Abstract
Background
Oncologic patients are vulnerable to prolonged or severe COVID-19 due to immunosuppression and comorbidities. Our initial Phase I/II clinical trial has showed that epigallocatechin-3-gallate (EGCG), a catechin monomer isolated from tea, exhibits favorable safety profiles with therapeutic effects against COVID-19 pneumonia. This phase II, open-label, randomized controlled trial further evaluated the efficacy and safety of 7-day aerosolized epigallocatechin-3-gallate (EGCG) in oncologic patients with COVID-19 pneumonia.
Methods
This trial was conducted from June 2023 to May 2024. Patients were randomized (2:1) to receive aerosolized EGCG plus standard treatment or standard treatment alone. The primary endpoint was CT imaging improvement. Secondary endpoints included symptom resolution and the safety of EGCG.
Results
114 patients were randomized, with 108 eligible (71 in EGCG group, 37 in control group). The EGCG group showed significantly greater CT improvement (P = 0.004) and faster symptom resolution for fever (P = 0.035), cough (P = 0.048), and dyspnea (P = 0.015). Improvement rates were higher in the EGCG group for fever (95% confidence interval: 1.380 -10.352) and dyspnea (95% confidence interval:1.750-60.446). Post-treatment lactate dehydrogenase levels were significantly lower in the EGCG group (P = 0.028). Safety profiles were comparable, with only mild adverse events observed in the EGCG group.
Conclusions
Aerosolized EGCG significantly improved both radiological and clinical outcomes with a favorable safety profile in oncologic patients with COVID-19 pneumonia, although broader application requires further validation in larger multi-center trials.
Trial registry
ClinicalTrials.gov, TRN: NCT06924749, Registration date: 22 August 2023.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12885-026-15553-x.
Keywords: Epigallocatechin gallate (EGCG), Aerosolized inhalation, Tumor patients, Randomized clinical trial, COVID-19 pneumonia
Introduction
The COVID-19 virus continues to mutate, often triggering several waves of COVID-19 outbreaks among the population and resulting in peaks in healthcare demand [1]. Cancer patients, a population with common risk factors like advanced age and immunosuppression, are predisposed to severe or long COVID-19 [2, 3]. When patients suffer from both COVID-19 and cancer, the formulation of a treatment plan requires comprehensive consideration of multiple factors, including the patient’s specific condition, physical status, treatment response and medical resources [4]. For cancer patients with COVID-19 pneumonia, priority should be given to treating the viral infection, while also taking into consideration cancer treatment [5]. Patients with radiological features of COVID-19 pneumonia often require more time to recover and are prone to developing long COVID [6]. And there is a huge number of co-infections with other viruses, fungi, and bacteria which complicates the symptoms and prognosis of the disease [7]. Therefore, controlling lung inflammation is crucial. However, due to issues such as drug accessibility, rationality, and side effects, there are few safe, economical, and effective drugs specifically for lung inflammation. Treatments with corticosteroids and IL-6 inhibitors are not ideal.
Tea, a natural product used in traditional folk medicine for centuries, contains epigallocatechin-3-gallate (EGCG) as its core bioactive component, which demonstrates significant anti-inflammatory, antioxidant, antiviral, and antitumor properties. EGCG in COVID-19 treatment has played an important role as an antiviral kinase [8]. It effectively interfered with the activity of viral protease, particularly at physiological concentrations, which inhibited the replication of SARS-CoV-2 virus. In addition, it regulated multiple inflammatory pathways to reduce levels of infection factors and activate the cell immune system, thereby protecting the host from systemic damage caused by the infection. He Y reported that EGCG inhibited the activity of the main protein kinase at its key activation site, thereby blocking the SARS-CoV-2 virus’s viral protein maturation process [9]. It activates the Cytokine Activator 1 enzyme to directly regulate the NF-κB complex pathway, inhibits NLR family pyrin structure-containing proteins (NLRP3) inflammatory signal pathways and lower STAT1 and STAT3 activities, thereby reducing white blood cell interleukin-1 (IL-1) and interleukin-6 (IL-6) levels. As an antioxidant, EGCG neutralized free radicals (ROS) and reactive nitrogen species (RNS), thereby reducing oxidative stress damage to the host cells caused by infection.
Our previous Phase I-II clinical study found aerosolized EGCG was safe and exhibited preliminary efficacy in treating COVID-19 pneumonia [10]. Therefore, we conducted this Phase II study to further validate its effectiveness and safety.
Methods
Study design
This clinical trial was conducted at the Shandong Cancer Hospital and Institute in Shandong, China. The inclusion criteria were as follows: patients aged 18 years or older with histologically confirmed malignant tumors; confirmed SARS-CoV-2 infection with radiological evidence of characteristic active COVID-19 pneumonia, as defined in the Diagnosis and Treatment Protocol for COVID-19 Infection (Trial Version 10) issued by the National Health Commission of China; tolerable to aerosolized inhalation treatment; and hospitalized patients with SARS-CoV-2 infection confirmed by polymerase chain reaction assay within 2 months of randomization, presenting with moderate-to-severe COVID-19 pneumonia (defined as any radiographic evidence of pulmonary infiltrates and oxygen saturation > 94% on room air). COVID-19 pneumonia severity assessments were independently evaluated by three senior specialists according to the aforementioned criteria, with final classification determined only upon achieving consensus among all three experts. The exclusion criteria included: rapid clinical deterioration within 2 days prior to enrollment, characterized by progressive respiratory distress or radiological evidence of lesion progression > 50% within 24–48 h, or resting oxygen saturation ≤ 93% while breathing room air at the time of enrollment; non-SARS-CoV-2 infectious interstitial pneumonia; known allergy or hypersensitivity to EGCG; alanine aminotransferase or aspartate aminotransferase levels greater than five times the upper limit of normal; creatinine clearance < 50 mL/min; and pregnant or lactating women (Trial protocol detail in Supplement 1).
