A complete backup of https://hcqmeta.com

More Annotations

Favourite Annotations

Text

HCQ FOR COVID-19: REAL-TIME META ANALYSIS OF 255 STUDIES 66% improvement for early treatment, RR 0.34 HCQ for COVID-19: real-time meta analysis of 246 studies. Covid Analysis, Oct 20, 2020 ( Version 111. HCQ FOR COVID-19: REAL-TIME META ANALYSIS OF 243 STUDIES HCQ is effective for COVID-19 when used early: real-time meta analysis of 233 studies. • HCQ is effective for COVID-19. The probability that an ineffective treatment generated results as positive as the 233 studies to date is estimated to be 1 in 8 quadrillion ( p = 0.00000000000000013). ALL COVID-19 HYDROXYCHLOROQUINE (HCQ) STUDY EFFECTS TO DATE The effects reported in all COVID-19 HCQ studies to date, and the probability that results this positive came from an ineffective

treatment.

ALL COVID-19 HYDROXYCHLOROQUINE (HCQ) EARLY TREATMENT The effects reported in all COVID-19 HCQ early treatment studies to date, and the probability that results this positive came from an ineffective treatment. Analysis of all HCQ COVID-19 studies to date. Please send us corrections, updates, or comments. Vaccines and HCQ IS EFFECTIVE FOR COVID-19 WHEN USED EARLY: REAL-TIME 233 HCQ COVID-19 controlled studies. 65% improvement for early treatment, p < 0.0001. ALL COVID-19 HYDROXYCHLOROQUINE (HCQ) STUDY EFFECTS TO DATE All effects reported in HCQ COVID-19 studies to date, and the effects for early treatment studies. Early treatment is more successful. Analysis of all HCQ COVID-19 studies to date. Please send us corrections, updates, or comments. Vaccines and treatments are both extremely valuable and complementary. We do not provide medical

advice.

PERCENTAGE OF STUDIES REPORTING POSITIVE EFFECTS FOR HCQ Percentage of studies reporting positive effects for HCQ in different regions of the world. Studies in North America are more likely to report negative effects. H C Q F O R C OV I D H C Q f o r C OV I D - 19: re a l - t i m e m e t a a n a l y s i s o f 252 s t u d i e s Covid Analysis, Oct 20, 2020 (Version 114, Jun 6, 2021 — added Lagier) @COVIDANALYSIS FREQUENTLY ASKED QUESTIONS All practical, effective, and safe means should be used. Elimination of COVID-19 is a race against viral evolution. No treatment, vaccine, or intervention is 100% available and effective for all current and future variants. Denying the efficacy of any method increases the risk of COVID-19 becoming endemic; and increases mortality, morbidity TWITTER CENSORS @COVIDANALYSIS SCIENTIFIC RESEARCH Twitter censors @CovidAnalysis scientific research. 12/27: Twitter has censored our account @CovidAnalysis. There was no notification, no explanation, no warning, and they have deleted all our contacts and messages. We only posted COVID-19 medical studies and never received

any kind of

treatment.

advice.

any kind of

ALL COVID-19 HYDROXYCHLOROQUINE (HCQ) STUDY EFFECTS TO DATE The effects reported in all COVID-19 HCQ studies to date, and the probability that results this positive came from an ineffective

treatment.

COVID-19 studies: C19 studies: C19: IvermectinIVM

Vitamin DV.D PXPX

FLVFLV

PVP-IPI BUBU BHBH

BLBL CICI

HC QHC Q NZNZ

COCO

More.. COVID-19 studies:

C19 studies: C19:

IvermectinIVM Vitamin

DV.D PXPX FLVFLV

PVP-IPI BUBU

BHBH BLBL CICI

HC QHC Q NZNZ COCO

More..

251 HCQ COVID-19 controlled studies to date 66% improvement for early treatment, RR 0.34 HCQ for COVID-19: real-time meta analysis of 251 studies Covid Analysis , Oct 20, 2020 (Version 113V113, JUN 5, 2021

— ADDED THOMPSON)

@CovidAnalysis

Twitter

is censoring and shadowbanning early treatment research . Tweets may be more visible if you post an image rather than a link.

PDF

Studies

Submit FeedbackFeedback https://hcqmeta.com/ •100% of the 29 early treatment studies report a positive effect (13 statistically significant in isolation). •Random effects meta-analysis with pooled effects using the most serious outcome reported shows 66% improvement for the 29 early treatment studies (RR 0.34 ). Results are similar after exclusion based sensitivity analysis: 67% (RR 0.33 ), and after restriction to 20 peer-reviewed studies: 65% (RR 0.35 ). Restricting to the 6 RCTs shows 46% improvement (RR 0.54 ). Restricting to the 13 mortality results shows 75% lower mortality (RR 0.25 ). •Late treatment is less successful, with only 70% of the 170 studies reporting a positive effect. Very late stage treatment is not effective and may be harmful, especially when using excessive dosages. •The probability that an ineffective treatment generated results as positive as the 251 studies to date is estimated to be 1 in 538 trillion (_p_ = 0.0000000000000019). •87% of Randomized Controlled Trials (RCTs) for early, PrEP, or PEP treatment report positive effects, the probability of this happening for an ineffective treatment is 0.0037. •There is substantial evidence of bias towards publishing negative results. 82% of prospective studies report positive effects, and only 72% of retrospective studies do. Studies from North America are 3.2 times more likely to report negative results than studies from the rest of the world combined, _p_ = 0.0000000113. •Negative meta analyses of HCQ generally choose a subset of trials, focusing on late treatment, especially trials with very late treatment and excessive dosages. •While many treatments have some level of efficacy, they do not replace vaccines and other measures to avoid infection. Only 5% of HCQ studies show zero events in the treatment

arm.

•Elimination of COVID-19 is a race against viral evolution. No treatment, vaccine, or intervention is 100% available and effective for all current and future variants. All practical, effective, and safe means should be used. Not doing so increases the risk of COVID-19 becoming endemic; and increases mortality, morbidity, and collateral

damage.

•All data to reproduce this paper and the sources are in the appendix. See for other meta analyses showing efficacy when HCQ is used early. Show forest plot for:

All studies

Mortality results

With exclusions

RCTs

Total

251 studies

3,994 authors

380,038 patients

Positive effects

187 studies

2,862 authors

266,059 patients

Early treatment

66% improvement

RR 0.34

Late treatment

22% improvement

RR 0.78

Download Image

A 00.250.50.7511.251.51.752+

Gautret

66%0.34

2.4gviral+6/2014/16Improvement, RR Dose (4d)TreatmentControl Huang (RCT)

92%0.08 4.0g (c)no

recov.0/106/12 Esper 64%0.36 2.0ghosp.8/41212/224

Ashraf

68%0.32 1.6gdeath10/772/5

Huang (ES)

59%0.41 2.0g (c)viral time32/3237/37 Guérin 61%0.39 2.4gdeath0/201/34

Chen (RCT)

72%0.28 1.6gviral

time18/1812/12 Derwand

79%0.21

1.6gdeath1/14113/377 Mitj�

(RCT) 16%0.84

2.0ghosp.8/13611/157

Skipper (RCT)

37%0.63

3.2ghosp./death5/2318/234

Hong

65%0.35 n/aviral+42/4248/48

Bernabeu-Wittel

59%0.41

2.0gdeath18983 Yu (ES) 85%0.15 1.6gdeath1/73238/2,604

Ly 56%0.44

2.4gdeath18/11629/110 Ip 55%0.45 n/adeath2/9744/970

Heras

96%0.04 n/adeath8/7016/30

Kirenga

26%0.74 n/arecov.

time29/2927/27 Sulaiman

64%0.36

2.0gdeath7/1,81754/3,724

Guisado-Vasco (ES)

67%0.33

n/adeath2/65139/542 Szente

Fonseca 64%0.36

2.0ghosp.25/17589/542

Cadegiani

81%0.19

1.6gdeath0/1592/137 Simova 94%0.06 2.4ghosp.0/332/5

Omrani (RCT)

12%0.88 2.4ghosp.7/3044/152

Agusti

68%0.32

2.0gprogression2/874/55 Su 85%0.15 1.6gprogression261355

Amaravadi (DB RCT)

60%0.40 3.2gno

recov.3/156/12 Roy

2%0.98 n/arecov. time1415

Mokhtari

70%0.30

2.0gdeath27/7,295287/21,464

Million

83%0.17

2.4gdeath5/8,31511/2,114Early treatment66%0.34 266/20,2531,116/34,09766% improvementAll 29 hydroxychloroquine COVID-19 early treatment studieshcqmeta.com 6/6/21Tau2 = 0.62; I2 = 87.4%; Z = 5.87 (p < 0.0001)Lower

RiskIncreased Risk

Download Image

B 00.250.50.7511.251.51.752+All studiesEarly treatmentmin, Q1, median, Q3, maxLower RiskIncreased Riskhcqmeta.com 6/6/21

Download Image

C 100+ 75 50 25 25 50 75 100 Gautret

viral+, p=0.001

Huang

no recov., p=0.02

Esper

hosp., p=0.02

Ashraf

death, p=0.15

Huang

viral- time, p<0.0001

Guérin

death, p=1.00

Chen

viral- time, p=0.01

Derwand

death, p=0.12

Mitj�

hosp., p=0.64

Skipper

hosp./death, p=0.58

Hong

viral+, p=0.001

Bernabeu-Wittel

death, p=0.03

Yu

death, p=0.02

Ly death,

p=0.02 Ip

death, p=0.43

Heras

death, p=0.004

Kirenga

recov. time, p=0.20

Sulaiman

death, p=0.01

Guisado-Vasco

death, p=0.19

Szente Fonseca

hosp., p=0.0008

Cadegiani

death, p=0.21

Simova

hosp., p=0.01

Omrani

hosp., p=1.00

Agusti

progression, p=0.21

Su

progression, p=0.006

Amaravadi

no recov., p=0.13

Roy

recov. time, p=0.96

Mokhtari

death, p<0.0001

Million

death, p=0.0009

Early treatment% Lower Risk% Increased Riskhcqmeta.com 6/6/21Probability results fromineffective treatmentJun 22 p<0.011 in 100Jul 16 p<0.0011 in 1 thousandAug 21 p<0.00011 in 10 thousandSep 9 p<0.000011 in 100 thousandOct 31 p<0.0000011 in 1 millionDec 9 p<0.00000011 in 10 million

Download Image

D 100+ 75 50 25 25 50 75 100 Xia, viral+,

p=0.17

Chen, progression, p=0.57 Gautret, viral+, p=0.001 Zhong, viral+, p<0.0001 Chen, pneumonia, p=0.04 Huang, no recov., p=0.02 Barbosa, death, p=0.58

Tang,

viral+, p=0.51

Esper, hosp., p=0.02 Magagnoli, death, p=0.74 Izoulet, death, p<0.001 Ashraf, death, p=0.15

Auld,

death, p=1.00

Sánchez..., death, p=0.005 Mallat, viral- time, p=0.02

Huh,

cases, p=0.09

Mitchell, death, p<0.0001 Gendelman, cases, p=0.88 Membrillo..., death, p=0.002 Geleris, int./death, p=0.76 Konig, hosp., p=0.88 Alberici, death, p=0.12 Rosenberg, death, p=0.31 Shabrawishi, viral+, p=0.66 Cassione, cases, p=0.59 Mahévas, death, p=0.75

Yu,

death, p=0.002

Macias, hosp., p=1.00

Kim,

hosp. time, p=0.01

Singh, death, p=0.72 Hraiech, death, p=0.21

Ip,

death, p=0.93

Goldman, death, p=0.46 Huang, viral- time, p<0.0001 Gianfrancesco, hosp., p=0.82 Chatterjee, cases, p<0.001 Kuderer, death, p<0.0001 Guérin, death, p=1.00 Boulware, cases, p=0.35 RECOVERY, death, p=0.15 Bhattacharya, cases, p=0.001

Wang, death, p=0.63

Huang, hosp., p<0.001

Luo,

death, p=0.99

Paccoud, death, p=0.88 Sbidian, death, p=0.74 Faíco-Filho, viral rate, p=0.40 Chen, viral- time, p=0.01 Fontana, death, p=0.53 Bousquet, death, p=0.15 Lagier, death, p=0.05 Gendebien, cases, p=0.93 Ferreira, cases, p<0.0001 Sosa-García, death, p=1.00 Komissarov, viral load, p=0.45 Mikami, death, p<0.0001 Martinez-Lopez, death, p=0.20 Arshad, death, p=0.009 Derwand, death, p=0.12 Zhong, cases, p=0.04

An,

viral+, p=0.92

Rivera-Izquierdo, death,

p=0.75

Chen, viral+, p=0.70 Chen, viral+, p=0.71 Cravedi, death, p=0.17 Lecronier, death, p=0.24 Trullàs, death, p=0.12 Gupta, death, p=0.41

Mitjà,

hosp., p=0.64

Skipper, hosp./death, p=0.58

Hong,

viral+, p=0.001

Lyngbakken, death, p=1.00 McGrail, death, p=0.69 Desbois, cases, p=1.00 Bernaola, death, p<0.0001 Kelly, death, p=0.03 Rivera, death, p=0.90 Cavalcanti, death, p=0.77 Khurana, cases, p=0.02 Mitjà, death, p=0.27 D'Arminio..., death, p=0.12 Bernabeu-Wittel, death, p=0.03 Davido, int./hosp., p=0.04

Yu,

progression, p=0.05

Berenguer, death, p<0.0001 Kamran, progression, p=1.00 Kalligeros, death, p=0.57 Singer, cases, p=0.62 Salvarani, cases, p=0.75 Saleemi, viral- time, p<0.05 Roomi, death, p=0.54 Abd-Elsalam, death, p=1.00 Peters, death, p=0.57 Pinato, death, p<0.0001 Dubernet, ICU, p=0.008 Gonzalez, death, p=0.06

Ly,

death, p=0.02

Pasquini, death, p=0.34 Catteau, death, p<0.0001 Di Castelnuovo, death, p<0.0001

Ip, death, p=0.43

Ferri,

cases, p=0.01

Fried, death, p<0.001 Albani, death, p=0.05 de la Iglesia, hosp., p=1.00 Heras, death, p=0.004 Synolaki, death, p=0.27 Laplana, cases, p=0.24 Rentsch, death, p=0.83 Kirenga, recov. time, p=0.20 Alamdari, death, p=0.03 Heberto, death, p=0.04 Sulaiman, death, p=0.01 Lauriola, death, p<0.001 Ashinyo, hosp. time, p=0.03 Grau-Pujol, cases, p=0.47 Rajasingham, hosp., p=1.00 Gentry, death, p=0.10 Serrano, death, p=0.14 Ulrich, death, p=1.00 Shoaibi, death, p<0.001 Lammers, death/ICU, p=0.02 Abella, cases, p=1.00 Ayerbe, death, p<0.001

