A systematic review of trial registry entries for randomized clinical trials investigating COVID-19 medical prevention and treatment

Anders Peder Højer Karlsen; Sebastian Wiberg; Jens Laigaard; Casper Pedersen; Kim Zillo Rokamp; Ole Mathiesen

doi:10.1371/journal.pone.0237903

. 2020 Aug 20;15(8):e0237903. doi: 10.1371/journal.pone.0237903

A systematic review of trial registry entries for randomized clinical trials investigating COVID-19 medical prevention and treatment

Anders Peder Højer Karlsen ^1,^*, Sebastian Wiberg ¹, Jens Laigaard ¹, Casper Pedersen ¹, Kim Zillo Rokamp ¹, Ole Mathiesen ^1,²

Editor: Lisa Susan Wieland³

PMCID: PMC7444584 PMID: 32817689

Abstract

Aim

To identify investigated interventions for COVID-19 prevention or treatment via trial registry entries on planned or ongoing randomised clinical trials. To assess these registry entries for recruitment status, planned trial size, blinding and reporting of mortality.

Methods

We identified trial registry entries systematically via the WHO International Clinical Trials Registry Platform and 33 trial registries up to June 23, 2020. We included relevant trial registry entries for randomized clinical trials investigating medical preventive, adjunct or supportive therapies and therapeutics for treatment of COVID-19. Studies with non-random and single-arm design were excluded. Trial registry entries were screened by two authors independently and data were systematically extracted.

Results

We included 1303 trial registry entries from 71 countries investigating 381 different single interventions. Blinding was planned in 47% of trials. Sample size was >200 participants in 40% of trials and a total of 611,364 participants were planned for inclusion. Mortality was listed as an outcome in 57% of trials. Recruitment was ongoing in 54% of trials and completed in 8%. Thirty-five percent were multicenter trials. The five most frequent investigational categories were immune modulating drugs (266 trials (20%)), unconventional medicine (167 trials (13%)), antimalarial drugs (118 trials (9%)), antiviral drugs (100 trials (8%)) and respiratory adjuncts (78 trials (6%)). The five most frequently tested uni-modal interventions were: chloroquine/hydroxychloroquine (113 trials with 199,841 participants); convalescent plasma (64 trials with 11,840 participants); stem cells (51 trials with 3,370 participants); tocilizumab (19 trials with 4,139 participants) and favipiravir (19 trials with 3,210 participants).

Conclusion

An extraordinary number of randomized clinical trials investigating COVID-19 management have been initiated with a multitude of medical preventive, adjunctive and treatment modalities. Blinding will be used in only 47% of trials, which may have influence on future reported treatment effects. Fifty-seven percent of all trials will assess mortality as an outcome facilitating future meta-analyses.

Background

The novel corona virus (SARS-CoV-2) outbreak began in late December 2019 and rapidly spread across the globe critically impacting public health systems. SARS-CoV-2 is causing respiratory disease (COVID-19) ranging from asymptomatic cases and mild symptoms of upper airway infection to fulminant acute respiratory distress syndrome (ARDS), multi-organ failure and death [1]. This accelerating pandemic has inclined researchers around the world to accelerate investigative efforts to find effective and safe COVID-19 prevention and treatment options.

On January 30, 2020 the Emergency Committee convened by the World Health Organization (WHO) declared the COVID-19 outbreak a Public Health Emergency of International Concern (PHEIC) and has presented a collaborative research agenda with eight defined areas that should be prioritized during the early phase of the pandemic [2, 3]. The first wave of published evidence for treatment modalities relied primarily on observational studies and indirect evidence from adjacent fields [4]. Now countries and authorities have established modified fast track pathways to ethical and other approvals [5, 6], and journals have fast track publication processes, all enabling rapid conduction and publication of randomized clinical trials (RCTs) to ensure a second wave of high-quality evidence with proper assessment of benefits and harms [7, 8] (preprint). WHO has created a Global Research Roadmap homepage to facilitate and oversee that critical research is prioritized and implemented in the correct order [9].

Even though multiple versions of trial registration databases are readily available for download online [10–12], trialists may find it difficult to get an overview of the constantly evolving multitude of planned or ongoing studies. Therefore, we aim to provide a global snapshot overview of interventions and main methodological aspects of planned and initiated randomised clinical trials on COVID-19 prevention and treatment. To do so, we assess available trial registry entries from 33 clinical trial registries to June 23, 2020.

Methods

For this topical review, we identified trial registry entries from the datafile of June 23, 2020 provided by the COVID-19 section of the WHO International Clinical Trials Registry Platform (ICTRP), which included information from 10 different trial registries [13]. Further, we systematically searched these and 23 other national and international trial registries (S1 Appendix) that are listed in the Cochrane recommended list of Clinical Trial Registers provided by York Health Economics Consortium, University of York [14]. We searched on Title: “corona OR COVID OR sars-cov-2”. The final search was performed on June 23, 2020.

We included trial registry entries on randomized clinical trials investigating medical preventive, adjunct or supportive therapies and therapeutics for treatment of COVID-19. We included trial registry entries irrespective of participant age. Trials with non-random and single-arm designs were excluded. Trials assessing non-medical interventions were excluded. Trial registry entries were screened for inclusion and data were extracted by two authors independently (KZR or APHK and JL or OM) and discrepancies were handled by a senior author (APHK or OM). Data were extracted into Excel and tables were generated using formatted coding.

Outcomes

The primary outcome was to identify and explore COVID-19 prevention or treatment interventions in planned or ongoing randomized clinical trials. The secondary outcomes were: 1) recruitment status; 2) planned trial size; 3) blinding; 4) reporting of mortality as a primary or secondary outcome.

Data handling

Data on type of intervention, mortality assessment, blinding, trial size, multicenter registration, recruitment status and disease severity were extracted as it was reported in the trial registry entries. Mortality was extracted binary regardless of cause-specificity or timely differences. The clinical research phase was registered (phase 1–4 trials) and whenever an entry had multiple trial phases, we registered the highest. We reported the number of blinded parties registered in the trial registry entries, but not who was blinded. Disease severity was subsequently categorized as either prevention, mild/moderate and severe/hospitalized/ICU. Recruitment status was updated up to June 23, 2020. Trial registry entries were categorized into intervention subgroups based on therapeutic class or mechanism of action. Data are presented as numbers and percentages.

Results

We identified 4,040 trial registry entries and included 1,303 registered RCTs, originating from 71 different countries on 6 continents (Fig 1 and Table 1 and S2 and S3 Appendices). The vast majority of exclusions were due to single-group, observational and non-randomised designs, duplicates and testing of other interventions than COVID-19 treatment or prevention. Our database is available as a .csv file (S4 Appendix).

Table 1. Characteristics of therapeutic groups.