Anti-tumor treatments were not permitted during the study period except concurrent endocrine therapy or anti-HER2 therapy. Corticosteroids could be administered at the physician’s discretion for tumor-related symptoms or pulmonary inflammation, with the indication clearly documented.
The study protocol and informed consent were approved by the local institutional review and ethical committees and registered at ClinicalTrials.gov (NCT06924749). Written informed consent was obtained from each participant. The study adhered to the consolidated standards of reporting trials guidelines.
Randomization and blinding
Based on previous evidence supporting the efficacy and safety of EGCG, the trial employed a 2:1 randomization ratio (EGCG group: control group). The design was primarily adopted for ethical reasons, to allow more high‑risk oncologic patients with COVID-19 pneumonia access to the investigational intervention while preserving scientific rigor. Such an approach is consistent with the need for exploratory research in vulnerable populations during a public health emergency. Patients and physicians were not blinded to the treatment assignment. However, CT evaluations were performed by a separate radiologist blinded to both treatment allocation and potential imaging artifacts. Subjective endpoints (e.g., COVID-19 symptoms) were collected via patient self-reporting, entirely recorded by the participants themselves to minimize human interference. The statistician generated the random allocation sequence using block randomization with blocks of six. Group assignment data were stored in sealed, sequentially numbered opaque envelopes, which were opened in consecutive order during participant recruitment to determine individual allocations.
Treatment
Patients randomized to the EGCG group received aerosolized EGCG (5878 µmol/L, 10 mL three times daily) plus standard care, while the control group received standard care alone. The EGCG formulation (HPLC purity ≥ 98%, Ningbo Hepu Biotechnology Co., Ltd.) was prepared as a 0.9% normal saline solution for nebulization. The protocol-defined treatment duration was 7 days, with optional patient-directed continuation for up to 14 days or until initiation of anti-tumor therapy, whichever occurred first. Patients who tested positive for COVID-19 were given antiviral treatment in accordance with the national guidelines for COVID-19. For those with evidence of bacterial pneumonia or a high clinical suspicion of concomitant bacterial infection, antibiotics could be administered at the discretion of the treating physician.
Evaluation
The primary endpoint was the change in CT imaging, used to assess the efficacy rate. The secondary endpoints included the degree of symptom improvement and the safety of EGCG application. CT scans were performed before treatment and within 7 ± 3 days after treatment to evaluate changes in imaging. The assessment criteria were based on Phase I-II of the protocol [10]. Symptoms were assessed before and after treatment. Patients evaluated 11 COVID-19-related symptoms, using a standardized approach for fever grading and self-assessment for other symptoms (detailed in the protocol). Fever was reported based on the highest objective temperature grade during the treatment period. Patients scored the severity of self-assessment symptom daily using a 4-point scale (0 for no symptoms, 1 for mild symptoms, 2 for moderate symptoms, and 3 for severe symptoms) and recorded their scores in patient self-reporting [11]. At final evaluation, patients compared their symptoms with the baseline and provided an assessment of whether the symptoms had remained stable, improved, or worsened.
Safety evaluations included hematological tests, blood chemistry tests, and electrocardiogram (ECG) tests, as well as additional laboratory studies. Hematological biomarkers previously identified as associated with poor clinical outcomes in COVID-19 were also prioritized and analyzed for relevant differences [12]. Based on the National Cancer Institute (NCI) Common Terminology Criteria for Adverse Events (AE) version 5.0, any adverse events potentially related to EGCG during treatment and within 7 days after treatment were recorded.
Statistical analysis
The sample size was determined a priori using a two-tailed superiority design, with event rate parameters derived from two independent sources: (1) the improvement rate of CT in our institution’s phase I-II single-arm trial of aerosolized EGCG (about 58.0%) and (2) standard care outcomes (about 30.0%) [10, 13]. Given a significance level (α) of 0.05 and a desired statistical power of (1-β) 0.8, a total of 102 participants were required for enrollment. Assuming a dropout rate of 10.0%, the sample size required for the control group is 38 cases, the sample size required for the experimental group is 76 cases, and the total sample size required is 114 cases. Data analysis was conducted using IBM SPSS Statistics software (version 23.0; IBM, Armonk, NY, USA). The efficacy analysis set included patients in the group who received treatment as randomized. After assessing the normality of each variable, independent t-tests, chi-square tests, or Mann–Whitney U tests were used to compare variables between the intervention and control groups, as appropriate. A generalized estimating equation (GEE) model was adopted to evaluate the overall intervention effect. The results were presented using three major indicators: (1) main effect or group effect, to demonstrate differences between groups; (2) time main effect, to demonstrate the impact of time on outcome variables; and (3) group × time interaction effect, to demonstrate the interaction between group and time. The study employed a GEE model to analyze the longitudinal effects of aerosolized EGCG on symptom scores. The GEE approach was selected based on the following considerations: (1) the study involved repeated assessments of patients at multiple timepoints (e.g., baseline and post-treatment days 1–7), resulting in within-subject correlations in the data; (2) the GEE methodology is appropriate for estimating population-average effects, enabling evaluation of the mean difference in symptom scores between the treatment and control groups. Hematological indicators before and after treatment (including lymphocyte, platelets, D-dimer, lactate dehydrogenase, C-reactive protein, etc.) were analyzed using Analysis of Covariance (ANCOVA) to control for the effects of patients’ baseline characteristics, thereby reducing random error and confounding bias. All the P values were two-sided.