Polat,

cases, p=0.03

Almazrou, ventilation, p=0.16 Nachega, death, p=0.17

Ader, death, p=1.00

Soto-Becerra, death, p<0.0001 Aparisi, death, p=0.008 Annie, death, p=0.83 SOLIDARITY, death, p=0.23 Guisado-Vasco, death, p=0.36

Solh, death, p=0.17

Ñamendys-Silva, death, p=0.18 Dubee, death, p=0.21

Lano,

death, p=0.28

Coll, death, p<0.0001

Goenka,

IgG+, p=0.03

Frontera, death, p=0.01

Choi,

viral- time, p<0.0001 Arleo, death, p=0.67 Tehrani, death, p=0.63 Szente Fonseca, hosp., p=0.0008 López, progression, p=0.02 Behera, cases, p=0.29 Cadegiani, death, p=0.21 Salazar, death, p=0.28 Rodriguez-Nava, death, p=0.77 Maldonado, death, p=0.17 Dhibar, cases, p=0.03 Mathai, cases, p<0.0001 Núñez-Gil, death, p=0.005

Self, death, p=0.84

Rodriguez, death, p=0.23 Águila-Gordo, death, p=0.10 Simova, cases, p=0.01 Simova, hosp., p=0.01 Sheshah, death, p<0.001 Boari, death, p<0.001 Budhiraja, death, p<0.0001 Falcone, death, p=0.20 Omrani, hosp., p=1.00 Revollo, cases, p=0.52

Qin,

death, p=0.61

van Halem, death, p=0.05 Rodriguez-Gonzalez, death,

p=0.26

Lambermont, death, p=0.46 Abdulrahman, death, p=1.00 Capsoni, ventilation, p=0.30

Peng,

progression, p=0.63

Modrák, death, p=0.04 Ozturk, death, p=0.14 Barnabas, hosp., p=1.00 Guglielmetti, death, p=0.22 Agusti, progression, p=0.21 Johnston, hosp., p=0.73 Alqassieh, hosp. time, p=0.11

Jung, death, p=1.00

Bielza,

death, p=0.09

Tan, hosp. time, p=0.04

Naseem,

death, p=0.34

Orioli, death, p=1.00 Gönenli, progression, p=0.77 Signes-Costa, death, p=0.0005 Matangila, death, p=0.21

Huh,

progression, p=0.11

Cangiano, death, p=0.03 Taccone, death, p=0.0004

Su,

progression, p=0.006 Chari, death, p=0.17 Cordtz, hosp., p=0.67

Güner, ICU, p=0.16

Vernaz, death, p=0.71 Texeira, death, p=0.10 Psevdos, death, p=0.52 Sands, death, p=0.01

Lotfy,

death, p=0.76

Sarfaraz, death, p=0.07 Yegerov, death, p=1.00 Rangel, death, p=0.77

Li,

viral- time, p=0.06

Li, no disch., p=0.08 Trefond, death, p=0.80

Roig,

death, p=0.76

Ubaldo, death, p=0.64 Ouedraogo, death, p=0.38 Hernandez-Cardenas, death,

p=0.66

Fitzgerald, cases, p=0.52 Purwati, viral+, p<0.0001 Thompson, death, p=0.84 Lora-Tamayo, death, p<0.0001

Awad, death, p=0.60

Lamback, death, p=0.83

Bae,

cases, p=0.17

Gonzalez, death, p=0.27 Amaravadi, no recov., p=0.13

Pham, death, p=0.77

Salvador, death, p=0.007 Martin-Vicente, death, p=0.41 Vivanco-Hidalgo, hosp., p=0.10 Roy, recov. time, p=0.96 Stewart, death, p=0.95 Stewart, death, p=0.0003 Stewart, death, p=0.65 Stewart, death, p=0.09 Stewart, death, p=0.26 Stewart, ventilation, p=0.09 Stewart, death, p=0.27 Barry, death, p=0.60

Dev,

cases, p=0.003

Alghamdi, death, p=0.88 Mokhtari, death, p<0.0001 Seet, severe case, p=0.14 Alegiani, death, p=0.64 Alzahrani, death, p=1.00

Reis, death, p=1.00

Mohandas, death, p=0.007 Réa-Neto, death, p=0.20 Kokturk, death, p=0.97 Aghajani, death, p=0.09 Bosaeed, death, p=0.91

De

Rosa, death, p=0.003 Sammartino, death, p=0.002 Rojas-Serrano, symp. case,

p=0.12

Syed, symp. case, p=0.41 Million, death, p=0.0009 Smith, death, p<0.0001 Kamstrup, hosp., p=0.25 Korkmaz, death, p=0.19 Byakika-Kibwika, recov. time, p=0.91 All studies% Lower Risk% Increased Riskhcqmeta.com 6/6/21Probability results fromineffective treatmentMay 19 p<0.011 in 100Jun 30 p<0.00011 in 10 thousandAug 18 p<0.000011 in 100 thousandSep 9 p<0.0000011 in 1 millionSep 21 p<0.00000011 in 10 millionOct 211 in 1 billionNov 201 in

1 trillion

Figure 1. A. Random effects meta-analysis of all early treatment studies. Simplified dosages are shown for comparison, these are the total dose in the first four days of treatment. Chloroquine is indicated with (c). For full details see the appendix. B. Scatter plot of the effects reported in early treatment studies and in all studies. Early treatment is more effective. C AND D. Chronological history of all reported effects, with the probability that the observed frequency of positive effects occurred due to random chance from an ineffective

treatment.

Introduction

We analyze all significant studies concerning the use of HCQ (or CQ) for COVID-19. Search methods, inclusion criteria, effect extraction criteria (more serious outcomes have priority), all individual study data, PRISMA answers, and statistical methods are detailed in Appendix 1. We present random-effects meta-analysis results for all studies, for studies within each treatment stage, for mortality results only, after exclusion of studies with critical bias, and for Randomized Controlled Trials (RCTs) only. Typical meta analyses involve subjective selection criteria and bias evaluation, requiring an understanding of the criteria and the accuracy of the evaluations. However, the volume of studies presents an opportunity for an additional simple and transparent analysis aimed at detecting

efficacy.

If treatment was not effective, the observed effects would be randomly distributed (or more likely to be negative if treatment is harmful). We can compute the probability that the observed percentage of positive results (or higher) could occur due to chance with an ineffective treatment (the probability of >= _k_ heads in _n_ coin tosses, or the one-sided sign test / binomial test). Analysis of publication bias is important and adjustments may be needed if there is a bias toward publishing positive results. For HCQ, we find evidence of a bias toward publishing negative results. Figure 2 shows stages of possible treatment for COVID-19. PRE-EXPOSURE PROPHYLAXIS (PREP) refers to regularly taking medication before being infected, in order to prevent or minimize infection. In POST-EXPOSURE PROPHYLAXIS (PEP), medication is taken after exposure but before symptoms appear. EARLY TREATMENT refers to treatment immediately or soon after symptoms appear, while LATE TREATMENT refers to more

delayed treatment.

Download Image

Figure 2. Treatment stages.

Results

Figure 3, Figure 4, and Table 1 show results by treatment stage, and Figure 5 shows a forest plot for a random effects meta-analysis of all studies. Figure 6 shows a forest plot restricted to mortality results

only.

Early treatment. 100% of early treatment studies report a positive effect, with an estimated reduction of 66% in the effect measured (death, hospitalization, etc.) from the random effects meta-analysis,

RR 0.34 .

Late treatment. Late treatment studies are mixed, with 70% showing positive effects, and an estimated reduction of 22% in the random effects meta-analysis. Negative studies mostly fall into the following categories: they show evidence of significant unadjusted confounding, including confounding by indication; usage is extremely late; or they use an excessively high dosage. Pre-Exposure Prophylaxis. 74% of PrEP studies show positive effects, with an estimated reduction of 28% in the random effects meta-analysis. Negative studies are all studies of systemic autoimmune disease patients which either do not adjust for the different baseline risk of these patients at all, or do not adjust for the highly variable risk within these patients. Post-Exposure Prophylaxis. 86% of PEP studies report positive effects, with an estimated reduction of 34% in the random effects

meta-analysis.

Treatment time

Number of studies reporting positive results Total number of studies Percentage of studies reporting positive results Probability of an equal or greater percentage of positive results from an ineffective treatment Random effects meta-analysis results

Early treatment

29 100%

0.0000000019 P = 1.9E-09

1 in 537 million

66% improvement

RR 0.34

p < 0.0001

Late treatment

120

171 70.2%

0.000000068 P = 6.8E-08

1 in 15 million

22% improvement

RR 0.78

p < 0.0001

Pre‑Exposure Prophylaxis

35

47 74.5%

0.00054 P = 0.00054

1 in 2 thousand

28% improvement

RR 0.72

p = 0.001

Post‑Exposure Prophylaxis

6

7 85.7%

0.062 p = 0.062

1 in 16

34% improvement

RR 0.66

p = 0.00043

All studies

187

251 74.5%

0.0000000000000019 P = 1.9E-15

1 in 538 trillion

27% improvement

RR 0.73

p < 0.0001

Table 1. Results by treatment stage. 3 studies report results for a subset with early treatment, these are not included in the overall

results.

Download Image

00.250.50.7511.251.51.752+All studiesPost-Exposure ProphylaxisPre-Exposure ProphylaxisLate treatmentEarly treatmentmin, Q1, median, Q3, maxLower RiskIncreased Riskhcqmeta.com 6/6/21 Figure 3. Results by treatment stage.

Download Image

100+ 75 50 25 25 50 75 100 Gautret

viral+, p=0.001

Huang

no recov., p=0.02

Esper

hosp., p=0.02

Ashraf

death, p=0.15

Huang

viral- time, p<0.0001

Guérin

death, p=1.00

Chen

viral- time, p=0.01

Derwand

death, p=0.12

Mitj�

hosp., p=0.64

Skipper

hosp./death, p=0.58

Hong

viral+, p=0.001

Bernabeu-Wittel

death, p=0.03

Yu

death, p=0.02

Ly death,

p=0.02 Ip

death, p=0.43

Heras

death, p=0.004

Kirenga

recov. time, p=0.20

Sulaiman

death, p=0.01

Guisado-Vasco

death, p=0.19

Szente Fonseca

hosp., p=0.0008

Cadegiani

death, p=0.21

Simova

hosp., p=0.01

Omrani

hosp., p=1.00

Agusti

progression, p=0.21

Su

progression, p=0.006

Amaravadi

no recov., p=0.13

Roy

recov. time, p=0.96

Mokhtari

death, p<0.0001

Million

death, p=0.0009

Download Image

100+ 75 50 25 25 50 75 100 Xia, viral+,

p=0.17

Chen, progression, p=0.57 Zhong, viral+, p<0.0001 Chen, pneumonia, p=0.04 Barbosa, death, p=0.58

Tang,

viral+, p=0.51

Magagnoli, death, p=0.74 Izoulet, death, p<0.001

Auld,

death, p=1.00

Sánchez..., death, p=0.005 Mallat, viral- time, p=0.02 Membrillo..., death, p=0.002 Geleris, int./death, p=0.76 Alberici, death, p=0.12 Rosenberg, death, p=0.31 Shabrawishi, viral+, p=0.66 Mahévas, death, p=0.75

Yu,

death, p=0.002

Kim, hosp. time, p=0.01

Singh,

death, p=0.72

Hraiech, death, p=0.21

Ip,

death, p=0.93

Goldman, death, p=0.46 Huang, viral- time, p<0.0001 Kuderer, death, p<0.0001 RECOVERY, death, p=0.15

Wang, death, p=0.63

Luo,

death, p=0.99

Paccoud, death, p=0.88 Sbidian, death, p=0.74 Faíco-Filho, viral rate, p=0.40 Fontana, death, p=0.53 Bousquet, death, p=0.15 Lagier, death, p=0.05 Sosa-García, death, p=1.00 Komissarov, viral load, p=0.45 Mikami, death, p<0.0001 Martinez-Lopez, death, p=0.20 Arshad, death, p=0.009

An,

viral+, p=0.92

Rivera-Izquierdo, death,

p=0.75

Chen, viral+, p=0.70 Chen, viral+, p=0.71 Cravedi, death, p=0.17 Lecronier, death, p=0.24 Trullàs, death, p=0.12 Gupta, death, p=0.41 Lyngbakken, death, p=1.00 McGrail, death, p=0.69 Bernaola, death, p<0.0001 Kelly, death, p=0.03 Rivera, death, p=0.90 Cavalcanti, death, p=0.77 D'Arminio..., death, p=0.12 Davido, int./hosp., p=0.04

Yu,

progression, p=0.05

Berenguer, death, p<0.0001 Kamran, progression, p=1.00 Kalligeros, death, p=0.57 Saleemi, viral- time, p<0.05 Roomi, death, p=0.54 Abd-Elsalam, death, p=1.00 Peters, death, p=0.57 Pinato, death, p<0.0001 Dubernet, ICU, p=0.008 Gonzalez, death, p=0.06 Pasquini, death, p=0.34 Catteau, death, p<0.0001 Di Castelnuovo, death, p<0.0001 Fried, death, p<0.001 Albani, death, p=0.05 Synolaki, death, p=0.27 Alamdari, death, p=0.03 Heberto, death, p=0.04 Lauriola, death, p<0.001 Ashinyo, hosp. time, p=0.03 Serrano, death, p=0.14 Ulrich, death, p=1.00 Shoaibi, death, p<0.001 Lammers, death/ICU, p=0.02 Ayerbe, death, p<0.001 Almazrou, ventilation, p=0.16 Nachega, death, p=0.17

Ader, death, p=1.00

Soto-Becerra, death, p<0.0001 Aparisi, death, p=0.008 Annie, death, p=0.83 SOLIDARITY, death, p=0.23 Guisado-Vasco, death, p=0.36

Solh, death, p=0.17

Ñamendys-Silva, death, p=0.18 Dubee, death, p=0.21

Lano,

death, p=0.28

Coll, death, p<0.0001 Frontera, death, p=0.01

Choi,

viral- time, p<0.0001 Tehrani, death, p=0.63 López, progression, p=0.02 Salazar, death, p=0.28 Rodriguez-Nava, death, p=0.77 Maldonado, death, p=0.17 Núñez-Gil, death, p=0.005

Self, death, p=0.84

Rodriguez, death, p=0.23 Águila-Gordo, death, p=0.10 Sheshah, death, p<0.001 Boari, death, p<0.001 Budhiraja, death, p<0.0001 Falcone, death, p=0.20

Qin,

death, p=0.61

van Halem, death, p=0.05 Rodriguez-Gonzalez, death,

p=0.26

Lambermont, death, p=0.46 Abdulrahman, death, p=1.00 Capsoni, ventilation, p=0.30

