Abstract
COVID‐19, the disease caused by SARS‐CoV‐2, is still afflicting thousands of people across the globe. Few studies on COVID‐19 in chronic lymphocytic leukemia (CLL) are available. Here, we analyzed data from the CLL cohort of the Italian Hematology Alliance on COVID‐19 (NCT04352556), which included 256 CLL patients enrolled between 25 February 2020 and 1 February 2021. Median age was 70 years (range 38–94) with male preponderance (60.1%). Approximately half of patients (n = 127) had received at least one line of therapy for CLL, including 108 (83.7%) who were on active treatment at the time of COVID‐19 or received their last therapy within 12 months. Most patients (230/256, 89.9%) were symptomatic at COVID‐19 diagnosis and the majority required hospitalization (n = 176). Overall, after a median follow‐up of 42 days (IQR 24–96), case fatality rate was 30.1%, and it was 37.5% and 24.4% in the first (25 February 2020–22 June 2020) and second wave (23 June 2020–1 February 2021), respectively (p = 0.03). At multivariate analysis, male sex (HR 1.82, 95% CI 1.03–3.24, p = 0.04), age over than 70 years (HR 2.23, 95% CI 1.23–4.05, p = 0.01), any treatment for CLL given in the last 12 months (HR 1.72, 95% CI 1.04–2.84, p = 0.04) and COVID‐19 severity (severe: HR 5.66, 95% CI 2.62–12.33, p < 0.0001; critical: HR 15.99, 95% CI 6.93–36.90, p < 0.0001) were independently associated with poor survival. In summary, we report a dismal COVID‐related outcome in a significant fraction of CLL patients, that can be nicely predicted by clinical parameters.
Keywords: BTK inhibitors, chronic lymphocytic leukemia, COVID‐19, outcome, SARS‐CoV‐2
1. INTRODUCTION
As of October 2022, more than 620 million individuals have been affected worldwide by the novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS‐CoV‐2), with more than 6.5 million deaths reported by the WHO. 1 The clinical course of COVID‐19, the disease caused by SARS‐CoV‐2, is highly heterogeneous and spans from flu‐like symptoms to severe respiratory failure. Cancer patients, and particularly those with hematological malignancies (HM), have been recognized as a high risk category for COVID‐19‐related complications and death, mostly due to their underlying immunosuppression. 2 Chronic lymphocytic leukemia (CLL) is paradigmatic in this sense, as it combines multiple aspects of immune dysfunction, including hypogammaglobulinemia, T‐cell anergy, and monocyte defects, which are further exacerbated by antileukemic treatments. 3 , 4 To date, two international cooperative groups, namely the US/Europe and the ERIC/CLL Campus study groups, have described the clinical features of COVID‐19 in the specific setting of CLL, identifying advanced age and high number of comorbidities as patient‐related factors that significantly worsen the outcome. 5 , 6 , 7 , 8 Recently, the updated ERIC/CLL Campus series pointed out a significantly worse survival after COVID‐19 in patients who received any CLL‐directed treatment in the last 12 months 8 More conflicting results have been reported about the outcome trends over time. While the US/Europe group demonstrated a case fatality rate (CFR) falling from 35% in the early cohort to 11% in the later cohort, 6 the ERIC/CLL Campus reported similar outcomes for the first and subsequent pandemic waves. 8 Moreover, it is still debatable whether COVID‐19 outcome is influenced by CLL‐related adverse genetic factors, which often amplify immune dysregulation and place patients in more stringent need for immunosuppressive medications. 9 , 10
Since the start of the pandemic, the Italian Hematology Alliance on COVID‐19 has been collecting data from adult patients with HM and COVID‐19 infection. 11 Here we report results from the CLL cohort study, which includes 256 patients temporally categorized into two waves and partially annotated for the most common genetic abnormalities.