Results
Demographics and baseline disease characteristics
Between June 2023 and May 2024, 124 patients were screened, and 114 eligible patients were enrolled. Among them, 108 (EGCG, N = 71; placebo, N = 37) were evaluable for efficacy (Fig. 1). The majority of patients (66.7%) were male. The most common tumor type was lung cancer (71.3%). 85.2% of patients had stage III or IV disease, and 59.3% of patients had stable disease. Nineteen cases were classified as severe COVID-19 pneumonia, and the specific criteria met are detailed in eTable 1 (Supplement 2). Baseline characteristics were well-balanced between groups (Table 1).
Fig. 1.
Enrollment and randomization of the study patients. EGCG indicates epigallocatechin-3-gallate;a One patient discontinued the medication after 4 days due to tumor-induced epilepsy; One patient stopped taking the medication after 3 days due to diarrhea caused by previous chemotherapy
Table 1.
Demographics and baseline disease characteristics
| Characteristics | EGCG group (N = 71) | Control group (N = 37) |
|---|---|---|
| Age, mean (SD), y | 65.52 (8.09) | 64.57 (8.99) |
| Time difference between COVID-19 confirmation and treatment initiation, mean (SD), d | 26.15 (20.56) | 20.22 (15.68) |
| Sex, No.(%) | ||
| Male | 47(66.2) | 25(67.6) |
| Female | 24(33.8) | 12(32.4) |
| Cardiovascular and cerebrovascular diseases, No.(%) | ||
| No | 49(69) | 27(73) |
| Yes | 22(31) | 10(27) |
| Diabetes, No.(%) | ||
| No | 63(88.7) | 35(94.6) |
| Yes | 8(11.3) | 2(5.4) |
| Chronic respiratory diseases, No.(%) | ||
| No | 69(97.2) | 35(94.6) |
| Yes | 2(2.8) | 2(5.4) |
| ECOG performance status, No.(%) | ||
| 0 | 31(43.7) | 14(37.8) |
| 1 | 40(56.3) | 23(62.2) |
| Smoking, No.(%) | ||
| No | 41 (57.7) | 19 (51.4) |
| Yes | 30 (42.3) | 18 (48.6) |
| Alcohol Consumption, No.(%) | ||
| No | 51 (71.8) | 26 (70.3) |
| Yes | 20 (28.2) | 11 (29.7) |
| BMI, No.(%) | ||
| Normal | 45 (63.4) | 24 (64.9) |
| Malnutrition | 2 (2.8) | 3 (8.1) |
| Overweight | 23 (32.4) | 9 (24.3) |
| Obesity | 1 (1.4) | 1 (2.7) |
| COVID-19 pneumonia, No.(%) | ||
| Moderate | 60 (84.5) | 29 (78.4) |
| Severe | 11 (15.5) | 8 (21.6) |
| Tumor Location, No.(%) | ||
| Lung Cancer | 49 (69) | 28 (75.7) |
| Esophageal Cancer | 14 (19.7) | 6 (16.2) |
| Breast Cancer | 5 (7) | 2 (5.4) |
| Cardiac Adenocarcinoma | 1 (1.4) | 0 (0) |
| Thymoma | 1 (1.4) | 1 (2.7) |
| Colon Cancer | 1 (1.4) | 0 (0) |
| Pathology, No.(%) | ||
| Adenocarcinoma | 25 (35.2) | 11 (29.7) |
| Squamous Cell Carcinoma | 32 (45.1) | 16 (43.2) |
| Small Cell Carcinoma | 5 (7) | 7 (18.9) |
| Invasive Ductal Carcinoma | 5 (7) | 2 (5.4) |
| Cardiac Adenocarcinoma | 1 (1.4) | 0 (0) |
| Small Cell Neuroendocrine Carcinoma | 3 (4.2) | 0 (0) |
| Adenosquamous Carcinoma | 0 (0) | 1 (2.7) |
| T, No.(%) | ||
| 1 | 18 (25.4) | 7 (18.9) |
| 2 | 11 (15.5) | 9 (24.3) |
| 3 | 21 (29.6) | 10 (27) |
| 4 | 17 (23.9) | 9 (24.3) |
| unkown | 4 (5.6) | 2 (5.4) |
| N, No.(%) | ||
| 0 | 18 (25.4) | 8 (21.6) |
| 1 | 8 (11.3) | 9 (24.3) |
| 2 | 23 (32.4) | 8 (21.6) |
| 3 | 21 (29.6) | 12 (32.4) |
| unkown | 1 (1.4) | 0 (0) |
| M, No.(%) | ||
| 0 | 40 (56.3) | 17 (45.9) |
| 1 | 31 (43.7) | 20 (54.1) |
| Stage, No.(%) | ||
| IA | 5 (7) | 0 (0) |
| IB | 2 (2.8) | 1 (2.7) |
| IIA | 3 (4.2) | 0 (0) |
| IIB | 2 (2.8) | 1 (2.7) |
| IIIA | 8 (11.3) | 6 (16.2) |
| IIIB | 14 (19.7) | 5 (13.5) |
| IIIC | 4 (5.6) | 1 (2.7) |
| IV | 3 (4.2) | 2 (5.4) |
| IVA | 10 (14.1) | 5 (13.5) |
| IVB | 19 (26.8) | 15 (40.5) |
| NA | 1 (1.4) | 1 (2.7) |
| Efficacy of the last antitumor treatment, No.(%) | ||
| CR | 1 (1.4) | 0 (0) |
