Abstract
目的
在中国鄞州电子健康档案研究(Chinese Electronic Health Records Research in Yinzhou,CHERRY)中,比较实施不同指南推荐的阿司匹林用于心血管病一级预防策略预期的获益与风险。
方法
采用马尔可夫(Markov)模型模拟所比较的不同策略:策略①:对40~69岁心血管病高风险人群使用低剂量阿司匹林干预(2020年《中国心血管病一级预防指南》);策略②:对40~59岁心血管病高风险人群使用低剂量阿司匹林干预(2022年美国预防服务工作组《阿司匹林用于心血管病一级预防的推荐声明》);策略③:对40~69岁心血管病高风险且基线血压控制良好(150/90 mmHg以下)的人群使用低剂量阿司匹林干预(2019年《中国心血管病风险评估和管理指南》)。循环周期设为1年,模拟10年,获益指标包括增加的质量调整生命年(quality-adjusted life year, QALY)和每预防一例缺血性事件的需治疗人数(number needed to treat, NNT),风险指标包括每增加一例出血性事件的需应对危害人数(number needed to harm, NNH),计算人群净获益(可预防的缺血性事件数减去增加的出血性事件数)及其NNT。
结果
共纳入212 153名研究对象,采用策略①~③进行阿司匹林干预的人数分别为34 235、2 813和25 111。策略③预期增加的QALY最多,为403[95%不确定性区间(uncertainty interval, UI):222~511]年,其获益指标的NNT仅比策略①增加了4(95%UI:3~4)人,但风险指标的NNH增加了39(95%UI:19~132)人,显示策略③的安全性更好。三种策略净获益的NNT分别为131(95%UI:102~239)人、256(95%UI:181~737)人和132(95%UI:104~232)人,在净获益效率相似时,QALY和安全性更好的策略③具有优势。
结论
采用三种策略在CHERRY人群中均能获得净获益,相比之下考虑血压控制水平的策略可兼顾效果获益与安全性风险,并获得较好的干预效率。
Keywords: 心血管疾病, 一级预防, 阿司匹林, 马尔可夫模型
Abstract
Objective
To compare the expected population impact of benefit and risk of aspirin treatment strategies for the primary prevention of cardiovascular diseases recommended by different guidelines in the Chinese Electronic Health Records Research in Yinzhou (CHERRY) study.
Methods
A decision-analytic Markov model was used to simulate and compare different strategies of aspirin treatment, including: Strategy ①: Aspirin treatment for Chinese adults aged 40-69 years with a high 10-year cardiovascular risk, recommended by the 2020 Chinese Guideline on the Primary Prevention of Cardiovascular Diseases; Strategy ②: Aspirin treatment for Chinese adults aged 40-59 years with a high 10-year cardiovascular risk, recommended by the 2022 United States Preventive Services Task Force Recommendation Statement on Aspirin Use to Prevent Cardiovascular Disease; Strategy ③: Aspirin treatment for Chinese adults aged 40-69 years with a high 10-year cardiovascular risk and blood pressure well-controlled (< 150/90 mmHg), recommended by the 2019 Guideline on the Assessment and Management of Cardio-vascular Risk in China. The high 10-year cardiovascular risk was defined as the 10-year predicted risk over 10% based on the 2019 World Health Organization non-laboratory model. The Markov model simulated different strategies for ten years (cycles) with parameters mainly from the CHERRY study or published literature. Quality-adjusted life year (QALY) and the number needed to treat (NNT) for each ischemic event (including myocardial infarction and ischemic stroke) were calculated to assess the effectiveness of the different strategies. The number needed to harm (NNH) for each bleeding event (including hemorrhagic stroke and gastrointestinal bleeding) was calculated to assess the safety. The NNT for each net benefit (i.e., the difference of the number of ischemic events could be prevented and the number of bleeding events would be added) was also calculated. One-way sensitivity analysis on the uncertainty of the incidence rate of cardiovascular diseases and probabilistic sensitivity analysis on the uncertainty of hazard ratios of interventions were conducted.
