;[Epub] CrossRef
Objective To develop a nomogram for the prediction of tracheostomy in patients with traumatic cervical spinal cord injury (TCSCI).
Methods A total of 689 TCSCI patients were included in our study. First, the variable selection was performed using between-group comparisons and LASSO regression analysis. Second, a multivariate logistic regression analysis (MLRA) with a step-by-step method was performed. A nomogram model was developed based on the MLRA. Finally, the model was validated on the training set and validation set.
Results The nomogram prediction model incorporated 5 predictors, including smoking history, dislocation, thoracic injury, American Spinal Injury Association (ASIA) grade, and neurological level of injury (NLI). The area under curve in the training group and in the validation group were 0.883 and 0.909, respectively. The Hosmer-Lemeshow test result was p = 0.153. From the decision curve analysis curve, the model performed well and was feasible to make beneficial clinical decisions.
Conclusion The nomogram combining dislocation, thoracic injury, ASIA grade A, NLI, and smoking history was validated as a reliable model for the prediction of tracheostomy.
Citations
Citations to this article as recorded by
Development and validation of a nomogram for predicting tracheostomy risk in traumatic cervical spinal cord injury Weiting Chen, Xiaoshuang Jiang, Xixi Guo, Jiuzhou Lin, Min Tang, Nanlin Dou Frontiers in Neurology.2026;[Epub] CrossRef
Management of acute cervical spinal cord injury in the non‐specialist intensive care unit: a narrative review of current evidence M. D. Wiles, I. Benson, L. Edwards, R. Miller, F. Tait, A. Wynn‐Hebden Anaesthesia.2024; 79(2): 193. CrossRef
Traumatic spinal cord injury in South Korea for 13 years (2008–2020) Sung Hyun Noh, Eunyoung Lee, Kyoung-Tae Kim, Sang Hyun Kim, Pyung Goo Cho Scientific Reports.2024;[Epub] CrossRef
Co-Administration of Resolvin D1 and Peripheral Nerve-Derived Stem Cell Spheroids as a Therapeutic Strategy in a Rat Model of Spinal Cord Injury Seung-Young Jeong, Hye-Lan Lee, SungWon Wee, HyeYeong Lee, GwangYong Hwang, SaeYeon Hwang, SolLip Yoon, Young-Il Yang, Inbo Han, Keung-Nyun Kim International Journal of Molecular Sciences.2023; 24(13): 10971. CrossRef
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