Peng,

progression, p=0.63

Modrák, death, p=0.04 Ozturk, death, p=0.14 Guglielmetti, death, p=0.22 Johnston, hosp., p=0.73 Alqassieh, hosp. time, p=0.11 Bielza, death, p=0.09

Tan,

hosp. time, p=0.04

Naseem, death, p=0.34 Orioli, death, p=1.00 Signes-Costa, death, p=0.0005 Matangila, death, p=0.21 Cangiano, death, p=0.03 Taccone, death, p=0.0004 Chari, death, p=0.17

Güner,

ICU, p=0.16

Vernaz, death, p=0.71 Texeira, death, p=0.10 Psevdos, death, p=0.52 Sands, death, p=0.01

Lotfy,

death, p=0.76

Sarfaraz, death, p=0.07 Yegerov, death, p=1.00

Li,

viral- time, p=0.06

Li, no disch., p=0.08

Roig,

death, p=0.76

Ubaldo, death, p=0.64 Ouedraogo, death, p=0.38 Hernandez-Cardenas, death,

p=0.66

Purwati, viral+, p<0.0001 Thompson, death, p=0.84 Lora-Tamayo, death, p<0.0001

Awad, death, p=0.60

Lamback, death, p=0.83 Gonzalez, death, p=0.27 Salvador, death, p=0.007 Martin-Vicente, death, p=0.41 Stewart, death, p=0.95 Stewart, death, p=0.0003 Stewart, death, p=0.65 Stewart, death, p=0.09 Stewart, death, p=0.26 Stewart, ventilation, p=0.09 Stewart, death, p=0.27 Barry, death, p=0.60 Alghamdi, death, p=0.88

Reis,

death, p=1.00

Mohandas, death, p=0.007 Réa-Neto, death, p=0.20 Kokturk, death, p=0.97 Aghajani, death, p=0.09 Bosaeed, death, p=0.91

De

Rosa, death, p=0.003 Sammartino, death, p=0.002 Smith, death, p<0.0001 Byakika-Kibwika, recov. time, p=0.91 Late treatment% Lower Risk% Increased Riskhcqmeta.com 6/6/21Probability results fromineffective treatmentMay 24 p<0.051 in 20Aug 21 p<0.011 in 100Sep 24 p<0.0011 in 1 thousandOct 8 p<0.00011 in 10 thousandNov 17 p<0.000011 in 100 thousandNov 28 p<0.0000011 in 1 millionDec 9 p<0.00000011 in 10 million

Download Image

100+ 75 50 25 25 50 75 100 Huh cases,

p=0.09 Mitchell

death, p<0.0001

Gendelman

cases, p=0.88

Konig

hosp., p=0.88

Cassione

cases, p=0.59

Macias

hosp., p=1.00

Gianfrancesco

hosp., p=0.82

Chatterjee

cases, p<0.001

Bhattacharya

cases, p=0.001

Huang

hosp., p<0.001

Gendebien

cases, p=0.93

Ferreira

cases, p<0.0001

Zhong

cases, p=0.04

Desbois

cases, p=1.00

Khurana

cases, p=0.02

Singer

cases, p=0.62

Salvarani

cases, p=0.75

Ferri

cases, p=0.01

de la Iglesia

hosp., p=1.00

Laplana

cases, p=0.24

Rentsch

death, p=0.83

Grau-Pujol

cases, p=0.47

Rajasingham

hosp., p=1.00

Gentry

death, p=0.10

Abella

cases, p=1.00

Goenka

IgG+, p=0.03

Arleo

death, p=0.67

Behera

cases, p=0.29

Mathai

cases, p<0.0001

Revollo

cases, p=0.52

Jung

death, p=1.00

Gönenli

progression, p=0.77

Huh

progression, p=0.11

Cordtz

hosp., p=0.67

Rangel

death, p=0.77

Trefond

death, p=0.80

Fitzgerald

cases, p=0.52

Bae

cases, p=0.17

Pham death,

p=0.77 Vivanco-Hidalgo

hosp., p=0.10

Dev

cases, p=0.003

Alegiani

death, p=0.64

Alzahrani

death, p=1.00

Rojas-Serrano

symp. case, p=0.12

Syed

symp. case, p=0.41

Kamstrup

hosp., p=0.25

Korkmaz

death, p=0.19

Pre-Exposure Prophylaxis% Lower Risk% Increased Riskhcqmeta.com 6/6/21Probability results fromineffective treatmentJun 25 p<0.051 in 20Sep 30 p<0.011 in 100Nov 21 p<0.0011 in 1

thousand

Download Image

100+ 75 50 25 25 50 75 100 Boulware, cases, p=0.35 Mitjà, death, p=0.27 Polat, cases, p=0.03 Dhibar, cases, p=0.03 Simova, cases, p=0.01 Barnabas, hosp., p=1.00 Seet, severe case, p=0.14 Post-Exposure Prophylaxis% Lower Risk% Increased Riskhcqmeta.com 6/6/21 Figure 4. Chronological history of results by treatment stage, with the probability that the observed frequency of positive results occurred due to random chance from an ineffective treatment.

Download Image

00.250.50.7511.251.51.752+ Gautret

66%0.34

viral+6/2014/16Improvement, RR TreatmentControl

Huang (RCT)

92%0.08 no

recov.0/106/12 Esper 64%0.36 hosp.8/41212/224

Ashraf

68%0.32 death10/772/5

Huang (ES)

59%0.41 viral

time32/3237/37 Guérin 61%0.39 death0/201/34

Chen (RCT)

72%0.28 viral time18/1812/12

Derwand

79%0.21 death1/14113/377

Mitjà (RCT)

16%0.84 hosp.8/13611/157

Skipper (RCT)

37%0.63

hosp./death5/2318/234 Hong 65%0.35 viral+42/4248/48

Bernabeu-Wittel

59%0.41 death18983

Yu (ES)

85%0.15 death1/73238/2,604

Ly 56%0.44

death18/11629/110 Ip 55%0.45 death2/9744/970

Heras

96%0.04 death8/7016/30

Kirenga

26%0.74 recov.

time29/2927/27 Sulaiman

64%0.36

death7/1,81754/3,724

Guisado-Vasco (ES)

67%0.33

death2/65139/542 Szente

Fonseca 64%0.36

hosp.25/17589/542

Cadegiani

81%0.19 death0/1592/137

Simova

94%0.06 hosp.0/332/5

Omrani (RCT)

12%0.88 hosp.7/3044/152

Agusti

68%0.32 progression2/874/55

Su 85%0.15

progression261355

Amaravadi (DB RCT)

60%0.40 no

recov.3/156/12 Roy

2%0.98 recov. time1415

Mokhtari

70%0.30

death27/7,295287/21,464

Million

83%0.17

death5/8,31511/2,114Tau2 = 0.62; I2 = 87.4%Early treatment66%0.34 266/20,2531,116/34,09766%

improvement Xia

38%0.62

viral+5/1012/15Improvement, RR TreatmentControl

Chen (RCT)

29%0.71

progression5/157/15 Zhong 80%0.20 viral+5/11517/82

Chen (RCT)

57%0.43 pneumonia6/3114/31

Barbosa

-147%2.47 death2/171/21

Tang (RCT)

21%0.79 viral+11/7514/75

Magagnoli

11%0.89

death39/14818/163 Auld -3%1.03 death33/11429/103

Sánchez-Álvarez

46%0.54 death32253

Mallat

-203%3.03 viral time2311

Membrillo de Nov..

55%0.45 death27/12321/43

Geleris

-4%1.04

int./death262/81184/565

Alberici

43%0.57 death17/729/22

Rosenberg

-35%1.35

death189/73528/221

Shabrawishi

15%0.85

viral+12/4515/48 Mahévas -20%1.20 death9/848/89

Yu 60%0.40

death9/48238/502 Kim 51%0.49 hosp. time22/2240/40

Singh

5%0.95 death104/910109/910

Hraiech

65%0.35 death2/175/15

Ip 1%0.99

death432/1,914115/598

Goldman

22%0.78 death10/10934/288

Huang

67%0.33 viral

time197/197176/176 Kuderer

-134%2.34

death45/181121/928

RECOVERY (RCT)

-9%1.09

death421/1,561790/3,155

Wang

6%0.94 death1,8665,726

Luo -2%1.02

death11/354/13 Paccoud 11%0.89 death21/3826/46

Sbidian

-5%1.05

death111/623830/3,792

Faíco-Filho

81%0.19 viral rate3432

Fontana

50%0.50 death4/122/3

Bousquet

43%0.57 death5/2723/81

Lagier

59%0.41 death35/3,11958/618

Sosa-García

-11%1.11 death7/383/18

Komissarov

-25%1.25 viral

load26/2610/10 Mikami

47%0.53

death575/2,077231/743

Martinez-Lopez

33%0.67

death47/1489/19 Arshad

51%0.49

death162/1,202108/409 An 3%0.97 viral+31/31195/195

Rivera-Izquierdo

19%0.81 death21523

Chen

-29%1.29 viral+16/284/9

Chen (RCT)

24%0.76 viral+4/213/12

Cravedi

-53%1.53 death36/10110/43

Lecronier

42%0.58 death9/389/22

Trullàs

36%0.64 death20/6616/34

Gupta

-6%1.06

death631/1,761153/454

Lyngbakken (RCT)

4%0.96 death1/271/26

McGrail

-70%1.70 death4/333/42

Bernaola

17%0.83

death236/1,49828/147 Kelly -143%2.43 death23/826/52

Rivera

-2%1.02 death44/17959/327

Cavalcanti (RCT)

16%0.84 death8/3315/173

D'Arminio Monforte

34%0.66

death53/19747/92 Davido

55%0.45

int./hosp.12/8013/40 Yu

83%0.17

progression1/23132/1,291

Berenguer

62%0.38

death681/2,618939/1,377

Kamran

5%0.95

progression11/3495/151

Kalligeros

-67%1.67 death3672

Saleemi

-21%1.21 viral

time65/6520/20 Roomi -38%1.38 death13/1446/32

Abd-Elsalam (RCT)

-20%1.20 death6/975/97

Peters

-9%1.09

death419/1,59653/353 Pinato 59%0.41 death30/182181/446

Dubernet

88%0.12 ICU1/179/19

Gonzalez

27%0.73

death1,246/8,476341/1,168

Pasquini

16%0.84 death23/3315/18

Catteau

32%0.68

death804/4,542957/3,533

Di Castelnuovo

30%0.70

death386/2,63490/817 Fried

-27%1.27

death1,048/4,2321,466/7,489

Albani

18%0.82 death60/211172/605

Synolaki

24%0.76 death21/9860/214

Alamdari

55%0.45 death42732

Heberto

54%0.46 death139115

Lauriola

74%0.27 death102/29735/63

Ashinyo

33%0.67 hosp.

time61/6161/61 Serrano 43%0.57 death6/146/8

Ulrich (RCT)

-6%1.06 death7/676/61

Shoaibi

15%0.85

death686/5,0473,923/24,404

Lammers

32%0.68

death/ICU30/189101/498

Ayerbe

52%0.48

death237/1,85749/162

Almazrou

65%0.35

ventilation3/956/66

Nachega

28%0.72 death69/63028/96

Ader (RCT)

6%0.94 death11/14512/148

Soto-Becerra

18%0.82

death346/6921,606/2,630

Aparisi

63%0.37 death122/60527/49

Annie

4%0.96 death48/36750/367

SOLIDARITY (RCT)

-19%1.19

death104/94784/906

Guisado-Vasco

20%0.80

death127/55814/49 Solh -18%1.18 death131/265134/378

Ñamendys-Silva

32%0.68

death24/5442/64 Dubee (RCT) 46%0.54 death6/12411/123

Lano

33%0.67 death5666

Coll

46%0.54 death55/307108/328

Frontera

37%0.63

death121/1,006424/2,467 Choi

-22%1.22 viral

time701/701701/701 Tehrani 13%0.87 death16/6554/190

López

64%0.36

progression5/3614/36

Salazar

-37%1.37 death12/9280/811

Rodriguez-Nava

-6%1.06

death22/6579/248

Maldonado

91%0.09 death1/111/1

Núñez-Gil

8%0.92

death200/686100/268 Self

(RCT) -6%1.06

death25/24125/236

Rodriguez

59%0.41 death8/392/4

Águila-Gordo

67%0.33

death151/34647/70 Sheshah

80%0.20 death26733

Boari

55%0.45 death41/20225/56

Budhiraja

65%0.35

death69/83434/142 Falcone 65%0.35 death40/23830/77

Qin 34%0.66

death3/4375/706 van Halem 32%0.68 death34/16447/155

Rodriguez-Gonzalez

23%0.77

death251/1,14817/60

Lambermont

32%0.68

death97/22514/22

Abdulrahman

17%0.83

death5/2236/223 Capsoni

40%0.60

ventilation12/406/12 Peng

11%0.89

progression29/453256/3,567

Modrák

59%0.41 death108105

Ozturk

44%0.56 death165/1,1276/23

Guglielmetti

35%0.65 death18137

Johnston (RCT)

30%0.70 hosp.5/1484/83

Alqassieh

18%0.82 hosp. time6368

Bielza

21%0.79 death33/91249/539

Tan

35%0.65 hosp. time8277

Naseem

33%0.67 death771,137

Orioli

13%0.87 death8/553/18

Signes-Costa

47%0.53 death4,854993

Matangila

55%0.45 death25/1478/13

Cangiano

73%0.27 death5/3337/65

Taccone

25%0.75

death449/1,308183/439 Chari 33%0.67 death8/29195/473

Güner

77%0.23 ICU604100

Vernaz

15%0.85 death12/9316/105

Texeira

-79%1.79 death17/6514/96

Psevdos

-63%1.63 death17/523/15

Sands

-70%1.70 death101/97356/696

Lotfy

-25%1.25 death6/995/103

Sarfaraz

-45%1.45 death40/9427/92

Yegerov

95%0.05 death0/2320/1,049

Li -40%1.40

viral time1819 Li

50%0.50 no disch.1414

Roig

16%0.84 death33/677/12

Ubaldo

18%0.82 death17/255/6

Ouedraogo

33%0.67 death39759

Hernandez-C.. (RCT)

12%0.88

death106108 Purwati (DB

RCT) 66%0.34

viral+38/121111/119

Thompson (DB RCT)

-6%1.06 death25/24125/236

Lora-Tamayo

50%0.50 death7,1921,361

Awad

-19%1.19 death56/18837/148

Lamback

9%0.91 death11/10111/92

Gonzalez (DB RCT)