Results
A total of 212 153 Chinese adults, were included in this study. The number of people who were recommended for aspirin treatment Strategies ①-③ was 34 235, 2 813, and 25 111, respectively. The Strategy ③ could gain the most QALY of 403 [95% uncertainty interval (UI): 222-511] years. Compared with Strategy ①, Strategy ③ had similar efficiency but better safety, with the extra NNT of 4 (95%UI: 3-4) and NNH of 39 (95%UI: 19-132). The NNT per net benefit was 131 (95%UI: 102-239) for Strategy ①, 256 (95%UI: 181-737) for Strategy ②, and 132 (95%UI: 104-232) for Strategy ③, making Strategy ③ the most favorable option with a better QALY and safety, along with similar efficiency in terms of net benefit. The results were consistent in the sensitivity analyses.
Conclusion
The aspirin treatment strategies recommended by the updated guidelines on the primary prevention of cardiovascular diseases showed a net benefit for high-risk Chinese adults from developed areas. However, to balance effectiveness and safety, aspirin is suggested to be used for primary prevention of cardiovascular diseases with consideration for blood pressure control, resulting in better intervention efficiency.
Keywords: Cardiovascular diseases, Primary prevention, Aspirin, Markov model
探讨适宜的心血管病一级预防策略是重要的公共卫生研究热点之一,阿司匹林由于能够减少血小板聚集从而降低动脉粥样硬化性心血管病的风险,已成为心血管病单一抗血小板治疗的首选方案[1],但因其同时可能导致出血风险增加,特别是用于无心血管病史人群一级预防的效果与安全性需要权衡。国内外关于阿司匹林用于心血管病一级预防的最新指南推荐存在明显差异[2],考虑到人群净获益,各指南对于应用人群的年龄范围和需要考虑的出血危险因素的推荐并不一致,例如2020年《中国心血管病一级预防指南》推荐对40~70岁心血管病高风险且无高出血风险的人群使用低剂量阿司匹林进行心血管病一级预防(Ⅱb级推荐,A级证据)[3];美国预防服务工作组(United States Preventive Services Task Force, USPSTF)2022年《阿司匹林用于心血管病一级预防的推荐声明》中推荐对40~59岁且心血管病高风险人群使用阿司匹林开展一级预防(C级推荐)[4];2007年《世界卫生组织(World Health Organization, WHO)心血管病风险评估和管理指南》和2019年《中国心血管病风险评估和管理指南》则建议在使用阿司匹林开展心血管病一级预防前应将血压水平控制在150/90 mmHg以下[5-6]。
中国人群的心血管病负担严重,阿司匹林由于价格便宜已在基层广泛使用,但由于目前中国人群高血压的患病率高且控制率低,特别是出血性卒中的比例明显高于西方人群的特点[3],对于实施上述指南推荐的不同策略在中国人群预期的获益与风险亟待补充研究证据。因此,本研究拟在中国鄞州电子健康档案研究(Chinese Electronic Health Records Research in Yinzhou, CHERRY)项目的队列人群中采用马尔可夫(Markov)模型的理论流行病学方法,模拟比较不同指南推荐的阿司匹林用于心血管病一级预防策略预期的获益与风险,一方面可以为后续开展随机对照试验的干预人群特征选择提供线索,另一方面也可以为心血管病预防实践的公共卫生决策提供依据。
1. 资料与方法
1.1. 研究对象
研究人群来源于CHERRY项目[7],该项目是一项在浙江省宁波市开展的双向性队列研究。本研究的基线时间定义为2012年1月1日,研究对象的纳入标准为:(1)具有唯一的有效身份标识码;(2)基线年龄为40~79岁。排除标准为:(1)基线时有心血管病史或胃肠道出血史;(2)基线时有阿司匹林规律用药史(定义为基线前任意一年内有3条及以上的阿司匹林用药记录);(3)用于心血管病风险评估所需的年龄、性别、收缩压、吸烟史和体重指数缺失。本研究已获得北京大学生物医学伦理委员会批准(IRB00001052-16011)。
