Use of hydroxychloroquine in hospitalised COVID-19 patients is associated with reduced mortality: Findings from the observational multicentre Italian CORIST study


The COVID-19 RISK and Treatments (CORIST) Collaboration members

Abstract 摘要

Background 背景

Hydroxychloroquine (HCQ) was proposed as potential treatment for COVID-19


Objective 目的

We set-up a multicenter Italian collaboration to investigate the relationship between HCQ therapy and COVID-19 in-hospital mortality.


Methods 方法

In a retrospective observational study, 3,451 unselected patients hospitalized in 33 clinical centers in Italy, from February 19, 2020 to May 23, 2020, with laboratory-confirmed SARS-CoV-2 infection, were analyzed. The primary end-point in a time-to event analysis was in-hospital death, comparing patients who received HCQ with patients who did not. We used multivariable Cox proportional-hazards regression models with inverse probability for treatment weighting by propensity scores, with the addition of subgroup analyses.


Results 結果

Out of 3,451 COVID-19 patients, 76.3% received HCQ. Death rates (per 1,000 person-days) for patients receiving or not HCQ were 8.9 and 15.7, respectively. After adjustment for propensity scores, we found 30% lower risk of death in patients receiving HCQ (HR=0.70; 95%CI: 0.59 to 0.84; E-value=1.67). Secondary analyses yielded similar results. The inverse association of HCQ with inpatient mortality was particularly evident in patients having elevated C-reactive protein at entry.


Conclusions 結論

HCQ use was associated with a 30% lower risk of death in COVID-19 hospitalized patients. Within the limits of an observational study and awaiting results from randomized controlled trials, these data do not discourage the use of HCQ in inpatients with COVID-19.


1. Introduction 介紹

The aminoquinoline hydroxychloroquine (HCQ) has been extensively used in the treatment of malaria and is currently widely used to treat autoimmune diseases like rheumatoid arthritis (RA), systemic lupus erythematosus (SLE) and anti-phospholipid syndrome (APS), due to its immunomodulatory and anti-thrombotic properties [1]. More recently, a promising role of HCQ has been suggested in viral infections [2], since it directly inhibits viral entry and spread in several in vitro and in vivo models. Due to these properties, HCQ has been used in Ebola virus disease [3, 4], human immunodeficiency virus (HIV) infection [5], SARS-CoV-1 infection and the Middle East Respiratory Syndrome (MERS) [6, 7] and gained worldwide attention as a possible therapy in COVID-19 patients [8].


HCQ might inhibit the intracellular glycosylation of ACE 2, the receptor used by the SARS-CoV-2 virus to enter the cells, resulting in a reduced ligand recognition and internalization of the virus [7] and exerting a possible protective role in SARS-CoV-2 infection. Moreover, due to its immunomodulatory, anti-inflammatory and anti-thrombotic effects, HCQ could also modulate the severity of the disease. However, the exact mechanism for the potential benefit in COVID-19 is largely speculative [9] and might be counterbalanced by adverse effects, mainly cardiovascular [10, 11], so that the net balance of this drug’s use remains to be established.


The American Food and Drug Administration (FDA) allowed Chloroquine (CQ) phosphate and HCQ to be provided to certain hospitalized patients because these drugs may possibly help patients with severe COVID-19 [12]. The European Medicines Agency (EMA) authorized the use of CQ and HCQ for COVID-19 in clinical trials or as emergency use [13], while the Italian Drug Agency (AIFA) stated in this emergency phase that therapeutic use of HCQ might be considered in COVID-19 patients, both in those with mild presentation managed at home and in hospitalized patients [14]. In clinical practice, HCQ rather than chloroquine has been used because of its more potent antiviral properties and better safety profile [15].


However, in the light of a recent publication [16], that was later retracted [17], on the lack of safety and efficacy of HCQ in the treatment for COVID-19 patients the Executive Group of the Solidarity Trial decided to implement a temporary pause of the HCQ arm within the trial as a precaution, while the safety data is being reviewed [18]. Similarly, the Italian drug Agency AIFA decided to suspend the authorization to use HCQ for COVID-19 treatment outside clinical trials [19].


Recent reviews of clinical trials or observational studies [20, 21, 22, 23, 24] have reported insufficient and often conflicting evidence on the benefits and harms of using HCQ to treat COVID-19 and concluded that as such, it was impossible to determine the balance of benefits to harm. Until now, although several trials had been started on the use of CQ and HCQ in COVID-19, only few of them have been published [25] on small numbers of patients or on surrogate endpoints or in exposed subjects for prophylaxis use [26].


While waiting the results from ongoing randomized clinical trials (RCT) to define the efficacy in preventing hard endpoints of this treatment so widely used during the emergency phase of the COVID-19 pandemic, powered retrospective observational studies performed in different geographical and disease conditions may still be useful to shed light on this debate. Two retrospective observational studies, both conducted in the New York metropolitan region, did not report any significant association between HCQ use and rates of intubation or death [27, 28].


