Predictive factors of clinical outcomes in patients with COVID-19 treated with tocilizumab: A monocentric retrospective analysis.

OBJECTIVE: The aim of this retrospective observational study is to analyse clinical, serological and radiological predictors of outcome in patients with COVID-19 pneumonia treated with tocilizumab, providing clinical guidance to its use in real-life.
METHOD: This is a retrospective, monocentric observational cohort study. All consecutive patients hospitalized between February the 11th and April 14th 2020 for severe COVID-19 pneumonia at Reggio Emilia AUSL and treated with tocilizumab were enrolled. The patient's clinical status was recorded every day using the WHO ordinal scale for clinical improvement. Response to treatment was defined as an improvement of one point (from the status at the beginning of tocilizumab treatment) during the follow-up on this scale. Bivariate association of main patients' characteristics with outcomes was explored by descriptive statistics and Fisher or Kruskal Wallis tests (respectively for qualitative or quantitative variables). Each clinically significant predictor was checked by a loglikelihood ratio test (in univariate logistic models for each of the considered outcomes) against the null model.
RESULTS: A total of 173 patients were included. Only hypertension, the use of angiotensin-converting enzyme inhibitors, PaO2/FiO2, respiratory rate and C-reactive protein were selected for the multivariate analysis. In the multivariable model, none of them was significantly associated with response.
CONCLUSIONS: Evaluating a large number of clinical variables, our study did not find new predictors of outcome in COVID19 patients treated with tocilizumab. Further studies are needed to investigate the use of tocilizumab in COVID-19 and to better identify clinical phenotypes which could benefit from this treatment.

Introduction

An aberrant immune-response characterized by uncontrolled hyperinflammation has been described in severe COVID-19 patients, and elevated blood levels of interleukin 6 (IL-6) have been related to a fatal outcome [1]. Tocilizumab (TCZ) is a humanized monoclonal antibody against IL6 receptor approved for the treatment of autoimmune rheumatic diseases. It has been administered as an off-label drug in the treatment of severe manifestation of COVID-19 with promising results [2, 3] but did not reduce mortality in the first published randomized controlled trials [4-7]. Nevertheless, recent data from two randomized platform trials, REMAP-CAP [8] and RECOVERY [9], showed a significant improvement in survival in patients with advanced-stage COVID-19 that underwent TCZ therapy.

Thus, the role of tocilizumab in COVID-19 treatment appears to be beneficial in selected subgroups of patients [10]. Early identification of personalized and efficacious treatment options for COVID-19 pneumonia, according to patient-specific or disease-specific parameters, could lead to a beneficial effect on prognosis and long-term outcome.

The aim of this retrospective observational study is to analyse clinical, serological and radiological predictors of outcome in patients with COVID-19 pneumonia treated with tocilizumab, providing clinical guidance to its use in real-life.

Materials and methods

Patients and case definition

This is a retrospective, monocentric observational cohort study performed at Reggio Emilia AUSL, at two different sites, the central research hospital of Reggio Emilia and Guastalla Hospital (Reggio Emilia province, Italy). We enrolled all consecutive patients hospitalized between February the 11th and April 14th 2020 for severe COVID-19 pneumonia and treated with TCZ.

The study was approved by Comitato Etico Area Vasta Emilia Nord. For most patients it was not possible to obtain a written consent as in the first phase of the pandemic at our site we did not want anything touched by the patients to be kept in the patients’ records. Nevertheless, verbal consent was always obtained, recorded, and signed by the attending physicians. This consent procedure was approved by both national and local ethics committee.

SARS-CoV2 infection was diagnosed at Hospital admission by a positive reverse-transcriptase polymerase chain-reaction in a respiratory tract specimen. COVID-19 pneumonia was confirmed if chest X-rays and/or high-resolution computed tomography (HRCT) scan showed suggestive findings [11-13].

Treatment

Tocilizumab was administered by intravenous (iv) or subcutaneous (sc) formulations. Sc TCZ was used in some patients because iv tocilizumab was not available for a period of time.

Iv TCZ was prescribed 8 mg/kg (maximum dose per single infusion: 800 mg), first dose at time 0 and a second dose after 12 hours. Sc TCZ was administered as 162 mg vials for a total of 2 to 4 administration, depending on patient’s weight.

Suggested clinical features for TCZ-therapy eligibility were the evidence of a severe pneumonia (oxygen saturation at rest on room air ≤93% and/or arterial oxygen partial pressure (PaO2)/oxygen concentration (FiO2) ≤300 mmHg), the presence of exaggerated inflammatory response (body temperature> 38°C; serum C reactive protein greater than or equal to 10 mg/dl or at least double the basal value) and absence of contraindications to TCZ therapy.

Together with TCZ therapy, patients could undergo other pharmacological treatments according to the standard of care that varied during the time-span considered for the study [14-16], namely: oxygen supply, hydroxychloroquine, lopinavir/ritonavir or darunavir/cobicistat, enoxaparin or unfractionated calcium heparin, glucocorticoids.