| PR | 4 (5.6) | 0 (0) |
| SD | 42 (59.2) | 22 (59.5) |
| PD | 10 (14.1) | 8 (21.6) |
| Untreated | 14 (19.7) | 7 (18.9) |
| Previous Surgery, No.(%) | ||
| No | 45 (63.4) | 31 (83.8) |
| Yes | 26 (36.6) | 6 (16.2) |
| Previous Radiotherapy, No.(%) | ||
| No | 43 (60.6) | 20 (54.1) |
| Yes | 28 (39.4) | 17 (45.9) |
| Previous Chemotherapy, No.(%) | ||
| No | 22 (31) | 9 (24.3) |
| Yes | 49 (69) | 28 (75.7) |
| Previous Targeted Therapy, No.(%) | ||
| No | 49 (69) | 31 (83.8) |
| Yes | 22 (31) | 6 (16.2) |
| Previous Immunotherapy, No.(%) | ||
| No | 56 (78.9) | 23 (62.2) |
| Yes | 15 (21.1) | 14 (37.8) |
The mean age of the participants was 65.52 years (SD = 8.09) in the EGCG group and 64.57 years (SD = 8.99) in the control group. Cardio-cerebrovascular diseases, diabetes and chronic respiratory diseases were similar between groups (31.0% vs. 27.0%, 11.3% vs. 5.4% and 2.8% vs. 5.4%). The average time difference between COVID-19 confirmation and treatment initiation was 26.15 days (SD = 20.56) in the EGCG group and 20.22 days (SD = 15.68) in the control group. COVID-19 pneumonia severity was categorized as moderate in 60 (84.5%) patients in the EGCG group and 29 (78.4%) in the control group, while severe cases were seen in 11 (15.5%) and 8 (21.6%) patients, respectively.
CT assessment
The study demonstrated a significant difference in CT-assessed efficacy between the EGCG and control groups (P = 0.004; Table 2). The EGCG group showed greater improvement (46 vs. 15 patients) and stability (20 vs. 11 patients) compared to the control group, while only a few patients in the EGCG group experienced deterioration. Patients in the EGCG group demonstrated a significantly higher improvement rate compared to the control group (adjusted odds ratio [OR] = 2.699; 95% confidence interval [CI]: 1.192–6.110; P = 0.017) (Fig. 2).
Table 2.
Primary and secondary outcomes
| Outcome | EGCG group | control group | P |
|---|---|---|---|
| Primary outcome | |||
| CT evaluation (N = 108), No.(%) | |||
| Improvement | 46 (64.8%) | 15 (40.5%) | 0.004 |
| Stable | 20 (28.2%) | 11 (29.7%) | |
| Deterioration | 5 (7.0%) | 11 (29.7%) | |
| Secondary outcomes | |||
| Symptoms | |||
| Fever (N = 108), No.(%) a | 0.035 | ||
| No | 54 (76.1%) | 22 (59.5%) | |
| Low-grade (37.3–38 °C) | 9 (12.7%) | 3 (8.1%) | |
| Moderate (38.1–39 °C) | 6 (8.5%) | 11 (29.7%) | |
| High (39–41 °C) | 2 (2.8%) | 1 (2.7%) | |
| Cough (N = 103), No.(%) | 0.048 | ||
| Improvement | 34 (50.0%) | 18 (51.4%) | |
| Stable | 29 (42.6%) | 9 (25.7%) | |
| Deterioration | 5 (7.4%) | 8 (22.9%) | |
| Dyspnea (N = 34), No.(%) | 0.015 | ||
| Improvement | 16 (69.6%) | 2 (18.2%) | |
| Stable | 5 (21.7%) | 6 (54.5%) | |
| Deterioration | 2 (8.7%) | 3 (27.3%) | |
| Fatigue (N = 71), No.(%) | 0.608 | ||
| Improvement | 28 (57.1%) | 10 (45.5%) | |
| Stable | 18 (36.7%) | 10 (45.5%) | |
| Deterioration | 3 (6.1%) | 2 (9.1%) | |
| Muscle or body aches (N = 37), No.(%) | 0.724 | ||
| Improvement | 14 (44.0%) | 8 (33.3%) | |
| Stable | 11 (56.0%) | 4 (66.7%) | |
| Deterioration | 0 (0.0%) | 0 (0.0%) | |
| Sore throat (N = 28), No.(%) | 1.000 | ||
| Improvement | 4 (33.3%) | 5 (31.3%) | |
| Stable | 7 (58.3%) | 10 (62.5%) | |
| Deterioration | 1 (8.3%) | 1 (6.3%) | |
| Safety | |||
| Choking | |||
| Grade 1 | 1 (1.4%) | ||
| Anorexia | |||
| Grade 1 | 1 (1.4%) | ||
| Dyspnea with wheezing | |||
| Grade 1 | 1 (1.4%) | ||
| Chest tightness | |||
| Grade 1 | 1 (1.4%) | ||
a Fever was reported based on the highest objective temperature grade during the treatment period (days 1–7)
Fig. 2.
