左心室射出分率低下之心臟衰竭病人使用sacubitril-valsartan治療之死亡或心臟移植預測因子

Predictors of Death or Heart Transplantation in Patients with Heart Failure and Reduced Ejection Fraction after Receiving Sacubitril-Valsartan Therapy

林奕軒(Yi-Hsuan Lin)

指導教授 ： 徐莞曾

國立臺灣大學/醫學院/臨床藥學研究所/碩士(2021年)

https://doi.org/10.6342/NTU202103343

摘要

研究背景
心臟衰竭 (heart failure, HF) 為臨床上複雜的症候群，主要為心臟結構或功能受損，使心室充血或射血功能下降，產生相關症狀或降低運動耐受。過去近30年來有許多針對左心室射出分率低下心臟衰竭 (heart failure with reduced ejection fraction, HFrEF) 治療之臨床試驗，國際心臟衰竭治療指引也根據大型試驗結果制定治療建議，且在最新指引一線治療藥物中新增了sacubitril/valsartan (S/V)。然而，在臨床使用上仍有部分病人使用S/V後預後不理想，因此欲藉由預後預測模型了解影響因子，但多數預後預測模型僅針對啟用S/V時基礎特性及併用藥，而未考慮啟用S/V後隨時間變動之用藥、心臟超音波及腎臟功能參數與住院情形。
研究目的
本研究目的有以下兩點：(1) 藉由臨床上接受S/V治療之HF病人，分析預後影響因子，建立預後之解釋與預測模型；(2) 探討啟用S/V後6個月左心室射出分率 (left ventricular ejection fraction , LVEF) 改善程度與預後之相關性，以及6個月LVEF改善程度之潛在影響因子。
研究方法
本研究回溯2017年3月1日至2019年2月28日於國立臺灣大學醫學院附設醫院啟用S/V之HF病人，根據啟用S/V前之心臟超音波參數篩選出LVEF < 40% 之HFrEF病人。同時利用臺大醫院電子病歷系統蒐集該族群啟用S/V前基礎特性、實驗室數值、治療史、住院史及相關用藥，以及啟用S/V後使用情形、併用藥物、心臟超音波與腎臟功能參數及住院情形。
本研究定義之研究終點為全因性死亡或接受心臟移植之綜合事件，藉由Cox’s proportional hazards model with time-dependent covariates (Cox’s model) 進行存活分析，啟用S/V前非隨時間變化相關參數以時間獨立共變數 (time-fixed covariate) 代入，啟用S/V後隨時間變化相關參數以時間相依共變數 (time-dependent covariate) 代入，以p-value < 0.05作為顯著標準納入最終預後之預測模型中。啟用S/V後6個月LVEF改善程度之潛在影響因子以單變項分析做初步探討，並利用Kaplan-Meier method及log-rank test了解其與綜合事件之相關性。
研究結果
針對模型之建立，初步納入333位接受S/V治療之HF病人，排除18位無法追溯啟用前用藥，並依據納入模型變項及相關定義，排除23位變項資料有缺失、1位於啟用後30天內發生事件無法分析者，最終有291位納入Cox’s model分析，在追蹤中位數33.6個月期間共有47位 (16.2%) 發生綜合事件。
本研究建立兩個模型，Cox’s model A納入啟用S/V前特性及用藥與啟用S/V後用藥，模型顯示有22個變項與較差之預後有關，包含：(1) 基礎特性：紐約心臟協會功能分級 (New York Heart Association functional class) III-IV、透析和心臟再同步節律器 (cardiac resynchronization pacemaker)；(2) 啟用S/V前心臟功能與結構：LVEF低下、左心室後壁厚度較薄和二尖瓣逆流 (mitral regurgitation, MR) 較嚴重；(3) 啟用S/V前用藥：未使用angiotensin-converting enzyme inhibitor或angiotensin receptor blocker、使用isosorbide mononitrate、nicorandil每日劑量較高；(4) 啟用S/V後校正latency period時間點之用藥：S/V每日劑量較低、3個月內β-blocker累積劑量較低、loop-diuretic每日平均劑量較高、3個月內ivabradine劑量降低及doxazosin總累積劑量較高。
Cox’s model B除了納入啟用S/V前特性及用藥與啟用S/V後用藥情形，同時納入啟用S/V後心臟超音波、腎臟功能參數以及住院情形，並篩選具臨床意義之變項。此模型顯示有11個變項與較差之預後有關，包含：(1) 基礎特性：透析；(2) 啟用S/V後心臟功能與結構：LVEF低下、LVEF降低、左心室舒張末期內徑 (left ventricular end-diastolic dimension, LVEDD) 較小；(3) 啟用S/V後腎臟功能：肌酸酐 (creatinine, CRE) 增加、血清尿素氮 (blood urea nitrogen)/ CRE平均值較高 (未達統計顯著)、血紅素低下；(4) 啟用S/V後校正latency period時間點之用藥：S/V每日劑量較低、β-blocker每日劑量較低、nicorandil每日劑量較高。
針對探討啟用S/V後LVEF改善程度與預後之相關性，以及LVEF改善程度之潛在影響因子，共有144位具有啟用S/V前及6個月後LVEF數值。Kaplan-Meier method顯示啟用S/V後6個月LVEF改善程度 < 5% (未反應者，n = 88) 事件發生風險較高 (log-rank test之p-value = 0.0313)。單變項分析顯示未反應者啟用S/V前LVEDD (未反應者 68.0 ± 9.9 vs. 反應者62.8 ± 7.9 mm，p-value = 0.0022)、左心室收縮末期內徑 (未反應者 58.7 ± 10.0 vs. 反應者53.7 ± 6.9 mm，p-value = 0.0033) 及左心房直徑較大 (未反應者 47.6 ± 8.1 vs. 反應者44.5 ± 5.8 mm，p-value = 0.0170)，MR較嚴重 (p-value = 0.0115)，同時HF病程也較長 (未反應者 5.2 ± 4.4 vs. 反應者2.7 ± 4.7年，p-value < 0.0001)。
結論
臨床上接受S/V治療之HF病人其預後受到其本身基礎特性、啟用S/V前後相關用藥、心臟結構功能及腎臟功能影響。在臨床上可參考本研究之預後解釋與預測模型，以作為臨床上優化藥物治療或預測預後的依據。未來建議此模型考慮變項與預後之非線性關係，找出具有臨床意義之數值範圍或臨界值，使其解釋與預測能力更佳。同時建議未來研究可利用多變項模型分析心臟重塑恢復之相關因子，以獲得更符合實際臨床狀況之結論。