No data are presently available from large cohorts of patients in Italy, which represents one of the most affected countries in terms of total deaths for COVID-19 in the world [29]. We undertook a multicenter Italian collaboration [30] to investigate the relationship between underlying risk factors and COVID-19 outcomes, and to evaluate the association between different drug therapy and disease severity and/or mortality. We report here the results obtained in 3,451 hospitalized COVID -19 patients receiving or not HCQ treatment.


2. Material and methods 材料和方法

2.1 Setting 設置

This national retrospective observational study was conceived, coordinated and analysed within the CORIST Project (ClinicalTrials.gov ID: NCT04318418, 30]. The study was approved by the institutional ethics board of the Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Neuromed, Pozzilli, and of all recruiting centres. Data for the present analyses were provided by 33 hospitals distributed throughout Italy (listed in the supplementary file). Acceptance to participate in the project or to provide data for the present analysis was not related to the use of CQ/HCQ. Each hospital provided data from hospitalized patients who had a positive test result for the SARS-CoV-2 virus at any time during their hospitalization from February 19 to May 23, 2020. The follow-up continued through May 29, 2020.

這項全國性的回顧性觀察研究是在CORIST項目中構思、協調和分析的(ClinicalTrials.gov)[ID:NCT04318418,30]。該項研究得到了波齊利市Istituto di Ricovero e Cura a Carattere Scientifico(IRCCS)Neuromed的機構倫理委員會,和所有應召中心的批准。本分析的數據由分布在意大利各地的33家醫院提供(在補充文件中列出)。是否接受參與該項目或為本分析提供數據與使用CQ/HCQ無關。每家醫院都提供了2020年2月19日至5月23日住院期間任何時候SARS-CoV-2病毒檢測結果為陽性的住院患者的數據。後續工作一直持續到2020年5月29日。

2.2 Data sources 數據源

We developed a cohort comprising 3,971 patients with laboratory-confirmed SARS-CoV-2 infection in an in-patient setting. The SARS-CoV-2 status was declared based on laboratory results (polymerase chain reaction on nasopharyngeal swab) from each participating hospital. Clinical data were abstracted at one-time point from electronic medical records or charts, and were collected using either a centrally designed electronic worksheet or a centralized web-based database. Collected data included patients’ demographics, laboratory test results, medication administration, historical and current medication lists, historical and current diagnoses, and clinical notes. In addition, specific information on the most severe manifestation of COVID-19 occurred during hospitalization was retrospectively captured. Maximum clinical severity observed was classified as mild pneumonia; or severe pneumonia; or acute respiratory distress syndrome (ARDS) [31]. Specifically, we obtained the following information for each patient: hospital; date of admission and date of discharge or death; age; sex; the first recorded inpatient laboratory tests at the entry (creatinine, C-reactive protein); past and current diagnoses (myocardial infarction, heart failure, diabetes, hypertension, respiratory disease and cancer) and current drug therapies for COVID-19 – HCQ, lopinavir/ritonavir or darunavir/cobicistat, remdesevir, tocilizumab or sarilumab, corticosteroids, heparin, and for comorbidities (insulin, anti-hypertensive treatments, aldosterone receptor antagonists, diuretics, statins, sacubitril/valsartan). A diagnosis of pre-existing cardiovascular disease was based on history of myocardial infarction or heart failure. Chronic kidney disease was classified as: stage 1: kidney damage with normal or increased glomerular filtration rate (GFR) (>90 mL/min/1.73 m2); stage 2: mild reduction in GFR (60-89 mL/min/1.73 m2); stage 3a: moderate reduction in GFR (45-59 mL/min/1.73 m2); stage 3b: moderate reduction in GFR (30-44 mL/min/1.73 m2); stage 4: severe reduction in GFR (15-29 mL/min/1.73 m2); stage 5: kidney failure (GFR <15 mL/min/1.73 m2 or dialysis). For statistical analysis, stages 3a and 3b and stages 4 and 5 were combined. GFR was calculated by the Chronic Kidney Disease Epidemiology Collaboration (CKD-Epi) equation. Patients were defined as receiving HCQ if they were receiving it at admission to hospital or received it during the follow-up period. According to the AIFA guidance [14], HCQ was administered at dose of 400 mg x 2/day or x4/day the first day, and 200 mg x 2/day from the second day onwards for at least 5 to a maximum of 10 days, according to the clinical evolution of the disease.

