Negative impact of hyperglycaemia on tocilizumab therapy in Covid-19 patients

Abstract

Tocilizumab (TCZ) is used for treating moderate-to-severe Covid-19 pneumonia by targeting interleukin-6 receptors (IL-6Rs) and reducing cytokine release. Yet, in spite of this therapy, patients with vs. patients without diabetes have an adverse disease course. In fact, glucose homoeostasis has influenced the outcomes of diabetes patients with infectious diseases. Of the 475 Covid-19-positive patients admitted to infectious disease departments (University of Bologna, University Vanvitelli of Napoli, San Sebastiano Caserta Hospital) in Italy since 1 March 2020, 31 (39.7%) hyperglycaemic and 47 (60.3%) normoglycaemic patients (blood glucose levels ≥140mg/dL) were retrospectively evaluated at admission and during their hospital stay. Of note, 20 (64%) hyperglycaemic and 11 (23.4%) normoglycaemic patients had diabetes (P<0.01). At admission, hyperglycaemic vs. normoglycaemic patients had fivefold higher IL-6 levels, which persisted even after TCZ administration (P<0.05). Intriguingly, in a risk-adjusted Cox regression analysis, TCZ in hyperglycaemic patients failed to attenuate risk of severe outcomes as it did in normoglycaemic patients (P<0.009). Also, in hyperglycaemic patients, higher IL-6 plasma levels reduced the effects of TCZ, while adding IL-6 levels to the Cox regression model led to loss of significance (P<0.07) of its effects. Moreover, there was evidence that optimal Covid-19 infection management with TCZ is not achieved during hyperglycaemia in both diabetic and non-diabetic patients. These data may be of interest to currently ongoing clinical trials of TCZ effects in Covid-19 patients and of optimal control of glycaemia in this patient subset.

Keywords: Covid-19; Diabetes mellitus; Interleukin-6.

Fig. 1

All patients were treated with intravenous (IV) infusions of tocilizumab (TCZ) at doses of 8 mg/kg, whereas seven (22.6%) hyperglycaemic patients and five (10.6%) normoglycaemic patients received two TCZ IV infusions (P = 0.134). Mean ± standard deviation (SD) age was 65.7 ± 13.4 years in hyperglycaemic and 66.6 ± 12.2 years in normoglycaemic patients (P = 0.662), and 21 (61.8%) hyperglycaemic and 34 (72.3%) normoglycaemic patients were male (P = 0.425). Median time from illness onset (before admission) to discharge or death was 17.6 ± 7.2 days in hyperglycaemic and 18.1 ± 6.6 days in normoglycaemic patients; 19 (61.3%) hyperglycaemic and 26 (55.3%) normoglycaemic patients had hypertension (P = 0.388); 10 (32.3%) hyperglycaemic and seven (14.9%) normoglycaemic patients had dyslipidaemias (P = 0.063); and six (19.4%) hyperglycaemic and 15 (31.9%) normoglycaemic patients were smokers (P = 0.168). Mean hospitalization glucose levels were calculated as the means ± SD of all daily glucose blood values (2nd, 3rd, 4th, 5th, 6th day …). There were no significant differences in blood pressure, creatinine and troponin levels in hyperglycaemic vs. normoglycaemic patients. All patients were treated, as per the standard protocol for antiviral treatment, with TCZ and hydroxychloroquine. (A) Boxplots of interleukin-6 levels (ELISA kits, R&D Systems, Minneapolis, MN, USA) before and after TCZ therapy in hyperglycaemic and normoglycaemic patients show medians, 25th and 75th percentiles, and range. *P < 0.05 vs. before TCZ administration; ^§P < 0.05 vs. normoglycaemic patients. (B) Risk-adjusted Cox regression analysis curves show rates of survival with severe disease over up to 18 days for Covid-19 patients stratified by hyperglycaemia vs. normoglycaemia. Cox models were adjusted for body mass index, age, gender, blood pressure, heart rate, total cholesterol, high-density (HDL) and low-density (LDL) lipoprotein cholesterol, triglycerides, troponin, heart disease, hypertension, dyslipidaemia, current smoking, and use of beta-blockers, angiotensin-converting enzyme (ACE) inhibitors, calcium inhibitors, thiazide diuretics and aspirin. All statistical analyses were performed using SPSS for Windows version 23.0 software (IBM Corp., Armonk, NY, USA). Two-sided P < 0.05 was considered statistically significant. HR: hazard ratio.

Fig. S1

Kaplan–Meier analysis shows survival rates without severe disease during follow-up of normoglycaemic patients without diabetes (green), normoglycaemics with diabetes (yellow), and hyperglycaemics with (violet) and without (red) diabetes. Survival rates free of study outcomes were higher in normoglycaemics without vs. with diabetes (P < 0 01), normoglycaemics with diabetes vs. hyperglycaemics with diabetes (P < 0.05), and hyperglycaemics with vs. without diabetes (P < 0.01).