本研究涉及的变量包括研究对象的社会人口学信息(年龄、性别等)、危险因素暴露信息(吸烟史、体重指数、血压和血脂水平、高血压和糖尿病病史、阿司匹林用药史及用药时间等)和结局事件及死亡信息。CHERRY研究以每年至少一次的频率更新结局事件信息,通过国际疾病分类第10版(International Classification of Disease 10th, ICD-10)编码确定本研究随访中的结局事件(包括缺血性心血管病事件与出血性结局事件),其中缺血性心血管病事件包括心肌梗死(I21~I22)和缺血性卒中(I63),出血性结局事件包括出血性卒中(I60~I61)和胃肠道出血(K92.0、K92.2),系统中的结局事件诊断经专业医生在浙江省疾病监测及死因登记平台核查确认。
1.2. 评估的阿司匹林干预策略
将阿司匹林在社区人群中的常规用药现状作为本研究的对照组(策略0),评估国内外不同指南推荐的阿司匹林一级预防干预的三种策略的效果、安全性和净获益,具体包括:策略①:根据2020年《中国心血管病一级预防指南》[3],对40~69岁的心血管病高风险人群使用低剂量阿司匹林干预;策略②:根据2022年美国预防服务工作组《阿司匹林用于心血管病一级预防的推荐声明》[4],对40~59岁的心血管病高风险人群使用低剂量阿司匹林干预;策略③:根据2019年《中国心血管病风险评估和管理指南》[6],对40~69岁的心血管病高风险且基线血压控制良好(定义为血压水平控制在150/90 mmHg以下)人群使用低剂量阿司匹林干预。采用WHO简易模型[8]评估研究人群的10年心血管病风险,以风险高于10%确定心血管病高风险人群。
1.3. 马尔可夫模型的构建
根据研究目的并参考既往已发表的研究[9]构建马尔可夫模型,本研究主要划分为未患心血管病和胃肠道出血(Status 1)、患心肌梗死(Status 2)、患缺血性卒中(Status 3)、患出血性卒中(Status 4)、患胃肠道出血(Status 5)、死于上述定义的结局事件(Status 6)以及死于其他事件(Status 7)共7个状态(图 1)。
图 1.
阿司匹林用于心血管病一级预防干预策略的马尔可夫模型状态转换图
Markov model diagram for aspirin treatment strategies for primary prevention of cardiovascular diseases
The defined events in the Status 6 include MI, IS, HS and GIB. P1-P13, transition probabilities. CVD, cardiovascular diseases; GIB, gastrointestinal bleeding; MI, myocardial infarction; IS, ischemic stroke; HS, hemorrhagic stroke.
研究对象在初始状态时均处于未患心血管病和胃肠道出血状态(Status 1),在每一周期初始根据当前所处状态按照各分支相应转移概率选择路径进入下一个状态或保持当前状态,在一定时间内按照状态间相互转换的概率模拟疾病发病过程,累积各状态和状态转换过程的健康效用。马尔可夫模型共设定10个周期,每个周期为1年,估计10年内的缺血性心血管病事件、出血性事件和死亡的结局。
马尔可夫模型的参数主要包括状态转换概率、干预措施的效应值和各状态的健康效用值(表 1),状态转换概率尽可能从CHERRY研究的队列人群中直接估计,干预效应值和健康效用值从已发表的系统综述、meta分析和相关研究中获取[10-13]。考虑到不同年龄和性别发生结局事件的差异,本研究按照年龄和性别分组,分别估计状态转换概率。本研究只考虑与缺血性心血管病结局事件或出血性结局事件患病状态相关的生命质量,即假设未发生结局事件时生命质量最高,死亡对应的生命质量为0,根据疾病的发展累积各个健康状态和状态转换过程的健康效用值计算质量调整生命年(quality-adjusted life year, QALY)。
表 1.
马尔可夫模型的参数及其来源
Parameters and data sources in the Markov model
Items | Men | Women | Data sources | |||
40-59 years | 60-79 years | 40-59 years | 60-79 years | |||
* The defined events include MI, IS, HS and GIB. Status 1 is the status alive without cardiovascular diseases or GIB. P1-P13, transition probabilities. MI, myocardial infarction; IS, ischemic stroke; HS, hemorrhagic stroke; GIB, gastrointestinal bleeding. | ||||||
Transition probabilities (1/100 000) | ||||||
Incidence | Estimated from the current study | |||||
MI (P1) | 39 | 97 | 29 | 71 | ||
IS (P2) | 430 | 1 063 | 407 | 1 144 | ||
HS (P3) | 101 | 151 | 86 | 152 | ||
GIB (P4) | 8 | 18 | 14 | 17 | ||
Death | Estimated from the current study | |||||
Defined events* | ||||||
MI (P5) | 5 786 | 8 492 | 7 426 | 10 903 | ||
IS (P6) | 1 552 | 2 789 | 916 | 2 773 | ||
HS (P7) | 7 369 | 13 125 | 5 904 | 11 492 | ||
GIB (P8) | 0 | 920 | 0 | 889 | ||