2. METHODS
This non‐interventional, multicenter study (NCT04352556) included a retrospective data review, partly reported in Passamonti et al., 11 and a prospective cohort, which was implemented since 23 June 2020. The study involved 52 Hematology departments in Italy. All consecutive adult patients previously diagnosed with CLL were included in this analysis. They were registered by single centers between 25 February 2020 and 22 June 2020 (retrospective cohort), and then between 23 June 2020 and 1 February 2021 (prospective cohort), with data cut‐off on 31 December 2021. Inclusion criteria were a diagnosis of CLL according to iwCLL criteria 12 and RT‐PCR‐confirmed SARS‐CoV‐2 infection. Written informed consent was collected from all patients after institutional approval of study protocol. Data on patient characteristics and clinical course were extracted from local medical records. Defining criteria for mild, severe, and critical COVID19 were as previously reported. 11
The primary outcomes were mortality among patients with CLL and COVID‐19 (overall survival, OS, from COVID‐19 diagnosis to death for any cause or last clinical evaluation), and assessment of predictors of mortality. Case‐fatality rate (CFR) was calculated as the proportion of deaths compared to the total number of subjects. Secondary outcomes were the characteristics of admitted versus (vs.) home‐managed patients, the impact of CLL treatments on mortality, and the survival differences between the retrospective cohort (first wave) and the prospective one (second wave). Discrete covariates were summarized by frequencies and percentages, whereas continuous covariates were summarized by median and range. Comparison between discrete covariates were performed by Fisher's exact test or Chi2 test, if appropriate. Comparison between continuous covariates was done using the Mann‐Whitney test. Kaplan‐Meier method with 95% confidence interval (95% CI) was used to estimate OS. We apply log rank test to compare OS in different cohorts. The effect of covariate was estimated using the Cox proportional hazard regression and hazard ratio (HR) together with 95% confidence interval (CI). All statistical tests were two‐sided and the limit of significance for all analyses was defined as P < 0.05. All statistical analyses were performed with SAS version 9.4.
3. RESULTS
3.1. Patients' characteristics
The study evaluated 256 patients with CLL diagnosed with COVID‐19 in Italy from February 2020 and February 2021, 58 of whom were included in the previous primary analysis evaluating all HM. 11 Median number of enrolled patients per center was 4 (range 1–26). Median age at the time of SARS‐CoV‐2 infection of this CLL population was 70 years (IQR 38–94) and the majority of patients (60.1%) were males (Table 1). Mean Charlson Comorbidity Index (CCI) was 3.6 (standard deviation 2.1). Concerning CLL history, 127 patients had never been treated for CLL (49.6%), while 129 (50.4%) had received at least one line of therapy (median 1, range 1–7). Among treated patients, 108 (83.7%) were on active treatment at the time of COVID‐19 or received their last therapy within 12 months (Table 2). The most common treatments were Bruton Tyrosine Kinase inhibitors (BTKi) (37.1%), chemo‐immunotherapy (21.3%), and venetoclax (18.5%).
TABLE 1.
Baseline Characteristics of 256 patients with Chronic Lymphocytic Leukemia and COVID‐19 infection according to early and late cohort
| Early cohort (first wave), N = 96 | Late cohort (second wave), N = 160 | Entire cohort, N = 256 | ||||
|---|---|---|---|---|---|---|
