Prediction Model for Freedom from TLR from a Multi-study Analysis of Long-Term Results with the Zilver PTX Drug-Eluting Peripheral Stent

Abstract

Purpose: Develop a prediction model to determine the impact of patient and lesion factors on freedom from target lesion revascularization (ffTLR) for patients who are candidates for Zilver PTX drug-eluting stent (DES) treatment for femoropopliteal lesions.

Methods: Patient factors, lesion characteristics, and TLR results from five global studies were utilized for model development. Factors potentially associated with TLR (sex, age, diabetes, hypertension, hypercholesterolemia, renal disease, smoking status, Rutherford classification, lesion length, reference vessel diameter (RVD), popliteal involvement, total occlusion, calcification severity, prior interventions, and number of runoff vessels) were analyzed in a Cox proportional hazards model. Probability of ffTLR was generated for three example patient profiles via combinations of patient and lesion factors. TLR was defined as reintervention performed for ≥ 50% diameter stenosis after recurrent clinical symptoms.

Results: The model used records from 2227 patients. The median follow-up time was 23.9 months (range: 0.03-60.8). The Kaplan-Meier estimates for ffTLR were 90.5% through 1 year and 75.2% through 5 years. In a multivariate analysis, sex, age, Rutherford classification, lesion length, RVD, total occlusion, and prior interventions were significant factors. The example patient profiles have predicted 1-year ffTLRs of 97.4, 92.3, and 86.0% and 5-year predicted ffTLRs of 92.8, 79.5, and 64.8%. The prediction model is available as an interactive web-based tool ( https://cooksfa.z13.web.core.windows.net ).

Conclusions: This is the first prediction model that uses an extensive dataset to determine the impact of patient and lesion factors on ffTLR through 5 years and provides an interactive web-based tool for expected patient outcomes with the Zilver PTX DES.

Clinical trial registrations: Zilver PTX RCT unique identifier: NCT00120406; Zilver PTX single-arm study unique identifier: NCT01094678; Zilver PTX China study unique identifier: NCT02171962; Zilver PTX US post-approval study unique identifier: NCT01901289; Zilver PTX Japan post-market surveillance study unique identifier: NCT02254837.

Levels of evidence: Zilver PTX RCT: Level 2, randomized controlled trial; Single-arm study: Level 4, large case series; China study: Level 4, case series; US post-approval study: Level 4, case series Japan PMS study: Level 4, large case series.

Keywords: Drug-eluting stent; Paclitaxel; Peripheral artery disease; Prediction model; Target lesion revascularization.

Conflict of interest statement

MDD, AEL, HR, XJ, and GMA are paid consultants for Cook Medical. FF is a paid consultant for Cook. Medtronic, Volcano, Philips, WL Gore & Associates. EEO’L is a paid employee of Cook Medical. MS is a paid consultant for Abbott, Endologix, and Medtronic. TZ has received honoraria from Abbott Vascular, Veryan, Biotronik, Boston Scientific Corp., Cook Medical, Gore & Associates, Medtronic, Philips-Spectranetics, Shockwave; consulted for Boston Scientific Corp., Gore & Associates, Medtronic, Veryan, Intact Vascular, Shockwave, Bayer, Vesper Medical; received (institution) research, clinical trial, or drug study funds from 480 biomedical, Bard Peripheral Vascular, Veryan, Biotronik, Efemoral, Cook Medical, Gore & Associates, Medtronic, Philips, Terumo, TriReme, Shockwave, Med Alliance, Intact Vascular, B. Braun; and has common stock in QT Medical. WF, OI, and KZ report no relevant conflicts to disclose.

Figures

Fig. 1

Kaplan–Meier curve for freedom from TLR. Five-year freedom from TLR outcomes and 95% confidence intervals for the DES across five clinical studies. The life table is included. DES, drug-eluting stent TLR, target lesion revascularization

Fig. 2

Receiver operating curves for the complete data set and for the training data set. ROCs for the complete data set (top panel) and for the training data set (bottom panel) at 1, 3, and 5 years show very similar performance. ROC, receiver operating curves

Fig. 3

Calibration curves for training data set versus test data set. Calibration groups were defined by cuts at the 27th and 73rd percentiles of the distribution of the linear predictor [13]. The solid lines represent the training data set for each of the three calibration groups; the dashed lines represent the test data sets for each of the three calibration groups

Fig. 4

Predicted freedom from TLR for example patient profiles. Curves for freedom from TLR correspond to the patient characteristics outlined in Table 5. Patient profile #1 is shown in red. Patient profile #2 is shown in blue. Patient profile #3 is shown in yellow. The predicted rates of freedom from TLR for each patient profile are included in the table. TLR, target lesion revascularization