Other causes | ||||||
MI (P9) | 1 533 | 3 671 | 854 | 3 622 | ||
IS (P10) | 1 687 | 5 683 | 916 | 3 669 | ||
HS (P11) | 3 226 | 7 213 | 2 150 | 6 584 | ||
GIB (P12) | 4 706 | 12 311 | 1 014 | 6 753 | ||
Status 1 (P13) | 534 | 1 294 | 258 | 923 | ||
Intervention effects, x±s | ||||||
Hazard ratio for MI | 0.70±0.09 | 0.92±0.09 | Meta-analysis[10] | |||
Hazard ratio for IS | 1.12±0.08 | 0.96±0.08 | Meta-analysis[10] | |||
Hazard ratio for HS | 1.44±0.09 | 1.48±0.09 | Meta-analysis[10] | |||
Hazard ratio for GIB | 1.56±0.06 | 1.56±0.06 | Meta-analysis[11] |
1.4. 统计学分析
研究人群的基线特征中,连续变量采用均数±标准差表示,分类变量用频数(%)表示,连续变量和分类变量分别采用t检验和卡方检验比较组间差异,均为双侧检验,显著性水平α取0.05。计算不同策略干预后可预防的缺血性事件发生数、增加的出血性事件发生数、可预防的心血管病结局事件死亡数、全因死亡数、获得的生命年和QALY等健康收益,以及每预防一例缺血性结局事件对应的需治疗人数(number needed to treat, NNT)和每增加一例出血性结局事件对应的需应对危害人数(number needed to harm, NNH),其中,获益指标主要包括增加的QALY、每预防一例缺血性事件对应的NNT,风险指标包括每增加一例出血性事件对应的NNH。计算各策略的人群净获益(即人群干预后预防的缺血性事件发生数减去增加的出血性事件发生数),以及每获得一例净获益对应的NNT。NNT越小表示干预效率越高,NNH越大表示安全性越好。考虑到状态转换概率参数对结果的影响,对心血管病发病率进行单因素敏感性分析;考虑到干预措施效应值参数的不确定性,采用蒙特卡罗(Monte Carlo)模拟的方法模拟10 000次,获得结果的95%不确定性区间(uncertainty interval, UI)。采用R 4.2.0软件进行统计学分析。
2. 结果
2.1. 队列人群的基本特征
本研究共纳入212 153名研究对象(表 2),其中男性98 366人,女性113 787人,男性的平均年龄、教育程度、吸烟率、体重指数和血压水平均高于女性,女性的高血压和糖尿病患病率以及血脂水平高于男性(P < 0.001)。
表 2.
研究人群的基线特征
Baseline characteristics of the study population
Characteristics | Men (n=98 366) | Women (n=113 787) | P value* |
* Compared between men and women. SBP, systolic blood pressure; DBP, diastolic blood pressure; TC, total cholesterol; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; BMI, body mass index. | |||
Age/years, x±s | 55.55±9.85 | 54.67±9.52 | < 0.001 |
Education (senior high school or high), n (%) | 15 569 (15.83) | 12 165 (10.69) | < 0.001 |
Urban, n (%) | 30 410 (30.92) | 37 639 (33.08) | < 0.001 |
Current smoker, n (%) | 37 833 (38.46) | 1 548 (1.36) | < 0.001 |
Diabetes, n (%) | 6 980 (7.09) | 8 789 (7.72) | < 0.001 |
Hypertension, n (%) | 25 823 (26.25) | 31 687 (27.85) | < 0.001 |
SBP/mmHg, x±s | 131.68±15.90 | 130.35±16.72 | < 0.001 |
DBP/mmHg, x±s | 82.83±9.61 | 81.25±9.64 | < 0.001 |
TC/(mmol/L), x±s | 4.81±0.96 | 5.04±0.98 | < 0.001 |
HDL-C/(mmol/L), x±s | 1.28±0.35 | 1.35±0.33 | < 0.001 |
LDL-C/(mmol/L), x±s | 2.79±0.82 | 2.94±0.85 | < 0.001 |
BMI/(kg/m2), x±s | 23.37±2.72 | 23.20±2.93 | < 0.001 |
2.2. 不同策略的获益与风险比较
采用策略①~③进行阿司匹林一级预防的人数分别为34 235、2 813和25 111人。与目前常规用药现状(策略0)相比,国内外最新指南推荐的阿司匹林用于心血管病一级预防的三种干预策略均能增加更多的生命年和QALY的健康效果,并预防更多缺血性心血管病(心肌梗死和缺血性卒中)事件的发生,但同时也会增加出血性事件(表 3)。总体而言,策略③能够获得最多的QALY,且安全性优于策略①。
表 3.
