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Tacrolimus Use and COVID-19 Infection in Patients After Solid Organ Transplantation

2021; Elsevier BV; Volume: 161; Issue: 2 Linguagem: Inglês

10.1053/j.gastro.2021.01.223

ISSN

1528-0012

Autores

Saifu Yin, Xianding Wang, Turun Song,

Tópico(s)

COVID-19 Clinical Research Studies

Resumo

We read with great interest the study by Belli et al1Belli L.S. et al.Gastroenterology. 2020; 160: 1151-1163Abstract Full Text Full Text PDF PubMed Scopus (120) Google Scholar in which the authors have retrospectively analyzed the effect of comorbidities, immunosuppression, and ageing on overall mortality in liver transplant patients with coronavirus disease 2019 (COVID-19). In this multicenter cohort study, multivariable Cox regression analysis showed that tacrolimus use had a positive effect on patient survival (hazard ratio, 0.55; 95% confidence interval [CI], 0.31–0.99).1Belli L.S. et al.Gastroenterology. 2020; 160: 1151-1163Abstract Full Text Full Text PDF PubMed Scopus (120) Google Scholar However, this association was not that solid owing to defects in the study design. In this study, 39 patients (16%) received homecare and 204 (84%) needed hospitalization. However, patients receiving homecare had a survival rate of 100% and 82.05% received tacrolimus, whereas those patients in hospital only had a survival rate of 76.0% and 63.7% received tacrolimus. Additionally, for inpatients, 7.8% stopped calcineurin inhibitors (CNI) and 17.6% decreased CNI compared with 0% stopping CNI and 5.13% decreasing CNI in outpatients. This point means that it was more likely for patients with a good prognosis (those receiving homecare) to use tacrolimus, whereas those needing hospitalized or intensive care unit admission with worse prognosis tended to stop tacrolimus after diagnosis of COVID-19. Hence, preexisting selection bias in the study contributed to the favorable association between tacrolimus use and a better prognosis. Although multivariate Cox analyses were conducted, disease severity was not adjusted. It may be more reasonable to do patient stratification or enroll in-hospital patients alone to explore the impact of tacrolimus on prognosis. In addition, in the study by Colmenero et al2Colmenero J. et al.J Hepatol. 2021; 74: 148-155Abstract Full Text Full Text PDF PubMed Scopus (255) Google Scholar of 111 hospitalized liver transplant recipients, more patients with nonsevere COVID-19 received tacrolimus initially (64.5% vs 48.6%), and tacrolimus use was not associated with severe COVID-19 (relative risk, 0.54; 95% CI, 0.29–1.07; P = .08).2Colmenero J. et al.J Hepatol. 2021; 74: 148-155Abstract Full Text Full Text PDF PubMed Scopus (255) Google Scholar Of interest, mycophenolate use was an independent predictor of severe COVID-19 (relative risk, 3.94; 95% CI. 1.59–9.74; P = .003). In the prospective cohort study involving 414 kidney transplant recipients with COVID-19,3Crespo M. et al.Transplantation. 2020; 104: 2225-2233Crossref PubMed Scopus (49) Google Scholar tacrolimus use was not associated with mortality (hazard ratio, 0.974; 95% CI, 0.593–1.598; P = .918). Bossini et al4Bossini N. et al.Am J Transplant. 2020; 20: 3019-3029Crossref PubMed Scopus (75) Google Scholar even reported that tacrolimus use was associated with an increased risk of death in a retrospective cohort of 53 kidney transplant recipients (odds ratio [OR], 4.0; 95% CI, 1.1–19.7; P = .05).4Bossini N. et al.Am J Transplant. 