63%0.37 death2/336/37

Salvador

33%0.67 death28/12158/124

Martin-Vicente

59%0.41

death37/911/1 Stewart

1%0.99

death66/578188/1,243

Stewart

-130%2.30

death32/10833/256 Stewart

-9%1.09

death212/1,157203/1,101

Stewart

-90%1.90

death46/20847/1,334

Stewart

-16%1.16

death428/1,711123/688

Stewart

-29%1.29

ventilation48/30595/1,302

Stewart

-18%1.18

death90/429141/737 Barry 99%0.01 death0/691/599

Alghamdi

-7%1.07 death44/56815/207

Reis (DB RCT)

66%0.34 death0/2141/227

Mohandas

-81%1.81

death27/384115/2,961

Réa-Neto (RCT)

-57%1.57 death16/5310/52

Kokturk

-4%1.04 death62/1,3825/118

Aghajani

19%0.81 death553438

Bosaeed (RCT)

4%0.96 death14/12515/129

De Rosa

35%0.65 death118/73180/280

Sammartino

-240%3.40 death137191

Smith

27%0.73 death19/37182/218

Byakika-Ki.. (RCT)

0%1.00 recov.

time3629Tau2 = 0.14; I2 = 89.3%Late treatment22%0.78 15,189/94,93018,883/100,80322% improvement

Huh -48%1.48

casescase controlImprovement, RR TreatmentControl

Gendelman

8%0.92

cases3/361,314/14,484 Konig 3%0.97 hosp.16/2929/51

Cassione

-50%1.50 cases10/1272/38

Macias

26%0.74 hosp.1/2902/432

Gianfrancesco

3%0.97

hosp.58/130219/470

Chatterjee

67%0.33

cases12/68206/387

Bhattacharya

81%0.19

cases4/5420/52 Huang

80%0.20

hosp.8/81,247/1,247

Gendebien

4%0.96 cases12/1526/73

Ferreira

47%0.53

casespopulation-based cohort

Zhong

91%0.09 cases7/1620/27

Desbois

17%0.83 cases3/2723/172

Khurana

51%0.49 cases6/2288/159

Singer

-9%1.09

cases55/10,700104/22,058

Salvarani

6%0.94

casespopulation-based cohort

Ferri

63%0.37 cases9/99416/647

de la Iglesia

-50%1.50

hosp.3/6872/688 Laplana -56%1.56 cases17/31911/319

Rentsch

-3%1.03

deathpopulation-based cohort

Grau-Pujol (RCT)

68%0.32 cases0/1421/127

Rajasingham (RCT)

50%0.50

hosp.1/9891/494 Gentry

91%0.09

death0/10,7037/21,406

Abella (RCT)

5%0.95 cases4/644/61

Goenka

87%0.13 IgG+1/77115/885

Arleo

50%0.50 death1/205/50

Behera

28%0.72 cases7/19179/353

Mathai

90%0.10 cases10/49122/113

Revollo

23%0.77 cases16/6965/418

Jung

59%0.41 death0/6491/1,417

Gönenli

30%0.70

progression3/14812/416 Huh

-251%3.51

progression5/8873/2,797

Cordtz

24%0.76

hosp.population-based cohort

Rangel

25%0.75 death4/5011/103

Trefond

-17%1.17 death4/6812/183

Fitzgerald

9%0.91

cases65/1,072200/3,594 Bae 30%0.70 cases16/74391/2,698

Pham

20%0.80 death2/145/28

Vivanco-Hidalgo

-46%1.46

hosp.40/6,74650/13,492 Dev

26%0.74 cases260499

Alegiani

-8%1.08 deathcase control

Alzahrani

59%0.41 death0/141/33

Rojas-Se.. (DB RCT)

82%0.18 symp.

case1/626/65 Syed (RCT) -60%1.60 symp. case10/486/46

Kamstrup

-44%1.44

hosp.population-based cohort

Korkmaz

82%0.18

death0/3852/299Tau2 = 0.23; I2 = 78.0%PrEP28%0.72 414/36,5004,978/90,88128% improvement

Boulware (RCT)

17%0.83

cases49/41458/407Improvement, RR TreatmentControl

Mitjà (RCT)

52%0.48

death4/1,1969/1,301 Polat 57%0.43 cases12/13814/70

Dhibar

41%0.59 cases14/13236/185

Simova

93%0.07 cases0/1563/48

Barnabas (RCT)

-4%1.04 hosp.1/4071/422

Seet (CLUS. RCT)

35%0.65 severe

case29/43264/619Tau2 = 0.00; I2 = 0.0%PEP34%0.66 109/2,875185/3,05234% improvementAll studies27%0.73 15,978/154,55825,162/228,83327% improvementAll hydroxychloroquine COVID-19 treatment studieshcqmeta.com 6/6/21Tau2 = 0.12; I2 = 88.0%; Z = 10.15 (p < 0.0001)Lower

RiskIncreased Risk

Figure 5. Random effects meta-analysis. (ES) indicates the early treatment subset of a study (these are not included in the overall

results).

Download Image 00.250.50.7511.251.51.752+

Ashraf

68%0.32

10/772/5Improvement, RR TreatmentControl

Guérin

61%0.39 0/201/34

Derwand

79%0.21 1/14113/377

Bernabeu-Wittel

59%0.41 18983

Yu (ES)

85%0.15 1/73238/2,604

Ly 56%0.44

18/11629/110 Ip

55%0.45 2/9744/970

Heras

96%0.04 8/7016/30

Sulaiman

64%0.36 7/1,81754/3,724

Guisado-Vasco (ES)

67%0.33 2/65139/542

Cadegiani

81%0.19 0/1592/137

Mokhtari

70%0.30

27/7,295287/21,464

Million

83%0.17

5/8,31511/2,114Tau2 = 0.33; I2 = 60.7%Early treatment75%0.25 81/18,434836/32,19475% improvement

Barbosa

-147%2.47

2/171/21Improvement, RR TreatmentControl

Magagnoli

11%0.89 39/14818/163

Auld

-3%1.03 33/11429/103

Sánchez-Álvarez

46%0.54 32253

Membrillo de Nov..

55%0.45 27/12321/43

Alberici

43%0.57 17/729/22

Rosenberg

-35%1.35 189/73528/221

Mahévas

-20%1.20 9/848/89

Yu 60%0.40

9/48238/502 Singh

5%0.95 104/910109/910

Hraiech

65%0.35 2/175/15

Ip 1%0.99

432/1,914115/598 Goldman 22%0.78 10/10934/288

Kuderer

-134%2.34 45/181121/928

RECOVERY (RCT)

-9%1.09

421/1,561790/3,155 Wang

6%0.94 1,8665,726

Luo -2%1.02

11/354/13 Paccoud

11%0.89 21/3826/46

Sbidian

-5%1.05 111/623830/3,792

Fontana

50%0.50 4/122/3

Bousquet

43%0.57 5/2723/81

Lagier

59%0.41 35/3,11958/618

Sosa-García

-11%1.11 7/383/18

Mikami

47%0.53 575/2,077231/743

Martinez-Lopez

33%0.67 47/1489/19

Arshad

51%0.49 162/1,202108/409

Rivera-Izquierdo

19%0.81 21523

Cravedi

-53%1.53 36/10110/43

Lecronier

42%0.58 9/389/22

Trullàs

36%0.64 20/6616/34

Gupta

-6%1.06 631/1,761153/454

Lyngbakken (RCT)

4%0.96 1/271/26

McGrail

-70%1.70 4/333/42

Bernaola

17%0.83 236/1,49828/147

Kelly

-143%2.43 23/826/52

Rivera

-2%1.02 44/17959/327

Cavalcanti (RCT)

16%0.84 8/3315/173

D'Arminio Monforte

34%0.66

53/19747/92 Berenguer

62%0.38

681/2,618939/1,377

Kalligeros

-67%1.67 3672

Roomi

-38%1.38 13/1446/32

Abd-Elsalam (RCT)

-20%1.20 6/975/97

Peters

-9%1.09 419/1,59653/353

Pinato

59%0.41 30/182181/446

Gonzalez

27%0.73

1,246/8,476341/1,168

Pasquini

16%0.84 23/3315/18

Catteau

32%0.68 804/4,542957/3,533

Di Castelnuovo

30%0.70

386/2,63490/817 Fried

-27%1.27

1,048/4,2321,466/7,489

Albani

18%0.82 60/211172/605

Synolaki

24%0.76 21/9860/214

Alamdari

55%0.45 42732

Heberto

54%0.46 139115

Lauriola

74%0.27 102/29735/63

Serrano

43%0.57 6/146/8

Ulrich (RCT)

-6%1.06 7/676/61

Shoaibi

15%0.85

686/5,0473,923/24,404

Ayerbe

52%0.48 237/1,85749/162

Nachega

28%0.72 69/63028/96

Ader (RCT)

6%0.94 11/14512/148

Soto-Becerra

18%0.82

346/6921,606/2,630 Aparisi 63%0.37 122/60527/49

Annie

4%0.96 48/36750/367

SOLIDARITY (RCT)

-19%1.19 104/94784/906

Guisado-Vasco

20%0.80 127/55814/49

Solh

-18%1.18 131/265134/378

Ñamendys-Silva

32%0.68 24/5442/64

Dubee (RCT)

46%0.54 6/12411/123

Lano

33%0.67 5666

Coll

46%0.54 55/307108/328

Frontera

37%0.63

121/1,006424/2,467 Tehrani

13%0.87 16/6554/190

Salazar

-37%1.37 12/9280/811

Rodriguez-Nava

-6%1.06 22/6579/248

Maldonado

91%0.09 1/111/1

Núñez-Gil

8%0.92 200/686100/268

Self (RCT)

-6%1.06 25/24125/236

Rodriguez

59%0.41 8/392/4

Águila-Gordo

67%0.33 151/34647/70

Sheshah

80%0.20 26733

Boari

55%0.45 41/20225/56

Budhiraja

65%0.35 69/83434/142

Falcone

65%0.35 40/23830/77

Qin 34%0.66

3/4375/706 van Halem 32%0.68 34/16447/155

Rodriguez-Gonzalez

23%0.77

251/1,14817/60

Lambermont

32%0.68 97/22514/22

Abdulrahman

17%0.83 5/2236/223

Modrák

59%0.41 108105

Ozturk

44%0.56 165/1,1276/23

Guglielmetti

35%0.65 18137

Bielza

21%0.79 33/91249/539

Naseem

33%0.67 771,137

Orioli

13%0.87 8/553/18

Signes-Costa

47%0.53 4,854993

Matangila

55%0.45 25/1478/13

Cangiano

73%0.27 5/3337/65

Taccone

25%0.75 449/1,308183/439

Chari

33%0.67 8/29195/473

Vernaz

15%0.85 12/9316/105

Texeira

-79%1.79 17/6514/96

Psevdos

-63%1.63 17/523/15

Sands

-70%1.70 101/97356/696

Lotfy

-25%1.25 6/995/103

Sarfaraz

-45%1.45 40/9427/92

Yegerov

95%0.05 0/2320/1,049

Roig

16%0.84 33/677/12

Ubaldo

18%0.82 17/255/6

Ouedraogo

33%0.67 39759

Hernandez-C.. (RCT)

12%0.88 106108

Thompson (DB RCT)

-6%1.06 25/24125/236

Lora-Tamayo

50%0.50 7,1921,361

Awad

-19%1.19 56/18837/148

Lamback

9%0.91 11/10111/92

Gonzalez (DB RCT)

63%0.37 2/336/37

Salvador

33%0.67 28/12158/124

Martin-Vicente

59%0.41 37/911/1

Aghajani

19%0.81 553438

Bosaeed (RCT)

4%0.96 14/12515/129

De Rosa

35%0.65 118/73180/280

Sammartino

-240%3.40 137191

Smith

27%0.73

19/37182/218Tau2 = 0.15; I2 = 89.9%Late treatment21%0.79 13,565/89,81216,858/91,01421% improvement

Rentsch

-3%1.03 population-based cohortImprovement, RR TreatmentControl

Gentry

91%0.09 0/10,7037/21,406

Arleo

50%0.50 1/205/50

Jung

59%0.41 0/6491/1,417

Rangel

25%0.75 4/5011/103

Trefond

-17%1.17 4/6812/183

Pham

20%0.80 2/145/28

Alegiani

-8%1.08 case control

Alzahrani

59%0.41 0/141/33

Korkmaz

82%0.18

0/3852/299Tau2 = 0.00; I2 = 0.0%PrEP1%0.99 11/11,90344/23,5191% improvement

Mitjà (RCT)

52%0.48

4/1,1969/1,301Improvement, RR TreatmentControlTau2 = 0.00; I2 = 0.0%PEP52%0.48 4/1,1969/1,30152% improvementAll studies25%0.75 13,661/121,34517,747/148,02825% improvementAll 158 hydroxychloroquine COVID-19 mortality resultshcqmeta.com 6/6/21Tau2 = 0.16; I2 = 89.2%; Z = 6.82 (p < 0.0001)Lower

RiskIncreased Risk

Figure 6. Random effects meta-analysis for mortality results only. (ES) indicates the early treatment subset of a study (these are not included in the overall results). Randomized Controlled Trials (RCTs) Randomized Controlled Trials (RCTs) minimize one source of bias and can provide a higher level of evidence. Results restricted to RCTs are shown in Figure 7, Figure 8, and Table 2. Even with the small number of RCTs to date, they confirm efficacy for early treatment. While late treatment RCTs are dominated by the very late stage and large RECOVERY/SOLIDARITY trials, prophylaxis and early treatment studies show 29% improvement in random effects meta-analysis, RR 0.71 , p = 0.0019. Early treatment RCTs show 46% improvement,

RR 0.54 , p = 0.01.

Evidence supports incorporating non-RCT studies. find that well-designed observational studies do not systematically overestimate the magnitude of the effects of treatment compared to RCTs. summarized reviews comparing RCTs to observational studies and found little evidence for significant differences in effect estimates. shows that only 14% of the guidelines of the Infectious Diseases Society of America were based on RCTs. Limitations in an RCT can easily outweigh the benefits, for example excessive dosages, excessive treatment delays, or Internet survey bias could easily have a greater effect on results. Ethical issues may prevent running RCTs for known effective treatments. For more on the problems

with RCTs see .