阿司匹林用于心血管病一级预防不同策略的效果、安全性及净获益比较
Comparisons of effectiveness, safety and net benefit by different strategies with aspirin treatment for primary prevention of cardiovascular diseases
Items | Strategy ① vs. Strategy 0 | Strategy ② vs. Strategy 0 | Strategy ③ vs. Strategy 0 | Strategy ① vs. Strategy ② | Strategy ③ vs. Strategy ① | Strategy ③ vs. Strategy ② |
* The defined events include MI, IS, HS and GIB; Strategy 0: usual care for comparison; Strategy ①: aspirin treatment for Chinese adults aged 40-69 with a high 10-year cardiovascular risk, recommended by the 2020 Chinese Guideline on the Primary Prevention of Cardiovascular Diseases; Strategy ②: aspirin treatment for Chinese adults aged 40-59 with a high 10-year cardiovascular risk, recommended by the 2022 United States Preventive Services Task Force Recommendation Statement on Aspirin Use to Prevent Cardiovascular Disease; Strategy ③: aspirin treatment for Chinese adults aged 40-69 with a high 10-year cardiovascular risk and blood pressure well-controlled (< 150/90 mmHg), recommended by the 2019 Guideline on the Assessment and Management of Cardiovascular Risk in China. QALY, quality-adjusted life year; MI, myocardial infarction; IS, ischemic stroke; HS, hemorrhagic stroke; GIB, gastrointestinal bleeding; NNT, number needed to treat; NNH, number needed to harm. | ||||||
Total numbers for assessment | 212 153 | 212 153 | 212 153 | |||
Total numbers for aspirin treatment | 34 235 | 2 813 | 25 111 | |||
Life years gained | 67 (-33, 147) | 2 (-7, 10) | 278 (191, 317) | 65 (-27, 138) | 211 (158, 236) | 276 (197, 307) |
QALY gained | 329 (84, 509) | 12 (1, 26) | 403 (222, 511) | 317 (89, 484) | 74 (0, 140) | 391 (227, 486) |
Ischemic events could be prevented | 368 (257, 427) | 19 (13, 22) | 260 (183, 300) | 349 (244, 405) | -108 (-127, -73) | 241 (170, 278) |
MI events could be prevented | 27 (8, 40) | 1 (0, 2) | 19 (6, 28) | 26 (7, 38) | -8 (-13, -1) | 18 (6, 26) |
IS events could be prevented | 341 (234, 400) | 18 (12, 21) | 241 (168, 281) | 323 (222, 380) | -100 (-119, -67) | 223 (156, 260) |
Bleeding events would be added | 107 (52, 156) | 8 (4, 12) | 70 (32, 105) | 99 (48, 144) | -37 (-51, -20) | 62 (28, 93) |
HS events would be added | 87 (32, 135) | 7 (3, 11) | 60 (22, 95) | 80 (30, 125) | -27 (-40, -10) | 53 (20, 84) |
GIB events would be added | 20 (12, 29) | 1 (1, 2) | 10 (6, 14) | 19 (12, 27) | -10 (-14, -7) | 9 (5, 12) |
Numbers of net benefit | 261 (143, 337) | 11 (4, 16) | 190 (108, 242) | 250 (139, 322) | -71 (-96, -35) | 179 (104, 226) |
Deaths from defined events* | 6 (-8, 18) | 0 (-1, 1) | 15 (4, 23) | 6 (-7, 18) | 9 (5, 12) | 15 (6, 22) |
