Colchicine in COVID-19

Jean-Claude Tardif CM, MD, FRCPC, FCCS, FACC, FAHA, FESC, FCAHSDirector, MHI Research Center

Canada Research Chair in personalized medicineUdeM Pfizer research chair in atherosclerosis

Professor of medicineMontreal Heart InstituteUniversity of Montreal

November 2020

Ridker PM, Luscher TF. Eur Heart J 2014;35:1782-1791

Inflammatory pathways as targets for therapies

HR = 0.77 (95% CI, 0.61-0.96)P = 0.02

Primary efficacy endpointCV death, resuscitated cardiac arrest, MI, stroke, urgent hospitalization for angina

requiring revascularization (ITT)

Time since randomization (months)

Cum

ulat

ive

inci

denc

e (%

)

Placebo

Colchicine

Tardif JC et al. N Engl J Med 2019;381:2497-2505

Hazard ratio, 0.69 (95% CI, 0.57-0.83), P<0.001

Placebo

Colchicine

0

5

10

15

20

0 12 24 36 48 60Months since Randomization

Cum

ulat

ive

Inci

denc

e (%

)

2760 2655 1703 821 590 1612762 2685 1761 890 629 166

No. at Risk

264 placebo vs 187 colchicine

Nidorf SM et al. N Engl J Med 2020 Aug 31

Cardiovascular death, myocardial infarction, ischemic stroke or ischemia-driven coronary revascularization

Primary endpoint

Meta-analysis of colchicine studies in CADPrimary composite endpoint

LoDoCo2 (2020)

COPS (2020)

COLCOT (2019)

Overall

Heterogeneity: τ2 = 0.01, I2 = 37.70%, H2 = 1.61

Test of θi = θj: Q(2) = 3.21, p = 0.20

Test of θ = 0: z = 9.90, p = 0.00

RCT

.2 .4 .6 .8 1

with 95% CIHR

0.69 [

0.47 [

0.77 [

0.68 [

0.56,

0.20,

0.59,

0.54,

0.82]

0.74]

0.95]

0.81]

47.65

18.60

33.74

(%)Weight

Random-effects DerSimonian-Laird model Favors Colchicine

*Primary composite endpoint includes cardiovascular mortality, myocardial infarction, ischemic stroke, and urgent coronary revascularization

Samuel M, Tardif JC, et al. Can J Cardiol 2020 (in press)

Meta-analysis of colchicine studies in CAD Myocardial infarction

LoDoCo2 (2020)

COPS (2020)

COLCOT (2019)

LoDoCo (2013)

Overall

Heterogeneity: τ2 = 0.05, I2 = 68.76%, H2 = 3.20

Test of θi = θj: Q(3) = 9.60, p = 0.02

Test of θ = 0: z = 4.65, p = 0.00

RCT

0 .5 1 1.5

with 95% CIHR

0.70 [

0.52 [

0.91 [

0.25 [

0.62 [

0.50,

0.11,

0.65,

-0.09,

0.36,

0.90]

0.93]

1.18]

0.59]

0.88]

30.69

19.44

27.00

22.87

(%)Weight

Favors Colchicine Favors PlaceboRandom-effects DerSimonian-Laird model

Samuel M, Tardif JC, et al. Can J Cardiol 2020 (in press)

Meta-analysis of colchicine studies in CAD Ischemic stroke

LoDoCo2 (2020)

COPS (2020)

COLCOT (2019)

LoDoCo (2013)

Overall

Heterogeneity: τ2 = 0.00, I2 = 0.00%, H2 = 1.00

Test of θi = θj: Q(3) = 2.16, p = 0.54

Test of θ = 0: z = 3.02, p = 0.00

RCT

Favors Colchicine

-.5 0 .5 1 1.5

with 95% CIHR

0.66 [

0.34 [

0.25 [

0.23 [

0.38 [

Favors Placebo

0.21,

-0.48,

-0.09,

-0.77,

0.13,

1.11]

1.16]

0.59]

1.23]

0.63]

30.20

9.21

54.48

6.11

(%)Weight

Random-effects DerSimonian-Laird model

Samuel M, Tardif JC, et al. Can J Cardiol 2020 (in press)

Meta-analysis of colchicine studies in CAD Urgent coronary revascularization

LoDoCo2 (2020)