2020; 20: 3019-3029Crossref PubMed Scopus (75) Google Scholar Given the disputes on the immunosuppression in solid organ transplant (SOT) recipients with COVID-19, we have registered a systematic review and meta-analysis in PROSPERO aimed to explore the risk factors of mortality in SOT patients (CRD42020215987). PubMed, Embase, and Cochrane library were searched, and the last search was conducted on December 15, 2020. Disease severity defined in the original study was adopted in this meta-analysis. The quality of observational studies was assessed by using the Newcastle-Ottawa Scale.5Sethia R. et al.Gastroenterology. 2020; 116: 600-608Google Scholar A meta-analysis was performed using R statistical software (version 4.0.0), with the package "meta." A random effects analysis was used for all meta-analyses, owing to the clinical heterogeneity inherent in the data and the different sample sizes of included studies. The ORs and 95% CIs were pooled by the inverse variance method.5Sethia R. et al.Gastroenterology. 2020; 116: 600-608Google Scholar Finally, 11 cohort studies were included.1Belli L.S. et al.Gastroenterology. 2020; 160: 1151-1163Abstract Full Text Full Text PDF PubMed Scopus (120) Google Scholar, 2Colmenero J. et al.J Hepatol. 2021; 74: 148-155Abstract Full Text Full Text PDF PubMed Scopus (255) Google Scholar, 3Crespo M. et al.Transplantation. 2020; 104: 2225-2233Crossref PubMed Scopus (49) Google Scholar, 4Bossini N. et al.Am J Transplant. 2020; 20: 3019-3029Crossref PubMed Scopus (75) Google Scholar,6Benotmane I. et al.Transplantation. 2021; 105: 158-169Crossref PubMed Scopus (33) Google Scholar, 7Cravedi P. et al.Am J Transplant. 2020; 20: 3140-3148Crossref PubMed Scopus (300) Google Scholar, 8Demir E. et al.Transpl Infect Dis. 2020; 22e13371Crossref PubMed Scopus (42) Google Scholar, 9Favà A. et al.Am J Transplant. 2020; 20: 3030-3041Crossref PubMed Scopus (76) Google Scholar, 10Hilbrands L.B. et al.Nephrol Dial Transplant. 2020; 35: 1973-1983Crossref PubMed Scopus (304) Google Scholar, 11Ali Malekhosseini S. et al.Transplantation. 2021; 105: 90-99Crossref PubMed Scopus (22) Google Scholar, 12Gaston D.C. et al.Am J Transplant. 2021; 21: 1304-1311Crossref PubMed Scopus (18) Google Scholar Among them, 7 studies involving 1348 SOT patients explored the association between tacrolimus use and mortality and other 4 involving 229 SOTs explored the association between tacrolimus use and severe COVID-19 (Supplementary Table 1). Four studies only included hospitalized patients, and 7 included both in- and out-patients. Seven studies included kidney transplant recipients, 2 included liver transplant recipients, and 2 included SOTs. Study population size ranged from 25 to 414 patients. COVID-19 was diagnosed based on real-time polymerase chain reaction (RT-PCR) in 6 studies, 4 studies included both PCR and specific chest image confirmed COVID-19 patients, and 1 did not report the COVID-19 diagnosis method. The median time from SOT to COVID-19 diagnosis ranged from 0 to 168 months. Based on the Newcastle-Ottawa Scale, 2 studies were of high quality, 6 of moderate, and 2 of low quality (Supplementary Tables 2 and 3). Pooled results showed that tacrolimus use was associated with neither higher risk of severe COVID-19 (OR, 1.31; 95% CI, 0.47–3.69) or increased mortality (OR, 1.11; 95% CI, 0.63–1.92) in SOT patients with COVID-19 infection (Figures 1 and 2). For mortality, similar results were indicated in subgroup analyses of hospitalized SOT patients (OR, 0.61; 95% CI, 0.28–1.30), kidney transplants (OR, 1.22; 95% CI, 0.65–2.30), a