關鍵字

心臟衰竭 ； sacubitril/valsartan ； 左心室射出分率 ； 全因性死亡 ； 心臟移植 ； Cox’s proportional hazards model with time-dependent covariates

並列摘要

Background
Heart failure (HF) is a complex syndrome resulting from cardiac disorders of structure and function, leading to the impairment of ventricular filling or ejection of blood that causes symptoms or exercise intolerance. In the past 30 years, several treatments have proven effective in patients with heart failure with reduced ejection fraction (HFrEF), including sacubitril/valsartan (S/V), one of the first-line treatments medications recommended by the latest guidelines. However, some patients have poor responses to S/V, and identifying factors associated with poor prognosis is an important issue.
Objectives
We have two main aims in the present study. First, we want to develop an explanatory and prognostic model for all-cause death or heart transplantation in patients with HFrEF receiving S/V. Second, we aim to examine the association between left ventricular ejection fraction (LVEF) change and prognosis and investigate predictors of LVEF change in these patients.
Methods
We retrospectively identified the patients with HF initiated S/V in National Taiwan University Hospital from March 1, 2017, to February 28, 2019, and excluded patients with LVEF ≥ 40% before initiation. Baseline characteristics before initiation of S/V, including laboratory data, medical history, history of hospitalization, and medications, were collected from electronic medical records. Also, medications, echocardiographic parameters, renal function, and hospitalization after initiating S/V were collected.
The study endpoint was the composite event of all-cause death or heart transplantation. The explanatory and prognostic model for the study endpoint was based on Cox’s proportional hazards model with time-dependent covariates (Cox’s model). To examine the association between LVEF change and prognosis and investigate predictors of LVEF change, we included patients with available LVEF data both before and at six months after initiation of S/V. Univariable analysis was performed to investigate the predictors of LVEF change. Kaplan-Meier method with log-rank test was performed to examine the association between LVEF change and study endpoint.
Results
To develop Cox’s model, we included 291 patients. During a median follow-up of 33.6 months, all-cause death or heart transplantation occurred in 47 (16.2%) patients. We developed two Cox’s models. Cox’s model A included baseline characteristics before initiating S/V and medications after initiating S/V, and we found that 22 variables were associated with the study endpoint, including the following: (1) baseline characteristics: New York Heart Association functional class III-IV, dialysis, cardiac resynchronization pacemaker; (2) baseline echocardiographic parameters: lower LVEF, thinner left posterior ventricular wall, more severe mitral valve regurgitation (MR); (3) medications before initiating S/V: without the usage of angiotensin-converting enzyme inhibitor or angiotensin receptor blocker, prescription of isosorbide mononitrate, higher daily dose of nicorandil; and (4) medications after initiating S/V adjusted the latency period: lower S/V daily dose, lower accumulative β-blocker dosage within three months prior to each event time, higher average daily loop-diuretic dosage since the first day of taking S/V, higher accumulative doxazosin dosage since the first day of taking S/V.
In addition to baseline characteristics before initiating S/V and medications after initiating S/V, Cox's model B also included echocardiographic parameters, renal function, and hospitalization after initiating S/V, and we found that 11 variables were associated with the study endpoint, including the following: (1) dialysis; (2) echocardiographic parameters after initiating S/V: lower LVEF, LVEF decrease per month, smaller left ventricular end-diastolic dimension (LVEDD); (3) renal function after initiating S/V: creatinine (CRE) increase per week, lower hemoglobin, higher average blood urea nitrogen/CRE ratio (not statistically significant); and (4) medications after initiating S/V adjusted the latency period: lower S/V daily dose; lower β-blocker daily dose to each event time, higher nicorandil daily dose to each event time.
Regarding the association between LVEF change and prognosis, there were 144 patients with available LVEF data both before and at six months after initiation of S/V. A total of 88 non-responders (LVEF response at six months < 5%) and 56 responders (LVEF response at six months ≥ 5%) to S/V treatment were identified for comparison. Kaplan–Meier survival curve demonstrated that non-responders had higher incidences of the study endpoint compared to responders. Increased diameter of the left ventricle and the left atrium were significantly more profound in non-responders compared with responders; high severity MR was more common in non-responders compared with responders. Finally, non-responders had longer HF duration than responders.
Conclusion
Explanatory variables and predictors of prognosis under S/V include baseline characteristics, cardiac function and structure, renal function, and medications after initiating S/V. Clinically, we can use Cox's model to optimize medications and predict patient outcomes in patients with HFrEF. In future studies, we should consider the nonlinear relationship between variables and outcomes in Cox’s models and assess the predictors of LVEF change with multivariable regression analysis.

並列關鍵字

Heart failure ； sacubitril/valsartan ； left ventricular ejection fraction ； all-cause death ； heart transplantation ； Cox’s proportional hazards model with time-dependent covariates

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