Trial intervention	Trial registry entries	Recruitment ongoing	Recruitment completed	Disease specification				Continents
				Prevention	Diagnosed/suspected COVID	Mild/moderate symptoms	Hospitalized/ severe/ ICU	Asia	Europe	North America	South America	Africa
	n	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)
All trials	1,303	708 (54%)	110 (8%)	160 (12%)	275 (21%)	203 (16%)	665 (51%)	556 (43%)	313 (24%)	290 (22%)	54 (4%)	48 (4%)
Unconventional medicine	167	76 (46%)	30 (18%)	13 (8%)	90 (54%)	25 (15%)	39 (23%)	158 (95%)	2 (1%)	1 (1%)	2 (1%)	3 (2%)
Antimalarial drugs	118	64 (54%)	7 (6%)	61 (52%)	21 (18%)	17 (14%)	19 (16%)	43 (36%)	26 (22%)	32 (27%)	6 (5%)	6 (5%)
Antiviral drugs	100	51 (51%)	13 (13%)	9 (9%)	21 (21%)	27 (27%)	43 (43%)	56 (56%)	10 (10%)	14 (14%)	8 (8%)	8 (8%)
Antimalarial and antibiotics/antiviral drugs in comparison or combination	46	23 (50%)	3 (7%)	6 (13%)	4 (9%)	10 (22%)	26 (57%)	15 (33%)	13 (28%)	11 (24%)	3 (7%)	3 (7%)
Antibodies	82	50 (61%)	7 (9%)	2 (2%)	5 (6%)	8 (10%)	67 (82%)	28 (34%)	13 (16%)	29 (35%)	9 (11%)	2 (2%)
Anti-IL-6	33	26 (79%)	-	-	2 (6%)	5 (15%)	26 (79%)	3 (9%)	16 (48%)	10 (30%)	1 (3%)	1 (3%)
Other immunotherapeutic drugs	151	93 (62%)	4 (3%)	5 (3%)	22 (15%)	18 (12%)	106 (70%)	43 (28%)	46 (30%)	49 (32%)	2 (1%)	2 (1%)
Respiratory adjuncts (inhaled, ventilator-related and gas-therapy)	78	43 (55%)	4 (5%)	1 (1%)	11 (14%)	11 (14%)	55 (71%)	20 (26%)	27 (35%)	30 (38%)	-	-
Dietary supplements	63	26 (41%)	12 (19%)	7 (11%)	15 (24%)	11 (17%)	30 (48%)	32 (51%)	13 (21%)	9 (14%)	2 (3%)	5 (8%)
Stem cells	51	24 (47%)	3 (6%)	1 (2%)	7 (14%)	2 (4%)	41 (80%)	25 (49%)	10 (20%)	10 (20%)	2 (4%)	1 (2%)
Vaccine	49	27 (55%)	-	44 (90%)	3 (6%)	1 (2%)	1 (2%)	15 (31%)	15 (31%)	7 (14%)	2 (4%)	5 (10%)
Anti-inflammatory drugs	45	31 (69%)	4 (9%)	-	14 (31%)	6 (13%)	25 (56%)	20 (44%)	14 (31%)	10 (22%)	-	-
Glucocorticoids	34	18 (53%)	5 (15%)	-	5 (15%)	8 (24%)	21 (62%)	12 (35%)	15 (44%)	4 (12%)	3 (9%)	-
Anticoagulants	32	20 (63%)	-	-	3 (9%)	5 (16%)	24 (75%)	5 (16%)	11 (34%)	11 (34%)	3 (9%)	-
Antihypertensives	26	16 (62%)	1 (4%)	1 (4%)	6 (23%)	3 (12%)	16 (62%)	3 (12%)	9 (35%)	8 (31%)	2 (8%)	2 (8%)
Antibiotics/antifungal drugs	27	13 (48%)	4 (15%)	1 (4%)	9 (33%)	6 (22%)	11 (41%)	8 (30%)	10 (37%)	7 (26%)	1 (4%)	1 (4%)
Other drug combinations	79	46 (58%)	5 (6%)	3 (4%)	17 (22%)	18 (23%)	41 (52%)	26 (33%)	32 (41%)	9 (11%)	3 (4%)	7 (9%)
Other drugs	122	61 (50%)	8 (7%)	6 (5%)	20 (16%)	22 (18%)	74 (61%)	44 (36%)	31 (25%)	39 (32%)	5 (4%)	2 (2%)

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Interventional characteristics

The 1303 trial registry entries included 381 different single interventions and 126 combinations or multiple comparisons (S3 Appendix).

Trial registry entries were categorized into 18 different therapeutic groups (Tables 1–3). The five most frequent investigational categories were immune modulating drugs (266 trials (20%)), unconventional medicine (167 trials (13%)), antimalarial drugs (118 trials (9%)), antiviral drugs (100 trials (8%)) and respiratory adjuncts (78 trials (6%)).

Table 3. Characteristics of therapeutic groups.

Trial intervention	Trial registry entries	Sample size				Total participants	Mortality outcome
		< 50	50–199	200–999	≥1000		Primary	Secondary	Participants assessed for mortality
	n	n (%)	n (%)	n (%)	n (%)	n	n (%)	n (%)	n (%)
All trials	1,303	224 (17%)	564 (43%)	392 (30%)	123 (9%)	611,364	278 (21%)	470 (36%)	317,099 (52%)
Unconventional medicine	167	20 (12%)	110 (66%)	33 (20%)	4 (2%)	47,232	12 (7%)	26 (16%)	6,018 (13%)
Antimalarial drugs	118	6 (5%)	27 (23%)	54 (46%)	31 (26%)	200,583	16 (14%)	41 (35%)	51,951 (26%)
Antiviral drugs	100	16 (16%)	57 (57%)	23 (23%)	4 (4%)	19,554	8 (8%)	35 (35%)	7,303 (37%)
Antimalarial and antibiotics/antiviral drugs in comparison or combination	46	2 (4%)	13 (28%)	18 (39%)	13 (28%)	36,069	18 (39%)	14 (30%)	32,062 (89%)
Antibodies	82	17 (21%)	43 (52%)	19 (23%)	3 (4%)	15,006	30 (37%)	33 (40%)	12,794 (85%)
Anti-IL-6	33	5 (15%)	12 (36%)	16 (48%)	-	6,485	9 (27%)	22 (67%)	6,215 (96%)
Other immunotherapeutic drugs	151	39 (26%)	68 (45%)	42 (28%)	2 (1%)	25,122	37 (25%)	70 (46%)	19,155 (76%)
Respiratory adjuncts (inhaled, ventilator-related and gas-therapy)	78	17 (22%)	28 (36%)	32 (41%)	1 (1%)	18,480	17 (22%)	33 (42%)	15,082 (82%)
Dietary supplements	63	12 (19%)	29 (46%)	15 (24%)	7 (11%)	18,337	10 (16%)	27 (43%)	13,558 (74%)
Stem cells	51	28 (55%)	20 (39%)	3 (6%)	-	3,370	16 (31%)	14 (27%)	2,124 (63%)
Vaccine	49	1 (2%)	7 (14%)	16 (33%)	25 (51%)	76,922	3 (6%)	15 (31%)	32,920 (43%)
Anti-inflammatory drugs	45	9 (20%)	19 (42%)	12 (27%)	5 (11%)	17,305	9 (20%)	18 (40%)	15,257 (88%)
Glucocorticoids	34	3 (9%)	12 (35%)	18 (53%)	1 (3%)	8,503	10 (29%)	16 (47%)	6,225 (73%)
Anticoagulants	32	2 (6%)	12 (38%)	14 (44%)	4 (13%)	15,348	13 (41%)	13 (41%)	14,090 (92%)
Antihypertensives	26	3 (12%)	7 (27%)	14 (54%)	2 (8%)	18,710	12 (46%)	9 (35%)	17,474 (93%)
Antibiotics/antifungal drugs	27	6 (22%)	8 (30%)	12 (44%)	1 (4%)	8,199	4 (15%)	11 (41%)	5,793 (71%)
Other drug combinations	79	9 (11%)	29 (37%)	22 (28%)	19 (24%)	56,271	20 (25%)	34 (43%)	44,633 (79%)
Other drugs	122	29 (24%)	63 (52%)	29 (24%)	1 (1%)	19,868	34 (28%)	39 (32%)	14,445 (73%)

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Twenty-two specific therapeutic medical interventions with seven or more trial registry entries per intervention were described separately (Table 4). The five most frequently tested uni-modal interventions were: chloroquine/hydroxychloroquine (113 trials with 199,841 participants); convalescent plasma (64 trials with 11,840 participants); stem cells (51 trials with 3,370 participants); tocilizumab (19 trials with 4,139 participants) and favipiravir (19 trials with 3,210 participants).

