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Erschienen in: BMC Cancer 1/2022

Open Access 30.11.2022 | COVID-19 | Research

The impact of anti-tumor approaches on the outcomes of cancer patients with COVID-19: a meta-analysis based on 52 cohorts incorporating 9231 participants

verfasst von: Qing Wu, Shuimei Luo, Xianhe Xie

Erschienen in: BMC Cancer | Ausgabe 1/2022

Abstract

Background

This study was designed to investigate the impact of anti-tumor approaches (including chemotherapy, targeted therapy, endocrine therapy, immunotherapy, surgery and radiotherapy) on the outcomes of cancer patients with COVID-19.

Methods

Electronic databases were searched to identify relevant trials. The primary endpoints were severe disease and death of cancer patients treated with anti-tumor therapy before COVID-19 diagnosis. In addition, stratified analyses were implemented towards various types of anti-tumor therapy and other prognostic factors. Furthermore, odds ratios (ORs) were hereby adopted to measure the outcomes with the corresponding 95% confidence intervals (CIs).

Results

As indicated in the study consisting of 9231 individuals from 52 cohorts in total, anti-tumor therapy before COVID-19 diagnosis could elevate the risk of death in cancer patients (OR: 1.21, 95%CI: 1.07–1.36, P = 0.0026) and the incidence of severe COVID-19 (OR: 1.19, 95%CI: 1.01–1.40, P = 0.0412). Among various anti-tumor approaches, chemotherapy distinguished to increase the incidence of death (OR = 1.22, 95%CI: 1.08–1.38, P = 0.0013) and severe COVID-19 (OR = 1.10, 95%CI: 1.02–1.18, P = 0.0165) as to cancer patients with COVID-19. Moreover, for cancer patients with COVID-19, surgery and targeted therapy could add to the risk of death (OR = 1.27, 95%CI: 1.00–1.61, P = 0.0472), and the incidence of severe COVID-19 (OR = 1.14, 95%CI: 1.01–1.30, P = 0.0357) respectively. In the subgroup analysis, the incidence of death (OR = 1.17, 95%CI: 1.03–1.34, P = 0.0158) raised in case of chemotherapy adopted for solid tumor with COVID-19. Besides, age, gender, hypertension, COPD, smoking and lung cancer all served as potential prognostic factors for both death and severe disease of cancer patients with COVID-19.

Conclusions

Anti-tumor therapy, especially chemotherapy, augmented the risk of severe disease and death for cancer patients with COVID-19, so did surgery for the risk of death and targeted therapy for the incidence of severe COVID-19.
Hinweise

Supplementary Information

The online version contains supplementary material available at https://​doi.​org/​10.​1186/​s12885-022-09320-x.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Abkürzungen
COVID-19
Coronavirus disease 2019
ORs
Odds ratios
CIs
Confidence intervals
COPD
Chronic obstructive pulmonary disease
SARS-CoV-2
Severe acute respiratory syndrome-related coronavirus 2
NOS
Newcastle-Ottawa Scale
ECOG PS
Eastern Cooperative Oncology Group Performance Scale
NLR
Neutrophil to lymphocyte ratio
ICIs
Immune checkpoint inhibitors
T-PCR
Reverse transcription-polymerase chain reaction
NA
Not available
ICU
Intensive care unit

Background

As is known to all, the sudden outbreak and global overrun of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) [1], have generated heavy burdens and great challenges to global public health since December 2019 [2]. Up to date, people all over the world have been fighting against the fatal disease, as reported in over 200 million infected individuals.
Cancer patients are generally in severe immunosuppressive status deriving from cancer itself and the anti-tumor regimens. Furthermore, they have to visit the hospital regularly for monitoring or anti-tumor treatment (such as chemotherapy, immunotherapy, endocrine therapy, targeted therapy, surgery and radiotherapy) leading to increasing exposure to virus.
A growing number of studies revealed that, during the pandemic, cancer patients with COVID-19 generally suffered from worse outcomes compared to patients with COVID-19 alone [37]. In addition, some investigations targeted at exploring whether anti-tumor therapy was an additional risk factor for adverse outcomes of COVID-19 and whether it was necessary to change therapeutic modalities to mitigate the risk [810].
As far as we know, accumulating prospective and retrospective studies were conducted to evaluate clinical characteristics of cancer patients with COVID-19, as well as the impact of anti-tumor therapy on clinical outcomes of COVID-19 [1113]. Nevertheless, research findings remained to be a bit conflicting and inconclusive as for the impact of anti-tumor therapeutic approaches on the severity of COVID-19 [1418]. Consequently, a comprehensive survey based on a larger scale (52 cohorts incorporating 9231 individuals) and diverse dimensions was hereby carried out to clarify the correlation between anti-tumor therapy and COVID-19 prognosis.