All deaths could be prevented | 19 (-6, 39) | 1 (-1, 3) | 74 (52, 83) | 18 (-5, 36) | 55 (42, 61) | 73 (53, 81) |
NNT per ischemic event | 93 (80, 133) | 148 (128, 214) | 97 (84, 137) | -55 (-80, -48) | 4 (3, 4) | -51 (-77, -45) |
NNH per bleeding event | 320 (219, 660) | 352 (231, 716) | 359 (239, 789) | -32 (-58, -12) | 39 (19, 132) | 7 (6, 74) |
NNT per net benefit | 131 (102, 239) | 256 (181, 737) | 132 (104, 232) | -125 (-506, -78) | 1 (-7, 3) | -124 (-514, -76) |
比较三种干预策略我们发现,将阿司匹林一级预防的应用人群年龄上限从69岁(策略①)降低到59岁(策略②),每增加一例出血性事件的NNH增加了32 (95%UI:12~58)人,但每预防一例缺血性事件的NNT也从93 (95%UI:80~133)人增加至148 (95%UI:128~214)人,即策略②虽然安全性更好但效率欠佳;若年龄上限不变但考虑基线血压控制水平(策略③),每预防一例缺血性事件的NNT仅比策略①增加了4 (95%UI:3~4)人,而每增加一例出血性事件的NNH却增加了39 (95%UI:19~132)人,因此策略③在与策略①效率相似的情况下安全性更好。
2.3. 不同策略的人群净获益比较
与目前常规用药现状(策略0)相比,阿司匹林一级预防的不同策略均能获得人群净获益,策略①~③能够获得的人群净获益数分别为261 (95%UI:143~337)人,11 (95%UI:4~16)人和190 (95%UI:108~242)人,策略①~③每获得一例净获益的NNT分别为131 (95%UI:102~239)人、256 (95%UI:181~737)人和132 (95%UI:104~232)人。因此,虽然策略①获得的人群净获益最多,但策略③与策略①获得净获益的效率相似。
2.4. 阿司匹林一级预防的性别差异
如图 2所示,策略②中每预防一例缺血性事件的NNT在男性和女性分别为142 (95%UI:126~209)人和161 (95%UI:133~223)人,提示在40~59岁人群中开展阿司匹林一级预防的效率存在性别差异;而对于每增加一例出血性事件的NNH,策略①在男性和女性中分别为328 (95%UI:224~672)人和313 (95%UI:214~644)人,策略②分别为369 (95%UI:229~754)人和322 (95%UI:237~661)人,策略③分别为377 (95%UI:248~834)人和335 (95%UI:227~734)人,提示更需要在女性中关注阿司匹林一级预防的安全性问题。
图 2.
分性别比较不同策略的效果和安全性的影响
Impact evaluation of effectiveness and safety of different strategies by gender
Strategy 0: usual care for comparison; Strategy ①: aspirin treatment for Chinese adults aged 40-69 with a high 10-year cardiovascular risk, recommended by the 2020 Chinese Guideline on the Primary Prevention of Cardiovascular Diseases; Strategy ②: aspirin treatment for Chinese adults aged 40-59 with a high 10-year cardiovascular risk, recommended by the 2022 United States Preventive Services Task Force Recommendation Statement on Aspirin Use to Prevent Cardiovascular Disease; Strategy ③: aspirin treatment for Chinese adults aged 40-69 with a high 10-year cardiovascular risk and blood pressure well-controlled (< 150/90 mmHg), recommended by the 2019 Guideline on the Assessment and Management of Cardiovascular Risk in China.
2.5. 敏感性分析
单因素敏感性分析的结果(图 3)显示,随着不同年份的基线人群心血管病发病率的升高,开展阿司匹林一级预防的不同策略获得健康效果的QALY增加,且各策略间获得QALY的差别增大,策略③获得的QALY始终最多。概率敏感性分析10 000次模拟结果提示,对于开展阿司匹林一级预防干预后可多获得的健康效果QALY,策略③被选为最优策略的频率最高(97.42%);对于每获得一例净获益的NNT效率指标,策略①和策略③被选为最优策略的频率分别为71.95%和28.01%;但对于每增加一例出血事件的NNH风险指标,策略③被选为最优策略的频率最高(99.99%)。因此,单因素敏感性分析和概率敏感性分析的结果与主分析结果一致。
图 3.
心血管病发病率的变化对质量调整生命年影响的单因素敏感性分析
One-way sensitivity analyses on quality-adjusted life year by different incidence rates of cardiovascular diseases
The figure annotation as in Figure 2.