Table 4. Characteristics of specific interventions reported in seven or more trial registry entries.

A
Trial intervention	Trial registry entries	Recruitment ongoing	Recruitment completed	Disease specification				Continents					Multicenter
				Prevention	Diagnosed/suspected COVID	Mild/moderate symptoms	Hospitalized/severe/ ICU	Asia	Europe	North America	South America	Africa
	n	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)
Chloroquine	113	62 (55%)	7 (6%)	60 (53%)	21 (19%)	15 (13%)	17 (15%)	42 (37%)	24 (21%)	32 (28%)	6 (5%)	4 (4%)	36 (32%)
Convalescent Plasma	64	38 (59%)	5 (8%)	1 (2%)	5 (8%)	5 (8%)	53 (83%)	23 (36%)	11 (17%)	19 (30%)	9 (14%)	2 (3%)	22 (34%)
Stem cells	51	24 (47%)	3 (6%)	1 (2%)	7 (14%)	2 (4%)	41 (80%)	25 (49%)	10 (20%)	10 (20%)	2 (4%)	1 (2%)	9 (18%)
Chloroquine + other	30	17 (57%)	4 (13%)	4 (13%)	5 (17%)	4 (13%)	17 (57%)	12 (40%)	14 (47%)	2 (7%)	0	0	17 (57%)
Chloroquine / Azithromycin	22	9 (41%)	0	2 (9%)	2 (9%)	5 (23%)	13 (59%)	4 (18%)	6 (27%)	8 (36%)	3 (14%)	1 (5%)	7 (32%)
Tocilizumab	19	15 (79%)	0	0	1 (5%)	3 (16%)	15 (79%)	3 (16%)	9 (47%)	4 (21%)	1 (5%)	0	11 (58%)
Favipiravir	19	10 (53%)	2 (11%)	0	2 (11%)	10 (53%)	7 (37%)	13 (68%)	2 (11%)	2 (11%)	0	2 (11%)	7 (37%)
BCG vaccine	17	12 (71%)	0	17 (100%)	0	0	0	3 (18%)	8 (47%)	1 (6%)	2 (12%)	2 (12%)	14 (82%)
Ivermectin	17	9 (53%)	2 (12%)	2 (12%)	2 (12%)	7 (41%)	6 (35%)	7 (41%)	4 (24%)	0	4 (24%)	2 (12%)	5 (29%)
Prone position	16	13 (81%)	0	0	0	3 (19%)	13 (81%)	1 (6%)	6 (38%)	9 (56%)	0	0	7 (44%)
Colchicine	16	15 (94%)	1 (6%)	0	5 (31%)	4 (25%)	7 (44%)	4 (25%)	7 (44%)	4 (25%)	0	0	7 (44%)
Azithromycin	15	8 (53%)	2 (13%)	0	5 (33%)	3 (20%)	7 (47%)	4 (27%)	7 (47%)	2 (13%)	1 (7%)	1 (7%)	6 (40%)
Enoxaparin	11	7 (64%)	0	0	0	4 (36%)	7 (64%)	2 (18%)	4 (36%)	3 (27%)	2 (18%)	0	5 (45%)
Vitamin C	10	2 (20%)	4 (40%)	0	1 (10%)	1 (10%)	8 (80%)	6 (60%)	0	3 (30%)	0	0	1 (10%)
Nitric Oxide	10	5 (50%)	0	1 (10%)	1 (10%)	3 (30%)	5 (50%)	0	0	10 (100%)	0	0	2 (20%)
Ozone autohemotherapy	9	4 (44%)	2 (22%)	0	2 (22%)	1 (11%)	6 (67%)	4 (44%)	4 (44%)	1 (11%)	0	0	2 (22%)
INF-Beta	9	5 (56%)	2 (22%)	0	4 (44%)	1 (11%)	4 (44%)	8 (89%)	1 (11%)	0	0	0	2 (22%)
Glucocorticoid	9	5 (56%)	1 (11%)	0	1 (11%)	1 (11%)	7 (78%)	5 (56%)	2 (22%)	0	2 (22%)	0	3 (33%)
Vitamin D	8	5 (63%)	0	0	2 (25%)	2 (25%)	4 (50%)	1 (13%)	5 (63%)	1 (13%)	1 (13%)	0	3 (38%)
Sarilumab	8	6 (75%)	0	0	1 (13%)	2 (25%)	5 (63%)	0	6 (75%)	2 (25%)	0	0	2 (25%)
Vitamin A	7	2 (29%)	2 (29%)	0	2 (29%)	1 (14%)	4 (57%)	6 (86%)	0	0	0	1 (14%)	1 (14%)
Heparin	7	5 (71%)	0	0	0	0	7 (100%)	0	1 (14%)	5 (71%)	0	0	4 (57%)
B
Trial intervention	Trial registry entries	No. of blinded parties					Sample size				Total participants	Mortality outcome
		None (open label)	1	2	3	4	< 50	50–199	200–999	≥1000		Primary	Secondary	Participants assessed for mortality
	n	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)	n	n (%)	n (%)	n (%)
Chloroquine	113	41 (36%)	9 (8%)	23 (20%)	9 (8%)	24 (21%)	5 (4%)	25 (22%)	52 (46%)	31 (27%)	199,841	16 (14%)	39 (35%)	51,829 (26%)
Convalescent Plasma	64	37 (58%)	3 (5%)	12 (19%)	7 (11%)	4 (6%)	12 (19%)	33 (52%)	17 (27%)	2 (3%)	11,840	27 (42%)	25 (39%)	10,331 (87%)
Stem cells	51	17 (33%)	4 (8%)	10 (20%)	5 (10%)	10 (20%)	28 (55%)	20 (39%)	3 (6%)	0	3,370	16 (31%)	14 (27%)	2,124 (63%)
Chloroquine + other	30	21 (70%)	0	3 (10%)	2 (7%)	3 (10%)	0	9 (30%)	8 (27%)	13 (43%)	46,944	11 (37%)	12 (40%)	39,314 (84%)
Chloroquine / Azithromycin	22	13 (59%)	1 (5%)	2 (9%)	2 (9%)	4 (18%)	2 (9%)	5 (23%)	11 (50%)	4 (18%)	12,186	5 (23%)	8 (36%)	9,960 (82%)
Tocilizumab	19	10 (53%)	0	7 (37%)	0	1 (5%)	1 (5%)	9 (47%)	9 (47%)	0	4,139	7 (37%)	12 (63%)	4,139 (100%)
Favipiravir	19	14 (74%)	0	4 (21%)	0	0	2 (11%)	12 (63%)	4 (21%)	1 (5%)	3,210	0	8 (42%)	1,232 (38%)
BCG vaccine	17	2 (12%)	4 (24v	3 (18%)	0	8 (47%)	0	0	4 (24%)	13 (76%)	27,262	1 (6%)	10 (59%)	15,616 (57%)
Ivermectin	17	5 (29%)	1 (6%)	7 (41%)	1 (6%)	3 (18%)	3 (18%)	12 (71%)	2 (12%)	0	1,752	1 (6%)	1 (6%)	326 (19%)
Prone position	16	12 (75%)	3 (19%)	1 (6%)	0	0	0	5 (31%)	11 (69%)	0	4,228	8 (50%)	5 (31%)	3,612 (85%)
Colchicine	16	9 (56%)	2 (13%)	3 (19%)	1 (6%)	1 (6%)	1 (6%)	8 (50%)	3 (19%)	4 (25%)	12,268	4 (25%)	6 (38%)	11,624 (95%)
Azithromycin	15	10 (67%)	1 (7%)	1 (7%)	1 (7%)	2 (13%)	1 (7%)	6 (40%)	7 (47%)	1 (7%)	5,591	3 (20%)	8 (53%)	4,893 (88%)
Enoxaparin	11	10 (91%)	1 (9%)	0	0	0	1 (9%)	4 (36%)	3 (27%)	3 (27%)	6,134	5 (45%)	4 (36%)	6,014 (98%)
Vitamin C	10	2 (20%)	1 (10%)	3 (30%)	1 (10%)	3 (30%)	2 (20%)	5 (50%)	3 (30%)	0	1,706	1 (10%)	6 (60%)	1,490 (87%)
Nitric Oxide	10	5 (50%)	1 (10%)	1 (10%)	1 (10%)	2 (20%)	4 (40%)	0	6 (60%)	0	2,082	0	7 (70%)	1,292 (62%)
Ozone autohemotherapy	9	3 (33%)	4 (44%)	1 (11%)	0	0	2 (22%)	6 (67%)	1 (11%)	0	872	1 (11%)	3 (33%)	470 (54%)
INF-Beta	9	4 (44%)	0	2 (22%)	1 (11%)	1 (11%)	3 (33%)	3 (33%)	3 (33%)	0	1,348	1 (11%)	4 (44%)	630 (47%)
Glucocorticoid	9	5 (56%)	1 (11%)	0	0	1 (11%)	1 (11%)	4 (44%)	4 (44%)	0	1,542	3 (33%)	4 (44%)	1,342 (87%)
Vitamin D	8	3 (38%)	0	2 (25%)	0	3 (38%)	0	3 (38%)	2 (25%)	3 (38%)	4,487	4 (50%)	3 (38%)	4,423 (99%)
Sarilumab	8	6 (75%)	0	0	0	2 (25%)	1 (13%)	2 (25%)	5 (63%)	0	1,726	2 (25%)	5 (63%)	1,486 (86%)
Vitamin A	7	5 (71%)	0	1 (14%)	1 (14%)	0	2 (29%)	3 (43%)	2 (29%)	0	1,089	0	2 (29%)	405 (37%)
Heparin	7	2 (29%)	2 (29%)	0	1 (14%)	2 (29%)	0	3 (43%)	3 (43%)	1 (14%)	4,454	3 (43%)	3 (43%)	4,354 (98%)