我們建立了一個由3971名實驗室證實感染SARS-CoV-2的住院患者組成的群組。SARS-CoV-2狀態是根據每個參與醫院的實驗室結果(鼻咽拭子上的聚合酶鏈反應)宣布的。臨床數據是從電子病歷或圖表中在一個時間點上提取,並採用集中設計的電子工作表或集中網絡數據庫進行收集。收集的數據包括患者的人口統計數據、實驗室測試結果、用藥情況、過往和當前的用藥清單、過往和當前的診斷以及臨床記錄。此外,還追溯採集了關於住院期間發生的COVID-19最嚴重表現的具體信息。觀察到的最高臨床嚴重程度被分為輕度肺炎;或嚴重肺炎;或急性呼吸窘迫綜合徵(ARDS)[31]。具體來說,我們獲得了每位患者的以下信息:醫院;入院日期及出院或死亡日期;年齡;性別;入院時首次記錄的住院患者實驗室檢查(肌氨酸,C反應蛋白);過往和當前的診斷(心肌梗死、心力衰竭、糖尿病、高血壓、呼吸系統疾病和癌症)以及當前COVID-19的藥物療法——HCQ、洛匹那韋/利托那韋或達蘆那韋/科比西斯特(cobicistat)、瑞德西韋、托珠單抗布或沙里魯馬布(sarilumab)、皮質類固醇、肝素、以及對合併症的(胰島素、抗高血壓治療、醛固酮受體拮抗劑、利尿劑、他汀類藥物、薩庫比特利(sacubitril)/纈沙坦)。已有的心血管疾病的診斷基於心肌梗死或心力衰竭的病史。慢性腎臟疾病被分為:第1階段:腎臟損傷,腎小球濾過率(GFR)正常或增高(>90 mL/min/1.73 m2);第2階段:GFR輕度降低(60-89 mL/min/1.73 m2);第3階段a:GFR中度降低(45-59 mL/min/1.73 m2);第3階段b:GFR中度降低(30-44 mL/min/1.73 m2);第4階段:GFR嚴重降低(15-29 mL/min/1.73 m2);第5階段:腎衰竭(GFR <15 mL/min/1.73 m2 或透析)。統計分析合併了第3a和3b階段以及第4和5階段。GFR由慢性腎臟疾病流行病學合作項目(CKD-Epi)的方程計算。如果患者在入院時或隨訪期間接受了HCQ,則被定義為接受HCQ治療。根據AIFA指導方針[14],根據疾病的臨床演變情況,第一天的HCQ的劑量為400毫克2次/天或4次/天,從第二天起按200毫克2次/天,至少5天至最長10天。

2.3 Statistical analysis 統計分析

The study index date was defined as the date of hospital admission. Index dates ranged from February 19, 2020 to May 23, 2020. The study end point was the time from study index to death. The number of patients who either died, or had been discharged alive, or were still admitted to hospital as of May 29, 2020, were recorded, and hospital length of stay was determined. Patients alive had their data censored on the date of discharge or as the date of the respective clinical data collection. Data were censored at 35 days of follow up in n=330 (8.3%) patients with a follow up greater than 35 days.


Of the initial cohort of 3,971 patients, 350 patients were excluded from the analysis because they had at least one missing data at baseline or lost to follow up on HCQ use (N=94), other drug therapies for COVID-19 (n=265), time to event (n=59), outcome (death/alive, n=8), COVID-19 severity (n=4), age (n=4 with missing data and n=2 with age<18 years) or sex (n=2). Of the remaining 3,621 patients, 170 patients died or were discharged within 24 hours after presentation, and were also excluded from the analysis.


At the end, the analysed cohort consisted of n=3,451 patients. In patients not included in the analysis (n=520), as unique difference with the analysed group, the prevalence of diabetics (19.9% vs 14.8%, P=0.0066) and, to a less extent, of men (62.3% vs 58.3%, P=0.081) was higher. Out of 3,541 patients, 295 (8.5%) had at least a missing value for covariates. Distribution of missing values was as follows: n=178 for C-reactive protein; n=69 for GFR; n=74 for history of ischemic disease; n=64 for history of chronic pulmonary disease; n=51 for diabetes; n=51 for hypertension and n=56 for cancer. We used multiple imputation techniques (SAS PROC MI, n=10 imputed datasets; and PROC MIANALYZE) to maximize data availability. As sensitivity analysis, we also conducted a case-complete analysis on 3,156 patients.