| N (%) unless otherwise specified | Number of available cases | N (%) unless otherwise specified | Number of available cases | N (%) unless otherwise specified | Number of available cases | |
| Baseline characteristics | ||||||
| Age at CLL diagnosis, median (range), years | 62 (33–90) | 96 | 64 (38–87) | 159 | 63 (33–90) | 256 |
| Age at COVID‐19 diagnosis, median (range), years | 70 (38–94) | 96 | 70 (40–94) | 160 | 70 (38–94) | 256 |
| Male/Female | 57/39 (59.4/40.6) | 96 | 98/62 (61.2/38.8) | 160 | 155/101 (60.6/49.4) | 256 |
| Charlson comorbidity index, mean (SD) | 3.6 (2.1) | 94 | 3.5 (2.2) | 154 | 3.6 (2.2) | 248 |
| Coexisting condition, n (%) | 256 | |||||
| Diabetes | 15 (15.6) | 94 | 23 (13.4) | 154 | 38 (14.9) | |
| Congestive heart failure | 12 (12.5) | 12 (7.5) | 24 (9.4) | |||
| Chronic renal disease | 3 (3.1) | 6 (3.8) | 9 (3.5) | |||
| Myocardial infarction | 11 (11.5) | 11 (7.0) | 22 (8.7) | |||
| Cerebrovascular accident | 3 (3.1) | 7 (4.4) | 10 (3.9) | |||
| Other malignancy | 10 (10.4) | 23 (14.4) | 33 (12.9) | |||
| Hypogammaglobulinemia | 17 (50) | 34 | 29 (33) | 88 | 46 (37.7) | 122 |
| Binet stage (A/B + C) | 36/12 (75/25) | 48 | 71/63 (53/47) | 134 | 107/75 (58.8/41.2) | 182 |
| Del17p/TP53 mutated | 3 (9.3) | 32 | 16 (17.6) | 91 | 19 (15.4) | 123 |
| IgHV unmutated | 17 (53.1) | 32 | 44 (52.8) | 84 | 61 (52.6) | 116 |
| Never treated | 57 (59.4) | 96 | 70 (43.7) | 160 | 127 (49.6) | 256 |
| Prior/Current therapy | 39 (40.6) | 90 (56.3) | 129 (50.4) | |||
| Treated within the last 12 months | 32 (33.3) | 96 | 76 (45) | 160 | 108 (42.2) | 256 |
| Lines of therapy for previously treated pts, median (range) | 1 (1–4) | 33 | 1 (1–7) | 72 | 1 (1–7) | 256 |
| Receiving therapy at the time of COVID‐19 infection | 23 (23.9) | 96 | 60 (37.5) | 160 | 83 (32.4) | 256 |
| Receiving BTK‐inhibitor at the time of COVID‐19 infection | 12 (12.5) | 96 | 30 (18.8) | 160 | 42 (16.4) | 256 |
| Receiving venetoclax at the time of COVID‐19 infection | 8 (8.3) | 96 | 13 (8.1) | 160 | 21 (8.2) | 256 |
| Receiving Anti‐CD20 mAb within 1/3/6/12 months | 3/3/4/10 (3.1/3.1/4.2/10.4) | 96 | 11/20/21/25 (6.9/12.5/13.1/15.6) | 160 | 14/23/25/35 (5.7/9.0/9.0/13.7) | 256 |
| Receiving I‐CT at the time of COVID‐19 infection | 3(6.4) | 96 | 14 (8.8) | 160 | 17 (6.6) | 256 |
| COVID‐19 severity | 248 | |||||
| Mild | 36 (38.3) | 94 | 82 (53.2) | 154 | 118 (47.6) | |
| Severe | 43 (45.7) | 56 (36.3) | 99 (39.9) | |||
| Critical | 15 (16) | 16 (10.4) | 31 (12.5) | |||
| Hospitalized, n (%) | 79 (82.3) | 96 | 97 (60.6) | 160 | 176 (68.8) | 256 |
| Pneumonia at imaging | 64 (82.1) | 78 | 70 (87.5) | 80 | 134 (84.8) | 158 |
| ICU admission | 24 (25) | 96 | 26 (17.3) | 160 | 50 (19.5) | 256 |
| Supplemental oxygen | 66 (68.7) | 96 | 73 (45.6) | 160 | 139 (54.3) | 256 |
| Mechanical ventilation | 13 (13.5) | 96 | 10 (6.3) | 160 | 23 (8.9) | 256 |
| Steroids | 39 (40.6) | 96 | 82 (51.3) | 160 | 121 (47.3) | 256 |
| Antivirals | 44 (45.8) | 96 | 23 (14.4) | 160 | 67 (26.2) | 256 |
TABLE 2.
Treatments at the time of COVID‐19 diagnosis or within 12 months
| Overall, N = 108 | ||
|---|---|---|
| N | (%) | |
| BTKi a | 40 | 37.1 |
| BTKi b + Anti‐CD20 | 1 | 0.9 |
| Venetoclax | 17 | 15.7 |
| Venetoclax + Anti‐CD20 | 3 | 2.8 |
| PI3K inhibitors | 3 | 2.8 |
| Pi3K inhibitors + Anti‐CD20 | 1 | 0.9 |
| Anti‐CD20 only | 7 | 6.5 |
| Chemotherapy | 11 | 10.2 |
| Chemo‐immunotherapy | 23 | 21.3 |
| BTKi c + venetoclax | 1 | 0.9 |
| Allogeneic transplant | 1 | 0.9 |
Ibrutinib (n = 39), Zanubrutinib (n = 1).
Ibrutinib (n = 1).
Acalabrutinib (n = 1).