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Methodological characteristics

Recruitment was registered as ongoing in 708 (54%) trial registry entries and completed in 110 (8%) (Table 1), of which 97 (88%) were from Iran. Blinded setups were planned in 607 (47%) trial registry entries (Table 2). A total of 458 (35%) trial registry entries were categorized as multicenter investigations (Table 2). The planned sample size was >200 participants in 515 (40%) entries and the total number of participants planned for enrolment was 611,364 (Table 3). Mortality was planned to be assessed as a primary or secondary outcome in 748 (57%) trial registry entries with a total of 317,099 participants (Table 3). Participants were included regardless of sex in 1296 (99%) entries. Participants under 18 years of age were included in 95 (7%) entries.

Table 2. Characteristics of therapeutic groups.

Trial intervention	Trial registry entries	Clinical research phase				No. of blinded parties					Multicenter
		1	2	3	4	None (open label)	1	2	3	4
	n	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)
All trials	1,303	124 (10%)	407 (31%)	423 (32%)	89 (7%)	601 (46%)	117 (9%)	230 (18%)	98 (8%)	162 (12%)	458 (35%)
Unconventional medicine	167	25 (15%)	17 (10%)	41 (25%)	4 (2%)	76 (46%)	9 (5%)	33 (20%)	11 (7%)	5 (3%)	41 (25%)
Antimalarial drugs	118	17 (14%)	20 (17%)	55 (47%)	16 (14%)	43 (36%)	9 (8%)	24 (20%)	10 (8%)	24 (20%)	37 (31%)
Antiviral drugs	100	8 (8%)	23 (23%)	46 (46%)	5 (5%)	44 (44%)	10 (10%)	25 (25%)	6 (6%)	8 (8%)	40 (40%)
Antimalarial and antibiotics/antiviral drugs in comparison or combination	46	4 (9%)	9 (20%)	26 (57%)	3 (7%)	28 (61%)	2 (4%)	5 (11%)	6 (13%)	5 (11%)	21 (46%)
Antibodies	82	5 (6%)	40 (49%)	26 (32%)	-	41 (50%)	3 (4%)	20 (24%)	7 (9%)	10 (12%)	31 (38%)
Anti-IL-6	33	1 (3%)	19 (58%)	11 (33%)	2 (6%)	17 (52%)	-	9 (27%)	1 (3%)	5 (15%)	15 (45%)
Other immunotherapeutic drugs	151	17 (11%)	74 (49%)	42 (28%)	8 (5%)	69 (46%)	9 (6%)	25 (17%)	11 (7%)	29 (19%)	76 (50%)
Respiratory adjuncts (inhaled, ventilator-related and gas-therapy)	78	3 (4%)	18 (23%)	13 (17%)	1 (1%)	38 (49%)	19 (24%)	8 (10%)	3 (4%)	5 (6%)	23 (29%)
Dietary supplements	63	5 (8%)	15 (24%)	21 (33%)	4 (6%)	25 (40%)	5 (8%)	12 (19%)	6 (10%)	12 (19%)	12 (19%)
Stem cells	51	6 (12%)	28 (55%)	6 (12%)	-	17 (33%)	4 (8%)	10 (20%)	5 (10%)	10 (20%)	9 (18%)
Vaccine	49	7 (14%)	16 (33%)	18 (37%)	5 (10%)	3 (6%)	11 (22%)	14 (29%)	3 (6%)	16 (33%)	29 (59%)
Anti-inflammatory drugs	45	5 (11%)	17 (38%)	17 (38%)	3 (7%)	21 (47%)	6 (13%)	8 (18%)	3 (7%)	4 (9%)	14 (31%)
Glucocorticoids	34	2 (6%)	9 (26%)	14 (41%)	5 (15%)	19 (56%)	4 (12%)	4 (12%)	2 (6%)	3 (9%)	13 (38%)
Anticoagulants	32	-	8 (25%)	14 (44%)	7 (22%)	22 (69%)	6 (19%)	1 (3%)	1 (3%)	2 (6%)	18 (56%)
Antihypertensives	26	4 (15%)	12 (46%)	4 (15%)	4 (15%)	12 (46%)	2 (8%)	3 (12%)	4 (15%)	4 (15%)	8 (31%)
Antibiotics/antifungal drugs	27	-	10 (37%)	14 (52%)	2 (7%)	15 (56%)	1 (4%)	4 (15%)	3 (11%)	4 (15%)	9 (33%)
Other drug combinations	79	6 (8%)	23 (29%)	33 (42%)	11 (14%)	55 (70%)	7 (9%)	6 (8%)	4 (5%)	3 (4%)	30 (38%)
Other drugs	122	9 (7%)	49 (40%)	22 (18%)	9 (7%)	56 (46%)	10 (8%)	19 (16%)	12 (10%)	13 (11%)	32 (26%)

Open in a new tab

Geographical characteristics

The five countries with the highest number of registered trial registry entries were The United States (241 trials) accounting for 109,102 (18%) participants, China (239 trials) accounting for 64,707 (10%) participants, Iran (193 trials) accounting for 21,488 (4%) participants, Spain (80 trials) accounting for 28,625 (5%) participants and France (69 trials) accounting for 30,791 (5%) participants.