Download Image

A 00.250.50.7511.251.51.752+non-RCTsRandomized Controlled Trialsmin, Q1, median, Q3, maxLower RiskIncreased Riskhcqmeta.com 6/6/21

Download Image

B 100+ 75 50 25 25 50 75 100 Chen

progression, p=0.57

Chen

pneumonia, p=0.04

Huang

no recov., p=0.02

Tang

viral+, p=0.51

Boulware

cases, p=0.35

RECOVERY

death, p=0.15

Chen

viral- time, p=0.01

Chen

viral+, p=0.71

Mitj�

hosp., p=0.64

Skipper

hosp./death, p=0.58

Lyngbakken

death, p=1.00

Cavalcanti

death, p=0.77

Mitj�

death, p=0.27

Abd-Elsalam

death, p=1.00

Grau-Pujol

cases, p=0.47

Rajasingham

hosp., p=1.00

Ulrich

death, p=1.00

Abella

cases, p=1.00

Ader

death, p=1.00

SOLIDARITY

death, p=0.23

Dubee

death, p=0.21

Self

death, p=0.84

Omrani

hosp., p=1.00

Barnabas

hosp., p=1.00

Johnston

hosp., p=0.73

Hernandez-Cardenas

death, p=0.66

Purwati

viral+, p<0.0001

Thompson

death, p=0.84

Gonzalez

death, p=0.27

Amaravadi

no recov., p=0.13

Seet

severe case, p=0.14

Reis

death, p=1.00

Réa-Neto

death, p=0.20

Bosaeed

death, p=0.91

Rojas-Serrano

symp. case, p=0.12

Syed

symp. case, p=0.41

Byakika-Kibwika

recov. time, p=0.91

Randomized Controlled Trials% Lower Risk% Increased Riskhcqmeta.com 6/6/21Probability results fromineffective treatmentJul 10 p<0.051 in 20Dec 9 p<0.011 in 100

Download Image

C 00.250.50.7511.251.51.752+ Huang

(RCT) 92%0.08 no

recov.0/106/12Improvement, RR TreatmentControl

Chen (RCT)

72%0.28 viral time18/1812/12

Mitjà (RCT)

16%0.84 hosp.8/13611/157

Skipper (RCT)

37%0.63

hosp./death5/2318/234

Omrani (RCT)

12%0.88 hosp.7/3044/152

Amaravadi (DB RCT)

60%0.40 no

recov.3/156/12Tau2 = 0.01; I2 = 2.1%Early treatment46%0.54 41/71447/57946% improvement

Chen (RCT)

29%0.71

progression5/157/15Improvement, RR TreatmentControl

Chen (RCT)

57%0.43 pneumonia6/3114/31

Tang (RCT)

21%0.79 viral+11/7514/75

RECOVERY (RCT)

-9%1.09

death421/1,561790/3,155

Chen (RCT)

24%0.76 viral+4/213/12

Lyngbakken (RCT)

4%0.96 death1/271/26

Cavalcanti (RCT)

16%0.84 death8/3315/173

Abd-Elsalam (RCT)

-20%1.20 death6/975/97

Ulrich (RCT)

-6%1.06 death7/676/61

Ader (RCT)

6%0.94 death11/14512/148

SOLIDARITY (RCT)

-19%1.19

death104/94784/906 Dubee

(RCT) 46%0.54

death6/12411/123 Self (RCT) -6%1.06 death25/24125/236

Johnston (RCT)

30%0.70 hosp.5/1484/83

Hernandez-C.. (RCT)

12%0.88

death106108 Purwati (DB

RCT) 66%0.34

viral+38/121111/119

Thompson (DB RCT)

-6%1.06 death25/24125/236

Gonzalez (DB RCT)

63%0.37 death2/336/37

Reis (DB RCT)

66%0.34 death0/2141/227

Réa-Neto (RCT)

-57%1.57 death16/5310/52

Bosaeed (RCT)

4%0.96 death14/12515/129

Byakika-Ki.. (RCT)

0%1.00 recov.

time3629Tau2 = 0.17; I2 = 73.0%Late treatment16%0.84 715/4,7591,149/6,07816% improvement

Grau-Pujol (RCT)

68%0.32

cases0/1421/127Improvement, RR TreatmentControl

Rajasingham (RCT)

50%0.50

hosp.1/9891/494 Abella (RCT) 5%0.95 cases4/644/61

Rojas-Se.. (DB RCT)

82%0.18 symp.

case1/626/65 Syed (RCT)

-60%1.60 symp.

case10/486/46Tau2 = 0.06; I2 = 6.8%PrEP8%0.92 16/1,30518/7938% improvement

Boulware (RCT)

17%0.83

cases49/41458/407Improvement, RR TreatmentControl

Mitjà (RCT)

52%0.48

death4/1,1969/1,301

Barnabas (RCT)

-4%1.04 hosp.1/4071/422

Seet (CLUS. RCT)

35%0.65 severe

case29/43264/619Tau2 = 0.00; I2 = 0.0%PEP26%0.74 83/2,449132/2,74926% improvementAll studies22%0.78 855/9,2271,346/10,19922% improvementAll 37 hydroxychloroquine COVID-19 RCTshcqmeta.com 6/6/21Tau2 = 0.14; I2 = 62.9%; Z = 2.56 (p = 0.0052)Lower RiskIncreased Risk Figure 7. Randomized Controlled Trials. A. Scatter plot of all effects comparing RCTs to non-RCTs. B. Chronological history of all reported

effects.

Download Image

A 00.250.50.7511.251.51.752+non-RCTs excluding late treatmentRCTs excluding late treatmentmin, Q1, median, Q3, maxLower RiskIncreased Riskhcqmeta.com 6/6/21

Download Image

B 100+ 75 50 25 25 50 75 100 Huang

no recov., p=0.02

Boulware

cases, p=0.35

Chen

viral- time, p=0.01

Mitj�

hosp., p=0.64

Skipper

hosp./death, p=0.58

Mitj�

death, p=0.27

Grau-Pujol

cases, p=0.47

Rajasingham

hosp., p=1.00

Abella

cases, p=1.00

Omrani

hosp., p=1.00

Barnabas

hosp., p=1.00

Amaravadi

no recov., p=0.13

Seet

severe case, p=0.14

Rojas-Serrano

symp. case, p=0.12

Syed

symp. case, p=0.41

Randomized Controlled Trials (excluding late treatment)% Lower Risk% Increased Riskhcqmeta.com 6/6/21Probability results fromineffective treatmentJul 16 p<0.051 in 20Sep 21 p<0.011 in 100

Download Image

C 00.250.50.7511.251.51.752+ Huang

(RCT) 92%0.08 no

recov.0/106/12Improvement, RR TreatmentControl

Chen (RCT)

72%0.28 viral time18/1812/12

Mitjà (RCT)

16%0.84 hosp.8/13611/157

Skipper (RCT)

37%0.63

hosp./death5/2318/234

Omrani (RCT)

12%0.88 hosp.7/3044/152

Amaravadi (DB RCT)

60%0.40 no

recov.3/156/12Tau2 = 0.01; I2 = 2.1%Early treatment46%0.54 41/71447/57946% improvement

Grau-Pujol (RCT)

68%0.32

cases0/1421/127Improvement, RR TreatmentControl

Rajasingham (RCT)

50%0.50

hosp.1/9891/494 Abella (RCT) 5%0.95 cases4/644/61

Rojas-Se.. (DB RCT)

82%0.18 symp.

case1/626/65 Syed (RCT)

-60%1.60 symp.

case10/486/46Tau2 = 0.06; I2 = 6.8%PrEP8%0.92 16/1,30518/7938% improvement

Boulware (RCT)

17%0.83

cases49/41458/407Improvement, RR TreatmentControl

Mitjà (RCT)

52%0.48

death4/1,1969/1,301

Barnabas (RCT)

-4%1.04 hosp.1/4071/422

Seet (CLUS. RCT)

35%0.65 severe

case29/43264/619Tau2 = 0.00; I2 = 0.0%PEP26%0.74 83/2,449132/2,74926% improvementAll studies29%0.71 140/4,468197/4,12129% improvementHydroxychloroquine COVID-19 RCTs excluding late treatmenthcqmeta.com 6/6/21Tau2 = 0.00; I2 = 0.0%; Z = 3.12 (p = 0.0009)Lower RiskIncreased Risk Figure 8. RCTs excluding late treatment. A. Scatter plot of all effects comparing RCTs to non-RCTs. B. Chronological history of all reported effects. C. Random effects meta-analysis.

Treatment time

27

37 73.0%

0.0038 P = 0.0038

1 in 262

22% improvement

RR 0.78 p = 0.01

Randomized Controlled Trials (excluding late treatment)

13

15 86.7%

0.0037 P = 0.0037

1 in 271

29% improvement

RR 0.71 p = 0.0019 Table 2. Summary of RCT results. Analysis with Exclusions Many meta-analyses for HCQ have been written, most of which have become somewhat obselete due to the continuing stream of more recent studies. Recent analyses with positive conclusions include which considers significant bias from an understanding of each trial, and which focus on early or prophylactic use studies. Meta analyses reporting negative conclusions focus on late treatment studies, tend to disregard treatment delay, tend to follow formulaic evaluations which overlook major issues with various studies, and end up with weighting disproportionate to a reasoned analysis of each study's contribution. For example, assigns 87% weight to a single trial, the RECOVERY trial , thereby producing the same result. However, the RECOVERY trial may be the most biased of the studies they included, due to the excessive dosage used, close to the level shown to be very dangerous in (OR 2.8), and with extremely sick late stage patients (60% requiring oxygen, 17% ventilation/ECMO, and a very high mortality rate in both arms). There is little reason to suggest that the results from this trial are applicable to more typical dosages or to earlier treatment (10/22: the second version of this study released 10/22 assigns 74% to RECOVERY and 15% to SOLIDARITY , which is the only other trial using a similar excessive dosage). We include all studies in the main analysis, however there are major issues with several studies that could significantly alter the results. Here, we present an analysis excluding studies with significant issues, including indication of significant unadjusted group differences or confouding by indication, extremely late stage usage >14 days post symptoms or >50% on oxygen at baseline, very minimal detail provided, excessive dosages which have been shown to be dangerous, significant issues with adjustments that could reasonably make substantial differences, and reliance on PCR which may be inaccurate and less indicative of severity than symptoms. The aim here is not to exclude studies on technicalities, but to exclude studies that clearly have major issues that may significantly change the outcome. We welcome feedback on improvements or corrections to this. The studies excluded are as follows, and the resulting forest plot is

shown in Figure 9.

, very late stage, >50% on oxygen/ventilation at baseline. , substantial unadjusted confounding by indication likely. , substantial unadjusted confounding by indication likely, substantial time varying confounding likely due to declining usage over the early period when overall treatment protocols improved

dramatically.

, confounding by indication is likely and adjustments do not consider COVID-19 severity. , results only for PCR status which may be significantly different

to symptoms.

, confounding by indication is likely and adjustments do not consider COVID-19 severity. , unadjusted results with no group details. , substantial time varying confounding likely due to declining usage over the early period when overall treatment protocols improved dramatically, substantial unadjusted confounding by indication likely. , excessive unadjusted differences between groups. , unadjusted results with no group details. , unadjusted results with no group details. , very late stage, >50% on oxygen/ventilation at baseline. , excessive unadjusted differences between groups. , not fully adjusting for the different baseline risk of systemic autoimmune patients. , unadjusted results with no group details. , results only for PCR status which may be significantly different to symptoms. , results only for PCR status which may be significantly different to symptoms. , results only for PCR status which may be significantly different to symptoms. , excessive unadjusted differences between groups. , unadjusted results with no group details. , substantial unadjusted confounding by indication likely. , not fully adjusting for the different baseline risk of systemic autoimmune patients. , not fully adjusting for the baseline risk differences within systemic autoimmune patients. , excessive unadjusted differences between groups, substantial unadjusted confounding by indication likely. , excessive unadjusted differences between groups, results only for PCR status which may be significantly different to symptoms. , significant issues found with adjustments. , not fully adjusting for the baseline risk differences within systemic autoimmune patients. , not fully adjusting for the different baseline risk of systemic autoimmune patients. , not fully adjusting for the baseline risk differences within systemic autoimmune patients. , unadjusted results with no group details. , very late stage, >50% on oxygen/ventilation at baseline. , results only for PCR status which may be significantly different to symptoms. , very late stage, ICU patients. , significant unadjusted confounding possible. , results only for PCR status which may be significantly different to symptoms. , results only for PCR status which may be significantly different to symptoms. , not fully adjusting for the different baseline risk of systemic autoimmune patients. , not fully adjusting for the different baseline risk of systemic autoimmune patients. , excessive unadjusted differences between groups. , excessive unadjusted differences between groups. , not fully adjusting for the different baseline risk of systemic autoimmune patients. , substantial unadjusted confounding by indication likely. , not fully adjusting for the baseline risk differences within systemic autoimmune patients. , substantial unadjusted confounding by indication likely. , substantial time varying confounding likely due to declining usage over the early period when overall treatment protocols improved dramatically. , not fully adjusting for the different baseline risk of systemic autoimmune patients. , very late stage, >50% on oxygen/ventilation at baseline. , substantial time varying confounding likely due to declining usage over the early period when overall treatment protocols improved dramatically, substantial unadjusted confounding by indication likely. , substantial unadjusted confounding by indication likely. , results only for PCR status which may be significantly different to symptoms. , not fully adjusting for the baseline risk differences within systemic autoimmune patients. , treatment or control group size extremely small. , unadjusted results with no group details, treatment or control group size extremely small. , excessive unadjusted differences between groups. , excessive unadjusted differences between groups. , substantial unadjusted confounding by indication likely, unadjusted results with no group details, substantial time varying confounding likely due to declining usage over the early period when overall treatment protocols improved dramatically. , unadjusted results with no group details. , excessive unadjusted differences between groups. , unadjusted results with no group details, no treatment details, substantial time varying confounding likely due to declining usage over the early period when overall treatment protocols improved dramatically, substantial unadjusted confounding by indication likely. , unadjusted results with no group details. , not fully adjusting for the different baseline risk of systemic autoimmune patients. , excessive dosage, results do not apply to typical dosages. , not fully adjusting for the baseline risk differences within systemic autoimmune patients, medication adherence unknown and may significantly change results. , unadjusted results with no group details. , substantial unadjusted confounding by indication likely, excessive unadjusted differences between groups, unadjusted results with no group details. , unadjusted results with no group details. , substantial unadjusted confounding by indication likely. , no serious outcomes reported and fast recovery in treatment and control groups, there is little room for a treatment to improve

results.

, substantial unadjusted confounding by indication likely, unadjusted results with no group details. , results only for PCR status which may be significantly different to symptoms, substantial unadjusted confounding by

indication likely.

, not fully adjusting for the different baseline risk of systemic autoimmune patients. , substantial time varying confounding likely due to declining usage over the early period when overall treatment protocols improved dramatically. , includes PCR+ patients that may be asymptomatic for COVID-19 but in hospital for other reasons, substantial unadjusted confounding by indication likely. , substantial unadjusted confounding by indication likely, significant unadjusted confounding possible, unadjusted results with

no group details.

