Cost-effectiveness of tenecteplase versus alteplase for acute ischemic stroke.

INTRODUCTION: Alteplase is widely used as an intravenous thrombolytic drug in acute ischemic stroke (AIS). Recently however, tenecteplase, a modified form of tissue plasminogen activator, has been shown to increase early recanalization rate and has proven to be non-inferior with a similar safety profile compared to alteplase. This study aims to evaluate the cost-effectiveness of 0.25 mg/kg tenecteplase versus 0.9 mg/kg alteplase for intravenous thrombolysis in AIS patients from the Dutch healthcare payer perspective. METHODS: A Markov decision-analytic model was constructed to assess total costs, total quality-adjusted life year (QALY), an incremental cost-effectiveness ratio, and incremental net monetary benefit (INMB) of two treatments at willingness-to-pay (WTP) thresholds of €50,000/QALY and €80,000/QALY over a 10-year time horizon. One-way sensitivity analysis, probabilistic sensitivity analysis, and scenario analysis were conducted to test the robustness of results. Clinical data were obtained from large randomized controlled trials and real-world data. RESULTS: Treatment with tenecteplase saved €21 per patient while gaining 0.05 QALYs, resulting in INMB of €2381, clearly rendering tenecteplase cost-effective compared to alteplase. Importantly, tenecteplase remained the cost-effective alternative in all scenarios, including AIS patients due to large vessel occlusion (LVO). Probabilistic sensitivity analysis proved tenecteplase to be cost-effective with a 71.0% probability at a WTP threshold of €50,000/QALY. CONCLUSIONS: Tenecteplase treatment was cost-effective for all AIS patients (including AIS patients with LVO) compared to alteplase. The finding supports the broader use of tenecteplase in acute stroke care, as health outcomes improve at acceptable costs while having practical advantages, and a similar safety profile.

Clinical prediction of thrombectomy eligibility: A systematic review and 4-item decision tree.

BACKGROUND: A clinical large anterior vessel occlusion (LAVO)-prediction scale could reduce treatment delays by allocating intra-arterial thrombectomy (IAT)-eligible patients directly to a comprehensive stroke center. AIM: To subtract, validate and compare existing LAVO-prediction scales, and develop a straightforward decision support tool to assess IAT-eligibility. METHODS: We performed a systematic literature search to identify LAVO-prediction scales. Performance was compared in a prospective, multicenter validation cohort of the Dutch acute Stroke study (DUST) by calculating area under the receiver operating curves (AUROC). With group lasso regression analysis, we constructed a prediction model, incorporating patient characteristics next to National Institutes of Health Stroke Scale (NIHSS) items. Finally, we developed a decision tree algorithm based on dichotomized NIHSS items. RESULTS: We identified seven LAVO-prediction scales. From DUST, 1316 patients (35.8% LAVO-rate) from 14 centers were available for validation. FAST-ED and RACE had the highest AUROC (both >0.81, p < 0.01 for comparison with other scales). Group lasso analysis revealed a LAVO-prediction model containing seven NIHSS items (AUROC 0.84). With the GACE (Gaze, facial Asymmetry, level of Consciousness, Extinction/inattention) decision tree, LAVO is predicted (AUROC 0.76) for 61% of patients with assessment of only two dichotomized NIHSS items, and for all patients with four items. CONCLUSION: External validation of seven LAVO-prediction scales showed AUROCs between 0.75 and 0.83. Most scales, however, appear too complex for Emergency Medical Services use with prehospital validation generally lacking. GACE is the first LAVO-prediction scale using a simple decision tree as such increasing feasibility, while maintaining high accuracy. Prehospital prospective validation is planned.