The vast majority of patients (230/256, 89.9%) were symptomatic at the time of SAR‐CoV‐2 diagnosis. The most common COVID‐19‐related symptom was fever (N = 186, 72.7%), followed by dyspnea (n = 127, 49.6%) (Supplementary Table S1). Overall, hospital admission was required in 176 patients (68.7%), 50 of whom were treated at ICU level (28.4%; 19.5% of all patients), while 80 patients were confined at home and were managed as outpatients (31.3%) (Supplementary Table S2). Overall, signs of pneumonia at chest X‐rays and/or computed tomography scan were detected in 134 out of 158 evaluated patients (84.8%), the vast majority of whom were hospitalized (124/140, 88.6%). Supplemental oxygen was administered in 139 patients (54.3%), while mechanical ventilation was required in 23 (8.9%). Most hospitalized patients received at least one type of pharmacologic treatment for COVID‐19, mainly corticosteroids (64.8%), followed by antivirals (36.4%) and tocilizumab (5.7%). Only 8 patients received convalescent plasma (4.6%) (Supplementary Table S3). Overall, 60/83 patients (72.3%) stopped CLL‐directed treatment at the time of SARS‐CoV‐2 infection, including 45/58 admitted patients (77.5%) and 15/25 outpatients (60%).
A history of prior cerebrovascular accident was identified as the only risk factor for severe or critical COVID‐19 infection by univariate analysis (OR 9.30, 95% CI 1.16–74.50, p = 0.04), while age, hypogammaglobulinemia, CCI, other specific comorbidities or CLL‐specific treatments were neutral. By multivariable Cox regression analysis, the only factors associated with hospital admission were COVID‐19 severity (severe: HR 21.5, 95% CI 8.5–54.4, p < 0.001; critical: HR 40.0, 95% CI 5.2–308.3, p < 0.001) and male sex (HR 3.0, 95% CI 1.5–5.9, p = 0.002).
3.2. Outcome of COVID‐19
With a median follow‐up of 42 days (IQR 24–96) for the entire cohort and 55 days for survivors (IQR 34–178), 77 patients died (CFR 30.1%), including 72 in the hospitalized cohort (CFR 40.9%) and 5 in the outpatient cohort (CFR 6.2%). At the last follow‐up, only 3 patients (1.1%) were still admitted. Patients diagnosed with severe or critical COVID‐19 accounted for the vast majority of deaths (67/77, 87%), with a CFR of 51.5%, while only 10 deaths were recorded among 118 mild COVID‐19 cases (CFR 8.5%). We identified 4 deaths (5.2%) unrelated to COVID‐19 but ascribed to CLL progression after full recovery from COVID‐19. Among 73 COVID‐19‐related deaths, 69 occurred within 100 days from infection, while 4 patients died because of long‐term complications after SARS‐CoV‐2 clearance (after 100 days). Considering patients who recovered from the infection, the median time from SARS‐CoV‐2‐RNA detection to viral clearance was 28 days (IQR 17–39).
Overall, 96 patients were diagnosed during the first pandemic wave (early cohort), while 160 were prospectively enrolled during the second wave (late cohort). The baseline characteristics were similar between the two waves, except for higher proportion of Binet stage A in the first wave (75% vs. 53%, p = 0.008) (Supplementary Tables S4 and S5). A larger proportion of patients in the first wave required hospitalization with respect to the second wave (82.3% vs. 60.6%, p = 0.003), while the rate of ICU admission among hospitalized patients was similar (31.6% vs. 28.0%, p = 0.61). CFR was 37.5% (36/96) in the early cohort versus 24.4% (39/160) in the late cohort (p = 0.03). Focusing on patients requiring hospitalization, CFR was 43% (34/79) in the early cohort versus 38.1% (37/97) in the late cohort (p = 0.51), while for the ones admitted to ICU, CFR was slightly higher in the late cohort (54.2% vs. 76.9%, p = 0.09). For patients requiring oxygen (139, 54.3%), CFR was superimposable between the first and the second wave (28/66 [42.4%] vs. 31/73 [42.5%], p = 0.99).