最後,被分析的群組包括n=3451名患者。在未納入分析的患者中(n=520),作為與分析組的獨特差異,糖尿病患者(19.9%對14.8%,P=0.0066)和男性(62.3%對58.3%,P=0.081)的患病率更高。在3541名患者中,295人(8.5%)至少有一個協變量的缺失值。缺失值的分布如下:C反應蛋白為n=178;GFR為n=69;缺血性疾病史為n=74;慢性肺部疾病史為n=64;糖尿病為n=51;高血壓為n=51;癌症為n=56。我們使用多重歸因法(SAS PROC MI,n=10歸因數據集和PROC MIANALYZE)以最大限度地提高數據的可用性。作為敏感性分析,我們還對3156名患者進行了病例的完整分析。

Cox proportional-hazards regression models were used to estimate the association between HCQ use and death. Since multiple imputation was applied, the final standard error was obtained using the Rubin’s rule based on the robust variance estimator in Cox regression [32]. The proportional hazards assumption was assessed using weighed Schoenfeld residuals, and no violation was identified. To account for the non-randomized HCQ administration and to reduce the effects of confounding, the propensity-score method was used. The individual propensities for receiving HCQ treatment were assessed with the use of a multivariable logistic-regression model that included age, sex, diabetes, hypertension, history of ischemic heart disease, chronic pulmonary disease, GFR, C-reactive protein, hospitals clustering and use of other drug therapies for COVID-19 (lopinavir/ritonavir or darunavir/cobicistat, remdesivir, corticosteroids, tocilizumab or sarilumab). Associations between HCQ treatment and death was then appraised by multivariable Cox regression models with the use of propensity-score and further controlling for hospitals clustering as random effect (frailty model). The use of a frailty model was chosen as suggested in [33]. The primary analysis used inverse probability by treatment weighting; the predicted probabilities from the propensity-score model was used to calculate the stabilized inverse-probability-weighting weight [34]. Stabilized weights were normalized so that they added up the actual sample size. Secondary analyses used propensity-score stratification (n=5 strata) or multivariable Cox regression analysis or multivariable logistic regression analyses comparing death versus alive patients, or accounted for hospitals clustering via stratification or by robust sandwich estimator. Pre-established subgroup analyses were conducted according to age or sex of patients, degree of COVID-19 severity experienced during the hospital stay, C-reactive protein at basal or other drug therapies for COVID-19. Hospitals were clustered according to their geographical distribution, as illustrated in Table 1. To quantify the potential for an unmeasured confounder to render apparent statistically significant hazard ratio non-significant, the E-value was calculated [35]. Analyses were performed with the aid of the SAS version 9.4 statistical software for Windows.

利用考克斯比例危害回歸模型用於估計HCQ使用與死亡之間的關係。由於採用的是多重歸因法,所以最後的標準誤差是利用根據考克斯回歸模型中[32] 的穩健方差估計量的魯賓法所得到的。使用加權Schoenfeld殘差對比例危險性假設進行了評估,沒有發現違規現象。考慮到非隨機性的HCQ管理,和為了減少混雜變量的影響,採用了傾向性得分法。使用包括年齡在內的多變量邏輯回歸模型評估了接受HCQ治療的個體特徵,包括年齡、性別、糖尿病、高血壓、缺血性心臟病史、慢性肺病史、GFR、C反應蛋白、醫院聚類和使用COVID-19的其他藥物治療(洛匹那韋/利托那韋或達蘆那韋/科比西斯特、瑞德西韋、皮質類固醇、托珠單抗布或沙里魯馬布)。然後,利用傾向得分和進一步控制醫院聚類為隨機效應(脆弱模型),對HCQ治療與死亡之間的關聯進行了多變量考克斯回歸模型的評估。按照[33] 中的建議,選擇了使用脆弱模型。主要分析採用治療加權的反概率;利用傾向得分模型的預測概率計算穩定的反向概率加權權重[34] 。穩定權重經過了歸一化處理,以便使其與實際樣本量相加。二次分析使用傾向性評分分層(n=5分層)或多變量考克斯回歸分析或多變量邏輯回歸分析,比較死亡與存活患者,或通過分層或通過穩健夾心估計量對醫院聚類進行核算。根據患者的年齡或性別、住院期間經歷的COVID-19嚴重程度、基礎C反應蛋白或COVID-19的其他藥物治療進行預先建立的分組分析。如表格1所示,根據醫院的地理分布情況對醫院進行了聚類。為了量化未測量的混雜變量使明顯的統計顯著性風險比變得非顯著的可能性,計算了E值[35]。分析藉助於SAS 9.4版本的Windows統計軟件進行的。

Table 1 General characteristics of COVID-19 patients at baseline, according to hydroxychloroquine use.