3. 讨论
本研究发现,在我国沿海发达地区采用最新指南推荐的阿司匹林一级预防策略,预防了缺血性心血管病的同时也增加了出血性事件,但各策略均能获得人群净获益。一项在英国人群开展的随机对照试验提示,阿司匹林用于糖尿病患者的心血管病一级预防时能够降低主要不良心血管事件的风险,但同时增加了大出血的发生风险[14],因此在制定阿司匹林一级预防策略时应综合评估获益与风险,以确定可能具有净获益的人群亚组。基线心血管病风险是影响阿司匹林一级预防净获益的因素之一,本研究结果显示,阿司匹林用于心血管病一级预防的高风险人群,能够增加QALY并获得净获益,此结果与一项在美国人群中开展的模型研究一致,提示在10年心血管病发病风险高于10.6%的美国人群中使用阿司匹林将获得明显的健康收益[9]。
年龄增长将同时影响缺血性心血管病和出血风险的升高[15],采用阿司匹林进行心血管病一级预防时应考虑人群净获益随年龄的变化。一项在荷兰人群中开展的模型研究显示,阿司匹林干预的健康收益随着年龄的增大而增加[16],但另一项随机对照试验并未发现阿司匹林能够预防西方老年人群心血管病事件的发生[17]。美国USPSTF最新发表的模型研究结果提示,阿司匹林一级预防的健康收益随年龄增大而减少[13]。本研究发现按照USPSTF的最新指南推荐,将干预人群的年龄范围上限从69岁降低至59岁虽然可以提高用药安全性,但预防的缺血性心血管病事件及增加的QALY等健康收益变小,提示现阶段在我国人群中只降低使用阿司匹林的年龄上限并没有明显优势,而如果采用2019年《中国心血管病风险评估和管理指南》对于使用阿司匹林前将血压控制在150/90 mmHg以下的建议[6],能够兼顾效果与安全性。考虑到我国出血性卒中高发,并且高血压患病率高而控制率低的现状,在中国人群中推行阿司匹林一级预防策略时,考虑血压控制水平可能更有意义。
2022年USPSTF的一项系统综述提示,阿司匹林一级预防可能存在性别差异,在男性中可能会有更高的出血风险[18]。本研究结果同样提示了性别差异,但更强调关注女性的出血风险,这可能与本研究人群高血压患病率女性高于男性有关,同样也反映了控制高血压的必要性。虽然目前国内外主要指南推荐的阿司匹林一级预防策略并未考虑性别差异,鉴于证据缺乏,未来仍需深入研究。越来越多的研究提示,阿司匹林用于心血管病一级预防应综合考虑年龄、性别及血压等多项因素进行个体化评估[2],但如何准确选择净获益人群需要深入探讨。例如,一项在新西兰人群中开展的研究[19]通过建立出血风险预测模型,可以个体化评估使用阿司匹林的获益与风险,并进一步识别具有净获益的人群亚组,但目前中国人群出血风险预测的相关评估工具仍有待开发。
考虑到我国心血管病发病率仍处于持续上升阶段[20],本研究在单因素敏感性分析中探讨了人群心血管病发病率的不同水平对结果的影响,显示心血管病发病率越高,阿司匹林一级预防策略的效果越明显,特别是在40~69岁的心血管病高风险且基线血压控制在150/90 mmHg以下的人群,并且各策略之间的效果差异逐渐增大,提示应根据目标人群心血管病发病率及危险因素流行情况因地制宜地选择阿司匹林一级预防策略。
与其他采用马尔可夫模型的研究相似,本研究的局限性也包括马尔可夫模型简单化的假设,即状态转移概率仅取决于当前健康状态,而与停留在当前状态的时间或之前的经历无关,后续研究将考虑采用基于个体特征的微观模拟模型进一步探讨。另外,虽然本研究针对模型参数的不确定性进行了敏感性分析,并提示了研究结果的稳健性,但来自我国发达地区的区域性人群数据可能会影响结论的外推性,因此还需要在其他人群中开展研究以提供更多的证据。
综上所述,本研究结果提示采用国内外最新指南推荐的阿司匹林用于心血管病一级预防策略在我国发达地区人群中能够带来人群净获益。根据美国指南推荐的干预人群年龄上限从69岁降至59岁的策略虽然可以提高用药安全性,但人群净获益也将明显降低。如果考虑血压控制水平后使用阿司匹林开展心血管病一级预防,可兼顾效果与安全性,且干预效率高。后续研究需关注阿司匹林一级预防策略的性别差异,以提供更准确的决策依据。
Funding Statement
国家自然科学基金(81973132)和国家重点研发计划(2020YFC2003503)
Supported by the National Natural Sciences Foundation of China (81973132) and the National Key Research and Development Program of China (2020YFC2003503)
Contributor Information
唐 迅 (Xun TANG), Email: tangxun@bjmu.edu.cn.
高 培 (Pei GAO), Email: peigao@bjmu.edu.cn.
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