Mortality at 30 days and at 100 days from COVID‐19 diagnosis in the whole cohort was 19.5% and 27%, respectively (Figure 1A). As expected, mortality was significantly higher in the hospitalized cohort with respect to the patients managed as outpatients (21%vs. 5% at 30 days, p = 0.001; 37% vs. 5% at 100 days, p < 0.0001; Figure 1B). With a median follow‐up of 199 days in the first wave (IQR = 29–269) and of 39 days for the second wave (IQR = 24–60), OS at 30 days was improved with a borderline significance in the second wave with respect to the first wave (82.8%, 95% CI 75.6–88.1 vs. 73.8%, 95%CI 63.8–81.5, p = 0.075, Supplementary Figure S1). Conversely, OS at 100 days did not differ between early and late cohort (p = 0.94, Supplementary Figure S2).
FIGURE 1.
(A) Overall survival of all patients with CLL and Covid‐19 infection (N = 256). (B) Overall survival of patients with CLL and Covid‐19 infection according to hospitalization (N = 156) or outpatient management (N = 80) (p < 0.0001). (C) Overall survival according to CLL treatment status in the last 12 months. (D) Overall survival according to treatment group, that is, untreated, anti‐CD20‐based treatments in the last 12 months or biologics agents (BTK inhibitors, PI3K inhibitors, Venetoclax)
3.3. Impact of CLL‐directed treatments
We assessed the impact on mortality of the CLL‐directed treatments. OS was significantly reduced in patients who received any CLL‐directed treatment with respect to untreated ones (HR 1.77, 95% CI 1.11–2.81, p = 0.026, Supplementary Figure S3), as well as in those who received any treatment in the last 12 months with respect to the remaining patients (HR 1.88, 95% CI 1.19–2.97, p = 0.0065, Figure 1C). Particularly, patients treated with biologic agents (BTKi, venetoclax or PI3K inhibitors) exhibited a significantly reduced OS with respect to untreated patients (HR 2.13, 95% CI 1.27–3.56, p = 0.0035), while those who received anti‐CD20‐based treatments within the last 12 months did not (HR 1.47, 95% CI 0.68–3.18, p = 0.337) (Figure 1D). By comparing specific biologic treatments, we did not find difference in terms of mortality after COVID‐19 between patients treated with BTKi (15/42, 35.7%) or with venetoclax (10/20, 50%) (p = 0.43). Concerning drug interruption at COVID‐19 diagnosis, all venetoclax‐treated patients and 28/42 (67%) on BTKi (19 with severe/critical and 9 with mild COVID‐19) temporarily or permanently suspended therapy. Conversely, 14 patients (3 with severe/critical and 11 with mild COVID‐19) continued to receive BTKi at COVID‐19 diagnosis. Interestingly, no death was reported in this latter group.
3.4. Prognostic factors for survival
At univariate analysis, many demographic characteristics (male sex, age over 70 years), blood count parameters (platelet count <100.000/mmc), biologic features (unmutated IgHV, TP53 mutation, del17p), comorbidities (including CCI and its individual components) and treatment‐related factors (use of biologic treatments) resulted significantly associated with worse OS (Table 3, Supplementary Figure S4A). However, at multivariate Cox regression analysis, male sex (HR 1.82, 95% CI 1.03–3.24, p = 0.04), age over than 70 years (HR 2.23, 95% CI 1.23–4.05, p = 0.01), any treatment for CLL given in the last 12 months (HR 1.72, 95% CI 1.04–2.84, p = 0.04) and COVID‐19 severity (severe: HR 5.66, 95% CI 2.62–12.33, p < 0.0001; critical: HR 15.99, 95% CI 6.93–36.90, p < 0.0001) were independently associated with poor survival (Table 3, Supplementary Figure S4B). If restricting the multivariate Cox regression analysis to the COVID‐19 severe or critical cases, only male sex (HR 2.16, 95% CI 1.16–4.04, p = 0.02) and age over than 70 years (HR 2.08, 95% CI 1.11–3.89, p = 0.02) retained prognostic influence on OS (Supplementary Table S6).
TABLE 3.
