Risk stratification in critical limb ischemia: derivation and validation of a model to predict amputation-free survival using multicenter surgical outcomes data.

BACKGROUND: Patients with critical limb ischemia (CLI) are a heterogeneous population with respect to risk for mortality and limb loss, complicating clinical decision-making. Endovascular options, compared with bypass, offer a tradeoff between reduced procedural risk and inferior durability. Risk stratified data predictive of amputation-free survival (AFS) may improve clinical decision making and allow for better assessment of new technology in the CLI population.
METHODS: This was a retrospective analysis of prospectively collected data from patients who underwent infrainguinal vein bypass surgery for CLI. Two datasets were used: the PREVENT III randomized trial (n = 1404) and a multicenter registry (n = 716) from three distinct vascular centers (two academic, one community-based). The PREVENT III cohort was randomly assigned to a derivation set (n = 953) and to a validation set (n = 451). The primary endpoint was AFS. Predictors of AFS identified on univariate screen (inclusion threshold, P < .20) were included in a stepwise selection Cox model. The resulting five significant predictors were assigned an integer score to stratify patients into three risk groups. The prediction rule was internally validated in the PREVENT III validation set and externally validated in the multicenter cohort.
RESULTS: The estimated 1-year AFS in the derivation, internal validation, and external validation sets were 76.3%, 72.5%, and 77.0%, respectively. In the derivation set, dialysis (hazard ratio [HR] 2.81, P < .0001), tissue loss (HR 2.22, P =.0004), age >or=75 (HR 1.64, P = .001), hematocrit <or=30 (HR 1.61, P = .012), and advanced CAD (HR 1.41, P = .021) were significant predictors for AFS in the multivariable model. An integer score, derived from the ss coefficients, was used to generate three risk categories (low <or= 3 [44.4% of cohort], medium 4-7 [46.7% of cohort], high >or=8 [8.8% of cohort]). Stratification of the patients, in each dataset, according to risk category yielded three significantly different Kaplan-Meier estimates for 1-year AFS (86%, 73%, and 45% for low, medium, and high risk groups, respectively). For a given risk category, the AFS estimate was consistent between the derivation and validation sets.
CONCLUSION: Among patients selected to undergo surgical bypass for infrainguinal disease, this parsimonious risk stratification model reliably identified a category of CLI patients with a >50% chance of death or major amputation at 1 year. Calculation of a "PIII risk score" may be useful for surgical decision making and for clinical trial designs in the CLI population.

RCT Entities:   Population Interventions Outcomes