Methods

Data sources and literature searches

A systematic electronic literature retrieval was in place for study screening, searching for abstracts of relevant studies in the published literature. PubMed, Cochrane Library and EMBASE were all searched with data updated as of 27th March 2021. Basic search terms entered were as follows: “COVID-19”, “SARS-CoV2”, “SARS-CoV-2”, “2019-nCoV”, “novel coronavirus”, “cancer”, “neoplasm”, “malignancy”, “carcinoma” and “tumor” (the full search strategy as shown in Additional file 1: Appendix 1). In addition, full-text papers were scrutinized as for abstracts without substantial information, and the references of relevant articles were reviewed for additional studies. Data retrieval was completed in English, with reviews, editorials comments and case reports all excluded.

Selection of studies and definition

Initially, two investigators performed a screening of titles and abstracts respectively, then examined the full-text of articles to acquire eligible studies. Regarding the duplicate studies based on the same patients, only the latest or most comprehensive data were recruited as a whole.
Definition:
Anti-tumor therapy: patients receiving chemotherapy (cytotoxic chemotherapy), immunotherapy (immune checkpoint inhibitor), targeted therapy (molecular targeted therapy), surgery, radiotherapy, endocrine therapy (hormonal drugs) within the last 6 months before COVID-19 diagnosis.
Age: defined as “old” or “young” depending on each cut-off used to calculate the odds ratios (ORs) of age in the included studies.
Eastern Cooperative Oncology Group Performance Scale (ECOG PS): defined as “high” or “low” with a cut-off of 2.
Comorbidities: defined as “yes” or “no” to identify cancer patients with or without hypertension, diabetes, chronic obstructive pulmonary disease (COPD), cardiovascular disease, obesity status and smoking in the corresponding studies.
Blood parameters: defined as “high” or “normal” on the basis of each cut-off applied to calculate the ORs of white blood cell count, C-reactive protein (CRP), lymphocyte count, D-dimer, neutrophil to lymphocyte ratio (NLR), and creatine kinase in each included study.
Severe COVID-19: depending on respective definitions in the included studies, including infections requiring intensive care unit (ICU) admission, mechanical ventilation or even resulting in death.

Inclusion criteria

1) Prospective or retrospective studies to evaluate the impact of anti-tumor therapy on cancer patients with COVID-19; 2) patients pathologically confirmed as cancer; 3) patients diagnosed as COVID-19; 4) studies with data available for ORs and corresponding 95% confidence intervals (CIs) of severe COVID-19 and death rates in groups receiving anti-tumor treatments or not.

Data extraction

In this study, data extraction was implemented strictly according to the PRISMA guidelines (as shown in Additional file 2: Appendix 2). Meanwhile, all eligible studies involved the information as follows: the publication year and region, first author’s name, study type, number of patients, anti-tumor therapy, severe COVID-19 and/or death cases.

Quality assessment

The quality of included studies was assessed independently by two reviewers using the Newcastle-Ottawa Scale (NOS) for case-control and cohort studies, encompassing three dimensions of selection, comparability and exposure, with a full score of 9 points.

Statistical methods

The primary endpoints were composed of death and/or severe COVID-19 of cancer patients treated with anti-tumor therapy before COVID-19 diagnosis. Moreover, the correlation between anti-tumor therapy and the outcomes was determined by ORs with the corresponding 95%CIs. Subgroup analyses were further accomplished based on the type of anti-tumor therapy, type of cancer (solid cancer or haematological malignancy) and other prognostic factors. In addition, funnel plots and Egger’s test were applied to evaluate publication bias, and statistical analysis was realized via R 4.0 statistical software. Heterogeneity was assessed by means of I-square tests and chi-square, with remarkable heterogeneity in case of P < 0.1 or I2 > 40%. Furthermore, a random effect model was adopted to analyze the pooled data when heterogeneity existed; otherwise, a fixed effect model was employed accordingly.

Results

Selection of study

Initially, 9462 relevant articles were scrutinized intensively, of which 443 were filtered for duplication, and 8766 were excluded for digression after screening the titles and abstracts. After that, the full text of remaining 253 articles was thoroughly reviewed, among which 201 were excluded as they were reviews or case reports, not human research, not in English, without data for ORs and corresponding 95%CIs of severe COVID-19 and/or death in groups receiving anti-tumor therapy or not. Finally, a total of 52 cohorts [4, 6, 7, 11, 12, 1460] incorporating 9231 participants were recruited in this study. See Fig. 1 for detailed procedures.