sample size of >100 patients (OR, 0.89; 95% CI, 0.52–1.53), and PCR-confirmed cases (3 studies, OR, 0.97; 95% CI, 0.36–2.61). For severe COVID-19, similar results were also observed in hospitalized SOT patients (OR, 3.46; 95% CI, 0.74–16.21), kidney transplant recipients (OR, 1.71; 95% CI, 0.58–5.03), and PCR-confirmed cases (OR, 1.39; 95% CI, 0.30–6.41).Figure 2Forest plot of studies investigating the association between tacrolimus use and severe COVID-19 in solid organ transplant recipients.View Large Image Figure ViewerDownload Hi-res image Download (PPT) In conclusion, our study found that tacrolimus use is not a risk factor for mortality and severity in SOT patients with COVID-19. Well-designed prospective study is encouraged to verify these findings in the future. Supplementary Table 1Baseline Characteristics of Included Studies (the Other 10 Studies)AuthorLocationPeriodOrganTotal No. of PatientsTotal No. of Hospitalized PatientsTestAge (years)Male sex (%)Duration after TransplantInitial Maintenance TherapyChanged Maintenance Therapy after COVID-19TreatmentFollow-upBenotmane et al6Benotmane I. et al.Transplantation. 2021; 105: 158-169Crossref PubMed Scopus (33) Google ScholarEuropeMarch 4 and April 7, 2020Kidney4941RT-PCR and/or typical lung lesions from chest CT62.2 (52.3–67.8)75.57.1 (2.9–14.4)Tac (53.1%)/Cyc (32.7%) + MMF (77.6%) + mTOR (22.5%) + steroids (57.1%)MMF/MPA withdrawal (100%) + calcineurin inhibitors withdrawal (41.7%) + delayed belatacept administration (50%) + mTORi withdrawal (41.7%)Azithromycin (65%) + azole (2.5%) + lopinavir-ritonavir (12.2%) + hydroxychloroquine (36.6%) + tocilizumab (9.8%) + high-dose corticosteroids (34.2%)UnknownBossini et al4Bossini N. et al.Am J Transplant. 2020; 20: 3019-3029Crossref PubMed Scopus (75) Google ScholarEuropeMarch 1 to April 16, 2020Kidney5345RT-PCRMedian 60 (IQR 50–67)799.2 (IQR 4–16)Tac (58%)/Cyc (32%) + MMF (60%) + mTORi (11%) + pred (57%)UnknownLopinavir/ritonavir (34%) + darunavir plus ritonavir (26%) + hydroxychloroquine (79%)UnknownCravedi et al7Cravedi P. et al.Am J Transplant. 2020; 20: 3140-3148Crossref PubMed Scopus (300) Google ScholarNorth AmericaMarch 2 and May 15, 2020Kidney144144Unknown60 (±12)66UnknownTac (91%)/Eve (7.6%) + MMF (77.1%) + pred (86.8%)MMF withdrawal (68%) + calcineurin inhibitor withdrawal (23%)Hydroxychloroquine (71%) + antibiotics (74%) + tocilizumab (13%) + and antivirals (14%)Median 52 days (IQR, 16–66 days)Crespo et al3Crespo M. et al.Transplantation. 2020; 104: 2225-2233Crossref PubMed Scopus (49) Google ScholarEuropeMarch 18 to May 16Kidney414380RT-PCR or bronchoalveolar lavageMedian 62 (IQR: 52–71)64UnknownTac (82.6%)/mTORi (23%) + MMF (72.6%) + Pred (75.8%)UnknownHydroxychloroquine (89.1%) + azithromycin (49.8%) + glucocorticoids (45%) + lopinavir/ritonavir (33.8%) + tocilizumab (18.6%)Mean, 44 daysColmenero et al2Colmenero J. et al.J Hepatol. 2021; 74: 148-155Abstract Full Text Full Text PDF PubMed Scopus (255) Google ScholarEuropeFebruary 28, 2020 to April 7, 2020Liver11196RT-PCR65.34 ± 10.9668105 (35–168)Tac (66%)/Cyc (6%) + MMF (57%) + Eve (23%) + steroid (24%)UnknownAzithromycin (60%) + hydroxychloroquine (88%) + lopinavir/ritonavir (40%) + remdesivir (1%) + interferon beta (3%) + tocilizumab (15%) + corticosteroids (12%)Median follow-up of 23 daysDemir et al8Demir E. et al.Transpl Infect Dis. 2020; 22e13371Crossref PubMed Scopus (42) Google ScholarAsiaFebruary 1, 2020, and May 4, 2020Kidney4444RT-PCR44.9 ± 14.850Median, 74.5 (IQR, 31.5–128.3)Tac (77.5%)/Cyc (12.5%)/mTORi (10%) + MMF (90%) + steroids (100%)CNIs withdrawal (27.5%) + MMF withdrawal (100%) + mTORi withdrawal (10%)Favipiravir (45%) + Tocilizumab (12.5%) + Anakinra (7.5%) + Antibiotics (60%)Median 32 days (IQR, 14–51 days)Fava et al9Favà A. et al.Am J Transplant. 