Univariable (N = 256) and multivariable analysis (N = 238) of prognostic factors for death in CLL patients with Covid‐19
| Univariable analysis | HR | 95% CI | p level |
|---|---|---|---|
| Sex: Male | 2.31 | 1.36–3.93 | 0.002 |
| Age >70 years | 2.34 | 1.46–3.77 | 0.0004 |
| Platelet count < 100.000/mmc | 1.76 | 1.03–3.03 | 0.039 |
| Current smokers | 0.53 | 0.13–2.16 | 0.37 |
| Charlson comorbidity index | 1.23 | 1.12–1.35 | <0.0001 |
| Chronic renal disease | 3.71 | 1.69–8.11 | 0.001 |
| Myocardial infarction | 2.04 | 1.08–3.87 | 0.03 |
| COPD | 1.13 | 0.52–2.47 | 0.75 |
| Cerebrovscular accident | 3.96 | 1.81–8.68 | 0.0006 |
| Hypogammglobulinemia | 0.95 | 0.45–2.01 | 0.89 |
| Other malignancies | 3.71 | 1.69–8.11 | 0.001 |
| Ever treated versus watch and wait | 1.77 | 1.11–2.81 | 0.02 |
| Treated in the last 6 months | 1.74 | 1.10–2.75 | 0.02 |
| Treated in the last 12 months | 1.88 | 1.19–2.97 | 0.007 |
| CLL status at COVID‐ progression | 2.10 | 1.00–4.38 | 0.04 |
| COVID severe | 5.36 | 2.59–11.06 | <0.0001 |
| COVID critical | 18.25 | 8.50–39.16 | <0.0001 |
| IgHV unmutated | 2.07 | 1.03–4.14 | 0.04 |
| Del17p (FISH) | 2.35 | 0.98–5.62 | 0.06 |
| TP53 mutated | 4.02 | 1.84–882 | 0.0005 |
| Del17p/TP53 mutated | 2.41 | 1.15–5.04 | 0.02 |
| Biologic therapy | 2.04 | 1.23–3.41 | 0.006 |
| Anti‐CD20 alone or in combination | 1.27 | 0.61–2.64 | 0.52 |
| Steroids | 1.42 | 0.79–2.58 | 0.24 |
| Antivirals | 0.89 | 0.36–2.23 | 0.81 |
| Mutivariable analysis | HR | 95% CI | p level |
|---|---|---|---|
| Sex: Male | 1.82 | 1.03–3.24 | 0.04 |
| Age >70 years | 2.23 | 1.23–4.05 | 0.01 |
| Charlson comorbidity index (continuous) | 1.08 | 0.95–1.22 | 0.22 |
| Treated in the last 12 months | 1.72 | 1.04–2.84 | 0.04 |
| Severity of COVID | |||
| Mild | 1.0 | Reference | <0.0001 |
| Severe | 5.66 | 2.62–12.22 | <0.0011 |
| Critical | 15.99 | 6.93–36.90 | |
| CLL status at COVID‐19 progression | 0.80 | 0.35–1.86 | 0.6 |
4. DISCUSSION
We here presented the clinical features and outcome of a cohort of CLL patients diagnosed with COVID‐19 in 52 Hematology departments in Italy. Interestingly, the observed mortality rate of approximately 30% in CLL patients with COVID‐19 infection seems to invariantly recur across all studies from different countries, 6 , 7 , 8 , 13 , 14 , 15 and appear to be among the highest across HM. In particular, 100‐day mortality in CLL seems to be of similar magnitude to non‐Hodgkin lymphoma (NHL) and multiple myeloma, higher than Hodgkin lymphoma (6%) and inferior only to acute myeloid leukemia and high risk myelodysplastic syndrome patients (40%). 16 , 17 , 18 , 19 Moreover, compared with COVID‐19 mortality in the general Italian population in the same timeframe (0.8%), 1 these data further highlight the vulnerability of CLL patients to SARS‐CoV‐2‐related acute and late complications, mainly due to the disease‐related immune dysfunction and immunosuppressive treatments. 20
Our study categorized CLL patients into two consecutive COVID‐19 waves in a pre‐vaccine era, and found that CFR significantly decreased in the late cohort. This aligns with data reported by Roeker and colleagues, 6 yet contrasts with the recent European results. 8 Such discrepancies might be partly due to heterogeneity in COVID‐19 management and different supportive care capacity across different countries. In this regard, our report may be more informative than previous studies, as it only includes patients treated in reference secondary or tertiary‐care Hematologic centers from an individual country. Another strength of our study relies on the prospective collection of consecutive patients during the second wave and on the longest median follow‐up (42 days) with respect to the previously cited series, 5 , 6 , 7 which may have allowed to capture mid‐term and late complications of COVID‐19 infection in this specific population of highly immunocompromized patients.