Discussion

From January 23 to June 23, 2020 a total of 1,303 randomized clinical trials were registered on the 33 trial registries searched, investigating 381 therapeutics or adjunct therapies in treatment of COVID-19. The five most frequent investigational categories were immune modulating drugs, unconventional medicine, antimalarial drugs, antiviral drugs and respiratory adjuncts. Target sizes were above 200 participants in 40%, blinding was used in 47% and mortality was registered as an outcome in 57% of trial registry entries.

We found a steep increase in trial registry entries on RCTs, currently focusing on immune modulating-, antimalarial- and antiviral drugs. Ongoing trials initiated before the pandemic and now including COVID-19 patients are not described in this review, but can provide important information on treatment modalities and should be continued [15].

Early trial registry entries from Asia generally had smaller trial sizes. Small trial sizes can lead to overestimated intervention effects and underestimated harms [16]. Entries in the Iranian Registry of Clinical Trials (IRCT) accounted for 15% of all registered RCTs, but only for 4% of all planned participants. Maybe because of the generally smaller trial sizes in entries from the IRCT, this registry contributed with 85% of all trials that had completed recruitment per June 23.

Though there is no firm evidence that lack of blinding affects estimates of mortality [17], we consider blinding as an important factor in COVID-19 trial designs. Especially as 79% of trial registry entries had other primary outcomes than mortality and many were preventive with subjective and patient-reported outcomes such as self-assessed symptom severity where bias, including lack of blinding, that can exaggerate intervention effects [18].

The number of trial registry entries from Europe and the US has been rapidly increasing and are generally of larger sample sizes. Further, international multicenter trials are planned to include huge numbers of participants–currently eight with above 10,000 participants. Collaboration to compile evidence in meta-analyses and network meta-analyses in order to achieve higher levels of evidence has been initiated, such as The Living Mapping and Living Systematic Review of COVID-19 Studies [19, 20]. These websites can be very useful in finding trial registry entries for specific pharmacological treatment categories and dynamic changes in activity. The current review builds upon these works by providing a per June 23 updated snapshot overview, with inclusion of trial registry entries from an additional 22 trial registries and removal of duplicates, on research activity for both treatment categories and specific drugs with details on mortality assessment and blinding.

COVID-19 mortality rates and overcrowded intensive care units underline the importance of identifying therapeutics and adjunct therapies that can reduce mortality and shorten hospital admissions, and trials should assess these outcomes whenever appropriate. Accordingly, a core outcome set qualified by a Delphi process has been developed for clinical trials on COVID-19, which included all-cause mortality for ordinary, severe and critical COVID-19 infection [21]. RCTs on COVID-19 treatment have been criticized for not being sufficiently powered to assess mortality [22], which seem justifiable as a large part of trial registry entries with small trial sizes used mortality as an outcome. Mortality was an outcome in 57% of the included trial registry entries, which is encouraging although improvement is possible. Mortality as a primary outcome requires larger sample sizes, which can affect the conductibility of some trials, but even inclusion of mortality as a secondary or exploratory outcome can be important, as such data will add essential information for future meta-analyses. We endorse adherence to the core outcome set, as it will facilitate homogeneous outcome reporting and improve the quality of evidence in up-coming meta-analyses and subsequent evidence-based recommendations [21, 23].

Clinical research is time consuming and costly. In time of a pandemic, worldwide research collaboration is encouraged [24]. Several cases of such partnerships have been developed including the Adaptive COVID-19 Treatment Trial (ACTT) that investigate remdesivir for COVID-19 treatment in up to 75 study locations [25], and the active recruiting WHO initiated Solidarity trial collaboration that tests four different active treatments (remdesivir, chloroquine/hydroxy-chloroquine, lopinavir + ritonavir, or lopinavir + ritonavir + interferon beta-1a) versus local standard of care [26]. According to the WHO homepage, July 1, 2020, 39 countries have approvals to begin recruiting and 5,500 participants have already been recruited in 21 countries [26].

Strengths and limitations

The comprehensive and structured search in public registries, double screening for inclusion, transfer of trial registry entry data from original registers, independent parallel screening and extraction and assessment of blinding status are strengths of this study. Further, we updated our search, the status of recruitment and cancellations just prior to submission. We screened for registrations in multiple registers, but we may have missed some due to incomplete, late, or heterogeneous data registration in trial registries. Some included trial registry entries may subsequently be ethically denied, retracted, or fail to reach planned trial size. Altogether, this means that our results may overestimate the number of participants that will be randomized to each intervention and the number of trials that will reach publication.

This is a dynamic and rapidly developing research field and with the present study, we only provide a snapshot overview of trial registry entries of June 23, 2020. We however, believe that the overview of investigated interventions and quantification of several methodological parameters, not provided elsewhere, have merits. More adaptable inventories for finding trial registry entries of specific interventions are available elsewhere [11, 12, 27]. We reviewed trial registry entries and not actual trial protocols, mainly because these were not always available. Evaluation of trial protocols could have provided more detailed information on trial methodology and outcomes and we endorse recent suggestions of public access to all trial protocols concomitant with trial registration [28]. Categorisation of interventions is to some extent arbitrary as some drugs fit into more categories. We chose to categorize trials that tested multiple interventions in factorial design or as multimodal regimens into one heterogenic group to maintain overview.

Perspective

An encouraging amount of research has been launched to fight SARS-CoV-2. We expect trialists can use this review to get an overview of the ongoing research related to COVID-19 treatment which could help prioritize and design future clinical trials.

Conclusion

An extraordinary number of randomized clinical trials investigating COVID-19 management have been initiated with a multitude of medical preventive, adjunctive and treatment modalities. Blinding was used in only 47% of trial registry entries, which may influence future reported treatment effects. Fifty-seven percent of all trials will assess mortality as an outcome facilitating future meta-analyses. Large multicenter and international collaborative trials are being prioritized and many are currently recruiting.

Supporting information

S1 Appendix. Trial registration sites.

(PDF)

Click here for additional data file.^{(116.8KB, pdf)}

S2 Appendix. Excluded trial registry entries.

(PDF)

Click here for additional data file.^{(6.8MB, pdf)}

S3 Appendix. Included trial trial registry entries.

(PDF)

Click here for additional data file.^{(4.6MB, pdf)}

S4 Appendix. Database.

