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SPINE-RISK VE: Multimodal Predictive Model for Failed Back Surgery Syndrome in Venezuelan Surgical Patients

Observational Persistent Spinal Pain Syndrome Type 2 (PSPS-T) Lower Spine Chronic Low Back Pain Postoperative Pain Lumbar Spine Surgery

For patients and families

In plain language

An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.

What is being studied
The protocol lists: SPINE-RISK VE multimodal preoperative assessment.
Who it may be relevant to
Registry conditions: Persistent Spinal Pain Syndrome Type 2 (PSPS-T) Lower Spine, Chronic Low Back Pain, Postoperative Pain, Lumbar Spine Surgery. Basic parameters: 18 years — 100 years · All.
What needs checking
Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
Where it takes place
Venezuela
Next step
Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
Official title

SPINE-RISK VE: Development and Internal Validation of a Multimodal Preoperative Predictive Model for Failed Back Surgery Syndrome Using Inflammatory Biomarkers, Lumbar MRI Findings, and Psychosocial Factors in Venezuelan Surgical Patients

Overview

SPINE-RISK VE is a prospective multicenter cohort study designed to develop and internally validate a multimodal preoperative predictive model for Failed Back Surgery Syndrome (FBSS), now classified as Persistent Spinal Pain Syndrome Type 2 (PSPS-T2) per ICD-11 (code MG30.51), in Venezuelan adults patients undergoing elective lumbar spine surgery. The model integrates three variable domains obtainable from routine preoperative evaluation at zero additional cost to the patient: (1) inflammatory laboratory biomarkers (C-reactive protein \[CRP\], neutrophil-to-lymphocyte ratio \[NLR\], albumin, glycated hemoglobin \[HbA1c\], erythrocyte sedimentation rate \[ESR\]); (2) preoperative lumbar magnetic resonance imaging (MRI) findings (Modic changes, Pfirrmann disc degeneration grade, foraminal stenosis, number of surgical levels, spondylolisthesis); and (3) validated psychosocial instruments (Patient Health Questionnaire-9 \[PHQ-9\], Pain Catastrophizing Scale \[PCS\], smoking status, benzodiazepine use, prior lumbar surgery). Analysis proceeds in two phases: Phase 1 applies multivariable logistic regression with Least Absolute Shrinkage and Selection Operator (LASSO) variable selection to generate a printable clinical nomogram; Phase 2 applies a random forest machine learning algorithm with 10-fold cross-validation. Model reporting follows Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis plus Artificial Intelligence (TRIPOD+AI) guidelines. SPINE-RISK VE aims to produce the first validated multimodal predictive model for PSPS-T2/FBSS was developed in a Latin American surgical cohort, providing neurosurgeons with an evidence-based preoperative risk stratification tool applicable without Additional technological infrastructure.

Detailed description

Failed Back Surgery Syndrome (FBSS), formally reclassified as Persistent Spinal Pain Syndrome Type 2 (PSPS-T2) in ICD-11 (code MG30.51), affects 10-40% of patients undergoing lumbar spine surgery and constitutes one of the most complex therapeutic challenges in contemporary neurosurgery. Despite the identification of individual risk factors in the literature, no validated multimodal predictive model integrating laboratory biomarkers, lumbar magnetic resonance imaging (MRI) morphology, and psychosocial variables exist for Latin American surgical populations.

The best available predictive model to date achieved Area Under the Receiver Operating Characteristic Curve (AUC) of 0.715 for decompression and 0.701 for fusion using only electronic health record variables, without laboratory biomarkers or MRI-derived predictors, and without validation in any Latin American cohort. SPINE-RISK VE addresses this gap through a prospective multicenter cohort design enrolling 100-150 adults with Elective lumbar surgery indication at three Venezuelan referral centers.

PREDICTOR DOMAINS:

Domain 1 - Inflammatory biomarkers:

C-reactive protein (CRP greater than 3 mg/L), neutrophil-to-lymphocyte ratio (NLR greater than 3.0), serum albumin (less than 3.5 g/dL), glycated hemoglobin (HbA1c greater than 7%), and erythrocyte sedimentation rate (ESR). All obtainable from standard preoperative Laboratory panels.

Domain 2 - Lumbar MRI findings: Modic changes (Types I-III), disc degeneration grade (Pfirrmann scale I-V), foraminal stenosis, number of surgical levels, and Spondylolisthesis grade (Meyerding I-IV). All from already-requested preoperative imaging.

Domain 3 - Psychosocial factors: depression (Patient Health Questionnaire-9 \[PHQ-9\] cutoff of 10 or greater), pain catastrophizing (Pain Catastrophizing Scale \[PCS\] cutoff of 30 or greater, active smoking, preoperative benzodiazepine use, and prior lumbar surgery history.

PRIMARY OUTCOME: PSPS-T2/FBSS incidence at 12 months, defined as the Numeric Rating Scale (NRS) of 4 or greater AND Oswestry Disability Index (ODI) of 40% or greater at postoperative follow-up, consistent with International Association for the Study of Pain (IASP) criteria.

ANALYTICAL PLAN:

Phase 1: Multivariable logistic regression with Least Absolute Shrinkage and Selection Operator (LASSO) regularization to identify independent predictors and generate a Printable clinical nomogram. Software: R Version 4.x (glmnet, rms packages).