COPS (2020)

COLCOT (2019)

Overall

Heterogeneity: τ2 = 0.03, I2 = 65.10%, H2 = 2.87

Test of θi = θj: Q(2) = 5.73, p = 0.06

Test of θ = 0: z = 4.21, p = 0.00

RCT

-.5 0 .5 1

with 95% CIHR

0.75 [

0.26 [

0.50 [

0.56 [

0.58,

-0.18,

0.25,

0.30,

0.92]

0.69]

0.75]

0.82]

43.18

21.29

35.53

(%)Weight

Favors ColchicineRandom-effects DerSimonian-Laird model

Samuel M, Tardif JC, et al. Can J Cardiol 2020 (in press)

Meta-analysis of colchicine studies in CAD CV death, MI and ischemic stroke

LoDoCo2 (2020)

COLCOT (2019)

Overall

Heterogeneity: τ2 = 0.00, I2 = 6.00%, H2 = 1.06

Test of θi = θj: Q(1) = 1.06, p = 0.30

Test of θ = 0: z = 10.66, p = 0.00

RCT

.6 .8 1 1.2

with 95% CIHR

0.72 [

0.87 [

0.78 [

0.55,

0.65,

0.63,

Favors Placebo

0.90]

1.09]

0.92]

61.57

38.43

(%)Weight

Favors ColchicineRandom-effects DerSimonian-Laird model

Samuel M, Tardif JC, et al. Can J Cardiol 2020 (in press)

LoDoCo2 (2020)

COPS (2020)

COLCOT (2019)

LoDoCo (2013)

LoDoCo2 (2020)

COPS (2020)

COLCOT (2019)

LoDoCo (2013)

All-Cause Mortality

Non-Cardiovascular Mortality

Heterogeneity: τ2 = 0.15, I2 = 62.01%, H2 = 2.63

Heterogeneity: τ2 = 0.00, I2 = 0.00%, H2 = 1.00

Test of θi = θj: Q(3) = 7.90, p = 0.05

Test of θi = θj: Q(3) = 2.92, p = 0.40

RCT

73

8

43

4

53

5

23

4

YesColchicine

2,689

388

2,323

278

2,709

391

2,343

246

No

60

1

44

10

35

0

20

5

Favors Colchicine

YesPlacebo

2,700

398

2,335

240

2,725

399

2,359

277

No

Favors Placebo1 20 3

with 95% CIRisk Ratio

1.22 [

8.06 [

0.98 [

0.35 [

1.51 [

11.08 [

1.16 [

0.90 [

1.04 [

1.38 [

0.87,

1.01,

0.65,

0.11,

0.99,

0.61,

0.64,

0.25,

0.61,

0.99,

1.70]

64.15]

1.49]

1.12]

2.31]

199.77]

2.10]

3.32]

1.78]

1.93]

41.13

5.87

37.90

15.10

61.30

1.32

30.91

6.47

(%)Weight

Random-effects DerSimonian-Laird model

Meta-analysis of colchicine studies in CAD All-cause and non-CV mortality

Samuel M, Tardif JC, et al. Can J Cardiol 2020 (in press)

Meta-analysis of colchicine studies in CAD Safety outcomes

LoDoCo2 (2020)

COLCOT (2019)

LoDoCo2 (2020)

COLCOT (2019)

LoDoCo2 (2020)

COLCOT (2019)

LoDoCo2 (2020)

COLCOT (2019)

Infection

Pneumonia

Hospitalization for Gastrointestinal Event

Diagnosis of Cancer

Heterogeneity: τ2 = 0.03, I2 = 52.24%, H2 = 2.09

Heterogeneity: τ2 = 0.43, I2 = 81.50%, H2 = 5.41

Heterogeneity: τ2 = 0.00, I2 = 0.00%, H2 = 1.00

Heterogeneity: τ2 = 0.00, I2 = 0.00%, H2 = 1.00

Test of θi = θj: Q(1) = 2.09, p = 0.15

Test of θi = θj: Q(1) = 5.41, p = 0.02

Test of θi = θj: Q(1) = 0.53, p = 0.47

Test of θi = θj: Q(1) = 0.01, p = 0.93

RCT

137

51

46

21

53

47

120

44

YesColchicine

2,625

2,315

2,716

2,345

2,709

2,319

2,642

2,322

No

144

38

55

9

50

36

122

46

YesPlacebo

2,616

2,341

2,705

2,370

2,710

2,343

2,638

2,333

No

Favors Placebo1 2 4

with 95% CIRisk Ratio

0.95 [

1.35 [

0.84 [

2.35 [

1.06 [

1.31 [

0.98 [

0.96 [

1.08 [

1.32 [

1.16 [

0.98 [

0.76,

0.89,

0.57,

1.08,

0.72,

0.85,

0.77,

0.64,

0.78,

0.48,

0.87,

0.79,

1.19]