, significant issues found with adjustments. , results only for PCR status which may be significantly different to symptoms. , unadjusted results with no group details. , not fully adjusting for the baseline risk differences within systemic autoimmune patients. , confounding by indication is likely and adjustments do not consider COVID-19 severity. , immortal time bias may significantly affect results. , very late stage, >50% on oxygen/ventilation at baseline, substantial unadjusted confounding by indication likely. , excessive dosage, results do not apply to typical dosages, very late stage, >50% on oxygen/ventilation at baseline. , very late stage, >50% on oxygen/ventilation at baseline, substantial unadjusted confounding by indication likely. , substantial unadjusted confounding by indication likely, includes PCR+ patients that may be asymptomatic for COVID-19 but in hospital for other reasons. , substantial unadjusted confounding by indication likely, substantial time varying confounding likely due to declining usage over the early period when overall treatment protocols improved dramatically, includes PCR+ patients that may be asymptomatic for COVID-19 but in hospital for other reasons. , substantial unadjusted confounding by indication likely, substantial time varying confounding likely due to declining usage over the early period when overall treatment protocols improved dramatically, includes PCR+ patients that may be asymptomatic for COVID-19 but in hospital for other reasons. , substantial unadjusted confounding by indication likely, substantial time varying confounding likely due to declining usage over the early period when overall treatment protocols improved dramatically, includes PCR+ patients that may be asymptomatic for COVID-19 but in hospital for other reasons. , substantial unadjusted confounding by indication likely, substantial time varying confounding likely due to declining usage over the early period when overall treatment protocols improved dramatically, includes PCR+ patients that may be asymptomatic for COVID-19 but in hospital for other reasons. , substantial unadjusted confounding by indication likely, substantial time varying confounding likely due to declining usage over the early period when overall treatment protocols improved dramatically, includes PCR+ patients that may be asymptomatic for COVID-19 but in hospital for other reasons. , substantial unadjusted confounding by indication likely, substantial time varying confounding likely due to declining usage over the early period when overall treatment protocols improved dramatically, includes PCR+ patients that may be asymptomatic for COVID-19 but in hospital for other reasons. , substantial unadjusted confounding by indication likely, substantial time varying confounding likely due to declining usage over the early period when overall treatment protocols improved dramatically, includes PCR+ patients that may be asymptomatic for COVID-19 but in hospital for other reasons. , results only for PCR status which may be significantly different to symptoms. , substantial unadjusted confounding by indication likely, unadjusted results with no group details. , unadjusted results with no group details, no treatment details, substantial time varying confounding likely due to declining usage over the early period when overall treatment protocols improved dramatically, substantial unadjusted confounding by indication likely. , not fully adjusting for the different baseline risk of systemic autoimmune patients, significant unadjusted confounding possible, excessive unadjusted differences between groups. , substantial unadjusted confounding by indication likely, very late stage, ICU patients, unadjusted results with no group

details.

, very late stage, >50% on oxygen/ventilation at baseline. , substantial time varying confounding likely due to declining usage over the early period when overall treatment protocols improved dramatically, substantial unadjusted confounding by indication likely. , not fully adjusting for the different baseline risk of systemic autoimmune patients. , confounding by indication is likely and adjustments do not consider COVID-19 severity. , detail too minimal. , unadjusted results with no group details. , results only for PCR status which may be significantly different to symptoms. Download Image 00.250.50.7511.251.51.752+

Huang (RCT)

92%0.08 no

recov.0/106/12Improvement, RR TreatmentControl

Esper

64%0.36 hosp.8/41212/224

Ashraf

68%0.32 death10/772/5

Guérin

61%0.39 death0/201/34

Derwand

79%0.21 death1/14113/377

Mitjà (RCT)

16%0.84 hosp.8/13611/157

Skipper (RCT)

37%0.63

hosp./death5/2318/234

Bernabeu-Wittel

59%0.41 death18983

Yu (ES)

85%0.15 death1/73238/2,604

Ly 56%0.44

death18/11629/110 Ip 55%0.45 death2/9744/970

Heras

96%0.04 death8/7016/30

Kirenga

26%0.74 recov.

time29/2927/27 Sulaiman

64%0.36

death7/1,81754/3,724

Guisado-Vasco (ES)

67%0.33

death2/65139/542 Szente

Fonseca 64%0.36

hosp.25/17589/542

Cadegiani

81%0.19 death0/1592/137

Simova

94%0.06 hosp.0/332/5

Omrani (RCT)

12%0.88 hosp.7/3044/152

Agusti

68%0.32 progression2/874/55

Su 85%0.15

progression261355

Amaravadi (DB RCT)

60%0.40 no

recov.3/156/12 Mokhtari

70%0.30

death27/7,295287/21,464

Million

83%0.17

death5/8,31511/2,114Tau2 = 0.25; I2 = 54.4%Early treatment67%0.33 168/20,1271,005/33,96967% improvement Chen (RCT)

29%0.71

progression5/157/15Improvement, RR TreatmentControl

Chen (RCT)

57%0.43 pneumonia6/3114/31

Magagnoli

11%0.89

death39/14818/163 Auld -3%1.03 death33/11429/103

Sánchez-Álvarez

46%0.54 death32253

Mallat

-203%3.03 viral time2311

Membrillo de Nov..

55%0.45 death27/12321/43

Alberici

43%0.57 death17/729/22

Rosenberg

-35%1.35

death189/73528/221

Mahévas

-20%1.20 death9/848/89

Yu 60%0.40

death9/48238/502 Kim 51%0.49 hosp. time22/2240/40

Ip 1%0.99

death432/1,914115/598

Paccoud

11%0.89 death21/3826/46

Faíco-Filho

81%0.19 viral rate3432

Fontana

50%0.50 death4/122/3

Bousquet

43%0.57 death5/2723/81

Lagier

59%0.41 death35/3,11958/618

Komissarov

-25%1.25 viral

load26/2610/10 Mikami

47%0.53

death575/2,077231/743

Martinez-Lopez

33%0.67

death47/1489/19 Arshad

51%0.49

death162/1,202108/409

Rivera-Izquierdo

19%0.81 death21523

Trullàs

36%0.64 death20/6616/34

Bernaola

17%0.83

death236/1,49828/147 Rivera -2%1.02 death44/17959/327

Cavalcanti (RCT)

16%0.84 death8/3315/173

D'Arminio Monforte

34%0.66

death53/19747/92 Davido

55%0.45

int./hosp.12/8013/40 Yu

83%0.17

progression1/23132/1,291

Berenguer

62%0.38

death681/2,618939/1,377

Kalligeros

-67%1.67 death3672

Abd-Elsalam (RCT)

-20%1.20 death6/975/97

Pinato

59%0.41 death30/182181/446

Dubernet

88%0.12 ICU1/179/19

Gonzalez

27%0.73

death1,246/8,476341/1,168

Catteau

32%0.68

death804/4,542957/3,533

Di Castelnuovo

30%0.70

death386/2,63490/817

Synolaki

24%0.76 death21/9860/214

Heberto

54%0.46 death139115

Lauriola

74%0.27 death102/29735/63

Ashinyo

33%0.67 hosp.

time61/6161/61 Serrano 43%0.57 death6/146/8

Lammers

32%0.68

death/ICU30/189101/498

Ayerbe

52%0.48

death237/1,85749/162

Almazrou

65%0.35

ventilation3/956/66

Nachega

28%0.72 death69/63028/96

Guisado-Vasco

20%0.80

death127/55814/49

Ñamendys-Silva

32%0.68

death24/5442/64 Dubee (RCT) 46%0.54 death6/12411/123

Lano

33%0.67 death5666

Frontera

37%0.63

death121/1,006424/2,467

López

64%0.36

progression5/3614/36

Núñez-Gil

8%0.92

death200/686100/268 Self

(RCT) -6%1.06

death25/24125/236

Águila-Gordo

67%0.33

death151/34647/70 Sheshah

80%0.20 death26733

Falcone

65%0.35 death40/23830/77

van Halem

32%0.68 death34/16447/155

Rodriguez-Gonzalez

23%0.77

death251/1,14817/60

Lambermont

32%0.68

death97/22514/22

Abdulrahman

17%0.83

death5/2236/223 Capsoni

40%0.60

ventilation12/406/12 Peng

11%0.89

progression29/453256/3,567

Modrák

59%0.41 death108105

Ozturk

44%0.56 death165/1,1276/23

Guglielmetti

35%0.65 death18137

Johnston (RCT)

30%0.70 hosp.5/1484/83

Alqassieh

18%0.82 hosp. time6368

Tan

35%0.65 hosp. time8277

Naseem

33%0.67 death771,137

Orioli

13%0.87 death8/553/18

Signes-Costa

47%0.53 death4,854993

Matangila

55%0.45 death25/1478/13

Cangiano

73%0.27 death5/3337/65

Taccone

25%0.75

death449/1,308183/439 Güner

77%0.23 ICU604100

Li -40%1.40

viral time1819 Li

50%0.50 no disch.1414

Ouedraogo

33%0.67 death39759

Hernandez-C.. (RCT)

12%0.88

death106108 Purwati (DB

RCT) 66%0.34

viral+38/121111/119

Thompson (DB RCT)

-6%1.06 death25/24125/236

Lora-Tamayo

50%0.50 death7,1921,361

Gonzalez (DB RCT)

63%0.37 death2/336/37

Salvador

33%0.67 death28/12158/124

Barry

99%0.01 death0/691/599

Reis (DB RCT)

66%0.34 death0/2141/227

Réa-Neto (RCT)

-57%1.57 death16/5310/52

Kokturk

-4%1.04 death62/1,3825/118

Aghajani

19%0.81 death553438

De Rosa

35%0.65 death118/73180/280

Byakika-Ki.. (RCT)

0%1.00 recov.

time3629Tau2 = 0.10; I2 = 80.2%Late treatment36%0.64 7,793/60,9095,743/29,49736% improvement

Chatterjee

67%0.33

cases12/68206/387Improvement, RR TreatmentControl

Bhattacharya

81%0.19

cases4/5420/52 Ferreira

47%0.53

casespopulation-based cohort

Zhong

91%0.09 cases7/1620/27

Desbois

17%0.83 cases3/2723/172

Khurana

51%0.49 cases6/2288/159

Ferri

63%0.37 cases9/99416/647

Grau-Pujol (RCT)

68%0.32 cases0/1421/127

Rajasingham (RCT)

50%0.50

hosp.1/9891/494 Gentry

91%0.09

death0/10,7037/21,406

Abella (RCT)

5%0.95 cases4/644/61

Goenka

87%0.13 IgG+1/77115/885

Arleo

50%0.50 death1/205/50

Behera

28%0.72 cases7/19179/353

Mathai

90%0.10 cases10/49122/113

Revollo

23%0.77 cases16/6965/418

Jung

59%0.41 death0/6491/1,417

Gönenli

30%0.70

progression3/14812/416

Cordtz

24%0.76

hosp.population-based cohort

Bae 30%0.70

cases16/74391/2,698 Pham 20%0.80 death2/145/28

Dev 26%0.74

cases260499 Alegiani -8%1.08 deathcase control

Alzahrani

59%0.41 death0/141/33

Rojas-Se.. (DB RCT)

82%0.18 symp.

case1/626/65 Syed (RCT) -60%1.60 symp. case10/486/46

Korkmaz

82%0.18

death0/3852/299Tau2 = 0.29; I2 = 73.2%PrEP53%0.47 113/16,078896/30,85253% improvement

Boulware (RCT)

17%0.83

cases49/41458/407Improvement, RR TreatmentControl

Mitjà (RCT)

52%0.48

death4/1,1969/1,301 Polat 57%0.43 cases12/13814/70

Dhibar

41%0.59 cases14/13236/185

Simova

93%0.07 cases0/1563/48

Barnabas (RCT)

-4%1.04 hosp.1/4071/422

Seet (CLUS. RCT)

35%0.65 severe

case29/43264/619Tau2 = 0.00; I2 = 0.0%PEP34%0.66 109/2,875185/3,05234% improvementAll studies42%0.58 8,183/99,9897,829/97,37042% improvementAll 151 hydroxychloroquine COVID-19 studies with exclusionshcqmeta.com 6/6/21Tau2 = 0.12; I2 = 77.5%; Z = 13.21 (p < 0.0001)Lower

RiskIncreased Risk

Figure 9. Random effects meta-analysis excluding studies with significant issues. (ES) indicates the early treatment subset of a study (these are not included in the overall results).

Heterogeneity

Heterogeneity in COVID-19 studies arises from many factors including: Treatment delay. The time between infection or the onset of symptoms and treatment may critically affect how well a treatment works. For example a medication may be very effective when used early but may not be effective in late stage disease, and may even be harmful. Figure 10 shows an example where efficacy declines as a function of treatment delay. Other medications might be beneficial for late stage complications, while early use may not be effective or may even be

100% of early treatment studies report a positive effect, with an estimated reduction of 66% in the effect measured (death, hospitalization, etc.) using a random effects meta-analysis, RR 0.34

.

Revisions

This paper is data driven, all graphs and numbers are dynamically generated. We will update the paper as new studies are released or with any corrections. Please submit updates and corrections at the bottom of this page.Please submit updates and corrections at https://hcqmeta.com/. 10/21: We added studies . We received a report that the United States National Institutes of Health is recommending against HCQ for hospitalized and non-hospitalized patients as of October 9, and we added a reference. 10/22: We added . We updated the discussion of for the second version of this study. We added a table summarizing RCT results. 10/23: We added . The second version of the preprint for includes a comparison with the control group (not reported in the first version). We updated to use the mortality result in the recent journal version of the paper (not reported in the preprint).

10/26: We added .

10/28: We added .

10/30: We added .

10/31: We added .

11/1: We added .

11/4: We added .

11/8: We added .

11/9: We added .

11/10: We added .

11/12: We added .

11/13: We added .

11/14: We added .

11/18: We added .

11/19: We added .

11/20: We added .

11/23: We added .

11/24: We added .

11/25: We added , and we added analysis restricted to mortality

results.

11/27: We added .

11/28: We added .

11/30: We added .

12/1: We added .

12/2: We added .

12/4: We added .

12/7: We added .

12/8: We added .

12/9: We added .

12/11: We added .

12/13: We added .

12/14: We added .

12/15: We added .

12/16: We added .

12/17: We added .

12/20: We added .

12/21: We added .

12/22: We added .

12/23: We added .

12/24: We added .

12/25: We added .

12/27: We added the total number of authors and patients.

12/28: We added .

12/29: We added .

12/31: We added additional details about the studies in the appendix.

1/1: We added .

1/2: We added the number of patients to the forest plots. 1/3: We added dosage information for early treatment studies.

1/4: We added .

1/5: We added .

1/6: We added direct links to the study details in the forest plots. 1/7: We added direct links to the study details in the chronological

plots.

1/9: We added .

1/11: We added .

1/12: We added .

1/15: We updated to the published version. 1/16: We added the effect measured for each study in the forest plots.

1/21: We added .

1/24: We added . We moved the analysis with exclusions and mortality analysis to the main text.

2/1: We added .

2/2: We added .

2/5: We added .