(CSV)

Click here for additional data file.^{(7.2MB, csv)}

S1 Checklist. PRISMA 2009 checklist.

(DOC)

Click here for additional data file.^{(66KB, doc)}

Data Availability

All relevant data are within the paper and its Supporting Information file.

Funding Statement

The authors received no specific funding for this work.

References

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3.WHO and Global Research Collaboration for Infectious Disease Preparedness. COVID 19 Public Health Emergency of International Concern (PHEIC). Global research and innovation forum: towards a research roadmap 12 February 2020. Available from: https://www.who.int/blueprint/priority-diseases/key-action/Global_Research_Forum_FINAL_VERSION_for_web_14_feb_2020.pdf?ua=1.
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PLoS One. doi: 10.1371/journal.pone.0237903.r001

Decision Letter 0

Lisa Susan Wieland

9 Jul 2020

PONE-D-20-13626

A systematic review of submitted protocols for randomized clinical trials investigating COVID-19 medical prevention and treatment

PLOS ONE

Dear Dr. Karlsen,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

A key issue noted by both reviewers is the incorrect reference to trial protocols when the meaning is actually trial registrations. Both reviewers also have additional comments which should be responded to.

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(2) https://www.iddo.org/research-themes/covid-19/live-systematic-clinical-trial-review.

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Reviewer's Responses to Questions

Comments to the Author

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Reviewer #1: Yes

Reviewer #2: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: N/A

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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5. Review Comments to the Author

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Reviewer #1: Thank you for the opportunity to review this manuscript.

The manuscript presents a rigorous study examining which clinical studies had been registered in 32 different registries. The manuscript presents the planned size, planned blinding, and whether mortality was a planned outcome for the identified planned studies. The authors suggest that the results of the study can be used to plan future studies and set research priorities. Unfortunately, considering the rapidly evolving situation I am afraid the findings might already be outdated. Additionally, several regularly updated alternatives exist, e.g. Cochranes “Covid-19 Study Register” (https://covid-19.cochrane.org/?pn=1), EBM Datalabs “Covid-19 TrialsTracker” (http://covid19.trialstracker.net/), and COVID-Evidence (https://covid-evidence.org/database)

Thus, I am afraid the reviewed manuscript will not be able to contribute substantially to priority setting or planning of future research activities: I do, however, find the methods to be technically sound and that the data supports the conclusions. My comments to the manuscript are presented below:

Major issues:

Introduction:

• Several resources that track planned and completed trials are available online (including, but not limited to, the ones mentioned above). These should be mentioned in the introduction and it should be clarified how the presented study contributes.

• Throughout the manuscript, the authors refer to protocols. A clinical study protocol is a quite elaborate document, that is e.g. submitted to ethical committees or institutional review boards to get ethical approval. Protocols are sometimes, but not always, published, but would not necessarily be available from trial registries, so it is my impression that the authors are in fact referring to trial registry entries. If the authors have in fact obtained protocols for all included trials, they should explain how these were obtained. Otherwise, I suggest changing the wording from protocol to trial registry entry throughout the text.

Methods:

• It is not explained why blinding is considered of particular importance. I would probably expect blinding to be less important for relatively objective outcomes such as overall mortality (although blinding could be very important for cause-specific mortality). Perhaps the authors could elaborate on the choice of outcome.

o Additionally, in the results, the authors use the categories “Open label, single blind, double blind, triple blind, and quadruple blind”. It is not clear what these different categories describe, and research has shown that e.g. “double blind” is an ambiguous term[1,2]. The authors should explain how they operationalise blinding in the methods section.

• Regarding mortality as an outcome: Are the authors only looking at overall mortality or also cause-specific? This should be elaborated on.

Discussion:

• Perspective: as mentioned above, I am afraid that the results of the study may already be outdated and more up-to-date resources exist.

Minor issues:

Throughout the text the terms blinding, and masking are used interchangeably. If the authors believe these words are not describing the same this should be elaborated on, otherwise the text should be revised so only one term is used.

Abstract

• In conclusions the authors write: “a second wave of higher level evidence” – it is unclear what the first wave was and thus what “higher” is relative to. This is explained in the introduction but is not mentioned in the abstract. Thus, I suggest rephrasing.

Background:

• First paragraph: the authors write: “symptoms ranging from mild symptoms of upper airway infection to …” – I believe many reports state that a high proportion of people infected with SARS-CoV-2 are completely asymptomatic. Perhaps the authors could consider mentioning this.

• Second paragraph: the authors write: “… to ensure a second wave of high-quality evidence with proper assessment of safety and efficacy measures” – I would suggest avoiding the term “safety” as this term tends to underplay harms and convey the idea that drugs have no, or non-important, side effects. I would suggest using “proper assessment of benefits and harms” – however, I am aware that this is not universally agreed upon, so just a suggestion.

Methods:

• Data handling: The authors refer to “trial phase” – it is not immediately clear to me what they are referring to here – I assume it is the phases of clinical research, but some trials have multiple phases (e.g. double-blind and open-label), so perhaps the authors could elaborate a bit.

Results:

• First paragraph: The authors exclude a high proportion of identified studies; I would suggest mentioning the main reasons for exclusion, although these are also available from the PRISMA flowchart

• Table 1 and Table 2: I suggest indenting the different types of interventions under “All trials” to make the table more legible.

• Table 4a: The recruiting / completed variable is somewhat confusing. Completed could easily be interpreted as “trial completed” rather than “recruiting completed”.

Discussion:

• First paragraph: The first sentence is perhaps a bit too strongly worded, 770 RCTs were registered on the trial registries searched, there might be trials registered elsewhere.

• Second paragraph, second line: delete “from” in “ongoing trials initiated from before the pandemic”.

• Second paragraph, fourth line: Rephrase the following sentence “China published 30% of the protocols”. The trials were not registered by China but from China. Also again, these are not published protocols but registry entries.

• Perhaps mention that such initiatives exist, e.g. the Living Meta-analysis from Cochrane France and others: https://covid-nma.com/

• Strengths and limitations: It is not mentioned in “methods” that data was extracted in duplicate.

• Strengths and limitations: The authors use the term “quality parameters”. Firstly, it is unclear to me what this refers to, I suppose blinding but that is only one parameter. Secondly, I would suggest avoiding the term “quality” which is somewhat normative and just call it blinding status instead.

• Strengths and limitations: I am unsure why including “unconventional medicine” would be controversial, it is an important part of the narrative of the research being conducted.

Supplementary information:

Appendix 2 and appendix 3 are called “Excluded articles” and “included articles”, however the unit of analysis is not articles but registry entries.

References

1 Hróbjartsson A, Pildal J, Chan A-W, et al. Reporting on blinding in trial protocols and corresponding publications was often inadequate but rarely contradictory. J Clin Epidemiol 2009;62:967–73. doi:10.1016/j.jclinepi.2009.04.003

2 Devereaux PJ, Manns BJ, Ghali WA, et al. Physician Interpretations and Textbook Definitions of Blinding Terminology in Randomized Controlled Trials. JAMA 2001;285:2000–3. doi:10.1001/jama.285.15.2000

Reviewer #2: This manuscript describes the results of a systematic search for registered drug trials in the WHO trial registry that assess prevention or treatment for COVID-19. This is important to provide an overview of ongoing research, as well as its characteristics and quality. The authors assess kkey components of the trials, such as number of participants, outcome measures, blinding, status for recruiting, etc.

