Research Incidence of COVID-19 in patients exposed to chloroquine and hydroxychloroquine: results from a population-based prospective cohort in Catalonia, Spain, 2020 Rosa Maria Vivanco-Hidalgo1,2, Israel Molina2,3 , Elisenda Martinez¹ , Ramón Roman-Viñas¹ , Adrián Sánchez-Montalvá³ , Joan Fibla4,5 , Caridad Pontes6,7 , César Velasco Muñoz¹ , on behalf of the Real World Data Working Group⁸ 1. Agència de Qualitat i Avaluació Sanitàries de Catalunya (AQuAS), Departament de Salut Generalitat de Catalunya, Carrer de Roc Boronat 81-95, Barcelona, Spain 2. These authors contributed equally 3. Infectious Diseases Department, Hospital Universitario Vall d’Hebron, PROSICS Barcelona, Universitat Autònoma de Barcelona, Barcelona, Spain 4. Unitat de Genètica Humana, Departament de Ciències Mèdiques Bàsiques, Universitat de Lleida, Av. Alcalde Rovira Roure, 80, 25198, Lleida, Spain 5. Institut de Recerca Biomedica de Lleida, Av. Alcalde Rovira Roure, 80, 25198, Lleida, Spain 6. 6 Gerència del Medicament – Àrea Assistencial, Servei Català de la Salut, Travessera de les Corts, 131-159, 08028 Barcelona, Spain 7. Departament de Farmacologia, de Terapèutica i de Toxicologia, Universitat Autònoma de Barcelona, Av. de Can Domènech, 737, 08193 Cerdanyola del Vallès, Barcelona, Spain 8. Members of the Real World Data Working Group have been acknowledged at the end of the article Correspondence: Rosa Maria Vivanco-Hidalgo (rvivanco@gencat.cat) Citation style for this article: Vivanco-Hidalgo Rosa Maria, Molina Israel, Martinez Elisenda, Roman-Viñas Ramón, Sánchez-Montalvá Adrián, Fibla Joan, Pontes Caridad, Velasco Muñoz César, on behalf of the Real World Data Working Group. Incidence of COVID-19 in patients exposed to chloroquine and hydroxychloroquine: results from a population- based prospective cohort in Catalonia, Spain, 2020. Euro Surveill. 2021;26(9):pii=2001202. https://doi.org/10.2807/1560-7917.ES.2021.26.9.2001202 Article submitted on 15 Jun 2020 / accepted on 19 Oct 2020 / published on 04 Mar 2021 Background: Several clinical trials have assessed the rate in the former, though differences were not con- protective potential of chloroquine and hydroxychloro- firmed after adjustment (HR: 1·46; 95% CI: 0.91–2.34; quine. Chronic exposure to such drugs might lower the p = 0.10). Conclusions: Patients chronically exposed to risk of infection with severe acute respiratory syndrome chloroquine/hydroxychloroquine did not differ in risk coronavirus 2 (SARS-CoV-2) or severe coronavirus dis- of COVID-19 nor hospitalisation, compared with con- ease (COVID-19). Aim: To assess COVID-19 incidence trols. As controls were mainly female, findings might and risk of hospitalisation in a cohort of patients not be generalisable to a male population. chronically taking chloroquine/hydroxychloroquine. Methods: We used linked health administration data- Introduction bases to follow a cohort of patients with chronic pre- The coronavirus disease (COVID-19) outbreak that scription of hydroxychloroquine/chloroquine and a started in January in China evolved into a pandemic control cohort matched by age, sex and primary care with global cumulative numbers totalling 110.7 mil- service area, between 1 January and 30 April 2020. lion confirmed cases and over 2.4 million deaths by 23 COVID-19 cases were identified using International February 2021, with figures constantly increasing [1]. Classification of Diseases 10 codes. Results: We ana- Since the beginning of the pandemic, non-pharmaceu- lysed a cohort of 6,746 patients (80% female) with tical interventions such as physical distancing, lock- active prescriptions for hydroxychloroquine/chloro- downs and the use of face masks in public spaces have quine, and 13,492 controls. During follow-up, there been implemented in an effort to reduce transmission were 97 (1.4%) COVID-19 cases in the exposed