Data collection

Data were collected from both paper and electronic clinical records.

A standardized protocol with predefined laboratory tests at admission and during the follow-up was followed for all hospitalized COVID-19 patients from March 31st. Moreover, from both paper and electronic clinical records we collected information about hospital discharge, the condition of the patients at hospital discharge, the type of respiratory support and death. Patients’ past medical history, including comorbidities and current medications at home as well as glucocorticoids use before or after TCZ administration during the follow-up time was also recorded.

Radiological data

CT scans were performed using one of three scanners (128-slice Somatom Definition Edge, Siemens Healthineers care; 64-slice Ingenuity, Philips Healthcare; 16-slice GE Brightspeed, GE Healthcare Medical System) without contrast media injection, with the patient in supine position, during end-inspiration. Scanning parameters were: tube voltage 120 KV, automatic tube current modulation, collimation width 0.625 or 1.25 mm, acquisition slice thickness 2.5 mm, and interval 1.25 mm. Images were reconstructed with a high-resolution algorithm at slice thickness 1.0/1.25 mm.

Computerized tomography (CT) scans performed at emergency department presentation were retrospectively reviewed by a single radiologist with 15 years of experience, collecting the presence/absence of ground-glass opacities, consolidations, crazy-paving pattern and reversed halo sign, as well as the extension of pulmonary lesions using a visual scoring system (< 20%, 20–40%, 40–60%, and > 60% of parenchymal involvement).

Outcome measures

Patients were assessed daily during the hospitalization. The patient’s clinical status was recorded every day using a six-category ordinal scale defined as follows: 1) not hospitalized; 2) hospitalized, not requiring supplemental oxygen; 3) hospitalized, requiring any supplemental oxygen; 4) hospitalized, requiring non-invasive ventilation or use of high-flow oxygen devices; 5) hospitalized, receiving invasive mechanical ventilation or ECMO; 6) death. Response to treatment was defined as an improvement of one point (from the status at the beginning of TCZ treatment) during the follow-up on a six-category ordinal scale or live discharge from the hospital, whichever came first. On the contrary, a non-response to treatment was defined as at least one-point worsening of the clinical status after TCZ therapy. Patients who initially declined and afterward improved on the six-category ordinal scale were defined as non-responders. Beside response to treatment, a composite outcome of death or intubation during follow-up was considered. Patients already intubated at the moment of TCZ administration were not included for analyses regarding this outcome.

Statistical analysis

Bivariate association of main patients’ characteristics with outcomes was explored by descriptive statistics and Fisher or Kruskal Wallis tests (respectively for qualitative or quantitative variables).

Each clinically significant predictor was checked by a loglikelihood ratio test (in univariate logistic models for each of the considered outcomes) against the null model. Multivariable models were estimated for the two considered outcomes including all the variables with a p-value was less than 0.2 in the univariate models. Odds ratio (OR) (with respective 95% confidence intervals and Wald tests) were provided for univariate and multivariate logistic models. For reporting completeness, we estimated final models’ area under the Receiver Operating Characteristic curve (AUC) with respective 95% confidence interval.

Statistical analysis was performed using R 3.5.2 R Core Team (2020).

Results

A total of 173 patients were recruited for the study. For 144 patients data were available for each covariate analysed (32 females and 112 males; median age 63.98 years). Demographic, clinical, serological and radiological features of patients are summarized in Table 1. Median Charlson’s score was 2 (range 0–8, IQR 2–3).

Table 1

Demographic, clinical, serological and radiological features of COVID19 patients treated with tocilizumab at baseline.

