Falls and Fractures among Nursing Home Residents Treated with Pimavanserin versus Other Atypical Antipsychotics: Analysis of Medicare Beneficiaries with Parkinson's Disease Psychosis.

IF 1.9 Q3 PHARMACOLOGY & PHARMACY

Drugs - Real World Outcomes Pub Date : 2024-09-01 Epub Date: 2024-06-24 DOI:10.1007/s40801-024-00433-2

Krithika Rajagopalan, Nazia Rashid, Daksha Gopal, Dilesh Doshi

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引用次数: 0

Abstract

Background: Reducing falls and fractures remains an important clinical goal in managing older residents with Parkinson's disease psychosis (PDP) in long-term care/nursing home (LTC/NH) settings.

Objectives: This analysis examined risk of all-cause falls or fractures among PDP residents on continuous monotherapy with pimavanserin (PIM) versus (i) other atypical antipsychotics (AAPs) [quetiapine (QUE), risperidone (RIS), olanzapine (OLA), aripiprazole (ARI)] and (ii) QUE.

Methods: A retrospective analysis of parts A, B, and D claims from a 100% Medicare sample (2013-2019) in LTC/NH settings was conducted. LTC/NH residents in the USA initiating continuous monotherapy (PIM versus other AAPs; PIM versus QUE) for ≥ 6 months between 01 January 2014 and 31 December 2018 were 1:1 propensity score matched (PSM) on 31 variables (age, sex, race, region, and 27 Elixhauser comorbidities). Outcomes included three measures: risks of falls only, fractures only, and falls/fractures during 6-months follow-up. Demographic characteristics were described using chi-square and t-tests. Generalized linear models were used to assess difference in risks of falls/fractures.

Results: Of 7187 residents, 47.59% (n = 3420) were female and mean age was 78.8 (± 7.75) years. In total, 14% (n = 1005) were on PIM and 86% (n = 6182) were on other AAPs. After PSM, falls only among PIM residents (n = 1005) was 4.58% (n = 46) versus 7.66% (n = 77) for other AAPs (n = 1005) [relative risk (RR) = 0.63 (0.46, 0.86), p < 0.05] and 8.26% (n = 83) for QUE (n = 1005) residents (p < 0.05). Fractures only among PIM residents was 1.39% (n = 14) compared with 2.09% (n = 21) for other AAPs (p = 0.31) and 1.89% (n = 19) for QUE (p = 0.49), respectively. Taken together, falls/fractures among PIM residents were 5.67% (n = 57) versus 9.05% (n = 91) for other AAPs [RR = 0.63 (0.46, 0.86), p < 0.05] and 9.55% (n = 96) for QUE (p < 0.05), respectively.

Conclusions: In this analysis of LTC/NH residents with PDP, PIM had a 37% and 41% lower risk of all-cause falls/fractures versus other AAPs and versus QUE, respectively.

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接受皮马凡色林与其他非典型抗精神病药物治疗的疗养院住院患者的跌倒和骨折情况：对患有帕金森病精神病的医疗保险受益人的分析。

背景：减少跌倒和骨折仍然是管理长期护理/疗养院（LTC/NH）中患有帕金森病精神病（PDP）的老年患者的一个重要临床目标：本分析研究了帕金森病患者在连续使用匹马伐林（PIM）与(i)其他非典型抗精神病药物（AAPs）[喹硫平（QUE）、利培酮（RIS）、奥氮平（OLA）、阿立哌唑（ARI）]和(ii)QUE进行单一疗法时发生全因跌倒或骨折的风险：方法：对 100%的医疗保险样本（2013-2019 年）中的 A、B 和 D 部分索赔进行了回顾性分析。美国的 LTC/NH 居民在 2014 年 1 月 1 日至 2018 年 12 月 31 日期间开始连续单药治疗（PIM 与其他 AAPs；PIM 与 QUE）≥ 6 个月，在 31 个变量（年龄、性别、种族、地区和 27 种 Elixhauser 合并症）上进行 1:1 倾向评分匹配 (PSM)。结果包括三个测量指标：仅跌倒风险、仅骨折风险以及随访 6 个月期间的跌倒/骨折风险。人口统计学特征采用卡方检验和 t 检验。采用广义线性模型评估跌倒/骨折风险的差异：在 7187 名住院患者中，47.59%（n = 3420）为女性，平均年龄为 78.8（± 7.75）岁。其中，14%（n = 1005）的居民服用了 PIM，86%（n = 6182）的居民服用了其他 AAPs。在 PSM 之后，仅 PIM 居民（n = 1005）的跌倒率为 4.58%（n = 46），而其他 AAPs 居民（n = 1005）的跌倒率为 7.66%（n = 77）[相对风险 (RR) = 0.63 (0.46, 0.86), p < 0.05]，QUE 居民（n = 1005）的跌倒率为 8.26%（n = 83）（p < 0.05）。仅在PIM居民中，骨折发生率为1.39%（n = 14），而其他AAPs的骨折发生率为2.09%（n = 21）（p = 0.31），QUE的骨折发生率为1.89%（n = 19）（p = 0.49）。综合来看，PIM 居民的跌倒/骨折率为 5.67% (n = 57)，而其他 AAPs 的跌倒/骨折率为 9.05% (n = 91) [RR = 0.63 (0.46, 0.86), p < 0.05]，QUE 的跌倒/骨折率为 9.55% (n = 96) (p < 0.05)：在对患有 PDP 的 LTC/NH 居民进行的这项分析中，PIM 与其他 AAPs 和 QUE 相比，全因跌倒/骨折风险分别降低了 37% 和 41%。

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来源期刊

Drugs - Real World Outcomes PHARMACOLOGY & PHARMACY-

CiteScore

3.60

自引率

5.00%

发文量

审稿时长

8 weeks

期刊介绍： Drugs - Real World Outcomes targets original research and definitive reviews regarding the use of real-world data to evaluate health outcomes and inform healthcare decision-making on drugs, devices and other interventions in clinical practice. The journal includes, but is not limited to, the following research areas: Using registries/databases/health records and other non-selected observational datasets to investigate: drug use and treatment outcomes prescription patterns drug safety signals adherence to treatment guidelines benefit : risk profiles comparative effectiveness economic analyses including cost-of-illness Data-driven research methodologies, including the capture, curation, search, sharing, analysis and interpretation of ‘big data’ Techniques and approaches to optimise real-world modelling.