cohort of SARS-CoV-2. However, such strict non-pharmaceuti- and 183 (1.4%) among controls. The incidence rate was cal interventions can only be maintained for a limited very similar between the two groups (12.05 vs 11.35 time without critically affecting citizens’ psychological cases/100,000 person-days). The exposed cohort was health and the economy. not at lower risk of infection compared with controls (hazard ratio (HR): 1.08; 95% confidence interval (CI): Prophylactic pharmaceutical interventions for COVID- 0.83–1.44; p = 0.50). Forty cases (0.6%) were admit- 19 have been explored and developed since the out- ted to hospital in the exposed cohort and 50 (0.4%) in set of the pandemic. Early clinical reports from China the control cohort, suggesting a higher hospitalisation and France suggested the potential antiviral activity www.eurosurveillance.org 1 Box 1 During the first wave of the pandemic it was therefore ICD-9 codes used for baseline comorbidities, Catalonia, reasonable to consider whether people who are chroni- Spain, 2020 cally taking CQ or HCQ for any therapeutic indication may have less risk of SARS-CoV-2 infection and, if they Asthma: 493xx contract COVID-19, whether they develop less severe Chronic obstructive pulmonary disease: 491.0, 419.2x, disease. 491.8, 491.9, 492xx, 494x, 496 For this reason, we have compared the incidence of Chronic renal failure: 403.01, 403.11, 403.91, 585xx, 586xx, 588.0 COVID-19 in people who are chronic users of CQ or HCQ and those who are not, among people living in Congestive heart failure: 398.91, 402.01, 402.11, 402.91, Catalonia, Spain. 404.01, 404.03, 404.11, 404.13, 404.91, 404.93,428xx Diabetes mellitus: 250xx Methods Catalonia is an autonomous province in the west of Dementia: 290xx, 331.0, 331.1, 331.2 Spain that has universal public healthcare coverage, Hypertension: 401x, 402xx, 403xx, 404xx, 405xx including primary and hospital healthcare, as well as prescription drug costs. Integrated registries are used Ischaemic heart disease: 410xx, 411xx, 412, 413xx, 414xx to manage administrative and clinical information on Liver cirrhosis: 571.2, 571.5 the entire population in Catalonia, i.e. 7.5 million peo- ple, including invoicing systems for pharmacies, epi- Malignant neoplasm: 140xx-230xx sode diagnoses for budgeting and payment purposes, Stroke: 430, 431,432x, 433xx, 434xx, 436, 437, 437.0, clinical information exchange systems across health- 437.1,437.8, 437.9, 438xx care providers and dedicated registries for epidemio- logical surveillance. ICD-9: Ninth revision of the International Classification of Diseases. We report this study according to the guidelines for observational studies using routinely collected data. of 4-aminoquinolines (chloroquine (CQ) and its ana- Registry features and data acquisition logue, hydroxychloroquine (HCQ)) against COVID-19 A Catalan central registry of insured persons allows [2,3]. Supported by preclinical evidence of its activity linking of information at the individual level between in cell culture [4], both testing and empirically using all health administration databases, and includes these drugs in the prevention and treatment of COVID- individual sociodemographic data and aggregated 19 increased [5]. However, a retrospective cohort study primary care service area data. An individual’s health- reported in July 2020 that continuous HCQ therapy care identification code allows Catalan residents to does not prevent infection with SARS-CoV-2, based on be tracked across several health administration data- a large healthcare database analysis in Israel [6]. bases, including the acute and emergency hospitals and emergency discharge datasets, conjunt mínim CQ is one of the most frequently prescribed drugs in bàsic de dades d’hospitalitzats d’aguts (CMBD-HA) the world and has been used for treating malaria and and