	WHOLE POPULATION	NON-RESPONDERS	RESPONDERS	p	DEATH/INTUBATION	ALIVE/NOT INT.	p
	(n = 144)	(n = 39)	(n = 105)		(n = 25)	(n = 119)
	N (%) or median (IQR)	N (%) or median (IQR)	N (%) or median (IQR)		N (%) or median (IQR)	N (%) or median (IQR)
Age	63.98 (56.99–71.34)	65.13 (58.21–69.62)	63.16 (57.02–71.99)	0.660	67.39 (62.46–70.08)	62.89 (55.01–71.53)	0.070
Female/Male ratio	32/112 (22.22%/77.78%)	10/29 (25.64%/74.36%)	22/83 (20.95%/79.05%)	0.650	7/18 (28%/72%)	25/94 (21.01%/78.99%)	0.440
Follow-up (days)	12 (8–19.25)
Days from symptoms onset to admission	7 (5–10)	6 (4–9.5)	7 (5–10)	0.210	6 (3–8)	7 (5.5–10)	0.038
Days from admission to tocilizumab administration	2 (1–5)	2 (1–5.5)	2 (1–4)	0.993	4 (1–6)	2 (1–4)	0.131
Current smokers	11 (7.64%)	3 (7.69%)	8 (7.62%)	0.240	3 (12%)	8 (6.72%)	0.010
Former smokers	10 (6.94%)	5 (12.82%)	5 (4.76%)		5 (20%)	5 (4.2%)
BMI	28.73 (26.12–32.34)	28.53 (25.79–31.44)	28.73 (26.12–32.58)	0.800	29.3 (26.23–38.06)	28.02 (26.12–31.99)	0.510
Hypertension	93 (64.58%)	30 (76.92%)	63 (60%)	0.077	20 (80%)	73 (61.34%)	0.110
Ischemic heart disease	10 (6.94%)	3 (7.69%)	7 (6.67%)	0.990	2 (8%)	8 (6.72%)	0.690
COPD	7 (4.9%)	3 (7.69%)	4 (3.85%)	0.390	3 (12%)	4 (3.39%)	0.100
Diabetes mellitus	34 (23.61%)	12 (30.77%)	22 (20.95%)	0.270	8 (32%)	26 (21.85%)	0.300
PaO2/FiO2 (mmHg)	150.5 (110–231.25)	130 (100–165)	164 (119–240)	0.010	110 (92–140)	161 (121.5–239.5)	<0.001
SO2 (%)	94 (91.5–96)	93 (91.4–94)	94.1 (92–96)	0.120	94 (92–94.3)	94 (91.4–96)	0.640
Respiratory rate (acts/min)	24 (20–28)	26 (20–32)	24 (20–28)	0.340	28 (22–33)	24 (20–28)	0.070
Room air at TCZ start	10 (6.94%)	6 (15.38%)	4 (3.81%)	0.020	2 (8%)	8 (6.72%)	0.010
Venturi mask at TCZ start	78 (54.17%)	16 (41.03%)	62 (59.05%)		7 (28%)	71 (59.66%)
NIV at TCZ start	53 (36.81%)	15 (38.46%)	38 (36.19%)		14 (56%)	39 (32.77%)
OTI at TCZ start	3 (2.08%)	2 (5.13%)	1 (0.95%)		2 (8%)	1 (0.84%)
CRP (mg/dl)	15.03 (9.04–20.18)	17.68 (11.57–23.06)	14.28 (8.2–19.68)	0.060	18.06 (11.93–23.05)	14.5 (8.98–19.69)	0.210
Procalcitonin (microgr/dl)	0.18 (0.12–0.33)	0.22 (0.14–0.42)	0.16 (0.11–0.33)	0.220	0.17 (0.12–0.34)	0.18 (0.11–0.33)	0.870
IL6 (pg/ml)	60.15 (31.25–109.5)	81.65 (41.10–171.90)	56.75 (29.98–82.85)	0.130	61.65 (36.57–115.23)	60.15 (31.13–109.05)	0.650
LDH (U/L)	584 (432–762)	591 (405–810)	569.5 (436–745.5)	0.380	591 (456–820)	569.5 (429.5–751)	0.230
Ferritin (ng/ml)	1096 (581–2624.5)	1394 (826–2704)	1078 (560.5–2481.5)	0.450	1560.15 (773.5–2245)	1083 (581–2636.25)	0.780
D-dimer (ng/ml)	812.5 (505.75–1946.25)	1446 (543–4004.5)	724 (463–1620)	0.220	3352.5 (1776.75–5457.75)	713 (448.25–1610.75)	0.002
Neutrophils (103/ml)	5475 (4145–7410)	5780 (4500–8320)	5230 (3945–7045)	0.130	5480 (4495–9110)	5310 (4010–7170)	0.170
Platelets (103/ml)	225.5 (167.75–298.75)	203 (163–285)	235 (178–312)	0.110	204 (157–2858.5)	227 (173–307)	0.350
Troponin	8.5 (4.45–18.65)	8.6 (5.15–22.55)	8.15 (4.25–17.55)	0.530	9.4 (6.25–39.43)	8 (4.3–17.4)	0.170
Consolidations	102 (70.83%)	28 (71.79%)	74 (70.48%)	0.990	20 (80%)	82 (68.91%)	0.340
Lung involvement <20%	31 (21.53%)	8 (20.51%)	23 (21.9%)	0.870	5 (20%)	26 (21.85%)	0.250
Lung involvement 20–40%	44 (30.56%)	11 (28.21%)	33 (31.43%)		4 (16%)	40 (33.61%)
Lung involvement 40–60%	37 (25.69%)	12 (30.77%)	25 (23.81%)		8 (32%)	29 (24.37%)
Lung involvement >60%	32 (22.22%)	8 (20.51%)	24 (22.86%)		8 (32%)	24 (20.17%)
Treatments:
Previous (at home)
ACE-I	34 (23.61%)	15 (38.46%)	19 (18.1%)	0.020	10 (40%)	24 (20.17%)	0.040
ARB	29 (20.14%)	8 (20.51%)	21 (20%)	0.990	5 (20%)	24 (20.17%)	0.990
During hospitalization
TCZ iv	68 (47.22%)	19 (48.72%)	49 (46.67%)	0.850	12 (48%)	56 (47.06%)	0.990
TCZ sc	76 (52.78%)	20 (51.28%)	56 (53.33%)		13 (52%)	63 (52.94%)
Oxygen supply	142 (98.61%)	39 (100%)	103 (98.1%)	0.990	25 (100%)	117 (98.32%)	0.990
GCs before TCZ	32 (22.22%)	8 (20.51%)	24 (22.86%)	0.830	6 (24%)	26 (21.85%)	0.800
GCs along with or after TCZ	61 (42.66%)	16 (41.02%)	45 (42.86%)	0.990	12 (48%)	49 (41.18%)	0.500
Discharged	124 (86.11%)	19 (48.72%)	105 (100%)	<0.001	5 (20%)	119 (100%)	<0.001
In room air	1 (0.69%)	1 (2.56%)	0 (0%)		1 (4%)	0 (0%)
Deceased	19 (13.19%)	19 (48.72%)	0 (0%)		19 (76%)	0 (0%)