2/6: We added .

2/7: We added .

2/9: We added .

2/10: We added .

2/15: We added .

2/16: We added .

2/17: We added .

2/18: We added .

2/20: We added .

2/23: We added .

2/25: We added .

2/26: We added .

2/28: We added .

3/2: We added .

3/3: We added .

3/5: We added .

3/7: We added .

3/8: We added .

3/9: We added .

3/13: We added .

3/24: We added .

3/27: We added , and we corrected an error in effect

extraction for .

3/28: We added .

3/29: We added .

4/1: We added .

4/2: We added .

4/4: We updated for 11 control hospitalizations. There is conflicting data, table S2 lists 12 control hospitalizations, while table 2 shows 11. A previous version of this paper also showed some values corresponding to 12 control hospitalizations in the abstract

and table 2.

4/6: We added .

4/9: We updated to the journal version.

4/14: We added .

4/20: We added .

4/23: We added .

4/29: We added .

5/1: We added .

5/3: We added an explanation of how some meta analyses produce

negative results.

5/4: We added .

5/7: We added .

5/8: We added .

5/10: We added additional information in the abstract.

5/12: We added .

5/14: We added more discussion of heterogeneity.

5/15: We added .

5/16: We added . We corrected the group sizes for , and we excluded hospitalizations that were reported as not being related to COVID-19.

5/17: We added .

5/28: We added .

6/2: We added .

6/4: We added .

6/5: We added .

Appendix 1. Methods and Study Results We performed ongoing searches of PubMed, medRxiv, ClinicalTrials.gov, The Cochrane Library, Google Scholar, Collabovid, Research Square, ScienceDirect, Oxford University Press, the reference lists of other studies and meta-analyses, and submissions to the site c19hcq.com , which regularly receives submissions of both positive and negative studies upon publication. Search terms were hydroxychloroquine or chloroquine and COVID-19 or SARS-CoV-2, or simply hydroxychloroquine or chloroquine. Automated searches are performed every hour with notifications of new matches. All studies regarding the use of HCQ or CQ for COVID-19 that report an effect compared to a control group are included in the main analysis. This is a living analysis and is updated regularly. We extracted effect sizes and associated data from all studies. If studies report multiple kinds of effects then the most serious outcome is used in calculations for that study. For example, if effects for mortality and cases are both reported, the effect for mortality is used, this may be different to the effect that a study focused on. If symptomatic results are reported at multiple times, we used the latest time, for example if mortality results are provided at 14 days and 28 days, the results at 28 days are used. Mortality alone is preferred over combined outcomes. Outcomes with zero events in both arms were not used. Clinical outcome is considered more important than PCR testing status. When basically all patients recover in both treatment and control groups, preference for viral clearance and recovery is given to results mid-recovery where available (after most or all patients have recovered there is no room for an effective treatment to do better). When results provide an odds ratio, we computed the relative risk when possible, or converted to a relative risk according to . Reported confidence intervals and _p_-values were used when available, using adjusted values when provided. If multiple types of adjustments are reported including propensity score matching (PSM), the PSM results are used. When needed, conversion between reported _p_-values and confidence intervals followed , and Fisher's exact test was used to calculate _p_-values for event data. If continuity correction for zero values is required, we use the reciprocal of the opposite arm with the sum of the correction factors equal to 1 . If a study separates HCQ and HCQ+AZ, we use the combined results were possible, or the results for the larger group. Results are all expressed with RR < 1.0 suggesting effectiveness. Most results are the relative risk of something negative. If a study reports relative times, the results are expressed as the ratio of the time for the HCQ group versus the time for the control group. If a study reports the rate of reduction of viral load, the results are based on the percentage change in the rate. Calculations are done in Python (3.9.2) with scipy (1.6.2), pythonmeta (1.23), numpy (1.20.2), statsmodels (0.12.2), and plotly (4.14.3). The forest plots are computed using PythonMeta with the DerSimonian and Laird random effects model (the fixed effect assumption is not plausible in this case). We received no funding, this research is done in our spare time. We have no affiliations with any pharmaceutical companies or political

parties.

We have classified studies as early treatment if most patients are not already at a severe stage at the time of treatment, and treatment started within 5 days after the onset of symptoms, although a shorter time may be preferable. Antivirals are typically only considered effective when used within a shorter timeframe, for example 0-36 or 0-48 hours for oseltamivir, with longer delays not being effective

.

A summary of study results is below. Please submit updates and corrections at the bottom of this page. A summary of study results is below. Please submit updates and corrections at https://hcqmeta.com/.

Early treatment

Effect extraction follows pre-specified rules as detailed above and gives priority to more serious outcomes. Only the first (most serious) outcome is used in calculations, which may differ from the effect a

paper focuses on.

, 12/9/2020, prospective, Spain, Europe, peer-reviewed, median age 37.0, 13 authors, dosage 400mg bid day 1, 200mg bid days

2-5.

Submit Corrections or Updates. RISK OF DISEASE PROGRESSION, 68.4% LOWER, RR 0.32, _P_ = 0.21, treatment 2 of 87 (2.3%), control 4 of 55

(7.3%), pneumonia.

time to viral-, 31.8% lower, relative time 0.68, treatment 87,

control 55.

, 2/26/2021, Double Blind Randomized Controlled Trial, USA, North America, preprint, 20 authors, dosage 400mg bid days 1-14. Submit Corrections or Updates. RISK OF NOT REACHING LOWEST SYMPTOM SCORE AT DAY 7 MID-RECOVERY, 60.0% LOWER, RR 0.40, _P_ = 0.13, treatment 3 of 15 (20.0%), control 6 of 12 (50.0%). relative time to first occurrence of lowest symptom score, 42.9% lower, relative time 0.57, _p_ = 0.21, treatment 15, control 12. relative time to release from quarantine, 27.3% lower, relative time 0.73, _p_ = 0.28, treatment 16, control 13. , 4/24/2020, retrospective, database analysis, Iran, Middle East, preprint, median age 58.0, 16 authors, dosage 200mg bid daily, 400mg qd was used when combined with Lopinavir-Ritonavir. Submit Corrections or Updates. RISK OF DEATH, 67.5% LOWER, RR 0.32, _P_ = 0.15, treatment 10 of 77 (13.0%), control 2 of 5 (40.0%). , 8/1/2020, retrospective, Spain, Europe, peer-reviewed, 13 authors, dosage 400mg bid day 1, 200mg bid days 2-7. Submit Corrections or Updates. RISK OF DEATH, 59.0% LOWER, RR 0.41, _P_ = 0.03, treatment 189, control 83. , 11/4/2020, prospective, Brazil, South America, preprint, 4 authors, dosage 400mg days 1-5. Submit Corrections or Updates. RISK OF DEATH, 81.2% LOWER, RR 0.19, _P_ = 0.21, treatment 0 of 159 (0.0%), control 2 of 137 (1.5%), continuity correction due to zero event (with reciprocal of the contrasting arm), control group 1. risk of mechanical ventilation, 95.1% lower, RR 0.05, _p_ < 0.001, treatment 0 of 159 (0.0%), control 9 of 137 (6.6%), continuity correction due to zero event (with reciprocal of the contrasting arm),

control group 1.

risk of hospitalization, 98.3% lower, RR 0.02, _p_ < 0.001, treatment 0 of 159 (0.0%), control 27 of 137 (19.7%), continuity correction due to zero event (with reciprocal of the contrasting arm),

control group 1.

, 6/22/2020, Randomized Controlled Trial, China, Asia, preprint, 19 authors, dosage 200mg bid days 1-10. Submit Corrections or Updates. MEDIAN TIME TO PCR-, 72.0% LOWER, RELATIVE TIME 0.28, _P_ = 0.01, treatment 18, control 12. , 10/26/2020, retrospective, USA, North America, peer-reviewed, 3 authors, dosage 200mg bid days 1-5. Submit Corrections or Updates. RISK OF DEATH, 79.4% LOWER, RR 0.21, _P_ = 0.12, treatment 1 of 141 (0.7%), control 13 of 377 (3.4%), odds ratio converted to relative risk. risk of hospitalization, 81.6% lower, RR 0.18, _p_ < 0.001, treatment 4 of 141 (2.8%), control 58 of 377 (15.4%), odds ratio converted to relative risk. , 4/15/2020, prospective, Brazil, South America, preprint, 15 authors, dosage 800mg day 1, 400mg days 2-7. Submit Corrections or Updates. RISK OF HOSPITALIZATION, 64.0% LOWER, RR 0.36, _P_ = 0.02, treatment 8 of 412 (1.9%), control 12 of

224 (5.4%).

, 3/17/2020, prospective, France, Europe, peer-reviewed, 18 authors, dosage 200mg tid days 1-10. Submit Corrections or Updates. RISK OF NO VIROLOGICAL CURE AT DAY 6, 66.0% LOWER, RR 0.34, _P_ = 0.001, treatment 6 of 20 (30.0%), control 14 of 16 (87.5%). , 10/15/2020, retrospective, Spain, Europe, peer-reviewed, median age 69.0, 25 authors, early treatment subset, dosage not specified. Submit Corrections or Updates. RISK OF DEATH, 66.9% LOWER, RR 0.33, _P_ = 0.19, treatment 2 of 65 (3.1%), control 139 of 542 (25.6%), adjusted per study, odds ratio converted to relative risk,

multivariate.

, 5/31/2020, retrospective, France, Europe, peer-reviewed, 8 authors, dosage 600mg days 1-10, 7-10 days. Submit Corrections or Updates. RISK OF DEATH, 61.4% LOWER, RR 0.39, _P_ = 1.00, treatment 0 of 20 (0.0%), control 1 of 34 (2.9%), continuity correction due to zero event (with reciprocal of the

contrasting arm).

recovery time, 65.0% lower, relative time 0.35, _p_ < 0.001, treatment 20, control 34. , 9/2/2020, retrospective, Andorra, Europe, peer-reviewed, median age 85.0, 13 authors, dosage not specified. Submit Corrections or Updates. RISK OF DEATH, 95.6% LOWER, RR 0.04, _P_ = 0.004, treatment 8 of 70 (11.4%), control 16 of 30 (53.3%),

adjusted per study.

, 7/16/2020, retrospective, South Korea, Asia, peer-reviewed, 7 authors, dosage not specified. Submit Corrections or Updates. RISK OF PROLONGED VIRAL SHEDDING, 64.9% LOWER, RR 0.35, _P_ = 0.001, treatment 42, control 48, odds ratio converted to relative risk. , 5/28/2020, prospective, China, Asia, peer-reviewed, 36 authors, early treatment subset, dosage chloroquine 500mg days 1-10, two groups, 500mg qd and 500mg bid. Submit Corrections or Updates. TIME TO VIRAL-, 59.1% LOWER, RELATIVE TIME 0.41, _P_ < 0.001, treatment 32, control 37. , 4/1/2020, Randomized Controlled Trial, China, Asia, peer-reviewed, 18 authors, dosage chloroquine 500mg bid days 1-10. Submit Corrections or Updates. RISK OF NO RECOVERY AT DAY 14, 91.7% LOWER, RR 0.08, _P_ = 0.02, treatment 0 of 10 (0.0%), control 6 of 12 (50.0%), continuity correction due to zero event (with reciprocal of the contrasting arm). risk of no improvement in pneumonia at day 14, 83.0% lower, RR 0.17, _p_ = 0.22, treatment 10, control 12. , 8/25/2020, retrospective, database analysis, USA, North America, peer-reviewed, 25 authors, dosage not specified. Submit Corrections or Updates. RISK OF DEATH, 54.5% LOWER, RR 0.45, _P_ = 0.43, treatment 2 of 97 (2.1%), control 44 of 970 (4.5%). risk of ICU admission, 28.6% lower, RR 0.71, _p_ = 0.79, treatment 3 of 97 (3.1%), control 42 of 970 (4.3%). risk of hospitalization, 37.3% lower, RR 0.63, _p_ = 0.04, treatment 21 of 97 (21.6%), control 305 of 970 (31.4%), adjusted per study, odds ratio converted to relative risk. , 9/9/2020, prospective, Uganda, Africa, peer-reviewed, 29 authors, dosage not specified. Submit Corrections or Updates. MEDIAN TIME TO RECOVERY, 25.6% LOWER, RELATIVE TIME 0.74, _P_ = 0.20, treatment 29, control 27. , 8/21/2020, retrospective, France, Europe, peer-reviewed, mean age 83.0, 21 authors, dosage 200mg tid days 1-10. Submit Corrections or Updates. RISK OF DEATH, 55.6% LOWER, RR 0.44, _P_ = 0.02, treatment 18 of 116 (15.5%), control 29 of 110 (26.4%), adjusted per study, odds ratio converted to relative risk. , 5/27/2021, retrospective, France, Europe, preprint, 28 authors, dosage 200mg tid days 1-10. Submit Corrections or Updates. RISK OF DEATH, 83.0% LOWER, RR 0.17, _P_ < 0.001, treatment 5 of 8315 (0.1%), control 11 of 2114 (0.5%),

adjusted per study.

, 7/16/2020, Randomized Controlled Trial, Spain, Europe, peer-reviewed, 45 authors, dosage 800mg day 1, 400mg days 2-7. Submit Corrections or Updates. RISK OF HOSPITALIZATION, 16.0% LOWER, RR 0.84, _P_ = 0.64, treatment 8 of 136 (5.9%), control 11 of

157 (7.0%).

risk of no recovery, 34.0% lower, RR 0.66, _p_ = 0.38, treatment 8 of 136 (5.9%), control 14 of 157 (8.9%). relative change in viral load from baseline, 2.0% lower, relative load 0.98, treatment 136, control 157, day 7. , 4/6/2021, retrospective, Iran, Middle East, peer-reviewed, 11 authors, dosage 400mg bid day 1, 200mg bid days 2-5. Submit Corrections or Updates. RISK OF DEATH, 69.7% LOWER, RR 0.30, _P_ < 0.001, treatment 27 of 7295 (0.4%), control 287 of 21464 (1.3%), adjusted per study, odds ratio converted to relative risk. risk of hospitalization, 35.3% lower, RR 0.65, _p_ < 0.001, treatment 523 of 7295 (7.2%), control 2382 of 21464 (11.1%), adjusted per study, odds ratio converted to relative risk. , 11/20/2020, Randomized Controlled Trial, Qatar, Middle East, peer-reviewed, 19 authors, dosage 600mg days 1-6. Submit Corrections or Updates. RISK OF HOSPITALIZATION, 12.5% LOWER, RR 0.88, _P_ = 1.00, treatment 7 of 304 (2.3%), control 4 of 152 (2.6%), HCQ+AZ or HCQ vs. control. risk of symptomatic at day 21, 25.8% lower, RR 0.74, _p_ = 0.58, treatment 9 of 293 (3.1%), control 6 of 145 (4.1%), HCQ+AZ or HCQ vs.

control.

risk of Ct<=40 at day 14, 10.3% higher, RR 1.10, _p_ = 0.13, treatment 223 of 295 (75.6%), control 98 of 143 (68.5%), HCQ+AZ or HCQ

vs. control.