2020; 20: 3030-3041Crossref PubMed Scopus (76) Google ScholarEuropeMarch 4 and April 17, 2020Kidney104104RT-PCR59.7 ± 12.4855.759 (18–130) monthsTac (85.5%)/Cyc (2.88%)/mTORi (19.28%) + MPA (83.6%) + Pred (92.3%)CNI withdrawal (50/104) + mTORi withdrawal (12/104) + MMF/MPA withdrawal (71/104) + steroid withdrawal (1/104)Lopinavir/ritonavir (50/104) + darunavir/ritonavir (3/104) + darunavir/cobicistat (5/104) + remdesivir (2/104) + interferon-beta-1a (9/104) + tocilizumab (35/104) + hydroxychloroquine (101/104) + azithromycin (66/104)14.5 days (IQR, 8–96 days)Hilbrands et al10Hilbrands L.B. et al.Nephrol Dial Transplant. 2020; 35: 1973-1983Crossref PubMed Scopus (304) Google ScholarEuropeFebruary 1 and May 1, 2020Kidney305271RT-PCR and/or typical lung lesions from chest CT60 + 13627% 5 yearsTac (77%)/Cyc (10%) + MPA (69%) + AZA (5%) + Pred (84%) + mTORi (14%)Pred increase (58%) + Tac withdrawal (27%)/decrease (26%) + Cyc decrease (3%)/withdrawal (2%) + MMF decrease (7%)/withdrawal (54%) + AZA decrease (1%)/withdrawal (3%) + mTORi decrease (3%)/withdrawal (11%)(Hydroxy)chloroquine (73%) + lopinavir/ritonavir (18%) + remdesevir (1%) + interferon (2%) + tocilizumab (9%) + anakinra, % (2%) + high-dose steroids (18%)UnknownMalekhosseini et al11Ali Malekhosseini S. et al.Transplantation. 2021; 105: 90-99Crossref PubMed Scopus (22) Google ScholarAsiaFebruary 25, 2020, to July 20, 2020Solid8565RT-PCR or chest CT scan46.4 ± 16.578.837.1 (14.7, 72.7)Prednisolone (56.5%) + mycophenolate (51.2%)/MMF (23.5%) + tacrolimus (81.2%)/Cyc (5.9%) + sirolimus (5.9%)UnknownHydroxychloroquine (35.3%) + lopinavir/ritonavir (4.7%) + tavanex (4.7%) + azithromycin (27.1%) + imipenem (4.7%) + cotrimoxazole (3.5%)UnknownGaston et al12Gaston D.C. et al.Am J Transplant. 2021; 21: 1304-1311Crossref PubMed Scopus (18) Google ScholarNorth AmericaMarch 1 to May 15, 2020Solid2525RT-PCR60.0 (IQR, 54.0–64.5)48UnknownTac (72%) + Bel (28%) + antimetabolite (68%) + Pred (88%)Antimetabolite discontinuedAtazanavir (24%) + Convalescent Plasma (12%) + Hydroxychloroquine (96%) + Methylprednisolone (28%) + Remdesivir (4%) + Tocilizumab (68%)UnknownAbbreviations: AZA, azathioprine; Cyc, cyclosporine; CNIs, calcineurin inhibitor; CT, computed tomography; Eve, everolimus; IQR, interquartile range; MMF, mycophenolate mofetil; mTORi, mechanistic target of rapamycin inhibitor; pred, prednisone; RT-PCR, real-time polymerase chain reaction; Tac, tacrolimus. Open table in a new tab Supplementary Table 2Quality Assessment of Included Studies (the Other 10 Studies)AuthorSelectionComparabilityOutcomeTotalBenotmane et al6Benotmane I. et al.Transplantation. 2021; 105: 158-169Crossref PubMed Scopus (33) Google Scholar3036Bossini et al4Bossini N. et al.Am J Transplant. 2020; 20: 3019-3029Crossref PubMed Scopus (75) Google Scholar3036Cravedi et al7Cravedi P. et al.Am J Transplant. 2020; 20: 3140-3148Crossref PubMed Scopus (300) Google Scholar3036Crespo et al3Crespo M. et al.Transplantation. 2020; 104: 2225-2233Crossref PubMed Scopus (49) Google Scholar4037Demir et al8Demir E. et al.Transpl Infect Dis. 2020; 22e13371Crossref PubMed Scopus (42) Google Scholar2013Fava et al9Favà A. et al.Am J Transplant. 2020; 20: 3030-3041Crossref PubMed Scopus (76) Google Scholar3036Hilbrands et al10Hilbrands L.B. et al.Nephrol Dial Transplant. 