Impact of colchicine on mortality in patients with COVID-19: A meta-analysis

Coronavirus disease 2019 (COVID-19) due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has urged clinicians to utilize traditional and novel drugs in a struggle against the virus and its complications.¹ Inflammatory over-reaction and cytokine storm are postulated to play a deleterious role in COVID-19 affecting not only the pulmonary but the cardiovascular system as well.² As expected, laboratory evidence of myocardial injury has been reported to be adversely related to short-term mortality in COVID-19 patients and therefore could be utilized in patient risk stratification.³ However, while a wide range of myocardial injury patterns in COVID-19 patients has been reported (e.g. supply-demand imbalance, acute coronary syndromes, microvascular thrombosis, stress cardiomyopathy, inflammation, myocarditis), it is not yet clear (a) whether there is a prominent mechanism and (b) if and which long-term consequences exist.^{4 , 5} In this context, colchicine – along with other drugs with anti-inflammatory properties – has been proposed to have a beneficial effect in terms of clinical outcomes COVID-19.^{6 , 7} Colchicine's potential COVID-19 is speculated to be mainly mediated by its inhibitory effect on the activation, destabilization, and degradation of inflammasomes, while a potential antiviral effect could be exerted through microtubule polymerization inhibition.^{1 , 8} Published studies suggest a clinical benefit of colchicine therapy including mortality. We aimed to provide a quantitative assessment of the effect of colchicine on mortality in patients with COVID-19.

We performed a systematic review and meta-analysis according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2009 guidelines. On November 6^th 2020, we searched PubMed, Medrxiv.org using the following query: “colchicine AND (“COVID” OR “COVID-19” OR “SARS-COV-2” OR “CORONAVIRUS DISEASE” OR “CORONAVIRUS DISEASE-19” OR “CORONOVIRUS DISEASE” OR “CORONOVIRUS DISEASE 19” OR “CORONOVIRUS” OR “CORONAVIRUS”)”, further we searched researchsquare.com using the query “colchicine”. Eligible studies had to satisfy the following criteria: 1) study population including patients with COVID-19, 2) studies evaluating the effect of colchicine on clinical outcomes, 3) written in English. The primary outcome of interest was the absolute number of patients who died/survived in each arm (colchicine plus standard-of-care versus standard-of-care alone) at the end of the follow up period. For pooling the primary outcome of interest, we performed a meta-analysis based on the logarithmic transformation (to allow for a more symmetric scale) of odds ratios and their corresponding 95% confidence intervals (CI). Because of the expected effect size dispersion between studies due to differences in interventions in the standard-of-care arm and variations in disease severity, a random effects (DerSimonian-Laird) model was adopted. Heterogeneity was assessed using I², with values between 50% and 90% representing substantial heterogeneity. All analyses were performed using STATA/MP version 16.0, Texas, USA software.

A total of 112 articles were screened, 106 were excluded since they did not meet inclusion criteria (Figure 1 ). A total of six studies, four published after peer-review^{7 ,} 9, 10, 11 and two pre-prints^{12 , 13} including 881 patients with confirmed COVID-19 were evaluated, 406 of whom were treated with colchicine in addition to standard-of-care (Table ). To address one study¹² that reported no events in both arms, a value of 0.5 was added to the respective cells.¹⁴ The pooled odds ratio for mortality was 0.35 (95% confidence interval 0.24-0.52) and a similar significant trend was observed in terms of the risk difference (Figure 2 A). The analysis was also conducted including only peer-reviewed articles (i.e. excluding pre-prints) and the pooled odds ratio for mortality was 0.28 (95% confidence interval 0.18-0.44) (Figure 2B). Heterogeneity was low in the odds ratio analysis (Figure 2). Further, a contour-enhanced funnel plot, centered at 0 is provided in Figure 3 . Although the small number of studies does not allow for safe conclusions, the plot does not suggest significant publication bias.

Fig. 1.

Flow diagram of search and selection strategy.

Table.

Studies evaluating impact of colchicine on mortality in patients with COVID-19.

Study	Country	Colchicine/Control Group
		Patients, N	Age (years)	Males (%)	DM (%)	HTN (%)	Known CAD (%)
Studies Published after Peer-Review
Deftereos et al.7	Greece	55/50	63/65	56/60	16/24	40/50	16/10
Scarsi et al.9	Italy	122/140	10/14	64/64	------- 64/74∗-------
Brunetti et al.10	USA	33/33	62/64	64/67	21/21	61/36	12/6#
Sandhu et al.11	USA	34/78	68/66	62/51	32/51	53/72	6/8
Pre-prints
Lopes et al.12	Brazil	17/18	48/54	53/28	29/33	------ 47/33§------
Pinzón et al.13	Colombia	145/156	NR	NR	NR	NR	NR
Overall		406/475

CAD: Coronary Artery Disease, DM = Diabetes Mellitus, HTN= Hypertension, NR=Not Reported.

^∗Reported as any cardiovascular comorbidity.

^§Reported as cardiovascular diseases.

^#Reported as previous myocardial infarction.

Fig. 2.

Log-odds ratios for mortality between colchicine on top of standard-of-care and standard-of-care. Negative values suggest superiority of colchicine. (A) for all studies (peer-reviewed and preprints) (B) for only peer-reviewed studies.

Fig. 3.

Contour-enhanced funnel plot, centered at 0.

The findings of the present meta-analysis suggest a definite signal of benefit of mortality with the addition of colchicine in patients with COVID-19. The small number of studies and the relatively small absolute number of patients included certainly warrant caution as to any definitive conclusion, but this signal cannot be ignored, considering the scarcity of effective treatments for COVID-19. The need for randomized controlled trials (RCTs) involving adequately numbered populations has been well stressed during this pandemic. On the other hand, a year after the first COVID-19 cases, current standards-of-care is not based upon such evidence. Study limitations include the lack of patient-level data which did not allow to assess or control for possible differences in baseline or procedural variables.

Funding

None.