表1 根據羥氯喹使用情況,基線上COVID-19患者的一般特徵。

年齡– 中位數(四分位距-歲)73 (58-83)66 (55-77)<.0001
性別– 數(%)

女性361 (44.2%)940 (36.7%)
男性456 (55.8%)1,694 (64.3%)
糖尿病– 數(%)

633 (77.5%)2,090 (79.3%)
162 (19.9%)515 (19.6%)
缺失數據22 (2.7%)29 (1.1%)
高血壓– 數(%)

378 (46.3%)1,294 (49.1%)
416 (50.9%)1,312 (49.8%)
缺失數據23 (2.7%)28 (1.1%)
缺血性心臟病– 數(%)

610 (74.7%)2,190 (83.1%)
179 (21.9%)398 (15.1%)
缺失數據28 (3.4%)46 (1.8%)
慢性肺病– 數(%)

666 (81.5%)2,225 (84.5%)
127 (15.5%)369 (14.0%)
缺失數據24 (2.9%)40 (1.5%)
癌症– 數(%)

694 (84.9%)2,338 (88.8%)
101 (12.4%)262 (9.9%)
缺失數據22 (2.6%)34 (1.3%)
慢性腎病階段** – 數(%)

第1階段241 (29.5%)970 (36.8%)
第2階段281 (34.4%)991 (37.6%)
第3階段a或第3階段b180 (22.0%)487 (18.5%)
第4階段或第5階段89 (10.9%)143 (5.4%)
缺失數據26 (3.2%)43 (1.6%)
C反應蛋白– 數(%)

<1毫克/升104 (12.7%)256 (9.7%)
1-3毫克/升120 (14.7%)301 (11.4%)
>3毫克/升549 (67.2%)1,943 (73.8%)
缺失數據44 (5.4%)134 (5.1%)

621 (76.0%)1,203 (36.7%)
196 (24.0%)1,431 (64.3%)

755 (92.4%)2,160 (82.0%)
62 (7.6%)474 (18.0%)

808 (98.9%)2,551 (96.9%)
9 (1.1%)83 (3.1%)

596 (73.0%)1,655 (62.8%)
221 (27.0%)979 (37.2%)

北部地區(米蘭省除外)(n)169 (20.7%)616 (23.4%)
米蘭省(m)161 (19.7%)525 (19.9%)
中部地區(羅馬除外)(c)303 (37.1%)747 (28.4%)
羅馬(r)94 (11.5%)390 (14.8%)
南部地區(s)90 (11.0%)356 (13.5%)

(n) include hospitals of Novara, Monza, Varese, Pavia, Cremona and Padova; (m) include Humanitas Clinical and Research Hospital, Centro Cardiologico Monzino, and hospitals of San Donato Milanese (Milano) and Cinisello Balsamo (Milano); (c) include hospitals of Modena, Ravenna, Forlì, Firenze, Pisa, Chieti and Pescara; (r) include National Institute for Infectious Diseases “L. Spallanzani” and Università Cattolica del Sacro Cuore; (s) include hospital of Napoli, Pozzilli (Isernia), Acquaviva delle Fonti (Bari), Foggia, Taranto, Catanzaro, Catania and Palermo


*Chi-square test. **Stage 1: Kidney damage with normal or increased glomerular filtration rate (GFR) (>90 mL/min/1.73 m2); Stage 2: Mild reduction in GFR (60-89 mL/min/1.73 m2); Stage 3a: Moderate reduction in GFR (45-59 mL/min/1.73 m2); Stage 3b: Moderate reduction in GFR (30-44 mL/min/1.73 m2); Stage 4: Severe reduction in GFR (15-29 mL/min/1.73 m2); Stage 5: Kidney failure (GFR < 15 mL/min/1.73 m2 or dialysis).

*卡方檢驗。**第1階段:腎臟損傷,腎小球濾過率(GFR)正常或增高(>90 mL/min/1.73 m2);第2階段:GFR輕度降低(60-89 mL/min/1.73 m2);第3階段a:GFR中度降低(45-59 mL/min/1.73 m2);第3階段b:GFR中度降低(30-44 mL/min/1.73 m2);第4階段:GFR嚴重降低(15-29 mL/min/1.73 m2);第5階段:腎衰竭(GFR <15 mL/min/1.73 m2 或透析)

3. Results 結果

We included in the final current analyses 3,451 patients who were hospitalized with confirmed SARS-CoV-2 infection at 33 clinical centres across Italy and either died, had been discharged, or were still in hospital as of May 29, 2020. Of these patients, 2,634 (76.3%, range among hospitals 53.2% to 93.6%) received HCQ. Timing of the first dose of HCQ after presentation to the hospital was 1 day for the large majority of centres, and 2 to 3 days for the others. HCQ was administered in all centres at the dose of 400 mg/day (in one centre however it was used at the dose of 600 mg/day and in another at the dose of 600 mg/day but only in patients younger than 65 years). Duration of treatment ranged from 5 to 15 days (with 10 days as the modal value). The drug used was HCQ in all hospitals.


Baseline characteristics according to HCQ use are shown in Table 1. Patients receiving HCQ were more likely younger, men and had higher levels of C-reactive protein and less likely had ischemic heart disease, cancer or stages 3a or greater chronic kidney disease (Table 1). Patients receiving HCQ more likely received another drug for COVID-19 treatment (78.4%; lopinavir/ritonavir or darunavir/cobicistat, remdesevir, tocilizumab or sarilumab, corticosteroids), in comparison with non-HCQ patients (46.3%; P<0.0001; Table 1).


