Host-state biomarkers and clinical factors for stratification and optimization of cell therapy trials in chronic limb-threatening ischemia: A review

Background: Chronic limb-threatening ischemia (CLTI) is a severe manifestation of peripheral arterial disease associated with high risks of amputation and mortality. Trials of cell-based therapies in patients unsuitable for revascularization (“no-option” or “poor-option” CLTI) have produced inconsistent results, underscoring the need for improved prognostic enrichment, baseline risk balancing, and protocol-defined stratification. Main body: This structured narrative review synthesizes evidence linking host-state markers—including laboratory biomarkers, clinical host-state factors, and physiologic/perfusion indices—to clinically meaningful CLTI outcomes. Inflammatory, nutritional, renal, metabolic, lipid, coagulation-related, infection, dialysis, frailty, smoking, etiology, and perfusion-related variables may shape the regenerative microenvironment and contribute to heterogeneity in cell therapy trial outcomes. However, current evidence primarily supports prognostic risk stratification rather than validated prediction of differential treatment response. We therefore interpret treated-cohort associations and post hoc subgroup observations as hypothesis-generating candidate variables for prospective host-state × treatment interaction testing, not as validated predictive biomarkers. We propose a conceptual trial-design framework: first, confirm no-option or poor-option CLTI through multidisciplinary review, guideline-aligned assessment, objective hemodynamic testing, vascular imaging, and multidomain assessment; second, provisionally categorize patients into favorable, intermediate, and unfavorable host-state profiles using approximate prognostic ranges for prospective validation rather than clinical eligibility cutoffs, treatment-selection rules, or gatekeeping thresholds; third, ensure clinically necessary stabilization before eligibility confirmation and treat any run-in or post-randomization optimization strategy only as an optional, secondary, protocol-justified design component; and fourth, apply stratified randomization, covariate adjustment, blinded outcome adjudication, and prespecified host-state × treatment interaction analyses. Conclusions: Integrating host-state biomarkers and clinical factors into CLTI cell therapy trial design may support prognostic enrichment, stratified enrollment, baseline risk adjustment, and hypothesis-driven evaluation of treatment-effect heterogeneity. The proposed profiles are hypothesis-generating trial-design strata, not validated clinical eligibility criteria, treatment-selection rules, or biomarker-based gatekeeping thresholds. Prospective validation will require standardized biomarker assays, harmonized endpoints, transparent reporting of cell products and concomitant care, and randomized testing of host-state × treatment interactions to advance precision regenerative medicine in this setting.