, 3/12/2021, retrospective, database analysis, India, South Asia, preprint, 5 authors, dosage not specified. Submit Corrections or Updates. RELATIVE TIME TO CLINICAL RESPONSE OF WELLBEING, 2.4% LOWER, RELATIVE TIME 0.98, _P_ = 0.96, treatment

14, control 15.

, 11/12/2020, retrospective, Bulgaria, Europe, peer-reviewed, 5 authors, dosage 200mg tid days 1-14. Submit Corrections or Updates. RISK OF HOSPITALIZATION, 93.8% LOWER, RR 0.06, _P_ = 0.01, treatment 0 of 33 (0.0%), control 2 of 5 (40.0%), continuity correction due to zero event (with reciprocal of the contrasting arm). risk of viral+ at day 14, 95.8% lower, RR 0.04, _p_ = 0.001, treatment 0 of 33 (0.0%), control 3 of 5 (60.0%), continuity correction due to zero event (with reciprocal of the contrasting arm). , 7/16/2020, Randomized Controlled Trial, USA, North America, peer-reviewed, 24 authors, dosage 800mg once, followed by 600mg in 6 to 8 hours, then 600mg daily for 4 more days. Submit Corrections or Updates. RISK OF COMBINED HOSPITALIZATION/DEATH, 36.7% LOWER, RR 0.63, _P_ = 0.58, treatment 5 of 231 (2.2%), control 8 of 234 (3.4%), COVID-19 adjudicated hospitalization/death. risk of hospitalization, 49.4% lower, RR 0.51, _p_ = 0.38, treatment 4 of 231 (1.7%), control 8 of 234 (3.4%), COVID-19 adjudicated hospitalization. risk of combined hospitalization/death, 49.4% lower, RR 0.51, _p_ = 0.29, treatment 5 of 231 (2.2%), control 10 of 234 (4.3%), all hospitalization/death. risk of hospitalization, 59.5% lower, RR 0.41, _p_ = 0.17, treatment 4 of 231 (1.7%), control 10 of 234 (4.3%), all

hospitalizations.

risk of no recovery at day 14, 20.0% lower, RR 0.80, _p_ = 0.21. , 12/23/2020, retrospective, China, Asia, peer-reviewed, 9 authors, dosage 400mg days 1-10, 400mg daily for 10-14 days. Submit Corrections or Updates. RISK OF DISEASE PROGRESSION, 84.9% LOWER, RR 0.15, _P_ = 0.006, treatment 261, control 355, adjusted per study, binary logistic regression. improvement time, 24.0% lower, relative time 0.76, _p_ = 0.02, treatment 261, control 355, adjusted per study, Cox proportional

hazards regression.

, 9/13/2020, prospective, Saudi Arabia, Middle East, preprint, 22 authors, dosage 400mg bid day 1, 200mg bid days 2-5. Submit Corrections or Updates. RISK OF DEATH, 63.7% LOWER, RR 0.36, _P_ = 0.01, treatment 7 of 1817 (0.4%), control 54 of 3724 (1.5%), adjusted per study, odds ratio converted to relative risk. risk of hospitalization, 38.6% lower, RR 0.61, _p_ = 0.001, treatment 171 of 1817 (9.4%), control 617 of 3724 (16.6%), adjusted per study, odds ratio converted to relative risk. , 10/31/2020, retrospective, Brazil, South America, peer-reviewed, mean age 50.6, 10 authors, dosage 400mg bid day 1,

400mg qd days 2-5.

Submit Corrections or Updates. RISK OF HOSPITALIZATION, 64.0% LOWER, RR 0.36, _P_ < 0.001, treatment 25 of 175 (14.3%), control 89 of 542 (16.4%), adjusted per study, odds ratio converted to relative risk, HCQ vs. nothing. risk of hospitalization, 50.5% lower, RR 0.49, _p_ = 0.006, treatment 25 of 175 (14.3%), control 89 of 542 (16.4%), adjusted per study, odds ratio converted to relative risk, HCQ vs. anything else. , 8/3/2020, retrospective, China, Asia, preprint, median age 62.0, 6 authors, early treatment subset, dosage 200mg bid days 1-10. Submit Corrections or Updates. RISK OF DEATH, 85.0% LOWER, RR 0.15, _P_ = 0.02, treatment 1 of 73 (1.4%), control 238 of 2604 (9.1%), HCQ treatment started early vs. non-HCQ.

1.Abd-Elsalam et al., American Journal of Tropical Medicine and Hygiene, 10.4269/ajtmh.20-0873 , Hydroxychloroquine in the Treatment of COVID-19: A Multicenter Randomized Controlled Study, https://www.ajtmh.org/content/journals/10.4269/ajtmh.20-0873. 2.Abdulrahman et al., medRxiv, doi:10.1101/2020.11.25.20234914 , The efficacy and safety of hydroxychloroquine in COVID19 patients : a multicenter national retrospective cohort , https://www.medrxiv.org/content/10.1101/2020.11.25.20234914v1. 3.Abella et al., JAMA Internal Medicine, doi:doi:10.1001/jamainternmed.2020.6319 , Efficacy and Safety of Hydroxychloroquine vs Placebo for Pre-exposure SARS-CoV-2 Prophylaxis Among Health Care Workers, https://jamanetwork.com/journals/j..ternalmedicine/fullarticle/2771265

.

4.Ader et al., medRxiv, doi:10.1101/2021.01.08.20248149 (news 10/6) , Antiviral drugs in hospitalized patients with COVID-19 - the DisCoVeRy trial, https://www.medrxiv.org/content/10.1101/2021.01.08.20248149v1.

5.AFP

,

India backs hydroxychloroquine for virus prevention, https://www.msn.com/en-ph/news/wor..us-prevention/ar-BB14EloP?ocid=st2

.

6.AfricaFeeds

,

Kenya approve the use of Chloroquine to treat COVID-19 patients, https://africafeeds.com/2020/04/01..oquine-to-treat-covid-19-patients/

.

7.Africanews

, How to obtain the

confidence interval from a P value, https://www.bmj.com/content/343/bmj.d2090. 23.Alzahrani et al., Rheumatology International , doi:10.1007/s00296-021-04857-9 , Clinical characteristics and outcome of COVID-19 in patients with

rheumatic diseases,

https://link.springer.com/article/10.1007/s00296-021-04857-9. 24.Amaravadi et al., medRxiv, doi:10.1101/2021.02.22.21252228 , Hydroxychloroquine for SARS-CoV-2 positive patients quarantined at home: The first interim analysis of a remotely conducted randomized clinical trial, https://www.medrxiv.org/content/10.1101/2021.02.22.21252228v1. 25.An et al., medRxiv, doi:10.1101/2020.07.04.20146548 , Treatment Response to Hydroxychloroquine and Antibiotics for mild to moderate COVID-19: a retrospective cohort study from South Korea, https://www.medrxiv.org/content/10.1101/2020.07.04.20146548v1.

26.Anadolu Agency

31.Archyde

43.Barron's

,

Hydroxychloroquine: A Drug Dividing The World, https://www.barrons.com/news/hydro..rug-dividing-the-world-01591006809

.

44.Barron's (B)

54.Bianet

,

Turkey begins distributing hydroxychloroquine to homes in capital city

amid bed shortage,

https://bianet.org/english/health/..-in-capital-city-amid-bed-shortage

Reunion Island,

https://www.sciencedirect.com/science/article/pii/S221371652030206X.

98.Efecto Cocuyo

,

204.Middle East Eye

COVID-19 registry,

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7649104/. 225.Omrani et al., EClinicalMedicine, doi:10.1016/j.eclinm.2020.100645 , Randomized double-blinded placebo-controlled trial of hydroxychloroquine with or without azithromycin for virologic cure of non-severe Covid-19, https://www.sciencedirect.com/science/article/pii/S2589537020303898.

226.Oneindia

,

No COVID-19 death in Manipur, Mizoram, Nagaland, Sikkim so far: Govt, https://www.oneindia.com/india/no-..o-far-health-ministry-3111048.html

.

227.Orioli et al., Diabetes & Metabolic Syndrome: Clinical Research & Reviews, doi:10.1016/j.dsx.2020.12.020 , Clinical characteristics and short-term prognosis of in-patients with diabetes and COVID-19: A retrospective study from an academic center in Belgium, https://www.sciencedirect.com/science/article/pii/S1871402120305154. 228.Ouedraogo et al., Revue des Maladies Respiratoires, doi:10.1016/j.rmr.2021.02.001 , Factors associated with the occurrence of acute respiratory distress and death in patients with COVID-19 in Burkina Faso, https://www.sciencedirect.com/science/article/pii/S0761842521000383. 229.Ozturk et al., Nephrology Dialysis Transplantation, doi:10.1093/ndt/gfaa271 , Mortality analysis of COVID-19 infection in chronic kidney disease, haemodialysis and renal transplant patients compared with patients without kidney disease: a nationwide analysis from Turkey, https://academic.oup.com/ndt/article/35/12/2083/6020341. 230.Paccoud et al., Clinical Infectious Diseases, doi:10.1093/cid/ciaa791 , Compassionate use of hydroxychloroquine in clinical practice for patients with mild to severe Covid-19 in a French university hospital, https://academic.oup.com/cid/article/doi/10.1093/cid/ciaa791/5859555. 231.Pan African Medical Journal

,

Clinical characteristics, treatment regimen and duration of hospitalization among COVID-19 patients in Ghana: a retrospective

cohort study,

https://www.panafrican-med-journal.com/content/series/37/1/9/full/.

232.Parola et al.

nothing? Use and avoidance of continuity corrections in meta‐analysis of sparse data, https://onlinelibrary.wiley.com/doi/10.1002/sim.1761. 305.Syed et al., medRxiv, doi:10.1101/2021.05.17.21257012 , Pre-Exposure Prophylaxis with Various Doses of Hdroxychloroquine among high-risk COVID 19 Healthcare Personnel: CHEER randomized controlled trial, https://www.medrxiv.org/content/10.1101/2021.05.17.21257012v1. 306.Synolaki et al., medRxiv, doi:10.1101/2020.09.05.20184655 , The Activin/Follistatin-axis is severely deregulated in COVID-19 and independently associated with in-hospital mortality, https://www.medrxiv.org/content/10.1101/2020.09.05.20184655v2. 307.Szente Fonseca et al., Travel Medicine and Infectious Disease, doi:10.1016/j.tmaid.2020.101906 , Risk of Hospitalization for Covid-19 Outpatients Treated with Various Drug Regimens in Brazil: Comparative Analysis, https://www.sciencedirect.com/scie../article/abs/pii/S1477893920304026

.

308.Taccone et al., The Lancet Regional Health - Europe, doi:10.1016/j.lanepe.2020.100019 , The role of organizational characteristics on the outcome of COVID-19 patients admitted to the ICU in Belgium, https://www.sciencedirect.com/science/article/pii/S2666776220300193. 309.Tan et al., Virus Research, doi:10.1016/j.virusres.2020.198262 , A retrospective comparison of drugs

against COVID-19,

https://www.sciencedirect.com/scie../article/abs/pii/S0168170220311692

.

310.Tang et al., BMJ 2020, 369, doi:10.1136/bmj.m1849 , Hydroxychloroquine in patients with COVID-19: an open-label, randomized, controlled trial, https://www.bmj.com/content/369/bmj.m1849. 311.Tehrani et al., International Journal of Infectious Diseases, doi:10.1016/j.ijid.2020.10.071 , Risk factors for mortality in adult COVID-19 patients; frailty predicts fatal outcome in older patients, https://www.sciencedirect.com/science/article/pii/S1201971220322761.

312.Teller Report

, Efficacy

and Safety of the Oral Neuraminidase Inhibitor Oseltamivir in Treating Acute Influenza: A Randomized Controlled Trial, https://jamanetwork.com/journals/jama/fullarticle/192425. 329.Trefond et al., SSRM, doi:10.2139/ssrn.3754815 , Impact of hydroxychloroquine used as DMARD on SARS CoV-2 tests and COVID-19 evolution, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3754815. 330.Trullàs et al., Research Square, doi:10.21203/rs.3.rs-39421/v1 , High in-hospital mortality due to COVID-19 in a community hospital in Spain: a prospective observational study, https://www.researchsquare.com/article/rs-39421/v1. 331.Ubaldo et al., Critical Care Research and Practice, 10.1155/2021/7510306 , COVID-19: A Single-Center ICU Experience of the First Wave in the Philippines, https://www.hindawi.com/journals/ccrp/2021/7510306/.

332.Ukrinform

Twitter

is censoring and shadowbanning early treatment research . Tweets may be more visible if you post an image rather than a link.

@CovidAnalysis

FAQ

Public domain CC0 1.0

Details

Image Url

HTML Url

Moderation By

More Annotations

Ellen Grant

2019-10-13 18:53:24

Ellen Grant

2019-10-13 18:53:28

Ellen Grant

2019-10-13 18:53:43

Ellen Grant

2019-10-13 18:54:05

Ellen Grant

2019-10-13 18:54:32

Ellen Grant

2019-10-13 18:54:49

Ellen Grant

2019-10-13 18:54:59

Ellen Grant

2019-10-13 18:55:10

Ellen Grant

2019-10-13 18:55:53

Ellen Grant

2019-10-13 18:56:06

Ellen Grant

2019-10-13 18:56:18

Ellen Grant

2019-10-13 18:56:29

Favourite Annotations

Ellen Grant

2019-11-06 12:34:42

Ellen Grant

2019-11-06 12:34:58

Ellen Grant

2019-11-06 12:35:54

Ellen Grant

2019-11-06 12:37:47

Ellen Grant

2019-11-06 12:38:09

Ellen Grant

2019-11-06 12:38:23

Ellen Grant

2019-11-06 12:38:37

Ellen Grant

2019-11-06 12:39:00

Ellen Grant

2019-11-06 12:39:01

Ellen Grant

2019-11-06 12:39:18

Ellen Grant

2019-11-06 12:39:23

Ellen Grant

2019-11-06 12:39:43

Text

treatment.

advice.

any kind of

treatment.

advice.

any kind of

treatment.

Vitamin DV.D PXPX

FLVFLV

PVP-IPI BUBU BHBH

BLBL CICI

HC QHC Q NZNZ

COCO

C19 studies: C19:

DV.D PXPX FLVFLV

PVP-IPI BUBU

BHBH BLBL CICI

More..

— ADDED THOMPSON)

@CovidAnalysis

Share

Tweet

Twitter

PDF

Studies

arm.

damage.

All studies

Mortality results