BMI: Body Mass Index; COPD: Chronic Obstructive Pulmonary Disease; PaO2/FiO2: partial arterial oxygen pressure to inspired oxygen fraction ratio; SO2: peripheral oxygen saturation; NIV: non invasive ventilation; OTI: oro-tracheal intubation; TCZ: tocilizumab; CRP: C-reactive protein; IL6: interleukin-6; LDH: lactate de-hydrogenasis; ACE-I: angiotensin converting-enzyme inhibitors; ARB: angiotensin II receptor blockers; GCs: glucocorticoids. We used Fisher tests to compare percentages and Kruskal Wallis tests to compare distribution of quantitative ones.

The median follow-up was 318 (IQR 51–428.5). Three patients had history of stroke or transient ischemic attack. Five patients had chronic kidney disease and one was a kidney transplant recipient. One patient had cirrhosis. Only two patients were on immunosuppressive therapy at baseline, one for ulcerative rectum-colitis and one for polymyalgia rheumatica. One patient had HIV infection.

Most patients responded to TCZ therapy (105 patients; 72.9%), 19 patients died while a total of 25 patients died or were intubated during the follow-up. Three patients received TCZ therapy during their stay in intensive care unit with oro-tracheal intubation and invasive ventilation.

TCZ was administered sc in 76 patients (52.8%) and iv in 68 (47.2%); 32 patients (22.2%) were treated with glucocorticoids before TCZ, while 61 (42.6%) received GCs together with or after TCZ treatment.

Table 2 shows univariate and multivariate models for non-response to TCZ therapy.

Table 2

Clinical, serological and radiological features associated with NON response to tocilizumab therapy.

	Univariate			Multivariate
	OR	CI (95%)	p-value	OR	CI (95%)	p-value
Gender	1.301	0.534–3.021	0.548
Age	1.003	0.971–1.038	0.845
Time symptoms to TCZ therapy	1.001	0.924–1.078	0.977
NIV or intubation at TCZ therapy	1.308	0.615–2.757	0.481
Hypertension	2.222	0.988–5.4	0.063	1.649	0.641–4.494	0.309
Diabetes mellitus	1.677	0.72–3.802	0.220
Ischemic heart disease	1.167	0.242–4.447	0.830
Current smoker	1.113	0.233–4.122	0.880
Former smoker	2.968	0.778–11.342	0.102
ACE-I	2.829	1.247–6.412	0.012	2.525	0.9996–6.464	0.0504
Angiotensin receptor blockers	1.032	0.395–2.501	0.946
PaO2/FiO2	0.993	0.987–0.998	0.013	0.995	0.988–1.0004	0.081
Respiratory rate	1.049	0.993–1.111	0.088	1.03	0.972–1.095	0.335
CRP	1.735	1.081–3.282	0.056	1.655	1.049–3.134	0.065
Lung involvement 20–40%	0.958	0.335–2.824	0.937
Lung involvement 40–60%	1.380	0.483–4.096	0.551
Lung involvement >60%	0.958	0.304–3.02	0.941
GCs before TCZ	0.871	0.336–2.08	0.764
GCs along with or after TCZ	0.928	0.435–1.947	0.843
TCZ: IV	0.928	0.435–1.947	0.843

Hypertension, the use of angiotensin-converting enzyme inhibitors (ACE-I) at home, PaO2/FiO2, respiratory rate and C-reactive protein (CRP) were selected for the multivariate analysis. In the multivariable model, none of them was significantly associated with response, however some borderline associations may be cautiously described. Particularly, the use of ACE-I (OR = 2.52, 95%CI = 1.25–6.41, p = 0.012) and increasing CRP values (OR for unit increase = 1.66, 95%CI = 1.08–3.28, p = 0.05) were inversely associated with response to TCZ therapy, while increasing PaO2/FiO2 was positively associated with response to therapy (OR for unit increase = 0.995; 95%CI = 0.98–1, p = 0.0013). No significant difference in response rates was observed between patients treated with intravenous or subcutaneous tocilizumab.