conjunt mínim bàsic de dades d’urgències hos- as chemoprophylaxis in travellers for decades, even pitalàries (CMBD-URG); the pharmacy invoicing data- for long periods of exposure [7]. Its safety profile is base; the episode diagnosis database for primary care, well known and its risk-benefit is deemed favourable conjunt mínim de dades d’atenció primària (CMBD-AP), to treat and prevent malaria [8]. HCQ, a chloroquine which records information on comorbidity and date of hydroxylated derivate, has also been widely used. diagnosis; the laboratory database, including data of Data from observational studies suggest that HCQ is SARS-CoV-2 nucleic acid amplification test results; and threefold less toxic than CQ; therefore, while the type the specific epidemiological mandatory registry for of adverse events is similar for both drugs, they occur SARS-CoV-2 infection. All CMBD databases register the less frequently with HCQ [9]. Moreover, CQ and HCQ information using the Ninth and Tenth Revisions of the are known immunomodulators that have been used for International Classification of Diseases codes (ICD-9 decades as chronic treatments in certain rheumatolog- and ICD-10) [13,14], and the pharmacy invoicing data- ical diseases [10-12]. base uses Anatomical Therapeutic Chemical/Defined Daily Dose index codes established by the World Health Based on this background, several clinical trials were Organization Collaborating Centre in Oslo, Norway. The designed to assess the protective potential of 4-amino- registries have an automated data validation system quinolines (CQ or HCQ) against SARS-CoV-2 infection, to check consistency of data and identify potential given as pre-exposure and post-exposure prophylaxis errors, and external audits are performed periodically in highly exposed populations, such as healthcare pro- to ensure quality and reliability of data. fessionals (clinicaltrials.gov register: NCT04303507, NCT04308668, NCT04304053). 2 www.eurosurveillance.org Table 1 Characteristics of control cohort and cohort exposed to chloroquine/hydroxychloroquine, Catalonia, Spain, 1 January 2020 Control Exposed Total Characteristics (n = 13,492) (n = 6,746) (N = 20,238) p value n % n % N % Age (years) Mean (SD) 57.1 (15.8) – 57.1 (15.8) – 57.1 (15.8) – Median (Q1, Q3) 57.0 (45.0, 69.0) – 57.0 (45.0, 69.0) – 57.0 (45.0, 69.0) – 1.000 Min–Max 8.0–96.0 – 8.0–96.0 – 8.0–96.0 – Sex Female 11,366 84.2 5,683 84.2 17,049 84.2 1.000 Male 2,126 15.8 1,063 15.8 3,189 15.8 Comorbidities Hypertension 4,056 30.3 2,513 37.3 6,569 32.7 < 0.001 Diabetes 1,512 11.2 763 11.3 2,275 11.3 0.841 Congestive heart failure 494 3.7 415 6.2 909 4.5 < 0.001 COPD 896 6.7 829 12.3 1,725 8.5 < 0.001 Chronic renal disease 798 5.9 851 12.6 1,649 8.2 < 0.001 Asthma 954 7.1 633 9.4 1,587 7.9 < 0.001 Dementia 227 1.7 78 1.2 305 1.5 0.004 Liver cirrhosis 63 0.5 60 0.9 123 0.6 < 0.001 Stroke 629 4.7 444 6.6 1,073 5.3 < 0.001 Coronary artery disease 517 3.8 409 6.1 926 4.6 < 0.001 Cancer 1,530 11.4 880 13.1 2,410 11.9 < 0.001 Tobacco use Non-smoker 5,319 58.7 2,756 56.1 8,075 57.8 Current smoker 2,310 25.5 1,238 25.2 3,548 25.4 < 0.001 Former smoker 1,440 15.9 919 18.7 2,359 16.9 AMG Very low risk 8,238 61.2 1,817 27.0 10,055 49.8 Low risk 3,352 24.9 2,753 40.9 6,105 30.2 Moderate risk 1,442 10.7 1,581 23.5 3023 15.0 < 0.001 High risk 339 2.5 467 6.9 806 4.0 Very high risk 82 0.6 114 1.7 196 1.0 IS level Exempts 540 4.0 325 4.8 865 4.3 < 18,000 € 8,056 59.7 4,170 61.8 12,226 60.4 < 0.0012 18,001–100,000 € 4,776 35.4 2,193 32.5 6,969 34.4 > 100,000 € 120 0.9 58 0.9 178 0.9 PCL deprivation index 0–32.2 3,490 26.3 1,745 26.3 5,235 26.3 32.2–41.2 3,210 24.2 1,605 24.2 4,815 24.2 1.000 41.2–49.7 3,296 24.8 1,648 24.8 4,944 24.8 49.7–100 3282 24.7 1,641 24.7 4,923 24.7 CQ/HCQ 0 0 6,746 100.0 6,746 33.3 CQ 0 0 114 1.7 114 1.7 < 0.001 HCQ 0 0 6,648 98.5 6,648 