Forest Plots of COVID-19 Symptom Improvements with EGCG Treatment. Positions of the squares in the forest plot show the estimate of the OR describing the relative effect of epigallocatechin-3-gallate (EGCG) compared with the control, with the 95% CI represented by the horizontal lines. Squares to the right of the vertical line indicate when the improvement rates were higher in the EGCG group compared with control
Symptom assessment
The EGCG intervention group demonstrated statistically superior outcomes across prespecified symptoms compared to controls. No statistically significant differences were detected in fatigue (P = 0.608; N = 71), muscle or body aches (P = 0.724; N = 37), or sore throat (P = 1.000; N = 28). Significant between-group differences were observed in fever (P = 0.035; N = 108), cough (P = 0.048; N = 103), and dyspnea (P = 0.015; N = 34) using Pearson’s chi-square tests (Table 2). Mantel-Haenszel analysis confirmed these findings, showing EGCG significantly increased the likelihood of resolving moderate-to-severe fever ([OR] = 3.780, 95% CI: 1.380–10.352) and improving dyspnea (OR = 10.286, 95% CI: 1.750–60.446). Trends toward symptom alleviation were noted for cough, fatigue, muscle or body aches, and sore throat, though without statistical significance (all P > 0.05; Fig. 2).
Figure 3 illustrates the daily changes in five symptom scores for both groups of patients. EGCG group exhibited significant improvements in symptom scores of cough and dyspnea compared to the control group, with notable time effects and interaction differences indicating superior symptom alleviation (All P < 0.001; eTable 2 in Supplement 2). The two symptoms’ scores of the EGCG group began to diverge from the control group on Day 3, with this divergence progressively intensifying and culminating in a statistically significant difference by Day 7 (as evidenced by the plotted curves). However, no significant differences were observed between the groups in fatigue, muscle or body aches, and sore throat, although these symptoms also showed significant time-related changes (eTable 2 in Supplement 2).
Fig. 3.
The comparison of symptoms scores between the EGCG and placebo groups during treatment. The comparison of symptom scores between the EGCG group (purple line) and the control group (cyan line) is presented. The figure includes five subplots, each corresponding to a different symptom, namely Cough (A), Dyspnea (B), Sore throat (C), Fatigue (D), and Muscle or body aches (E). The x-axis represents the assessment time points, and the y-axis indicates the symptom scores
Overall, the EGCG intervention was particularly effective in reducing cough and dyspnea, highlighting its potential benefits in managing these symptoms. Other symptoms, including stuffy or runny nose, headache, vomiting, nausea, and diarrhea, exhibited an overall occurrence rate below 10% (N ≤ 11) either at baseline or during treatment. Given the limited sample size, statistical comparisons between groups were deemed inappropriate due to insufficient power to detect clinically meaningful differences, thereby avoiding potential false-negative conclusions.
Hematological indicators
When comparing between groups using ANCOVA, it was observed that post-treatment lactate dehydrogenase (LDH) levels in the EGCG group were significantly lower than those in the conventional treatment group (P = 0.028). Other hematological indicators commonly utilized in the assessment of COVID-19, such as lymphocyte count, platelet count, D-dimer, C-reactive protein, aspartate aminotransferase, alanine aminotransferase, creatinine, procalcitonin, and creatine kinase, did not exhibit statistically significant differences either before or after treatment (P > 0.05).
Safety
The incidence of AE was similar between the two groups (eTable 3 in Supplement 2). No serious adverse events were reported in either group during the entire trial period. The most common AE with an incident rate exceeding 5% included: decreased lymphocytes, increased lactate dehydrogenase, decreased hemoglobin, increased urea, decreased red blood cells, and decreased platelets. Grade 2 adverse events, the highest level observed during the 7-day period, were limited to decreases in platelets and lymphocytes. The EGCG group experienced mild Grade 1 adverse events, including choking, anorexia, dyspnea with wheezing, and chest tightness, all deemed related to EGCG (Table 2).
Discussion
Current research indicates that oncologic patients are significantly underrepresented in COVID-19 treatment trials, resulting in a critical lack of efficacy data for this high-risk population [14]. Cancer patients present distinct clinical challenges during the COVID-19 pandemic, exhibiting higher rates of dyspnea and severe baseline CT findings [15]. Aerosolized EGCG exhibits a favorable safety profile, as confirmed in our Phase I-II study [10]. This randomized controlled trial further validates its clinical utility, with radiological improvements contrasting sharply with conventional therapies [16]. A 7-day regimen of aerosolized EGCG significantly improved radiological outcomes, lowered LDH level and accelerated resolution of critical symptoms such as fever, cough, and dyspnea. Lower post-treatment LDH levels in the EGCG group suggested its role in mitigating oxidative stress and inflammation. These findings are particularly relevant for immunocompromised cancer patients, who face heightened risks of long COVID-19. The rapid symptom and radiological alleviation observed suggests that aerosolized EGCG can reduce the impact of COVID pneumonia on the rhythm of anti-tumor therapy.
While monoclonal antibodies (e.g., sotrovimab) and antivirals (e.g., remdesivir) are still considered first-line therapies, their efficacy against emerging variants may diminish. Meantime, the potential for drug interactions with anti-tumor and antiviral agents remains a significant concern such as prolonging the QT interval [17, 18]. EGCG’s broad-spectrum protease inhibition and host-directed immunomodulation could theoretically counteract viral evolution, such as in HIV, influenza viruses, and COVID-19 [19]. EGCG demonstrates multimodal therapeutic potential in COVID-19 through synergistic antiviral, immunomodulatory, and antifibrotic mechanisms [20]. Preclinical studies reveal its direct inhibition of SARS-CoV-2 replication via high-affinity binding to the viral main protease (Mpro; IC50 = 0.26 µM), complemented by suppression of cytokine release syndrome through NLRP3 inflammasome and STAT1/3 pathway blockade [21–23]. This dual action reduces IL-6 levels by approximately 40% in acute lung injury models, correlating with radiological improvement of pulmonary infiltrates [24]. Aerosolized delivery enhances pulmonary bioavailability by 3.2-fold compared to oral administration, enabling localized antiviral efficacy while minimizing systemic exposure.