Regarding the composite outcome death/intubation (Table 3), the variables selected for the multivariate analysis were age, clinical status at the beginning of follow-up, hypertension, smoke, use of ACE-I, PaO2/FiO2, respiratory rate and CRP.

Table 3

Clinical, serological and radiological features associated with death or intubation.

	Univariate			Multivariate
	OR	95% CI	p-value	OR	95% CI	p-value
Gender	1.382	0.459–3.738	0.539
Age	1.047	1.002–1.098	0.049	1.034	0.978–1.101	0.258
Time symptoms to TCZ therapy	0.949	0.846–1.057	0.359
NIV or intubation at TCZ therapy	3.151	1.271–8.177	0.015	1.429	0.435–4.72	0.553
Hypertension	2.219	0.82–7.093	0.140	0.901	0.223–3.83	0.883
Diabetes mellitus	1.887	0.694–4.86	0.196
Ischemic heart disease	1.31	0.189–5.69	0.744
Current smoker	2.625	0.532–10.267	0.187	2.472	0.381–13.845	0.313
Former smoker	7	1.762–28.091	0.005	9.608	1.827–56.445	0.008
ACE-I	3.013	1.16–7.711	0.021	3.811	1.083–14.578	0.041
Angiotensin receptor blockers	0.825	0.224–2.445	0.746
PaO2/FiO2	0.986	0.976–0.994	0.003	0.99	0.978–1	0.073
Respiratory rate	1.09	1.023–1.169	0.010	1.07	0.997–1.159	0.076
CRP	1.496	0.957–2.804	0.110	1.474	0.892–2.673	0.119
Lung involvement 20–40%	0.533	0.122–2.195	0.381
Lung involvement 40–60%	1.255	0.357–4.699	0.724
Lung involvement >60%	1.517	0.427–5.738	0.522
Glucocorticoids before TCZ	0.983	0.302–2.741	0.975

The use of ACE-I and a past history of smoke were significantly related to unfavourable outcome, thus considered as risk factors for death or intubation (OR = 3.81, 95%CI = 1.16–7.71, p = 0.02, and OR = 9.6, 95%CI = 1.76–28.1, p = 0.005, respectively). Moreover, a borderline association was found for respiratory rate as a risk factor for death/intubation (OR for unit increase = 1.07, 95%CI = 1.02–1.17, p = 0.01), while an increase of PaO2/FiO2 had a trend towards significance as a protective factor for the composite outcome (OR for unit increase = 1, 95%CI = 0.98–0.99, p = 0.003).

Finally, response model achieved an AUC of 0.72 (0.95CI: 0.62–0.82) while death/intubation had an AUC of 0.83 (0.95CI: 0.73–0.93).

Regarding safety analysis one patient had an Acinetobacter baumannii sepsis and another one had oesophageal candidiasis, both in non-responders. No other opportunistic infection was detected.

Discussion

Our study showed that most patients improved after TCZ therapy (72.9%), while a total of 25 patients died or were intubated during the follow-up.

In our study many clinical, serological and radiological data have been analysed. Nevertheless, none of them was significantly associated with improvement after TCZ therapy. High CRP levels had a borderline association with a negative outcome.

On the contrary, some interesting findings emerged regarding the composite outcome death/intubation, as the use of ACE-I and a past history of smoke were found to be significant risk factors. Moreover, the unit increase of respiratory rate was significantly related to unfavourable outcome, while an increment of PaO2/FiO2 had a trend towards significance as a protective factor for the composite outcome. However, all these associated factors might be the expression of more severe disease instead than negative response to TCZ predictors.

We previously reported that higher CRP levels before starting TCZ and 3 days after the onset of the disease were associated with a reduced therapy response and an increased risk of being intubated or die [17]. Furthermore, CRP levels persisted elevated in non-responders and in patients who were intubated or died [17]. Higher CRP levels suggest a high systemic inflammation. We can speculate that in most severe clinical pictures, where a massive immune activation is sustained by several inflammatory pathways, TCZ might be not sufficient to down-regulate the hyperinflammation as it targets a single inflammatory pathway. In fact, even though high levels of IL6 were assessed as a risk factors for severe forms of COVID19, we previously not observe any association with IL-6 levels and response to TCZ therapy [17]. Consistently with this interpretation, the RECOVERY trial showed an improved survival in patients treated with TCZ only in the group treated also with glucocorticoids, whereas no improvement was shown in the group not treated with glucocorticoids [9].