98.5 Hospitalisation 50 0.4 40 0.6 90 0.4 0.025 COVID-19 diagnosis 183 1.4 97 1.4 280 1.4 0.640 AMG: Adjusted Morbidity Groups; COPD: chronic obstructive pulmonary disease; COVID-19: coronavirus disease; CQ: chloroquine; HQ: hydroxychloroquine; IS level: individual socioeconomic level; PCL deprivation index: index of deprivation at primary care service area level; Q1: first quartile; Q3: third quartile; SD: standard deviation. www.eurosurveillance.org 3 Figure 1 Cumulative incidence of SARS-CoV-2 infection in the cohort exposed to chloroquine/hydroxychloroquine and the control cohort, Catalonia, Spain, 1 January–30 April 2020 1.000 + ++ +++++ + ++ ++ ++ ++ + + ++ + + + +++++++ +++ +++++ ++++ + ++ ++ ++ + + + Control Proportion of patients not infected with SARS-CoV-2 ++ + CQ/HCQ ++ + 0.995 + + + + ++ + + 0.990 p = 0.63 + + + + + + + + ++ 0.985 0.980 0 30 60 90 120 Time (days) Number at risk Control 13,492 13,477 13,460 13,381 13,257 CQ/HCQ 6,746 6,737 6,730 6,676 6,616 0 30 60 90 120 Time (days) Control: non-exposed control cohort; CQ/HCQ: cohort exposed to chloroquine/hydroxychloroquine; SARS-CoV-2: severe acute respiratory syndrome coronavirus 2. Study design and participants population into five morbidity groups (very low risk, We conducted a population-based, prospective cohort low risk, moderate risk, high risk, very high risk) [15]. study using linked health administration databases in Information regarding socioeconomic status was also Catalonia, Spain. The first Catalan case in the COVID-19 retrieved from the Catalan central registry of insured outbreak was reported in late February, lockdown was persons for every subject using two levels (individual declared on 13 March and peak incidence was reached and primary care service area). Individual socioeco- in early April, with a progressive decline in incidence nomic status was derived from the individual yearly thereafter. Thus, we studied the period between 1 income range information used to calculate pharmacy January and 30 April 2020. copayment. Copayment ranges are derived from tax declarations and/or social security benefits received, The exposed cohort included patients who, on 1 as follows: exempted (non-working population or peo- January 2020, had been dispensed CQ/HCQ treatment ple receiving non-contributory pension), < €18,000 in the last 6 months according to the pharmacy invoic- ($US 20,468) income per year; €18,000 ($US 20,468) ing database. The Catalan central registry of insured to €100,000 ($US 113,710) income per year; and > €100 persons was used to select a control cohort of people 000 ($US 113,710) income per year. The primary care who, on 1 January 2020, did not have any invoices for service area socioeconomic status is defined by the CQ/HCQ in the same period. For each exposed patient, index of deprivation that ranges from 0 (less deprived) two non-exposed individuals (controls) of the same to 100 (more deprived); this was also a control cohort age, sex and primary care service area were chosen. matching parameter [16]. Information regarding baseline comorbidities was Estimation of chronic exposure to chloroquine/ obtained from the CMBD-AP using the ICD-9 given hydroxychloroquine in Box 1. A comorbidity index was also used (Adjusted We considered that patients had chronic exposure to Morbidity Groups), a recently developed morbid- CQ/HCQ if—according to the pharmacy invoicing data- ity measurement that enables classification of the base—they had been dispensed CQ/HCQ (ATC P01BA01 4 www.eurosurveillance.org Table 2 Adjusted hazard ratios and 95% confidence intervals for episodes of SARS-CoV-2 infection by comorbidities and individual socioeconomic status, Catalonia, Spain, 30 April 2020 Characteristics Adjusted hazard ratio Lower 0.95 CI Upper 0.95 CI p value Hypertension 0.93 0.68 1.27 0.65 Diabetes 1.17 0.81 1.70 0.40 