2020; 35: 1973-1983Crossref PubMed Scopus (304) Google Scholar4138Malekhosseini et al11Ali Malekhosseini S. et al.Transplantation. 2021; 105: 90-99Crossref PubMed Scopus (22) Google Scholar3036Colmenero et al2Colmenero J. et al.J Hepatol. 2021; 74: 148-155Abstract Full Text Full Text PDF PubMed Scopus (255) Google Scholar3025Gaston et al12Gaston D.C. et al.Am J Transplant. 2021; 21: 1304-1311Crossref PubMed Scopus (18) Google Scholar3014 Open table in a new tab Supplementary Table 3Original Data and R CodeMortalitySevere InfectionStudylogORselogORStudylogORselogORBossini et al4Bossini N. et al.Am J Transplant. 2020; 20: 3019-3029Crossref PubMed Scopus (75) Google Scholar1.3862940.736048Benotmane et al6Benotmane I. et al.Transplantation. 2021; 105: 158-169Crossref PubMed Scopus (33) Google Scholar0.5007750.629887Cravedi et al7Cravedi P. et al.Am J Transplant. 2020; 20: 3140-3148Crossref PubMed Scopus (300) Google Scholar–0.673340.585795Demir et al8Demir E. et al.Transpl Infect Dis. 2020; 22e13371Crossref PubMed Scopus (42) Google Scholar0.6523251.133758Crespo et al3Crespo M. et al.Transplantation. 2020; 104: 2225-2233Crossref PubMed Scopus (49) Google Scholar–0.026340.252886Colmenero et al2Colmenero J. et al.J Hepatol. 2021; 74: 148-155Abstract Full Text Full Text PDF PubMed Scopus (255) Google Scholar–0.616190.333044Fava et al9Favà A. et al.Am J Transplant. 2020; 20: 3030-3041Crossref PubMed Scopus (76) Google Scholar–0.356670.520116Gaston et al12Gaston D.C. et al.Am J Transplant. 2021; 21: 1304-1311Crossref PubMed Scopus (18) Google Scholar1.7917591.095452Hilbrands et al10Hilbrands L.B. et al.Nephrol Dial Transplant. 2020; 35: 1973-1983Crossref PubMed Scopus (304) Google Scholar0.9082590.395832Malekhosseini et al11Ali Malekhosseini S. et al.Transplantation. 2021; 105: 90-99Crossref PubMed Scopus (22) Google Scholar1.2237751.028389Belli et al1Belli L.S. et al.Gastroenterology. 2020; 160: 1151-1163Abstract Full Text Full Text PDF PubMed Scopus (120) Google Scholar–0.597840.296207library("meta")metabmi_rc=metagen(logOR,selogOR,data = bmi_rc,sm = "OR", studlab = study,comb.random =TRUE,comb.fixed=FALSE,title = gs("Any infection"))metabmi_rcforest(metabmi_rc,transf = exp)funnel(metabmi_rc) Open table in a new tab Abbreviations: AZA, azathioprine; Cyc, cyclosporine; CNIs, calcineurin inhibitor; CT, computed tomography; Eve, everolimus; IQR, interquartile range; MMF, mycophenolate mofetil; mTORi, mechanistic target of rapamycin inhibitor; pred, prednisone; RT-PCR, real-time polymerase chain reaction; Tac, tacrolimus. library("meta") metabmi_rc=metagen(logOR,selogOR,data = bmi_rc,sm = "OR", studlab = study,comb.random =TRUE,comb.fixed=FALSE,title = gs("Any infection")) metabmi_rc forest(metabmi_rc,transf = exp) funnel(metabmi_rc) Protective Role of Tacrolimus, Deleterious Role of Age and Comorbidities in Liver Transplant Recipients With Covid-19: Results From the ELITA/ELTR Multi-center European StudyGastroenterologyVol. 160Issue 4PreviewDespite concerns that liver transplant (LT) recipients may be at increased risk of unfavorable outcomes from COVID-19 due the high prevalence of co-morbidities, immunosuppression and ageing, a detailed analysis of their effects in large studies is lacking. Full-Text PDF ReplyGastroenterologyVol. 161Issue 2PreviewWe read with great interest the letter by Yin et al,1 where the authors comment the results of our recently published study.2 Full-Text PDF

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