In the study, a pattern of “significant local (pulmonary) efficacy” alongside “no significant changes in systemic inflammatory markers” was observed. Aerosolized delivery achieved a high local concentration of EGCG at the pulmonary infection site, enabling direct antiviral, anti‑inflammatory, and antioxidant effects. This explains the improvements in CT imaging, andalleviation of respiratory symptoms. Moreover, as the mode of administration limits systemic drug absorption and distribution, it avoids the broad impact on systemic immune and inflammatory pathways typical of systemic agents such as dexamethasone. Consequently, no significant fluctuations in systemic markers like CRP or D‑dimer were observed. The result supports the rationale for selecting the inhalation route, which effectively bypasses the poor oral bioavailability of EGCG and concentrates its therapeutic effect at the core target organ of the disease.
Unlike dexamethasone or IL-6 inhibitors, EGCG does not cause immunosuppression, making it particularly suitable for cancer patients [25, 26]. Corticosteroids show limited efficacy in resolving lung pathology in immunocompromised populations, while IL-6 inhibitors demonstrate radiographical benefits only at oxygen flow rates ≤ 13 L/min (FiO2 ≤ 57.5%) [27]. EGCG antioxidant activity mitigates viral-induced oxidative stress and preserves epithelial integrity [28]. EGCG may also inhibit fibrotic progression through TGF-β1/non-canonical Wnt pathway modulation, potentially reducing long-term lung damage from COVID-19 [29]. It should be noted that in the CT assessment of this study, the emergence of fibrotic shadows (e.g., linear or reticular opacities) within the original lesion area—when compared with baseline—was classified as “improvement” as fibrosis typically signals resolution of acute exudative inflammation and a transition to a reparative phase. Nevertheless, the long-term outcome of fibrosis and its intergroup differences require further validation through extended follow-up. Furthermore, given the broad-spectrum activity of EGCG, future large cohort studies may enroll patients across different stages of COVID-19 pneumonia for stratified efficacy analysis. This will help clarify whether EGCG is more effective during specific phases of the disease.
In this study, aerosolized EGCG also demonstrated a favorable safety profile (with only Grade 1 adverse events observed), further confirming its necessity as a viable alternative when corticosteroids or IL-6 inhibitors pose high clinical risks [30, 31]. Early administration or high-dose use of corticosteroids with the risk of immunosuppression may exacerbate viral replication, increase the risk of secondary bacterial/fungal coinfections, and elevate mortality [32, 33]. The COU-AA-301 trial suggested that long-term use of corticosteroids was associated with hospitalization and shortened overall survival (11.2 months vs. 16.1 months; HR = 0.68, P < 0.0001) [34, 35]. The RECOVERY trial indicated that multiple adverse events were associated with the use of dexamethasone, including hyperglycemia (14.4%), gastrointestinal bleeding (1.3%), and neuropsychiatric disorders (0.7%) [36]. Therefore, a comprehensive risk-benefit assessment is essential for cancer patients with COVID-19 pneumonia, warranting personalized therapeutic regimens and the use of high-efficacy, low-toxicity drugs (e.g., EGCG).
This study has limitations. The single-center design and moderate sample size of this study do affect the generalizability of the findings. These factors may limit the extrapolation of our results to broader and more diverse patient populations. The open-label design could introduce bias in subjective symptom reporting and clinical decision-making. We employed objective outcome measures and blinded radiological assessments to mitigate these potential biases, ensuring that the study findings remain valuable for informing clinical practice. Potential sources of heterogeneity among the enrolled patients may include tumor type, disease stage, and differences in prior anti-tumor treatments. Although statistical analysis of baseline characteristics showed no significant differences in these factors between groups, they may still exert a modifying effect on the severity of COVID-19 pneumonia and treatment response by influencing patients’ immune status and other physiological parameters. The absence of long-term follow-up precludes assessments of sustained efficacy or delayed complications. Future research should prioritize multicenter trials with extended follow-up to confirm these findings. Mechanistic studies exploring EGCG’s interactions with tumor biology and antiviral resistance patterns are warranted. Combination therapies with existing antivirals (e.g., remdesivir, nirmatrelvir) may further optimize outcomes, particularly amid evolving viral variants.
Moreover, This study applied the multi-parameter criteria from the Chinese Diagnosis and Treatment Protocol (Trial Version 10) to grade pneumonia severity, including a respiratory rate ≥ 30 breaths/min as a standalone criterion for severity. This differs from the WHO criteria, which use a composite standard requiring hypoxemia or significant lung involvement. This discrepancy may affect the global extrapolation of our findings. Specifically, cancer patients often have elevated baseline respiratory rates due to underlying conditions. After viral infection, they may more readily meet the 30 breaths/min threshold while maintaining oxygen saturation above 94% (i.e., without hypoxemia). Consequently, applying the criteria could lead to potential “over-classification” of cancer patients as severe cases. Although this protocol holds practical value in Chinese oncology practice, the noted differences may also limit direct comparability between our data and those from other global trials.
Conclusion
This trial provides the first effective evaluation of aerosolized EGCG in cancer patients with COVID-19 pneumonia, supporting its role as a safe and effective adjunctive therapy. The dual antiviral and anti-inflammatory properties of EGCG, combined with its favorable safety profile, establish it as an important treatment option for this high-risk population. These preliminary findings, considered alongside the limitations of this study, underscore the necessity for future large-scale, multi-center, double-blind randomized controlled trials to validate and extend our results, thereby providing evidence to support broader clinical application.