Heart failure 1.24 0.76 2.04 0.40 COPD 1.59 1.08 2.35 0.01 Chronic renal disease 1.30 0.87 1.95 0.20 Asthma 1.19 0.78 1.82 0.40 Dementia 4.33 2.61 7.17 < 0.001 Liver cirrhosis 0.70 0.10 5.03 0.72 Stroke 1.38 0.88 2.16 0.16 Coronary artery disease 1.27 0.77 2.10 0.35 Cancer 1.05 0.73 1.52 0.79 Current smoker 0.67 0.46 0.93 0.03 Former smoker 1.32 0.95 1.82 0.10 IS level < 18,000 € 1.04 0.55 1.99 0.90 IS level 18,001–100,000 € 0.85 0.44 1.68 0.60 IS level > 100,000 € 0.79 0.10 6.17 0.80 CQ/HCQ exposure 1.08 0.83 1.44 0.50 CI: confidence interval; COPD: chronic obstructive pulmonary disease; CQ/HCQ: chloroquine/hydroxychloroquine; IS level: individual socioeconomic level; SARS-CoV-2: severe acute respiratory syndrome coronavirus 2. or P01BA02) at least once in January 2020 and also (exposed and control), considered separately, using during the previous 6 months or more, with this treat- the Kaplan-Meier method and compared statistically ment ongoing during the study period. using the log rank test. We fitted a priori multivariable Cox proportional hazards regression model adjusted Outcome for all comorbidities and individual socioeconomic sta- Our main outcome of interest was incidence of SARS- tus to determine which variables were associated with CoV-2 infection or COVID-19 diagnosis, as defined an increased risk of infection. by one or more of the following: (i) a record with ICD-10 codes B97.29 or B34.2, as retrieved from the The same analysis was applied to time to event for CMBD-HA, CMBD-URG or CMBD-AP datasets; (ii) a the secondary outcome (admission to hospital due to record of infection retrieved from the specific registry COVID-19). for SARS-CoV-2 infection or (iii) a positive SARS-CoV-2 RT-PCR test in the laboratory database. Patients were We checked the proportional hazards assumption for followed from 1 January 2020 until diagnosis or until 30 all covariates using graphical methods (inspection of April 2020 (end of follow-up). As a secondary outcome, log minus log plot of survival). we also retrieved data on admission to hospital due to COVID-19. R statistical software, version R-4.0.0 was used for all analyses [17]. Statistical analysis We used descriptive statistics to show the base- Ethical statement line demographic and comorbidity information of the No patients were involved in setting the research ques- individuals included in our analyses. Incidence rate tion or the outcome measures, nor were they involved of SARS-CoV-2 infection was calculated for both the in the design or implementation of the study. Data from exposed cohort and the control cohort. The numera- different health administration databases were linked tor of the incidence was the number of subjects with and de-identified by a team not involved in the study SARS-CoV-2 infection observed during follow-up. The analysis; only a full de-anonymised database was denominator, in person-days, was the follow-up dura- available to the study investigators. The study proto- tion, which ended on 30 April 2020, at the time of a col was approved by the Ethical Review Board of Vall SARS-CoV-2 infection diagnosis, on the date of death d’Hebron University Hospital (Code VHI-HCQ-2020–01), or at the last available follow-up. Barcelona, Spain. For the time to event analyses for the main outcome Results (SARS-CoV-2 infection or COVID-19), cumulative inci- At the start of the follow-up (1 January 2020), 6,746 dence of event curves were estimated for each cohort patients were identified as chronic users of CQ (114)/ www.eurosurveillance.org 5 Figure 2 Cumulative incidence of hospitalisation for COVID-19 in cohort exposed to chloroquine/hydroxychloroquine and control cohort, Catalonia, Spain, 30 April 2020 1.000 + +++++++ + ++ + + ++ + + +++ + + +++++++ ++ +++ ++ ++ + ++ + ++ ++ + ++ + + + + ++ + + ++ ++ + + + + Proportion of patients not