Development and validation of a score to predict life expectancy after carotid endarterectomy in asymptomatic patients

Carmo, Michele; Barbetta, Iacopo; Bissacco, Daniele; Trimarchi, Santi; Catanese, Vincenzo; Bonzini, Matteo; Bonardelli, Stefano; Settembrini, Piergiorgio

doi:10.1016/j.jvs.2017.05.107

Cited by 17 publications

(32 citation statements)

References 26 publications

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“…This emerging body of research 16,17 suggests that these risk prediction models should be used to improve patient selection for CEA. The CMI was developed based on a population of veterans with carotid stenosis who received CEA in the VA and is especially informative to practice in the VA. General mortality models (eg, the Lee Index 33 ) have been developed using data from the US adult population and can also be incorporated into assessments regarding the benefits of CEA among patients with asymptomatic disease.…”

Section: Discussionmentioning

confidence: 99%

Risk Prediction Tools to Improve Patient Selection for Carotid Endarterectomy Among Patients With Asymptomatic Carotid Stenosis

et al. 2019

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IMPORTANCE Randomized clinical trials have demonstrated that patients with asymptomatic carotid stenosis are eligible for carotid endarterectomy (CEA) if the 30-day surgical complication rate is less than 3% and the patient’s life expectancy is at least 5 years. OBJECTIVE To develop a risk prediction tool to improve patient selection for CEA among patients with asymptomatic carotid stenosis. DESIGN, SETTING, AND PARTICIPANTS In this cohort study, veterans 65 years and older who received both carotid imaging and CEA in the Veterans Administration between January 1, 2005, and December 31, 2009 (n = 2325) were followed up for 5 years. Data were analyzed from January 2005 to December 2015. A risk prediction tool (the Carotid Mortality Index [CMI]) based on 23 candidate variables identified in the literature was developed using Veterans Administration and Medicare data. A simpler model based on the number of 4 key comorbidities that were prevalent and strongly associated with 5-year mortality was also developed (any cancer in the past 5 years, chronic obstructive pulmonary disease, congestive heart failure, and chronic kidney disease [the 4C model]). Model performance was assessed using measures of discrimination (eg, area under the curve [AUC])and calibration. Internal validation was performed by correcting for optimism using 500 bootstrapped samples. MAIN OUTCOME AND MEASURE Five-year mortality. RESULTS Among 2325 veterans, the mean (SD) age was 73.74 (5.92) years. The cohort was predominantly male (98.8%) and of white race/ethnicity (94.4%). Overall, 29.5% (n = 687) of patients died within 5 years of CEA. On the basis of a backward selection algorithm, 9 patient characteristics were selected (age, chronic kidney disease, diabetes, chronic obstructive pulmonary disease, any cancer diagnosis in the past 5 years, congestive heart failure, atrial fibrillation, remote stroke or transient ischemic attack, and body mass index) for the final logistic model, which yielded an optimism-corrected AUC of 0.687 for the CMI. The 4C model had slightly worse discrimination (AUC, 0.657) compared with the CMI model; however, the calibration curve was similar to the full model in most of the range of predicted probabilities. CONCLUSIONS AND RELEVANCE According to results of this study, use of the CMI or the simpler 4C model may improve patient selection for CEA among patients with asymptomatic carotid stenosis.

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Section: Discussionmentioning

confidence: 99%

Risk Prediction Tools to Improve Patient Selection for Carotid Endarterectomy Among Patients With Asymptomatic Carotid Stenosis

et al. 2019

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“…References and journal analysis have not added other articles. Five articles were eligible for inclusion 12,13,[14][15][16] and were reviewed in depth (Tables 1-3). Figure 1 shows the flowchart adopting for article selection.…”

Section: Resultsmentioning

confidence: 99%

“…Four of 5 studies included the use (AT) 13 or the absence (no ST) [14][15][16] of a certain treatment in their scores. This reflects an ongoing gap between international guidelines recommending ST and AT for all patients candidate to CEA and real-world clinical practice.…”

Section: Scoring System Parametersmentioning

confidence: 99%

“…The WS, CS, and CarS derived their scores from a homogeneous population of asymptomatic patients who underwent CEA. [14][15][16]…”

Section: Development Cohortmentioning

confidence: 99%

“…Carmo et al tested the score on an external population of asymptomatic patients with an acceptable predictive capacity. 16 An ROC curve and area under the curve analysis were used only in 1 study for an internal validation model. 14 Despite the method use, an external validation remains the best way to prove the score efficacy although it was evaluated only in 1 study.…”

Section: Score Validationmentioning

confidence: 99%

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Risk Scoring Systems to Predict Long-Term Mortality After Carotid Endarterectomy in Asymptomatic Patients: A Systematic Review

Bissacco

Barbetta

Carmo

2019

Vasc Endovascular Surg

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The present review was conducted to describe current published risk scoring systems to predict late mortality after carotid endarterectomy (CEA). The aim of the study is to identify simple, clinical, and reproducible tools to predict life expectancy in patients with asymptomatic carotid artery stenosis candidates to CEA and therefore which patients may benefit from surgery, reaching the goal of life expectancy >3 to 5 years, recommended by guidelines. Advantages, disadvantages, feasibility, simplicity, and reproducibility of each selected score were analyzed. Rigorous statistical analysis and validation of the score are essential components to produce a calibrated and usable score. Future studies should address the impact of using these tools in CEA candidates for asymptomatic disease.

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Prophylaktische Gefäßchirurgie im Alter

Aleksic

Böhner²,

Geier

et al. 2019

Gefässchirurgie

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Development and validation of a score to predict life expectancy after carotid endarterectomy in asymptomatic patients

Cited by 17 publications

References 26 publications

Risk Prediction Tools to Improve Patient Selection for Carotid Endarterectomy Among Patients With Asymptomatic Carotid Stenosis

Risk Prediction Tools to Improve Patient Selection for Carotid Endarterectomy Among Patients With Asymptomatic Carotid Stenosis

Risk Scoring Systems to Predict Long-Term Mortality After Carotid Endarterectomy in Asymptomatic Patients: A Systematic Review

Prophylaktische Gefäßchirurgie im Alter

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