Supplementary Information
Acknowledgements
We thank all patients and their families. We also thank the study investigators who participated in this study.
Consort
This randomized controlled trial adheres to the CONSORT guidelines.
Author contributions
HZ had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. HZ conceived of the present idea. LJ, XL, XP, XM, LK, and HZ contributed to the acquisition, analysis, and interpretation of data. HZ and WZ drafted the manuscript. QQ and WZ performed the statistical analysis. HZ obtained funding. Administrative, technical, or material support was provided by LJ, XL, XP, XM, LK, and HZ. HZ supervised the study. All authors discussed the results and commented on the manuscript. All authors read and approved the final version of the manuscript.
Funding
Shandong Province Traditional Chinese Medicine Science & Technology Project (Z-2023092); Science and Technology Department of State Administration of traditional Chinese Medicine to jointly build Science and Technology projects (GZY-KJS-SD-2023-073); Jinan Science and Technology Development Program (202328010).
Data availability
Data will be available from the corresponding author upon reasonable request. This clinical trial is prospectively registered at ClinicalTrials.gov with identifier number NCT06924749.
Declarations
Ethics approval and consent to participate
The study protocol and informed consent were approved by the local institutional review and ethical committees at the Shandong Cancer Hospital and Institute and registered at ClinicalTrials.gov (NCT 06924749). This study also was conducted in accordance with Declaration of Helsinki principles. Written informed consent was obtained from each participant.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.Yau JWK, Lee MYK, Lim EQY, Tan JYJ, Tan KBJC, Chua RSB. Genesis, evolution and effectiveness of singapore’s National sorting logic and home recovery policies in handling the COVID-19 delta and Omicron waves. Lancet Reg Health West Pac. 2023;35:100719. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Goldman JD, Gonzalez MA, Rüthrich MM, Sharon E, von Lilienfeld-Toal M. COVID-19 and cancer: special considerations for patients receiving immunotherapy and immunosuppressive cancer therapies. Am Soc Clin Oncol Educ Book. 2022;42:1–13. [DOI] [PubMed] [Google Scholar]
- 3.Lee LY, Cazier JB, Angelis V, Arnold R, Bisht V, Campton NA, et al. COVID-19 mortality in patients with cancer on chemotherapy or other anticancer treatments: a prospective cohort study. Lancet. 2020;395(10241):1919–26. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Lustberg MB, Kuderer NM, Desai A, Bergerot C, Lyman GH. Mitigating long-term and delayed adverse events associated with cancer treatment: implications for survivorship. Nat Rev Clin Oncol. 2023;20(8):527–42. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Pathania AS, Prathipati P, Abdul BA, Chava S, Katta SS, Gupta SC, et al. COVID-19 and cancer comorbidity: therapeutic opportunities and challenges. Theranostics. 2021;11(2):731–53. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Lee JH, Koh J, Jeon YK, Goo JM, Yoon SH. An integrated Radiologic-Pathologic Understanding of COVID-19 pneumonia. Radiology. 2023;306(2):e222600. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Chen X, Liao B, Cheng L, Peng X, Xu X, Li Y, et al. The microbial coinfection in COVID-19. Appl Microbiol Biotechnol. 2020;104(18):7777–85. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Mehta SK, Pradhan RB. Phytochemicals in antiviral drug development against human respiratory viruses. Drug Discov Today. 2024;29(9):104107. [DOI] [PubMed] [Google Scholar]
- 9.He Y, Hao M, Yang M, Guo H, Rayman MP, Zhang X, et al. Influence of EGCG oxidation on inhibitory activity against the SARS-CoV-2 main protease. Int J Biol Macromol. 2024;274(Pt 2):133451. [DOI] [PubMed] [Google Scholar]
- 10.Yin X, Zhu W, Tang X, Yang G, Zhao X, Zhao K, et al. Phase I/II clinical trial of efficacy and safety of EGCG oxygen nebulization inhalation in the treatment of COVID-19 pneumonia patients with cancer. BMC Cancer. 2024;24(1):486. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Cao B, Wang Y, Lu H, Huang C, Yang Y, Shang L, et al. Oral Simnotrelvir for adult patients with Mild-to-Moderate Covid-19. N Engl J Med. 2024;390(3):230–41. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Malik P, Patel U, Mehta D, Patel N, Kelkar R, Akrmah M, et al. Biomarkers and outcomes of COVID-19 hospitalisations: systematic review and meta-analysis. BMJ Evid Based Med. 2021;26(3):107–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Davoodi L, Abedi SM, Salehifar E, Alizadeh-Navaei R, Rouhanizadeh H, Khorasani G, et al. Febuxostat therapy in outpatients with suspected COVID-19: A clinical trial. Int J Clin Pract. 2020;74(11):e13600. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Buchrits S, Fredman D, Ben Tikva Kagan K, Gafter-Gvili A. A systematic review assessing the underrepresentation of cancer patients in COVID-19 trials. Acta Haematol. 2022;145(3):235–43. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Liang W, Guan W, Chen R, Wang W, Li J, Xu K, et al. Cancer patients in SARS-CoV-2 infection: a nationwide analysis in China. Lancet Oncol. 2020;21(3):335–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Prescott HC, Rice TW. Corticosteroids in COVID-19 ARDS: evidence and hope during the pandemic. JAMA. 2020;324(13):1292–5. [DOI] [PubMed] [Google Scholar]
