The Journal of rheumatology · 2018
The Cost-effectiveness of Biannual Serum Urate (SU) Monitoring after Reaching Target in Gout: A Health Economic Analysis Comparing SU Monitoring.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Robinson Philip C, Dalbeth Nicola, Donovan Peter
Аннотация
OBJECTIVE: The 2012 American College of Rheumatology gout management guidelines recommend monitoring serum urate (SU) every 6 months after target SU has been achieved. Our objective was to determine through modeling whether this testing would be cost-effective, considering financial cost, quality of life, and estimated change in adherence.
METHODS: A cost-utility analysis was completed with a 3-arm model: (1) no regular urate monitoring; (2) annual urate monitoring; and (3) biannual urate monitoring. Inputs to the model for health-related quality of life, flare rate, and treatment location were drawn from the medical literature and modeled over a lifetime horizon.
RESULTS: No monitoring was the least costly (Australian$6974) but least effective [13.51 quality-adjusted life-yrs (QALY)], while annual urate monitoring [A$7117; 13.53 QALY; incremental cost-effectiveness ratio (ICER) A$13,678/QALY gained] and biannual monitoring [A$7298; 13.54 QALY; ICER A$15,420 per QALY gained] were both cost-effective alternatives in base case analysis. Sensitivity analysis on both an individual component level and a probabilistic sensitivity analysis (PSA) demonstrated that the result was robust to changes in input variables. An improvement in adherence of ≥ 3.5% with biannual monitoring was all that was required to demonstrate cost-effectiveness. In PSA, the probability of biannual monitoring was 78%, no monitoring was 20%, and annual monitoring was 2%.
CONCLUSION: The results suggest that biannual SU monitoring after attaining target SU is the most cost-effective, compared with no testing and annual testing.
METHODS: A cost-utility analysis was completed with a 3-arm model: (1) no regular urate monitoring; (2) annual urate monitoring; and (3) biannual urate monitoring. Inputs to the model for health-related quality of life, flare rate, and treatment location were drawn from the medical literature and modeled over a lifetime horizon.
RESULTS: No monitoring was the least costly (Australian$6974) but least effective [13.51 quality-adjusted life-yrs (QALY)], while annual urate monitoring [A$7117; 13.53 QALY; incremental cost-effectiveness ratio (ICER) A$13,678/QALY gained] and biannual monitoring [A$7298; 13.54 QALY; ICER A$15,420 per QALY gained] were both cost-effective alternatives in base case analysis. Sensitivity analysis on both an individual component level and a probabilistic sensitivity analysis (PSA) demonstrated that the result was robust to changes in input variables. An improvement in adherence of ≥ 3.5% with biannual monitoring was all that was required to demonstrate cost-effectiveness. In PSA, the probability of biannual monitoring was 78%, no monitoring was 20%, and annual monitoring was 2%.
CONCLUSION: The results suggest that biannual SU monitoring after attaining target SU is the most cost-effective, compared with no testing and annual testing.