ArticleCardiovascular intervention and therapeutics2025
Nomogram predicting 2 year overall survival in dialysis patients with lower extremity peripheral arterial disease after endovascular therapy: a multicenter prospective cohort study.
Article in Cardiovascular intervention and therapeutics, 2025. 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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Abstract
Two year overall survival (OS) is crucial for treating symptomatic lower extremity arterial disease (LEAD). This study aimed to develop a nomogram to predict 2 year OS in dialysis patients with LEAD following endovascular therapy (EVT), addressing the gap in data for this high-risk population. This study, conducted at three centers in Taiwan between July 2005 and December 2019, included 593 dialysis patients (349 in the development group and 244 in the validation group). Multivariate logistic regression was used to identify 2 year OS predictors. The nomogram's predictive accuracy, discriminative ability, and clinical utility were evaluated using receiver-operating characteristic curves, calibration curves, the Hosmer-Lemeshow (HL) test, and decision curve analysis (DCA). The mean patient age was 68.4 ± 11.1 years (56% men); 251 died within 2 years (median follow-up 2.42 years), and the 2 year OS rates were similar between groups (59.3% vs. 55.0%, P = 0.220). Multivariate analysis revealed elevated neutrophil-to-lymphocyte ratio, congestive heart failure, chronic atrial fibrillation, use of renin-angiotensin-aldosterone system inhibitors, and prognostic nutritional index as predictors of 2 year OS. The areas under the curve were 0.822 (95% confidence interval [CI] 0.773-0.870) and 0.838 (95% CI 0.789-0.887) in the development and validation groups, respectively. The HL tests χ2 values were 11.61 (P = 0.170) and 6.706 (P = 0.569). DCA showed that this model was practical for 10-90% survival probabilities. This nomogram accurately predicts 2 year OS in dialysis patients with symptomatic LEAD post-EVT. This model can aid clinicians in personalized risk stratification and treatment planning in real-world clinical practice.
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