hospitalised for COVID-19 + + + + ++ 0.995 + + + 0.990 p = 0.025 + Control + CQ/HCQ 0.985 0.980 0 30 60 90 120 Time (days) Number at risk Control 13,492 13,477 13,460 13,435 133,92 CQ/HCQ 6,746 6,737 6,730 6,701 6,677 0 30 60 90 120 Time (days) Control: non-exposed control cohort; COVID-19: coronavirus disease: CQ/HCQ: cohort exposed to chloroquine/hydroxychloroquine. HCQ (6,648) and matched to 13,492 controls. All but between the two cohorts in the unadjusted cumulative one patient had at least one additional dispensation incidence of event curves (Figure 2). of CQ/HCQ during the study period. Baseline charac- teristics are described in Table 1. Median age in both Adjusted estimates by comorbidities and socioeco- cohorts was 57 years (interquartile range: 45–69) and nomic status did not show significant differences (HR: 84.2% were women. In general, patients in the exposed 1.46; 95% CI: 0.91–2.34; p = 0.10). In particular, demen- cohort had more comorbidities and lower individual tia was associated with a substantial increase of risk socioeconomic status than those in the control cohort. (Table 3). A total of 97 cases in the exposed cohort (1.4%) and 183 (1.4%) in the control cohort had SARS-CoV-2 infec- Discussion tion during the follow-up. The incidence rate was simi- After comparing the two cohorts, we found no differ- lar between both cohorts (12.05 vs 11.35 cases/100,000 ences between the incidence of COVID-19 in those person-days). No differences were observed in the under long-term CQ/HCQ therapy and the controls. crude cumulative incidence of event (SARS-CoV-2 infec- When analysing unadjusted risk of hospitalisation for tion) curves (Figure 1). COVID-19, patients receiving 4-aminoquinolines had more risk of hospitalisation; however, this effect did Table 2 shows hazard ratios (HRs) for time-to-infection not persist after adjustment for comorbidities, sug- for the CQ/HCQ cohort after adjusting for comorbidities gesting that it might be because of the higher propor- and individual socioeconomic status. Patients tion of comorbidities among the exposed patients. chronically exposed to CQ/HCQ were not at lower risk of infection compared to controls (HR: 1.08; 95% confi- The rapid spread of SARS-CoV-2 led to the need to seek dence interval (CI): 0.83–1.44; p = 0.50). pharmaceutical prevention strategies while waiting for an effective and safe vaccine. Different strategies have Unadjusted estimates for risk of hospitalisation for been evaluated, mainly in high-risk groups such as COVID-19 showed that 40 (0.6%) cases were admitted healthcare workers. CQ/HCQ were the first candidates to public hospitals in the exposed cohort and 50 (0.4%) to be evaluated, because of evidence shown in experi- in the control cohort, with significant differences mental models and incipient observational studies. As 6 www.eurosurveillance.org Table 3 Adjusted hazard ratios and 95% confidence intervals for hospitalisation for COVID-19, by comorbidities and individual socioeconomic status, Catalonia, Spain, 30 April 2020 Characteristics Adjusted hazard ratio Lower 0.95 CI Upper 0.95 CI p value Hypertension 1.40 0.82 2.38 0.20 Diabetes 1.04 0.54 1.97 0.90 Heart failure 0.83 0.33 2.09 0.70 COPD 1.17 0.57 2.40 0.60 Chronic renal disease 1.70 0.89 3.25 0.10 Asthma 1.42 0.69 2.90 0.30 Dementia 1.17 0.28 4.90 0.80 Liver cirrhosis 2.01 0.27 14.72 0.50 Stroke 1.28 0.57 2.88 0.50 Coronary artery disease 0.89 0.34 2.33 0.80 Cancer 1.44 0.80 2.60 0.20 Current smoker 0.58 0.29 1.16 0.10 Former smoker 1.23 0.68 2.19 0.48 IS level < 18,000 € 1.91 0.46 7.83 0.37 IS level 18,001–100,000 € 1.08 0.25 4.76 0.9 IS level > 100,000 € 0 0 – 0.99 CQ/HCQ exposure 1.46 0.91 2.34 0.10 CI: confidence interval; COPD: chronic obstructive pulmonary disease; COVID-19: coronavirus disease; CQ/HCQ: chloroquine/ hydroxychloroquine; IS level: individual