Beside COVID‐19 severity, older age (over 70 years), male sex and any CLL‐directed treatment in the last 12 months resulted independently associated with increased risk of death in our study. Notably, OS was negatively influenced by CLL‐directed treatments, particularly by targeted agents. This is in line with the ERIC and Campus CLL study, which reported a median OS probability of about 1 and 3 months in treated and naïve patients, respectively. 8 Interestingly, the recent ITA‐HEMA‐COV report on COVID‐19 in lymphoma patients did not detect any detrimental impact of anti‐lymphoma treatments on patients' outcome. 21 These differences might be the result of a more pronounced underlying immunosuppression in CLL patients, which is further exacerbated by CLL‐directed drugs, such as BTKi, venetoclax and anti‐CD20 monoclonal antibodies. Concerning BTKi‐treated patients, although the choice to hold the drug at COVID‐19 diagnosis may have been influenced by multiple factors, first of all by COVID‐19 severity, those continuing BTKi treatment seemed to have a favorable outcome, suggesting BTK inhibition might be somehow protective against COVID‐19‐related death, possibly by preventing cytokines‐mediated lung injury or keeping CLL under control. 22 Similar findings have been recently achieved by two larger cohorts 5 , 7 , 8 and form the clinical bases for current recommendations indicating no need to discontinue BTKi treatment at the time of COVID‐19 infection. 20 Interestingly, a survey among Italian centers, covering approximately the same timeframe of our study, highlighted that BTKi and venetoclax were withheld in 53.6% and 66.6% of patients at the time of COVID‐19 infection. 23
As high risk CLL might expose patients to a greater risk of infectious complications, we also looked for potential correlations with COVID‐19 outcome. However, in our study, similarly to the ERIC and Campus CLL cohort, 8 no CLL‐specific biological risk factor was independently associated with clinical outcome, with IgHV unmutated status conferring increased risk of death only at univariable analysis in both studies and TP53 mutation or disruption exclusively in our analysis.
Overall, our study confirms that patient‐related, more than disease‐intrinsic factors, drive COVID‐19 aggressiveness in CLL patients, and suggests that antineoplastic treatments negatively impact on COVID‐19 prognosis. Notably, we were able to confirm the recent finding of the ERIC and CLL Campus study that either CLL‐directed treatment in the last 12 months confers an independent risk of death after COVID‐19 infection. 8 The availability of easily assessable validated prognostic factors for mortality in CLL patients after SARS‐CoV‐2 infection may acquire an even increasing clinical relevance especially in the current therapeutic scenario, where a novel therapeutic armamentarium with proven efficacy (monoclonal antibodies such as tixagevimab/cilgavimab or antivirals such as remdesivir or nirmatrelvir‐ritonavir) are available for clinical use particularly in the early phases of the infection. 24 , 25 , 26 At this regard, recently treated CLL male patients, aged more than 70 years, with mild COVID‐19 infection do represent an ideal target for these pre‐emptive strategies. On the other hand, hospitalized patients with severe COVID‐19 infection and additional factors represent a group with even higher risk of mortality that require intensive treatment management with eventual use of experimental or off‐label use of varied combinations of antivirals, immunomodulators and/or monoclonal antibodies. 24 , 27 , 28 Future external validations will be needed to verify the performance of independent prognostic factors identified by our analysis in independent CLL patient series, likely including patients infected during more recent spreads of newer SARS‐CoV‐2 variants and after receiving a complete vaccination course including booster doses.