The unadjusted differences and differences adjusted by propensity scores between HCQ-treated and non-HCQ treated patients for each variable included in the propensity score are shown in Fig. 1. All the pre-treatment differences disappeared after adjustment by propensity score weighting. The C-statistic of the propensity-score model was 0.74.


Fig. 1 The unadjusted standardized differences and standardized differences adjusted by propensity scores between HCQ-treated and non-HCQ treated patients for the variables included in the propensity score. All differences for the matched observations are within the recommended limits of –0.25 and 0.25, which are indicated by reference lines.

圖1 HCQ治療和非HCQ治療患者之間,根據每個傾向評分中的變量,未經傾向評分調整的差異和調整後的差異。匹配觀測值的所有差異都在推薦的-0.25和0.25的範圍內,由參考線表示。

3.1 Primary outcome 主要成果

Out of 3,628 patients, 576 died (16.7%), 2,390 were discharged alive (69.3%) and 485 (14.1%) were still at the hospital. The median follow-up was 14 days (interquartile range 8 to 22; range 2 to 35; 55,388 person-days). Death rate (per 1,000 person-days) was 8.9 in HCQ and 15.7 in non-HCQ patients (Table 2). At univariable analysis, hazard ratio for mortality was 0.56 (95%CI: 0.47 to 0.67). In the primary multivariable analysis with inverse probability weighting according to the propensity score, HCQ use was associated with a 30% (95%CI: 16% to 41%) reduction in death risk (Fig. 2, Table 2, E-value=1.67). Secondary multivariable analyses yielded very similar results (Table 2), as well as case-complete analyses restricted to the 3,156 patients without missing data (Table 2). Considering secondary multivariable analyses overall, HR for mortality associated with HCQ ranged between 0.64 to 0.70, according to type of analyses. Control of hospitals clustering with different approaches also yielded similar results for the primary analysis (HR=0.71, 95%CI: 0.59 to 0.85 when hospitals clustering was stratified for and HR=0.69, 95%CI: 0.54 to 0.88 with the robust sandwich estimator).


Table 2 Incidence rates and hazard ratios for death in COVID-19 patients, according to hydroxychloroquine use.




否 – 數(%)190(23.3%)817(100%)12,08415.7
是 – 數(%)386(14.7%)2,634(100%)43,3048.9
粗略分析0.56(0.47 to 0.67)
多變量分析*0.70(0.58 to 0.85)
傾向評分分析,反向概率加權**(初步分析)0.70(0.59 to 0.84)
傾向評分分析,分層(n=5分層)**0.67(0.56 to 0.81)
傾向評分分析,反向概率加權**0.67(0.54 to 0.82)


否 – 數(%)170(22.9%)741(100%)11,05015.4
是 – 數(%)340(14.1%)2,415(100%)39,2748.7
粗略分析0.56(0.46 to 0.67)
多變量分析*0.71(0.59 to 0.86)
傾向評分分析,反向概率加權**0.64(0.53 to 0.76)
傾向評分分析,分層(n=5分層)**0.68(0.56 to 0.82)
傾向評分分析,反向概率加權**0.67(0.54 to 0.82)

Abbreviations: HR, hazard ratios; CI, confidence intervals. *Controlling for age, sex, diabetes, hypertension, history of ischemic heart disease, chronic pulmonary disease, chronic kidney disease, C-reactive protein, lopinavir/ritonavir or darunavir/cobicistat, tocilizumab or sarilumab, remdesivir or corticosteroids use as fixed effects and hospitals clustering as random effect. **Including hospitals clustering as random effect covariate.


Fig. 2 Survival curves according to hydroxychloroquine use. The curves are adjusted by propensity score analysis (inverse probability for treatment weighting) and hospital index as random effect, and are generated using the first imputed dataset. The other imputed datasets are similar and thus omitted.

圖2 根據羥氯喹使用而生存的曲線。曲線通過傾向評分分析(治療加權的反向概率)和醫院指數作為隨機效應進行調整,並使用第一個歸因數據集生成。其他歸因數據集類似,因此省略。

Subgroup analyses are presented in Table 3. HCQ use remained consistently associated with reduced mortality in almost all subgroups. The inverse association of HCQ with inpatient mortality is slightly more evident in women, elderly and in patients who experienced a higher degree of COVID-19 severity. It was absent in-patient with C-reactive protein <10 mg/L and clearly confined to patients with elevated C-reactive protein (Table 3).