In our study, the use of ACE-I was found to be significant risk factors for death or intubation. Both negative and positive effects of ACE-I on COVID-19 clinical outcomes have been described. However, it remains unclear whether their use affects the clinical course of SARS-CoV2 infection [18].

Notably, tocilizumab therapy showed a good safety profile. Nevertheless, it must be noticed that during the first months of the COVID-19 the awareness regarding secondary opportunistic infection was low and no specific screening for pulmonary aspergillosis was in place.

The current study has many limitations, but also some strengths. This was a retrospective observational cohort study conducted at a two-hospital healthcare organisation following the same internal protocol for the management of COVID19 pneumonia. The limitation could be the sample size and its retrospective nature. However, it represents one of the largest series of TCZ-treated patients and all patients were homogeneously followed-up using a common standardized protocol.

Another strength is that we analysed many clinical, serological and radiological data (Tables 2 and 3) in order to evaluate a great number of variables. Finally, not having an untreated control group, we cannot distinguish if the identified biomarkers are predictors of COVID-19 prognosis even independently of TCZ treatment.

In conclusion, even evaluating a large number of clinical variables, our study did not find new predictors of outcome in COVID-19 pneumonia patients treated with TCZ. It must be noted that 35.2% of our patients did not receive glucocorticoids-treatment and that the combination of glucocorticoids and TCZ appears to act synergistically and to be particularly beneficial in patients with severe COVID-19 and systemic inflammation.

Further studies are needed to investigate the use of this drugs in COVID-19 pneumonia and to better identify clinical phenotypes which could benefit from tocilizumab therapy.

8 Jun 2021

PONE-D-21-11985

Clinical outcomes predictive factors in patients with COVID-19 treated with tocilizumab: a monocentric retrospective analysis.

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #2: Partly

Reviewer #3: Partly

**********

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

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: No

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: No

Reviewer #3: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Dr Dolci, and colleagues addressed a nice study, “Clinical outcomes predictive factors in patients with COVID-19 treated with tocilizumab: a monocentric retrospective analysis”. However, there are many concerns that must be address.

Materials, methods, and Results

Major concerns:

1. The glucocorticoids (GCs) along with or after TCZ should be included in the uni and multi models at table 1 and 2 analysis, once 42 and 50% of each group were on GCs therapy

2. The median follow-up of 12 days (range 8-19 days) is too short to evaluate the outcomes, the authors should extent at least until 28 days.

3. The authors decided to include TCZ in subcutaneous formulation, please provide different analysis for each one, once the PK/PD could be different, and based on result of this analysis, please add in discussion section an explanation supporting or not its use.

Minor concerns:

1. The authors should include all abbreviation with meanings at the first time “CT scans performed at ER (???)” line 145, page 6

Reviewer #2: This is a single center retrospective review evaluating outcomes and predictor factors for the use of tocilizumab and COVID-19 infections. The study had a fairly large population of n=144. As this is a retrospective review, the conclusions and causality are difficult to infer. It is an interesting study as it proceeded the use of remdesivir.

I did have some comments/suggestions for the authors:

Other comorbidities associated with severe COVID were not included: pulmonary disease, stroke, kidney disease, and liver disease. What was the outcome of the non-responders who did not die? Were any of the individuals immunosuppressed at baseline? What was the cause of death for non-responders? Any further delineation on how sick patients were on admission (i.e. SOFA score) would be useful to understand the patient population in the study.

Any report of co-infections or opportunistic infections in the non-responders?

I would like further delineation on the use of SQ versus IV tocilizumab. Was there any difference in these groups and outcomes and deaths?

Additionally, including the median time of initiation of symptoms and/or the median time of admission to administration tocilizumab therapy would be helpful in the responder versus non responder groups.

I was also confused there is a variable in Table 3 of NIV or mechanical ventilation at time of tocilizumab therapy but I thought non-responders were identified as requiring mechanical ventilation or death.

Table 1: Would consider using decimal points instead of commas for p-value column. Consider adding a column for responders as this should be the direct comparison to non-responders. It is less useful to compare non-responder to total population.

Reviewer #3: Although the paper does highlight the paucity of information available on the utility of tocilizumab, unfortunately there are several flaws to the study.

1. The wording of the title is confusing. It would be preferable to read “Predictive factors of clinical outcomes in patients with COVID-19 …” rather than Clinical outcomes predictive factors in patients with COVID-19…

2. Multiple times throughout the paper, the writers use the term “heavy” – line 37, 64, 288 etc. It is unclear what is meant by this term and I suspect it may be a mistranslation.