We acknowledge that a major limitation of our study is represented by inclusion of patients in the pre‐vaccine era and prior to the emergence of the currently dominant SARS‐CoV‐2 variants. However, it has to be considered that patients with CLL, especially if on active treatment, are less prone to develop antibody response to the infection 29 , 30 and to the currently approved COVID‐19 vaccines. 31 , 32 , 33 , 34 At this regard, a preliminary multicentre survey of breakthrough COVID‐19 infections in vaccinated patients with HM showed that the 30 days mortality remains substantial, especially in patients with CLL (7.1%) or NHL (16.7%). Interestingly, approximately 70% of such patients did not generated antibody response to vaccines, suggesting that low of seroconversion may be related with higher rate of infection in this setting. 35 Moreover, a recent population analysis of more than 16,000 vaccinated patients with lymphoproliferative disorders reported of significantly increased rates of hospital admission (relative risk [RR] 13.87), severe disease (RR 12.06) and COVID‐19‐related death (RR 15.13) with respect to vaccinated control subjects without HM. 36 Finally, recent data confirmed that mortality rate remained high among CLL patients also during the recent omicron spread, including BA.2 sub‐lineage (31% in hospitalized patients in an Israel study 37 and 23% in patients tested at hospital sites in a Danish study 38 ), which is generally described as a milder disease course in the general population. For these reasons, we believe that our findings may be likely applicable to the majority of CLL patients in the present‐day scenario, although a reassessment and validation in the current vaccine‐ and omicron‐era is warranted.
AUTHOR CONTRIBUTIONS
Michele Merli, Isacco Ferrarini, Carlo Visco, Francesco Passamonti conceived the study, Michele Merli and Isacco Ferrarini contributed to study design, study supervision, and data interpretation and wrote the paper. Lorenza Bertù did the statistical plan, performed the analysis and interpreted the data. Michele Merli, Isacco Ferrarini, Carlo Visco, Francesco Passamonti, contributed to the interpretation of data analysis. Michele Merli, Isacco Ferrarini, Francesco Merli, Alessandro Busca, Roberto Mina, Brunangelo Falini, Riccardo Bruna, Roberto Cairoli, Monia Marchetti, Alessandra Romano, Michele Cavo, Luca Arcaini, Livio Trentin, Chiara Cattaneo, Enrico Derenzini, Nicola Stefano Fracchiolla, Francesco Marchesi, Annamaria Scattolin, Atto Billio, Monica Bocchia, Massimo Massaia, Carlo Gambacorti‐Passerini, Francesca Romana Mauro, Massimo Gentile, Sara Mohamed, Matteo Giovanni Della Porta, Elisa Coviello, Daniela Cilloni, Giuseppe Visani, Augusto Bramante Federici, Maria Chiara Tisi, Laura Cudillo, Sara Galimberti, Filippo Gherlinzoni, Livio Pagano, Anna Guidetti, Paolo Corradini, Francesco Passamonti and Carlo Visco recruited participants and collected and recorded data. All authors reviewed the manuscript and agreed with manuscript submission. All authors agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.
CONFLICTS OF INTEREST
The authors declare no conflicts of interest.
PEER REVIEW
The peer review history for this article is available at https://publons.com/publon/10.1002/hon.3092.
Supporting information
Supporting Information S1
ACKNOWLEDGMENTS
The study is supported by the charity Associazione italiana contro le leucemie, linfomi e mieloma–Varese Onlus. We thank Roberta Mattarucchi and Alessia Ingrassia from the Clinical Trial Center of the ASST Sette Laghi of Varese for managing study protocol and procedures across many institutional review boards.
Merli M, Ferrarini I, Merli F, et al. SARS‐CoV‐2 infection in patients with chronic lymphocytic leukemia: the Italian Hematology Alliance on COVID‐19 cohort. Hematol Oncol. 2022;1‐11. 10.1002/hon.3092
Michele Merli and Isacco Ferrarini co‐first authors. Francesco Passamonti and Carlo Visco co‐last authors.
DATA AVAILABILITY STATEMENT
Individual participant data that underlie the results reported in this Article, after de‐identification (text, tables, figures, and appendices), will be available together with the study protocol. This will be from 9 to 24 months following Article publication. Data will be available only for investigators whose proposed use of the data has been approved by an independent review committee identified for this purpose. Proposals should be directed to lorenza.bertu@uninsubria.it; to gain access, data requestors will need to provide a draft of a data access agreement that will be evaluated.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supporting Information S1
Data Availability Statement
Individual participant data that underlie the results reported in this Article, after de‐identification (text, tables, figures, and appendices), will be available together with the study protocol. This will be from 9 to 24 months following Article publication. Data will be available only for investigators whose proposed use of the data has been approved by an independent review committee identified for this purpose. Proposals should be directed to lorenza.bertu@uninsubria.it; to gain access, data requestors will need to provide a draft of a data access agreement that will be evaluated.