Table 3 Hazard ratios for mortality according to hydroxychloroquine use in different subgroups

表3 不同分組中使用羥氯喹的死亡率風險比

分组死亡人數/高危病人死亡人數/高危病人風險比 (95% CI)*
女人80/361116/9400.63 (0.46 to 0.86)
男人110/456270/1,6940.74 (0.60 to 0.93)
年齡<7022/35793/1,5420.76 (0.50 to 1.16)
年齡≥70168/460293/1,0920.68 (0.56 to 0.83)
輕度肺炎或更少28/42440/1,3580.70 (0.41 to 1.18)
重度肺炎80/253172/7640.76 (0.58 to 0.99)
急性呼吸窘迫綜合症82/140174/5120.68 (0.52 to 0.90)
101/43964/5700.63 (0.45 to 0.88)
89/378322/2,0640.77 (0.61 to 0.99)
<10毫克/升56/412125/1,1381.23 (0.86 to 1.77)
≥10毫克/升123/361241/1,3620.59 (0.47 to 0.73)

Abbreviations: HR, hazard ratios; CI, confidence intervals; *Propensity score analysis, inverse probability weighting, including hospital clustering as random effect covariate; multiple imputed analysis.


^Lopinavir/ritonavir or darunavir/cobicistat or tocilizumab or sarilumab or remdesivir or corticosteroids.


**Missing data for N=178. Frequencies and hazard ratios are based on a case complete analysis (N=3,273) without missing data for C-reactive Protein; multiple imputed analysis (N=3,451) yielded very similar results.


4. Discussion 討論

In a large cohort of 3,451 patients hospitalized for COVID-19 in 33 clinical centers all over Italy, covering almost completely the period of the hospitalization for COVID-19, the use of HCQ was associated with a significant better survival. In-hospital crude death rate was 8.9 per 1,000 person-day for patients receiving HCQ and 15.7 for those who did not. After adjustment for known possible confounders, we observed a 30% reduction in the risk of death in patients receiving HCQ therapy as compared with those who did not.


Our findings provide clinical evidence in support of guidelines by Italian and several international Societies suggesting to use HCQ therapy in patients with COVID-19. However, the observed associations should be considered with caution, as the observational design of our study does not allow to fully excluding the possibility of residual confounders. Large randomized clinical trials in well-defined geographical and socio-economic conditions and in well-characterized COVID-19 patients, should evaluate the role of HCQ before any firm conclusion can be reached regarding a potential benefit of this drug in patients with COVID-19.


Over 76% of patients received HCQ either alone or in combination with other drugs. They were more likely to be younger, men and with higher levels of C reactive protein at entry, while less likely had pre-existing comorbidities such as ischemic heart disease, cancer and severe chronic kidney disease, as compared to patients not receiving the drug. We adjusted our analyses for possible confounders, including age, sex, diabetes, hypertension, history of ischemic heart disease, chronic pulmonary disease, chronic kidney disease, C-reactive protein and additional treatments for COVID-19, and took into account possible differences across centres by either adjustment or stratification. To minimize bias due to the observational design, we used different analytical approaches aiming at creating an overall balance between comparison groups. Finally, we tried to limit bias due to missing data by using a multiple imputation approach, but in no case, the result was changed. Despite all these precautions, we recognize the possibility, however, of residual unmeasured confounders affecting results.


Systematic reviews of small clinical trials had reported contrasting results that were however scarcely reliable because of poor designs [20, 21, 22, 23, 24, 25]. The HCQ doses tested in a Chinese randomized clinical trial [25] were approximately double as compared to that used in our study (1200 mg vs 800 mg as loading dose, 800 mg vs 400 mg as maintenance dose) for twice the time (14-21 days versus 7-10 days). National guidelines in Italy suggest to use HCQ 200 mg twice daily for at least 5-7 days in patients over 70 years and/or with co-morbidities (chronic obstructive pulmonary disease, diabetes, cardiovascular disease) even with mild respiratory symptoms or with radiographically documented pneumonia or in severe patients [36]. The lower doses of HCQ used in our centers, as suggested by Italian official guidelines [19, 36], may have been both more effective and safer.


Two recently published large observational studies, both from large hospitals in New York City, showed no association between HCQ use and in-hospital mortality [27, 28], and deserve specific discussion. In the study of Geleris et al. [27], the percentage use of HCQ was lower than in Italy; moreover, in both US studies [27, 28] the drug was more frequently administered to patients with previous illnesses and a more severe presentation of the disease. Our cohort included milder pneumonia patients than the US population, due to between-country differences in indications to the drug for the beginning of therapy (e.g., mild pneumonia in Italy versus only severe pneumonia and ARDS in the US). Concomitant use of other drugs for COVID-19 was very low in one study [27] and was not reported in the other study [28]. In our cohort, patients receiving HCQ were more likely treated with another drug for COVID-19 treatment (78.4%), in comparison with non-HCQ patients (46.3%). Anyway, our findings are adjusted for concomitant other drugs use.