3. I am concerned about the difference in administration of the tocilizumab – some patients received the drug subcutaneously and some intravenously. I believe a subanalysis demonstrating no difference between the two formulations would be prudent given that how the drug is administered may impact outcomes. Additionally, there does not seem to be any subanalysis to determine if there are differences that could be attributed to patients who received other treatments, including hydroxychloroquine, lopinavir/ritonavir or darunavir/cobicistat

4. Line 145 has “???”. I suspect something else was meant to be written here.

5. The six-category ordinal scale used as an outcome measure was not described

6. Overall, this is a small study that does not include appropriately defined outcome measures nor does it explore potential biases appropriately. The conclusions are not substantially different from the larger trials that the authors themselves cite, including REMAP-CAP and RECOVERY.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

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31 Oct 2021

MANUSCRIPT ID: PONE-D-21-11985R1

23rd July 2021

Dear Editor,

We are very grateful for your constructive comments and suggestions to our paper entitled “Clinical outcomes predictive factors in patients with COVID-19 treated with tocilizumab: a monocentric retrospective analysis.”.

We here provide a point-by-point reply to the comments and we have incorporated the related changes in the manuscript. The page and lines reported refer to the manuscript with changes track. We thank for the thoughtful insights which helped to significantly improve the manuscript.

Reviewer #1: Dr Dolci, and colleagues addressed a nice study, “Clinical outcomes predictive factors in patients with COVID-19 treated with tocilizumab: a monocentric retrospective analysis”. However, there are many concerns that must be address.

Materials, methods, and Results

Major concerns:

1. The glucocorticoids (GCs) along with or after TCZ should be included in the uni and multi models at table 1 and 2 analysis, once 42 and 50% of each group were on GCs therapy.

Authors’ reply: we are grateful for this comment. We have performed this analysis and added it to table 1. No associations with the outcomes were found.

2. The median follow-up of 12 days (range 8-19 days) is too short to evaluate the outcomes, the authors should extent at least until 28 days.

Authors’ reply: we are grateful for this comment and we extended the follow-up to the last data available for each patient in our electronic system. The new median follow-up is 318 (IQR 51-428.5), but no variation in the primary outcome was witnessed. We updated the data in the manuscript (table 1 and page 18, line 203).

3. The authors decided to include TCZ in subcutaneous formulation, please provide different analysis for each one, once the PK/PD could be different, and based on result of this analysis, please add in discussion section an explanation supporting or not its use.

Authors’ reply: we are grateful for these comments and we explored this approach previously but we did not include it in the paper as splitting the analysis by type of administration would be detrimental for sample size/power of each analysis. However, we formally added administration type in the variable selection procedure (last line of table 2) and no differences in response/death-intubation were associated to it. We also added this sentence at lines 249-250: “No significant difference in response rates was observed between patients treated with intravenous or subcutaneous tocilizumab.”

Minor concerns:

1. The authors should include all abbreviation with meanings at the first time “CT scans performed at ER (???)” line 145, page 6.

Authors’ reply: we modified the paper accordingly.

Reviewer #2: This is a single center retrospective review evaluating outcomes and predictor factors for the use of tocilizumab and COVID-19 infections. The study had a fairly large population of n=144. As this is a retrospective review, the conclusions and causality are difficult to infer. It is an interesting study as it proceeded the use of remdesivir.

I did have some comments/suggestions for the authors:

Other comorbidities associated with severe COVID were not included: pulmonary disease, stroke, kidney disease, and liver disease.

Authors’ reply: regarding pulmonary diseases COPD was included in the first version of the manuscript (Table 1). Regarding the other conditions, we added “Three patients had history of stroke or transient ischemic attack. Five patients had chronic kidney disease and one was a kidney transplant recipient. One patient had cirrhosis.” (page 10, line 203-205).

What was the outcome of the non-responders who did not die?

Authors’ reply: non-responders who did not die underwent a subsequent clinical improvement. To clarify the responder/non responder definition we added this sentence “Patients who initially declined and afterward improved on the six-category ordinal scale were defined as non-responders.” at pag. 7, line 161-162.

Were any of the individuals immunosuppressed at baseline?

Authors’ reply: at page 18, line 205-207, we added “Only two patients were on immunosuppressive therapy at baseline, one for ulcerative rectum-colitis and one for polymyalgia rheumatica. One patient had HIV infection.”

What was the cause of death for non-responders?

Authors’ reply: the cause of death for non responders was respiratory failure or intensive care-related complications.

Any further delineation on how sick patients were on admission (i.e. SOFA score) would be useful to understand the patient population in the study.

Authors’ reply: we added the sentence “Median Charlson’s score was 2 (range 0-8, IQR 2-3).” at pag. 7-8, lines 182-183.

Any report of co-infections or opportunistic infections in the non-responders?

Authors’ reply: we added this sentence in the results section, page 23, lines 266-267: “Regarding safety analysis one patient had an Acinetobacter baumanii sepsis and another one had oesophageal candidiasis, both in non-responders. No other opportunistic infection was detected.”. We have discussed this result at page 24, lines 300-302 as follow: “Notably, tocilizumab therapy showed a good safety profile. Nevertheless, it must be noticed that during the first months of the COVID-19 the awareness regarding secondary opportunistic infection was low and no specific screening for pulmonary aspergillosis was in place.”

