Evidence map›Paper›PMID 42560503›Full record

ArticleEuropean spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society2026

Age-referenced modeling of lumbar disc degeneration and its association with chronic low back pain: an MRI-based cross-sectional study.

Tim Victor Mihalache, Lukas Schönnagel, Luis Becker, Lea Cordes, Hendrik Schmidt, Matthias Pumberger

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Article in European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Tim Victor MihalacheDepartment of Orthopaedic and Trauma Surgery, Charité - University Medicine Berlin, Berlin, Germany. tim-victor.mihalache@charite.de.
Lukas SchönnagelDepartment of Orthopaedic and Trauma Surgery, Charité - University Medicine Berlin, Berlin, Germany. lukas.schoennagel@charite.de.
Luis BeckerDepartment of Orthopaedic and Trauma Surgery, Charité - University Medicine Berlin, Berlin, Germany.
Lea CordesCenter for Musculoskeletal Biomechanics and Regeneration, Julius Wolff Institut Berlin, Berlin, Germany.
Hendrik Schmidt *Center for Musculoskeletal Biomechanics and Regeneration, Julius Wolff Institut Berlin, Berlin, Germany.
Matthias Pumberger *Department of Orthopaedic and Trauma Surgery, Charité - University Medicine Berlin, Berlin, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLumbar intervertebral disc degeneration is commonly found in patients with chronic low back pain (cLBP) but is also frequently observed in asymptomatic individuals. The lack of age-referenced values complicates the clinical interpretation of degenerative magnetic resonance imaging (MRI) findings. Using an age-dependent prediction model derived from a non-cLBP reference cohort, we estimated expected disc degeneration and examined whether degeneration exceeding age-expected levels is associated with cLBP status and pain intensity.

methodsThis cross-sectional analysis included 1,523 participants with complete lumbar Pfirrmann grading and clinical data (1,121 with cLBP; 402 without cLBP). Age-expected degeneration was modeled in the non-cLBP reference cohort using the Pfirrmann sum score from L1/2 to L5/S1. Standardized residuals were used to classify participants as below-expected, age-expected, or above-expected. Associations with cLBP and current pain intensity were assessed using multivariable regression adjusted for sex, body mass index (BMI), and smoking history; sensitivity models additionally adjusted for a cumulative score of Modic-classified vertebral bone marrow signal changes.

resultsBased on the non-cLBP reference cohort, a quadratic age-referenced reference model was established for the Pfirrmann sum score (L1/2-L5/S1):[Formula: see text] Above-expected lumbar Pfirrmann degeneration was associated with higher odds of cLBP compared with age-expected degeneration (odds ratio [OR] = 1.84; 95% confidence interval [CI], 1.36-2.50; p < 0.001) and compared with below-expected degeneration (OR = 4.13; 95% CI, 2.57-6.65; p < 0.001). After additional adjustment for the cumulative Modic score, the corresponding ORs were 1.66 (95% CI, 1.21-2.28; p = 0.002) and 3.63 (95% CI, 2.23-5.90; p < 0.001).

conclusionThis study provides an age-referenced framework for contextualizing lumbar Pfirrmann degeneration relative to expected values in individuals without cLBP. Above-age-expected multilevel disc degeneration was independently associated with cLBP status, supporting the clinical relevance of age-adjusted interpretation of conventional lumbar MRI degeneration grading.

Indexed as

Age-adjusted degenerationChronic low back painLumbar spineMagnetic resonance imagingNormative modelingPfirrmann score

Identifiers

PMID42560503

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