socioeconomical level. at March 2020, more than 80 clinical trials have been may reduce the viral load and diminish symptoms and registered to assess the potential activity of CQ/HCQ severity in infected individuals. against COVID-19, including the full spectrum of symp- toms. Although early observational studies reported We observed that patients receiving CQ/HCQ had more positive effects, as larger observational studies and admissions to hospital than controls (0.6% vs 0.4%, clinical trials emerged, the evidence to support the use p = 0.025), but the adjusted estimates by comorbidi- of 4-aminoquinolines declined. There are already sev- ties did not show significant differences in the risk eral clinical trials that have failed to demonstrate clini- of hospitalisation (HR: 1.5 95% CI: 0.9–2.3; p = 0.10), cal or virological efficacy of these drugs [18,19], while suggesting that comorbidity burden could explain the others concluded that their use could even be harmful differences. In particular, although comorbidities were [20,21]. considered as covariates to adjust the risk models in our analysis, dementia showed a significant asso- The current evidence from clinical trials refers to the ciation with higher risk of infection. The greatest pro- use of 4-aminoquinolines as either a treatment of portion of patients affected by COVID-19 has been in established infection or prophylaxys after exposure. long-term care facilities, with nursing home residents Results from clinical trials showed that after high-risk accounting for ca 25–50% of documented deaths or moderate-risk exposure to SARS-CoV-2, HCQ did not [25,26]. As dementia patients are likely to live in nurs- prevent illness compatible with COVID-19 or confirmed ing homes, this association could also be attributed COVID-19 when used as postexposure prophylaxis to living situation; regardless, we might still consider within 4 days after exposure [22,23]. dementia as a surrogate marker. The observed incidence rate alone is not an appropriate We did not find individual socioeconomic status to measure of the protective efficacy or harmful effects have any impact on risk of infection; it was only associ- of pharmaceutical interventions against SARS-CoV-2, ated with the risk of hospital admission for COVID-19. since despite comorbidity adjustments, colliding bias However, reports in other countries have shown that and residual confounding may persist. Antiviral activ- the most disadvantaged and vulnerable people are at ity of either CQ/HCQ could still have a role in reduc- increased risk for contracting COVID-19, because of ing population transmission of SARS-CoV-2 or reducing possible factors such as poorer baseline health status, the severity of COVID-19 in individuals before they are closer social contacts and lack of access to healthcare exposed. This should be studied through randomised, [27,28]. In our scenario, the universal healthcare sys- prospective comparisons [24]. Therefore, although the tem (RDL 7/2018) [29] in Spain might have played a role observed incidence rate in patients exposed to CQ/ in our results, as access to healthcare would not have HCQ could be the same as in controls, as in our study, been limited regardless of socioeconomic status. it would still be reasonable to accept a strategy that www.eurosurveillance.org 7 Funding statement: No funding was obtained for this study. Limitations of the available data and study approach The corresponding author had full access to all data in the must also be acknowledged. We did not explore con- study and had final responsibility for the decision to submit current medications; some of the treatments used for for publication. autoimmune diseases may also influence both suscep- tibility to infection and severity of disease, and this Data sharing: Data sharing requests will be considered by the