Quantifying Biopsychosocial Risk Factor Domains for Chronic Pain Treatment Outcomes: An Umbrella Review with De Novo Meta-Analyses, Formal Uncertainty Propagation, and the Pain Amplifier Loop Framework (PALF)

ObjectiveTo conduct de novo meta-analyses quantifying the association of five biopsychosocial risk factor domains with chronic pain or related treatment outcomes, and to construct a composite risk index with formal uncertainty propagation for interventional pain medicine. MethodsUmbrella review with de novo random-effects meta-analyses (DerSimonian-Laird and REML with Knapp-Hartung adjustment) across PubMed/MEDLINE, Scopus, and the Cochrane Library through March 2026. Five risk factor domains were evaluated: (1) sleep disturbance, (2) pain catastrophizing, (3) metabolic/obesity, (4) preoperative opioid exposure, and (5) benzodiazepine co-prescription. Publication bias was assessed via Eggers test and PET-PEESE regression. Primary study overlap was quantified using the Corrected Covered Area (CCA). We constructed a primary three-domain composite (sleep, catastrophizing, metabolic) and a secondary expanded six-domain composite (adding opioid, BZD, smoking), using the logistic link function with binary risk factor inputs (present/absent); composite score 95% confidence intervals were computed via delta method variance propagation. Risk of bias of the composite was assessed using PROBAST [Wolff RF et al., Ann Intern Med 2019]; TRIPOD+AI compliance is reported in Supplementary S6 [Collins GS et al., BMJ 2024]. Reviewer process (per registered protocol PROSPERO CRD420261360881): screening, data extraction, risk-of-bias assessment (AMSTAR-2/PROBAST/ROBINS-I), and GRADE certainty rating are conducted independently by at least two reviewers -- SPM (confirmed co-reviewer, registered in PROSPERO) as primary rater, with an external third reviewer to be identified and confirmed prior to peer-reviewed submission; JAD acts as guarantor and does not perform primary review tasks. All quantitative outputs reported here are preliminary estimates pending completion of the external third-reviewer audit; a triple-validated version will be posted as a subsequent preprint update before peer-reviewed submission. ResultsAdopted odds ratios: sleep disturbance 1.39 (95% CI 1.21-1.59; k=16; I{superscript 2}=51%), pain catastrophizing 2.10 (1.49-2.95; k=8; I{superscript 2}=0%), metabolic/obesity 1.43 (1.28-1.60; k=33), preoperative opioid exposure 5.32 (2.94-9.64; k=33; I{superscript 2}=99.96%; outcome: prolonged opioid use), and BZD co-prescription 1.77 (1.31-2.39; k=27; outcome: persistent opioid use). REML/Knapp-Hartung estimates produced wider confidence intervals for all loops (opioid: 1.87-15.13). PET-PEESE analysis suggested no substantial small-study effects for the sleep or catastrophizing loops. CCA=3.2% (slight overlap). Primary three-domain composite (sleep + catastrophizing + metabolic): delta method 95% confidence intervals for the composite score spanned 10-15 percentage points; PROBAST risk of bias: moderate. Secondary expanded six-domain composite (adding opioid, BZD, smoking): confidence intervals spanned 12-18 percentage points, crossing risk tier boundaries in moderate-risk patients; PROBAST risk of bias: high (driven by outcome heterogeneity in pharmacological domains). ConclusionsFive biopsychosocial risk factor domains are independently associated with chronic pain or related treatment outcomes. The PALF composite index is presented as a structured analytical framework for future prospective validation, not as a deployable clinical tool. The primary three-domain composite (sleep, catastrophizing, metabolic) achieves outcome homogeneity at the cost of reduced domain coverage; the expanded six-domain composite encompasses the pharmacological burden at the cost of outcome heterogeneity. Both composites carry wide confidence intervals that preclude clinical application without individual patient data validation. No claim to clinical validity is made in the absence of prospective individual-patient-data validation.