Overall, the methods and results are clearly presented and the authors use blinded data-extraction, a systematic search strategy, present a PRISMA flow-chart with reasons for exclusions, etc.

My main concern is that the authors have likely not, as stated in the manuscript, assessed the actual protocols for the trials. Trial registries generally do not included detailed protocols but a set of key pieces of information, which is a pity. Lots of important information is missing that would allow a more thorough assessment of the quality of the ongoing trials than just binding, e.g. by applying the Cochrane risk of bias tool and assess whether the randosmisation process was adequate and likely to produce comparable groups. Given that I am correct about this, it might be necessary to change the terminology of the manuscript and explain that it is an evaluation of clinical trial registry forms rather than protocols and perhaps even use this to push for requirements to publish the full protocol along with the trial registry forms.

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Reviewer #1: Yes: Asger Sand Paludan-Müller

Reviewer #2: Yes: Karsten Juhl Jørgensen

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PLoS One. 2020 Aug 20;15(8):e0237903. doi: 10.1371/journal.pone.0237903.r002

Author response to Decision Letter 0

21 Jul 2020

15th of July 2020

Response to editor

Dear editor,

Thank you very much for considering our manuscript for publication and for your thorough comments. We have been able to address all comments/concerns, and hope you agree that the manuscript has improved considerably. We have inserted the reviewer comments below, and will hereby address their points one by one, with our response in blue font. In addition, a copy of the manuscript with “track changes” will be uploaded. Text changes in the manuscript are written in red font.

Kind regards,

On behalf of the authors:

Dr. Anders Karlsen, MD, PhD

General comment.

Thank you for stating that "Collaboration to compile evidence in meta-analyses and network meta-analyses in order to achieve higher levels of evidence has been initiated, such as The Living Mapping and Living Systematic Review of COVID-19 Studies [19-20].". Please elaborate on how your work builds upon these similar previously published works. Please provide this information in your discussion.

Author response: Thank you for this comment. These websites have evolved towards more detail since our first submission and now provides important information on COVID-19 research activity. Still, the overview per July 21 on https://www.iddo.org/tool/covid-19-clinical-trials-interactive-tool is limited to 567 prospective trials and https://covid-nma.com/dataviz/# does not provide information on blinding, mortality. Further, the covid-nma overview function is limited to treatment categories and not specific interventions as we report in table 4. Further, by checking registry sites and manually screening our database we found and excluded 126 duplicate registry entries with 95,386 participants specifically from the ICTRP. In the https://covid-nma.com/dataviz/# we find duplicates, such as EUCTR-2020-001200-42-DK/NCT04321096 and ISRCTN14326006/NCT04374942 which may lead to overestimation of research activity. We send an email notification regarding this issue, but chose not to comment in the manuscript as they may choose to remove duplicates.

We added to the discussion:

”These websites can be very useful in finding trial registry entries for specific pharmacological treatment categories and dynamic changes in activity. The current review builds upon these works by providing a per June 23 updated snapshot overview, with inclusion of trial registry entries from an additional 22 trial registries and removal of duplicates, on research activity for both treatment categories and specific drugs with details on mortality assessment and blinding.” (page 13, line 27-31).

Further we added to the strength and limitation section:

Reviewer #1: Thank you for the opportunity to review this manuscript.

Author response: Thank you for thoroughly revising our manuscript. We agree that this study presents an overview of a dynamic research area, and in order to present the most relevant results, we have updated the manuscript with a new search on June 23, 2020.

Major issues:

Introduction:

Author response: The meta-overview of trial databases provided by The Global Health Network that sums up all these resources has been added as reference. We understand the concern regarding contribution, and much has changed since the first submission May 8. However, many resources transcript the ICTRP WHO-file without including registry entries from all 33 trial registries. In the current review, we assess outcome variables that are not easy to obtain from either of the databases available for download. Regarding contribution, we have revised:

“Even though multiple versions of trial registration databases are readily available for download online [10-12], trialists may find it difficult to get an overview of the constantly evolving multitude of planned or ongoing studies. Therefore, we aim to provide a global snapshot overview of interventions and main methodological aspects of planned and initiated randomised clinical trials on COVID-19 prevention and treatment. To do so, we assess available trial registry entries from 33 clinical trial registries to June 23, 2020.” (page 3, line 20-26).

Author response: We apologize for the mix up in terminology. We have revised the text accordingly using the term “trial registry entries” throughout the text.

Methods:

Author response: We agree that blinding is less important for mortality outcome, this is also supported by the literature (Anthon et al 2018 https://www.sciencedirect.com/science/article/abs/pii/S0895435617313501). However, we believe that the assessed parameters (blinding, use of mortality outcomes, trial size and multicentric designs) are individual contributors to better trial designs according to contemporary standards. Many other outcomes than mortality, including subjective outcomes, are being tested in the included trials, where lack of blinding can contribute to exaggerated interventions effects. In COVID-19 we have seen a much more liberal approach to implementation of new treatment modalities, and therefore believe that information on blinding is relevant. We have added to the Discussion:

“Though there is no firm evidence that lack of blinding affects estimates of mortality [17], we consider blinding as an important factor in COVID-19 trial designs. Especially as 79% of trial registry entries had other primary outcomes than mortality and many were preventive with subjective and patient-reported outcomes such as self-assessed symptom severity where bias, including lack of blinding, that can exaggerate intervention effects [18].” (page 13, line 18-22).

• Additionally, in the results, the authors use the categories “Open label, single blind, double blind, triple blind, and quadruple blind”. It is not clear what these different categories describe, and research has shown that e.g. “double blind” is an ambiguous term [1,2]. The authors should explain how they operationalise blinding in the methods section.

Author response: We agree that the terminology regarding blinding is ambiguous. Information regarding which parties were blinded were not available from all trial registries. Hence, we merely counted the number of parties blinded to provide an overview of trial methodology. We have revised to “No. of parties blinded” in the tables. In the method section we added:

“We reported the number of blinded parties registered in the trial registry entries, but not who was blinded.” (page 4, line 29-30).

• Regarding mortality as an outcome: Are the authors only looking at overall mortality or also cause-specific? This should be elaborated on.

Author response: We added to Methods:

“Mortality was extracted binary regardless of cause-specificity or timely differences.” (page 4, line 27-28).

Discussion:

• Perspective: as mentioned above, I am afraid that the results of the study may already be outdated and more up-to-date resources exist.

Author response: We agree with the author that this is a dynamic research field. We have therefore added to our discussion:

Minor issues:

Author response: Thank you for your comments, we have revised the text accordingly using the term blinding throughout the manuscript and tables.

Abstract

Author response: Thank you for your comment, the abstract has been revised accordingly:

“An extraordinary number of randomized clinical trials investigating COVID-19 management have been initiated with a multitude of medical preventive, adjunctive and treatment modalities.” (page 15, line 23-24).

Background:

Author response: Thank you for your comment. We agree and have revised as suggested and changed to a more updated reference:

“… ranging from asymptomatic cases and mild symptoms of upper airway infection to fulminant acute respiratory distress syndrome (ARDS), multi-organ failure and death [1].” (page 3, line 3-5).

Author response: Thank you for your comment. We agree and have revised as suggested:

“… to ensure a second wave of high-quality evidence with proper assessment of benefits and harms” (page 3, line 16-17).