Phase 2: Random forest (500 trees, 10-fold cross-validation) compared against Extreme Gradient Boosting (XGBoost) and logistic regression. Performance metrics: AUC-ROC (target 0.80 or greater), sensitivity, specificity, calibration (Hosmer-Lemeshow test, Brier score). Model interpretability via SHapley Additive exPlanations (SHAP) values.

REPORTING: Transparent Reporting of a multivariable prediction model for an individual Prognosis Or Diagnosis plus Artificial Intelligence (TRIPOD+AI) 2024 and Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.

EXPECTED OUTPUTS: (1) Printable preoperative nomogram applicable without additional technological infrastructure; (2) exportable machine learning (ML) model with AUC target of 0.80 or greater; (3) first structured lumbar surgery database with 12-month Follow-up generated in Venezuela.

Interventions

  • Other SPINE-RISK VE multimodal preoperative assessment
    Adult patients (18 years or older) with an indication for elective lumbar spine surgery (discectomy, spinal fusion, or decompression) for degenerative lumbar disease at three Venezuelan referral centers. All participants undergo standardized preoperative assessment, including inflammatory laboratory biomarkers, lumbar MRI morphological evaluation, and validated psychosocial instruments (PHQ-9, PCS). Primary outcome assessed at 12-month postoperative follow-up

Primary outcome measures

  • Predictive accuracy of SPINE-RISK VE model for PSPS-T2/FBSS at 12 months [Time frame: 12 months post-lumbar surgery]

Eligibility criteria

Inclusion Criteria:- Age 18 years or older

  • Confirmed indication for elective lumbar spine surgery (discectomy, spinal fusion, or decompression) for degenerative lumbar disease
  • Availability of preoperative lumbar MRI (with and without gadolinium contrast) within 6 months before surgery
  • Availability of standard preoperative laboratory panel (CRP, CBC with differential, albumin, HbA1c, ESR) within 30 days before surgery
  • Ability to complete validated psychosocial instruments (PHQ-9, PCS) in Spanish
  • Provision of written informed consent prior to any study procedure
  • Attending one of the three participating Venezuelan referral centers during the recruitment period

Exclusion Criteria:- Emergency lumbar spine surgery

  • Active spinal infection or spinal tumor requiring oncological surgery
  • Traumatic spinal fracture as primary indication
  • Cognitive impairment preventing completion of self-report psychosocial instruments
  • Active psychiatric emergency at time of preoperative assessment
  • Prior participation in another clinical trial that could influence surgical or pain outcomes
  • Inability to complete 12-month postoperative follow-up (geographic inaccessibility, planned relocation, or terminal illness)
  • Age under 18 years

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: No

Study design

Observational model
Cohort

Study locations

Venezuela · 1 center
  • Hopsital Universitario de Caracas — Caracas

Publications

  • von Elm E, Altman DG, Egger M, Pocock SJ, Gotzsche PC, Vandenbroucke JP; STROBE Initiative. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Prev Med. 2007 Oct;45(4):247-51. doi: 10.1016/j.ypmed.2007.08.012. Epub 2007 Sep 4. PMID 17950122
  • Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med. 2001 Sep;16(9):606-13. doi: 10.1046/j.1525-1497.2001.016009606.x. PMID 11556941
  • Riley RD, Snell KI, Ensor J, Burke DL, Harrell FE Jr, Moons KG, Collins GS. Minimum sample size for developing a multivariable prediction model: PART II - binary and time-to-event outcomes. Stat Med. 2019 Mar 30;38(7):1276-1296. doi: 10.1002/sim.7992. Epub 2018 Oct 24. PMID 30357870
  • Collins GS, Moons KGM, Dhiman P, Riley RD, Beam AL, Van Calster B, Ghassemi M, Liu X, Reitsma JB, van Smeden M, Boulesteix AL, Camaradou JC, Celi LA, Denaxas S, Denniston AK, Glocker B, Golub RM, Harvey H, Heinze G, Hoffman MM, Kengne AP, Lam E, Lee N, Loder EW, Maier-Hein L, Mateen BA, McCradden MD, Oakden-Rayner L, Ordish J, Parnell R, Rose S, Singh K, Wynants L, Logullo P. TRIPOD+AI statement: PMID 38626948
  • Xu W, Ran B, Zhao J, Luo W, Gu R. Risk factors for failed back surgery syndrome following open posterior lumbar surgery for degenerative lumbar disease. BMC Musculoskelet Disord. 2022 Dec 31;23(1):1141. doi: 10.1186/s12891-022-06066-2. PMID 36585650
  • Hajilo P, Imani B, Zandi S, Mehrafshan A, Khazaei S. Risk factors analysis and risk prediction model for failed back surgery syndrome: A prospective cohort study. Heliyon. 2024 Nov 22;11(1):e40607. doi: 10.1016/j.heliyon.2024.e40607. eCollection 2025 Jan 15. PMID 39866404
  • Khazanchi R, Kumar D, Oris RJ, Bajaj A, Herrera DE, Chen AR, Shah RM, Asthana S, Reyes SG, Bajaj P, Hsu WK, Patel AA, Divi SN. Identifying Predictors of Failed Back Surgery Syndrome Following Lumbar Spine Surgery: A Machine Learning Approach. Spine (Phila Pa 1976). 2026 May 15;51(10):736-742. doi: 10.1097/BRS.0000000000005411. Epub 2025 May 29. PMID 40443211

Identifiers

NCT: NCT07693517 · SPINE-RISK-VE-2026-001

Primary sources (government registries)

View this study on ClinicalTrials.gov ↗