An effective screening tool for uncovering degenerative cervical myelopathy: Results of the prospective multicenter SCREEN-DCM study
Year: 2026
Type: article
Study design: Observational Study
Abstract: Background context: Degenerative cervical myelopathy (DCM) is a leading cause of spinal cord injury, yet it remains frequently undiagnosed. Earlier identification may help guide patients into appropriate diagnostic and referral pathways before substantial neurological disability has accumulated. This study aimed to evaluate the diagnostic performance of SCREEN-DCM for identifying previously undiagnosed DCM. Material and methods: We conducted a prospective multicenter diagnostic accuracy study, where 200 consecutive adults presenting with lumbar degenerative disease were screened with the SCREEN-DCM clinical score, based on established DCM symptoms, signs, and risk factors. SCREEN-DCM scores ≥3 were considered positive. Results: 69 (34.5%) participants screened positive and 131 (65.5%) screened negative. Cervical MRI was performed in 83 participants. DCM was identified in 29 of 57 screen-positive patients and 1 of 26 screen-negative patients. SCREEN-DCM demonstrated 96.7% sensitivity, 47.2% specificity, 50.9% positive predictive value, 96.2% negative predictive value, and an AUC of 0.87 (95% CI, 0.79-0.95). Approximately two MRIs were required to detect one DCM case among screen-positive patients. Diagnostic sensitivity remained high across exploratory age groups. A simplified eight-variable model showed comparable discrimination (AUC, 0.85; 95% CI, 0.77-0.93), with Hoffman's sign, gait ataxia, and hand clumsiness among the strongest predictors of DCM. Conclusions: SCREEN-DCM has a very high sensitivity to identify DCM in previously undiagnosed patients. By identifying patients who may otherwise experience diagnostic delay, the screening tool could support earlier referral and prevention of avoidable neurological disability.
Source: Brain and Spine
Language: English
Subfield: Surgery
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $1,950
OpenAlex ID: W7222704037