management group upon written request to the corre- may have led to residual confounding. We did not have sponding author. De-identified participant data or other pre- information regarding the daily doses of CQ/HCQ per specified data will be available subject to a written proposal patient, and the dose could also influence the results. and a signed data sharing agreement. However, as this study analyses the effect of pre-expo- sure, we consider that chronic administration of higher Members of the Real World Data Working Group: Antoni Sisó-Almirall1, Silvia Cufí2, Marta Aymerich3, Lluís Martínez4, doses than are commonly prescribed would not be Pol Pérez5, Oriol Yuguero6, Marina Laplana6 feasible in general practice because of the expected side effects. As medication data were obtained from 1. Primary Healthcare Transversal Research Group, Institut the pharmacy invoicing database, we could not assure d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), treatment compliance. However, as these are mainly Barcelona, Spain chronic treatments, we inferred compliance by select- 2. Fundació Tic Salut i Social, Barcelona, Spain ing those individuals with chronic dispensation for 6 months before starting follow-up. The risk of SARS- 3. UOC eHealth Center (eHC), Universitat Oberta de Catalunya CoV-2 infection is also influenced by environmental (UOC), Barcelona, Spain characteristics, which have not been controlled. To 4. Agència de Qualitat i Avaluació Sanitàries de Catalunya overcome this, primary care service area was also a (AQuAS). Departament de Salut Generalitat de Catalunya, matching parameter for the control cohort. Regarding Barcelona, Spain hospitalisation, episodes of inpatient and outpatient care carried out in private hospitals were not available 5. Servei Català de la Salut, Barcelona, Spain for this analysis. However, during the COVID-19 epi- 6. Institut de Recerca Biomedica de Lleida, Lleida, Spain demic all private hospitals reported COVID-19 cases to the public healthcare system, so we can be confident that all cases were identified. Finally, around 80% of Conflict of interest the study population were female, probably because current prescriptions for CQ/HCQ are for autoimmune CV, RMVH, IM, AS, JF, EM, RRV and CP declare no competing interests regarding the content of this manuscript. diseases (such as rheumatoid arthritis), which are known to be more common in women. This is a major limitation with respect to generalisation of the results All members of the Real World Data Working Group de- to a male population. clare no competing interests regarding the content of this manuscript. Clinical trials continue to be the gold standard to gen- erate evidence regarding drug efficacy, but they are Authors’ contributions difficult to implement in rapidly evolving, emergency conditions, because of demanding implementation This study was conceived by CVM, RMVH and IM. Design, acquisition of data and statistical analysis of data were per- requirements. However, this analysis of the impact of formed by EM and supervised by RRV and RMVH. IM, EM, long-term 4-aminoquinolines therapy on the incidence RMVH and CVM drafted the manuscript and RRV, ASM, JF of COVID-19 is intended to serve as supportive infor- and CP reviewed the manuscript, contributing substantially mation to guide clinical practice while more robust evi- to the intellectual content. All authors are responsible for dence is generated. the approval of the final manuscript and its submission for publication. Conclusions Patients chronically exposed to 4-aminoquinolines References (CQ/HCQ) did not differ from non-exposed controls 1. World Health Organization (WHO). Novel Coronavirus (2019- with regard to risk of infection by SARS-CoV-2. Although nCoV) situation reports. Geneva: WHO; 2020. 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