Methods:

Author response: Thank you for your comment. We agree and have revised the term to “clinical trial phase” throughout the manuscript and tables. Further we elaborated in the method section:

“The clinical research phase was registered (phase 1-4 trials) and whenever an entry had multiple trial phases, we registered the highest.” (page 4, line 27-29).

Results:

Author response: Thank you for your comment. We agree and have added:

“The vast majority of exclusions were due to single-group, observational and non-randomised designs, duplicates and testing of other interventions than COVID-19 treatment or prevention.” (page 6, line 3-5).

• Table 1 and Table 2: I suggest indenting the different types of interventions under “All trials” to make the table more legible.

Author response: Thank you for your comment, we agree and have revised the text accordingly in Table 1-3.

• Table 4a: The recruiting / completed variable is somewhat confusing. Completed could easily be interpreted as “trial completed” rather than “recruiting completed”.

Author response: Thank you for your comment, we agree and have changed the term to “Recruitment ongoing” and “Recruitment completed”.

Discussion:

• First paragraph: The first sentence is perhaps a bit too strongly worded, 770 RCTs were registered on the trial registries searched, there might be trials registered elsewhere.

Author response: We revised:

“From January 23 to June 23, 2020 a total of 1303 randomized clinical trials were registered on the 33 trial registries searched, investigating 381 therapeutics or adjunct therapies in treatment of COVID-19.” (page 13, line 2-3).

• Second paragraph, second line: delete “from” in “ongoing trials initiated from before the pandemic”.

Author response: Revised accordingly.

Author response: Thank you for your comment, after the update, this does no longer apply for registry entries from China and therefore has been deleted.

However, we now find that 85% of completed recruitments were conducted in Iran, maybe because they still plan trials with smaller sample sizes. This was added to the discussion:

“Entries in the Iranian Registry of Clinical Trials (IRCT) accounted for 15% of all registered RCTs but only 4% of all planned participants. Maybe because of the generally smaller trial sizes in entries from the IRCT, this registry contributed with 85% of all trials that had completed recruitment per June 23.” (page 13, line 14-17).

• Perhaps mention that such initiatives exist, e.g. the Living Meta-analysis from Cochrane France and others: https://covid-nma.com/

Author response: we have revised:

“Collaboration to compile evidence in meta-analyses and network meta-analyses in order to achieve higher levels of evidence has been initiated, such as The Living mapping and living systematic review of Covid-19 studies [19-20].” (page 13, line 25-27).

• Strengths and limitations: It is not mentioned in “methods” that data was extracted in duplicate.

Author response: Revised accordingly:

“Trial registry entries were screened for inclusion and data were extracted by two authors independently (KZR or APHK and JL or OM)” (page 4, line 13-15.

Author response: Revised accordingly:

“… and assessment of blinding status are strengths.” (page 14, line 28).

• Strengths and limitations: I am unsure why including “unconventional medicine” would be controversial, it is an important part of the narrative of the research being conducted.

Author response: We appreciate your comment and have deleted this section.

• Supplementary information: Appendix 2 and appendix 3 are called “Excluded articles” and “included articles”, however the unit of analysis is not articles but registry entries.

Author response: Revised accordingly

References

Reviewer #2:

This manuscript describes the results of a systematic search for registered drug trials in the WHO trial registry that assess prevention or treatment for COVID-19. This is important to provide an overview of ongoing research, as well as its characteristics and quality. The authors assess key components of the trials, such as number of participants, outcome measures, blinding, status for recruiting, etc.

Overall, the methods and results are clearly presented and the authors use blinded data-extraction, a systematic search strategy, present a PRISMA flow-chart with reasons for exclusions, etc.

My main concern is that the authors have likely not, as stated in the manuscript, assessed the actual protocols for the trials. Trial registries generally do not included detailed protocols but a set of key pieces of information, which is a pity. Lots of important information is missing that would allow a more thorough assessment of the quality of the ongoing trials than just binding, e.g. by applying the Cochrane risk of bias tool and assess whether the randomisation process was adequate and likely to produce comparable groups. Given that I am correct about this, it might be necessary to change the terminology of the manuscript and explain that it is an evaluation of clinical trial registry forms rather than protocols and perhaps even use this to push for requirements to publish the full protocol along with the trial registry forms.

Author response: Thank you for revising our manuscript. It is correctly observed that the review is based on trial registry entries rather than full information protocols, that are not always linked in the registries. We apologize for the mix up in terminology between protocols and trial registry entries. We have changed “protocols” to “trial registry entries” throughout the manuscript.

A full protocol overview would definitely have merits but were seldom available from the trial registries. We added to the limitation section:

“This is a dynamic and rapidly developing research field and with the present study, we only provide a snapshot overview of trial registry entries of June 23, 2020. We however, believe that the overview of investigated interventions and quantification of several methodological parameters have merits. More adaptable inventories for finding trial registry entries of specific interventions are available elsewhere [11, 12, 27]. We reviewed trial registry entries and not actual trial protocols, mainly because these were not always available. Evaluation of trial protocols could have provided more detailed information on trial methodology and outcomes and we endorse recent suggestions of public access to all trial protocols concomitant with trial registration [28]” (page 15 line 4-11).

PLoS One. doi: 10.1371/journal.pone.0237903.r003

Decision Letter 1

Lisa Susan Wieland

6 Aug 2020

A systematic review of trial registry entries for randomized clinical trials investigating COVID-19 medical prevention and treatment

PONE-D-20-13626R1

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PLoS One. doi: 10.1371/journal.pone.0237903.r004

Acceptance letter

Lisa Susan Wieland

11 Aug 2020

PONE-D-20-13626R1

A systematic review of trial registry entries for randomized clinical trials investigating COVID-19 medical prevention and treatment

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Appendix. Trial registration sites.

(PDF)

Click here for additional data file.^{(116.8KB, pdf)}

S2 Appendix. Excluded trial registry entries.

(PDF)

Click here for additional data file.^{(6.8MB, pdf)}

S3 Appendix. Included trial trial registry entries.

(PDF)

Click here for additional data file.^{(4.6MB, pdf)}

S4 Appendix. Database.

(CSV)

Click here for additional data file.^{(7.2MB, csv)}

S1 Checklist. PRISMA 2009 checklist.

(DOC)

Click here for additional data file.^{(66KB, doc)}

Data Availability Statement

All relevant data are within the paper and its Supporting Information file.

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A systematic review of trial registry entries for randomized clinical trials investigating COVID-19 medical prevention and treatment

Anders Peder Højer Karlsen

Sebastian Wiberg

Jens Laigaard

Casper Pedersen

Kim Zillo Rokamp

Ole Mathiesen

Roles

Abstract

Aim

Methods

Results

Conclusion

Background

Methods

Outcomes

Data handling

Results

Fig 1. PRISMA flowchart of trial registry entries for trials investigating COVID-19 treatment.

Table 1. Characteristics of therapeutic groups.

Interventional characteristics

Table 3. Characteristics of therapeutic groups.

Table 4. Characteristics of specific interventions reported in seven or more trial registry entries.

Methodological characteristics

Table 2. Characteristics of therapeutic groups.

Geographical characteristics

Discussion

Strengths and limitations

Perspective

Conclusion

Supporting information

Data Availability

Funding Statement

References

Decision Letter 0

Lisa Susan Wieland

Roles

Author response to Decision Letter 0

Decision Letter 1

Lisa Susan Wieland

Roles

Acceptance letter

Lisa Susan Wieland

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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