- 17.Baburaj G, Thomas L, Rao M. Potential drug interactions of repurposed COVID-19 drugs with lung cancer pharmacotherapies. Arch Med Res. 2021;52(3):261–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Ledford H. Hundreds of COVID trials could provide a deluge of new drugs. Nature. 2022;603(7899):25–7. [DOI] [PubMed] [Google Scholar]
- 19.Mhatre S, Srivastava T, Naik S, Patravale V. Antiviral activity of green tea and black tea polyphenols in prophylaxis and treatment of COVID-19: A review. Phytomedicine. 2021;85:153286. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Zhang Z, Zhang X, Bi K, He Y, Yan W, Yang CS, et al. Potential protective mechanisms of green tea polyphenol EGCG against COVID-19. Trends Food Sci Technol. 2021;114:11–24. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Vidigal PG, Müsken M, Becker KA, Häussler S, Wingender J, Steinmann E, et al. Effects of green tea compound epigallocatechin-3-gallate against Stenotrophomonas maltophilia infection and biofilm. PLoS ONE. 2014;9(4):e92876. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Zhang Y, Lu P, Qin H, Zhang Y, Sun X, Song X, et al. Traditional Chinese medicine combined with pulmonary drug delivery system and idiopathic pulmonary fibrosis: rationale and therapeutic potential. Biomed Pharmacother. 2021;133:111072. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Luo ZL, Sun HY, Wu XB, Cheng L, Ren JD. Epigallocatechin-3-gallate attenuates acute pancreatitis induced lung injury by targeting mitochondrial reactive oxygen species triggered NLRP3 inflammasome activation. Food Funct. 2021;12(12):5658–67. [DOI] [PubMed] [Google Scholar]
- 24.Almatroodi SA, Almatroudi A, Alsahli MA, Aljasir MA, Syed MA, Rahmani AH. Epigallocatechin-3-Gallate (EGCG), an active compound of green tea attenuates acute lung injury regulating macrophage polarization and Krüpple-Like-Factor 4 (KLF4) expression. Molecules. 2020;25(12):2853. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Luo W, Zeng Y, Song Q, Wang Y, Yuan F, Li Q, et al. Strengthening the combinational immunotherapy from modulating the tumor inflammatory environment via Hypoxia-Responsive nanogels. Adv Healthc Mater. 2024;13(8):e2302865. [DOI] [PubMed] [Google Scholar]
- 26.Souan L, Al-Khairy Z, Battah A, Sughayer MA. Non-Dexamethasone corticosteroid therapy’s effect on COVID-19 prognosis in cancer patients: A retrospective study. Vaccines (Basel). 2023;11(2):290. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Anghel AM, Niculae CM, Manea ED, Lazar M, Popescu M, Damalan AC, et al. The impact of Tocilizumab on radiological changes assessed by quantitative chest CT in severe COVID-19 patients. J Clin Med. 2022;11(5):1247. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Cheng M, Yan X, Wu Y, Zeng Z, Zhang Y, Wen F, et al. Qingke Pingchuan granules alleviate airway inflammation in COPD exacerbation by inhibiting neutrophil extracellular traps in mice. Phytomedicine. 2025;136:156283. [DOI] [PubMed] [Google Scholar]
- 29.Cohen ML, Brumwell AN, Ho TC, Garakani K, Montas G, Leong D, et al. A fibroblast-dependent TGF-β1/sFRP2 noncanonical Wnt signaling axis promotes epithelial metaplasia in idiopathic pulmonary fibrosis. J Clin Invest. 2024;134(18):e174598. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Özbek L, Topçu U, Manay M, Esen BH, Bektas SN, Aydın S, et al. COVID-19-associated mucormycosis: a systematic review and meta-analysis of 958 cases. Clin Microbiol Infect. 2023;29(6):722–31. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Pawar A, Desai RJ, Solomon DH, Santiago Ortiz AJ, Gale S, Bao M, et al. Risk of serious infections in Tocilizumab versus other biologic drugs in patients with rheumatoid arthritis: a multidatabase cohort study. Ann Rheum Dis. 2019;78(4):456–64. [DOI] [PubMed] [Google Scholar]
- 32.Hui DS. Systemic corticosteroid therapy May delay viral clearance in patients with middle East respiratory syndrome coronavirus infection. Am J Respir Crit Care Med. 2018;197(6):700–1. [DOI] [PubMed] [Google Scholar]
- 33.Jeronimo CMP, Farias MEL, Val FFA, Sampaio VS, Alexandre MAA, Melo GC, et al. Methylprednisolone as adjunctive therapy for patients hospitalized with coronavirus disease 2019 (COVID-19; Metcovid): A Randomized, Double-blind, phase IIb, Placebo-controlled trial. Clin Infect Dis. 2021;72(9):e373–81. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Robilotti EV, Babady NE, Mead PA, Rolling T, Perez-Johnston R, Bernardes M, et al. Determinants of COVID-19 disease severity in patients with cancer. Nat Med. 2020;26(8):1218–23. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Geynisman DM, Szmulewitz RZ, Plimack ER. Corticosteroids and prostate cancer: friend or foe? Eur Urol. 2015;67(5):874–5. [DOI] [PubMed] [Google Scholar]
- 36.RECOVERY Collaborative Group, Horby P, Lim WS, Emberson JR, Mafham M, Bell JL, et al. Dexamethasone in hospitalized patients with Covid-19. N Engl J Med. 2021;384(8):693–704. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
Data will be available from the corresponding author upon reasonable request. This clinical trial is prospectively registered at ClinicalTrials.gov with identifier number NCT06924749.