I would like further delineation on the use of SQ versus IV tocilizumab. Was there any difference in these groups and outcomes and deaths?

Authors’ reply: we are grateful for this comment. As previously answered to Reviewer #1 we explored this approach previously but we did not include it in the paper as splitting the analysis by type of administration would be detrimental for sample size/power of each analysis. However, we formally added administration type in the variable selection procedure (last line of table 2) and no differences in response/death-intubation were associated to it. We also added this sentence at page 22 lines 249-250: “No significant difference in response rates was observed between patients treated with intravenous or subcutaneous tocilizumab.”

Additionally, including the median time of initiation of symptoms and/or the median time of admission to administration tocilizumab therapy would be helpful in the responder versus non responder groups.

Authors’ reply: we performed the suggested analysis, a slightly lower time from symptom onset to admission/first treatment was recorded for death/int patients (6 days in median) compared to the others (7, p = 0.038), likely due to more severe symptoms and quickier admission/treatment. No difference was found. We included the analysis in table one.

I was also confused there is a variable in Table 3 of NIV or mechanical ventilation at time of tocilizumab therapy but I thought non-responders were identified as requiring mechanical ventilation or death.

Authors’ reply: non responders were defined as “non-response to treatment was defined as at least one-point worsening of the clinical status after TCZ therapy.” (page 7, lines 161-162).

Table 1: Would consider using decimal points instead of commas for p-value column. Consider adding a column for responders as this should be the direct comparison to non-responders. It is less useful to compare non-responder to total population.

Authors’ reply: thank you for this comment, we modified table 1 accordingly.

Reviewer #3: Although the paper does highlight the paucity of information available on the utility of tocilizumab, unfortunately there are several flaws to the study.

1. The wording of the title is confusing. It would be preferable to read “Predictive factors of clinical outcomes in patients with COVID-19 …” rather than Clinical outcomes predictive factors in patients with COVID-19…

Authors’ reply: we are grateful for this suggestion, we modified the title accordingly: “Predictive factors of clinical outcomes in patients with COVID-19 treated with tocilizumab: a monocentric retrospective analysis.”.

2. Multiple times throughout the paper, the writers use the term “heavy” – line 37, 64, 288 etc. It is unclear what is meant by this term and I suspect it may be a mistranslation.

Authors’ reply: we are grateful for this suggestion, we modified the paper accordingly.

3. I am concerned about the difference in administration of the tocilizumab – some patients received the drug subcutaneously and some intravenously. I believe a subanalysis demonstrating no difference between the two formulations would be prudent given that how the drug is administered may impact outcomes. Additionally, there does not seem to be any subanalysis to determine if there are differences that could be attributed to patients who received other treatments, including hydroxychloroquine, lopinavir/ritonavir or darunavir/cobicistat Braglia, poi Giovanni

Authors’ reply: we are grateful for this comment. We have performed an analysis considering different ways of tocilizumab administration and added it to table 1. No associations with the outcomes were found.

4. Line 145 has “???”. I suspect something else was meant to be written here.

Authors’ reply: we are grateful for this comment and we apologize for the typo. We have changed the paper accordingly.

5. The six-category ordinal scale used as an outcome measure was not described.

Authors’ reply: the six-category ordinal scale used was described in the original manuscript and you can find it at pages 6-7, lines 154-157 of the revised version.

6. Overall, this is a small study that does not include appropriately defined outcome measures nor does it explore potential biases appropriately. The conclusions are not substantially different from the larger trials that the authors themselves cite, including REMAP-CAP and RECOVERY.

Authors’ reply: whereas we do agree that the conclusions are not substantially different from larger trials, we think that outcome measures were appropriately defined and potential biases explored in the context of the limitations that we have reported in the discussion. Furthermore, even though larger multicenter cohort studies and trials have been published, we describe one of the largest monocentric cohort of patients with COVID-19 treated with tocilizumab.

We would like to express our great appreciation to you and the reviewers for the comments on our paper. If you have any further queries, please do not hesitate to contact us.

Kind regards,

Giovanni Dolci

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

10 Jan 2022

Predictive factors of clinical outcomes in patients with COVID-19 treated with tocilizumab: a monocentric retrospective analysis.

PONE-D-21-11985R1

Dear Dr. Dolci,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Tai-Heng Chen, M.D.

Academic Editor

PLOS ONE

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

**********

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

Reviewer #1: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The authors addressed all answers to the comments . I don’t need of further information and the manuscript is fine in the current format.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

17 Jan 2022

PONE-D-21-11985R1

Predictive factors of clinical outcomes in patients with COVID-19 treated with tocilizumab: a monocentric retrospective analysis.

Dear Dr. Dolci:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

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Thank you for submitting your work to PLOS ONE and supporting open access.

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on behalf of

Dr. Tai-Heng Chen

Academic Editor

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