While the US studies were confined to one hospital only or a defined relatively small area in the Country, our study included 33 hospitals distributed all over Italy, covering regions with a high number of cases and a high intra-hospital mortality and regions with a lower burden of the disease. The participating Italian clinical centers have different healthcare facilities, different size, specialization, and ownership, and therefore quite closely represent the real-life Italian approach to COVID-19. Moreover, they differed for the percentage of use of HCQ and for the rate of in-hospital mortality that ranged between 34.1 and 1.5 per 1,000 persons/day. To consider this variability, we adjusted the analysis for recruiting center and performed a number of subgroup analyses. In all circumstances, the association between HCQ use and a reduced risk of death of about 30% was maintained. Quite interestingly, the inverse association of HCQ with inpatient mortality was more evident in elderly, in patients who experienced a higher degree of COVID-19 severity or especially having elevated C-reactive protein, suggesting that the anti-inflammatory potential of HCQ may have had more important role rather than its antiviral properties. HCQ, indeed, beside an antiviral activity, may have both anti-inflammatory and anti-thrombotic effects [8]. This can justify its effect in reducing mortality risk, since Sars-Cov-2 can induce pulmonary microthrombi and coagulopathy, that are a possible cause of its severity [37, 38] and the lack in preventing SARS-CoV-2 infection after exposure [26]


Nevertheless, large randomized clinical trials on the efficacy of HCQ on hard end-points are still lacking and the largest observational study showing no effect in reducing mortality has been retracted [16, 17], Agencies have suspended clinical trials on the efficacy of HCQ on COVID-19 disease or have restricted its use only to patients included in clinical trials, in the absence of an ample, serene and balanced discussion at international level.


Very recently, a large RCT has become available as a pre-print publication [39], reporting no beneficial effect of HCQ in patients hospitalized with COVID-19. However, the dose of HCQ used in that trial was almost the double of that administered in our real life conditions. A reduced mortality was also observed by other observational studies using low or intermediate doses of HCQ [40, 41],


Moreover, in our study patients taking HCQ more frequently received other anti-COVID drugs, whose interaction in reducing mortality cannot be completely ruled-out. Of note, despite the higher dosage used, the RCT did not show any excess in ventricular tachycardia or ventricular fibrillation in the HCQ arm (39.


Therefore, it will be very important to compare results of studies with different mode of use and doses of HCQ, different characteristics of treated and untreated patients and different academic or real-world conditions.


4.1 Strengths and limitations 優勢和局限性

A major strength of this study is the large, unselected patient sample from 33 hospitals, covering the entire Italian territory. Patient sampling covered all the overt epidemic period in Italy. Several statistical approaches were used to overcome biases due to the observational nature of the investigation.


This study has however, several recognized limitations. The study population pertains to Italy, and the results obtained may not be applicable to other populations with a possibly different geographical and socio-economic conditions and natural history of COVID-19. Due to the retrospective nature of the study, some parameters were not available in all patients, and all in-hospital medications might have been not fully recorded. Moreover, although guidelines on the use of HCQ in COVID-19 patients had been published in Italy since the first phase of the pandemic, individual centers could have deviated from recommendations and used different doses or treatment schemes. We have no information on the HCQ doses used individually nor of their possible association with azithromycin. Moreover, adverse events possibly related to drug therapy were not collected, thus we cannot exclude bias due to therapy interruption because of side effects; we do not know whether some deaths could have been due to cardiovascular complications of HCQ. However, recent data on Italian wards showed that COVID-19 patients receiving HCQ and azithromycin had a QTc-interval longer than before therapy, but did not experience, during their hospital stay, any arrhythmic complications, such as syncope or life-threatening ventricular arrhythmias [42], a finding also reported by the RCT mentioned above (39).


Finally, the possibility of unmeasured residual confounding cannot be completely ruled-out. However, the E-value for the lower boundary of the confidence interval of our main result is 1.67, indicating that the confidence interval could be moved to include the null by a strong unmeasured confounder associated with both HCQ treatment and death with a risk ratio of 1.67-fold for each, above and beyond all the measured confounders. Weaker confounders, however, could not do so.


5. Conclusions 結論

Our study, including a large real life sample of patients hospitalized with COVID-19 all over Italy, shows that HCQ use (200 mg twice/day) was associated with a 30% reduction of overall in-hospital mortality. In the absence of clear-cut results from controlled, randomized clinical trials, our data do not discourage the use of HCQ in inpatients with COVID-19. Given the observational design of our study, however, these results should be transferred with caution to clinical practice.




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Himalaya Rose Garden Team

“but those who hope in the Lord will renew their strength. They will soar on wings like eagles; they will run and not grow weary, they will walk and not be faint” 【Isaiah 40:31】 9月 06日