2.05]

1.23]

5.11]

1.55]

2.02]

1.26]

1.45]

1.51]

3.61]

1.55]

1.21]

73.64

26.36

55.57

44.43

55.83

44.17

73.40

26.60

(%)Weight

Favors ColchicineRandom-effects DerSimonian-Laird model

Also discussed in Roubille F, Tardif JC. Circulation 2020;142:1901-1904

Ridker PM, Luscher TF. Eur Heart J 2014;35:1782-1791

Inflammatory pathways as targets for therapies

SARS-CoV viroprotein E activates the NLRP3 inflammasome (INFL)

Nieto-Torres JL et al. Virology 2015;485:330-339.

Inflammasome components were transfected in Vero E6 cells, in absence or presence of SARS-CoV E protein with (IC+) or without (IC-) ion channel activity. EIC1- and EIC2- indicate mutants.As a negative control, cells were transfected solely with pro-IL1b (C-).

IL-6 in COVID-19: Systematic Review and Meta-Analysis

Coomes EA, Haghbayan H. medRxiv, 2020.2003.2030.20048058, doi:10.1101/2020.03.30.20048058 (2020).

Colchicine reduces lung injury in ARDS

Dupuis J, et al, Tardif JC. Can J Cardiol 2020 (in press)

Colchicine reduces lung injury by 61%

Dupuis J, et al, Tardif JC. Can J Cardiol 2020 (in press)

Colchicine reduces lung edema and improves oxygenation and gas exchanges

Dupuis J, et al, Tardif JC. Can J Cardiol 2020 (in press)

Colchicine reduces alveolar wall thickness

Dupuis J, et al, Tardif JC. Can J Cardiol 2020 (in press)

Colchicine reduces lung neutrophil recruitment

Dupuis J, et al, Tardif JC. Can J Cardiol 2020 (in press)

Colchicine reduces lung injury score, correlating with improved oxygenation

Dupuis J, et al, Tardif JC. Can J Cardiol 2020 (in press)

Colchicine vs standard care on biomarkers and clinical outcomes in patients hospitalized with COVID-19

The GRECCO-19 randomized trial

Deftereos SG et al. JAMA Network Open 2020; 3(6)

COLCORONA Study Design

COVID+ (n=6000 patients)≥40 years, non-hospitalized

≥1 risk factor for complications of COVID-19

Colchicine 0.5 mgX 30 days

Placebo X 30 days

Primary efficacy endpoint: Composite of death or hospitalization due to COVID-19 infection

Secondary efficacy endpoints: Components of primary endpoint; need for mechanical ventilation

* funded by the Government of Québec, the US NIH and the Gates Foundation

*

Risk factors for complicationsdetermining eligibility in COLCORONA

Patient must present ≥1 risk factor for complications:

• Age ≥ 70 years (all patients must be aged ≥40 years)

• Diabetes mellitus

• Body-mass index ≥30 kg/m2

• Uncontrolled hypertension (systolic BP ≥150 mm Hg)

• Known pulmonary disease (including asthma or COPD)

• Known heart failure

• Known coronary disease

• Fever ≥38.4°C in the last 48 hours

• Dyspnea at presentation

• Bicytopenia or pancytopenia

• Combination of high neutrophil count and low lymphocyte count

COLCORONA Study Design

COVID+ (n=6000 patients)≥40 years, non-hospitalized

≥1 risk factor for complications of COVID-19

Colchicine 0.5 mgX 30 days

Placebo X 30 days

Primary efficacy endpoint: Composite of death or hospitalization due to COVID-19 infection

Secondary efficacy endpoints: Components of primary endpoint; need for mechanical ventilation

* funded by the Government of Québec, the US NIH and the Gates Foundation

*