Study traits

As of 27th March 2021, altogether 9231 individuals in 52 cohorts were included with a sample size ranging from 12 to 1289, of which 45 were retrospective, 4 prospective and 3 retro-prospective. Meanwhile, ORs for severe COVID-19 and/or death were utilized to assess the impact of anti-tumor approaches on cancer patients with COVID-19. Among the foregoing studies, 41 cohorts witnessed death and 23 confronted with severe COVID-19. See Table 1 for principal characteristics.
Table 1
The principal characteristics and further details of eligible articles
Author
Year
Study design
Region
Number of patient
Male
Median age (IQR) (years)
Diagnosis method for COVID-19
Cancer type
Comparison group
Kuderer NM [6]
2020
Retro-prospective
multi-national
928
468
66 (57–76)
RT-PCR
non-specific
cancer patients with no treatment
Lee LYW [19]
2020
Prospective
UK
800
449
69 (59–76)
RT-PCR
non-specific
cancer patients with no treatment
Zhang L [14]
2020
Retrospective
China
28
17
65 (56–70)
RT-PCR
solid tumor
cancer patients with no treatment
Stroppa EM [20]
2020
Retrospective
Italy
25
20
71 (mean) (50–84)
RT-PCR
non-specific
cancer patients with no treatment
Yang K [7]
2020
Retrospective
China
205
96
63 (56–70)
RT-PCR
non-specific
cancer patients with no treatment
Zhang H [21]
2020
Retrospective
China
107
60
66 (36–98)
RT-PCR and/or radiology
non-specific
cancer patients with no treatment
Robilotti EV [22]
2020
Retrospective
USA
423
212
NA
RT-PCR
non-specific
cancer patients with no treatment
Yarza R [23]
2020
Prospective
Spain
63
34
NA
RT-PCR and/or radiology
solid tumor
cancer patients treated other options
Li Q [24]
2020
Retrospective
China
59
31
63 (54–70)
RT-PCR
non-specific
cancer patients with no treatment
Jee J [25]
2020
Retrospective
USA
309
159
NA
RT-PCR
non-specific
cancer patients with no treatment
Sanchez-Pina JM [26]
2020
Retrospective
Spain
39
23
64 (mean)
RT-PCR
hematological malignancies
cancer patients with no treatment
Pinato DJ [15]
2020
Retrospective
multi-national
890
503
68 (mean)
RT-PCR
non-specific
cancer patients with no treatment
Assaad S [27]
2020
Retrospective
France
55
26
64 (mean)
RT-PCR
non-specific
cancer patients with no treatment
Garassino MC [28]
2020
Retrospective
multi-national
200
141
68 (61–75)
RT-PCR
Thoracic Cancer
cancer patients with no treatment
Liang WH [29]
2020
Retrospective
China
18
12
60 (47–87)
RT-PCR
non-specific
cancer patients with no treatment
Ma J [30]
2020
Retrospective
China
37
20
62 (IQR: 59–70)
RT-PCR and/or antibody test
solid tumor
cancer patients with no treatment
Mehta V [11]
2020
Retrospective
USA
218
127
69 (10–92)
RT-PCR
non-specific
cancer patients with no treatment
Yu J [31]
2020
Retrospective
China
12
10
66 (48–78)
RT-PCR and/or CT
solid tumor
cancer patients with no active antitumor treatment
Tian J [4]
2020
Retrospective
China
232
119
64 (58–69)
RT-PCR
non-specific
cancer patients with surgery
Fox TA [32]
2020
Retrospective
UK
55
38
63 (23–88)
RT-PCR, CT, and clinical features
hematological malignancies
cancer patients with no treatment
Booth S [33]
2020
Prospective
UK
66
41
73 (IQR: 63–81)
RT-PCR, radiological, and clinical features
hematological malignancies
cancer patients with no treatment
Cattaneo C [34]
2020
Retrospective
Italy
102
66
68 (mean)
RT-PCR
hematological malignancies
cancer patients with no treatment
Lara OD [35]
2020
Retrospective
USA
121
NA
64 (IQR: 51–73)
RT-PCR and CT
gynecologic cancer
cancer patients with no treatment
Liu C [36]
2020
Retrospective
China
216
113
63 (IQR: 57–70)
RT-PCR
solid tumor
cancer patients with no treatment
Luo J [37]
2020
Retrospective
USA
102
49
68 (IQR: 61–75)
RT-PCR
lung cancer
cancer patients with no treatment
Mato AR [38]
2020
Retrospective
multi-national
198
125
63 (35–92)
RT-PCR
chronic lymphocytic leukemia
cancer patients with no treatment
Rogado J [39]
2020
Retrospective
Spain
45
30
71 (34–90)
RT-PCR
non-specific
cancer patients with no treatment
Russell B [40]
2020
Retro-prospective
UK
156
90
65 (mean)
RT-PCR
solid tumor
cancer patients with no treatment
Scarfò L [41]
2020
Retrospective
multi-national
190
126
72 (48–94)
RT-PCR
chronic lymphocytic leukemia
cancer patients with no treatment
Vuagnat P [42]
2020
Retrospective
France
58
NA
58 (IQR:48–68)
RT-PCR and/or CT
breast cancer
cancer patients with no treatment
Wang BO [43]
2020
Retrospective
USA
58
30
67
RT-PCR
multiple myeloma
cancer patients with no treatment
Wang J [44]
2020
Retrospective
China
283
141
63 (IQR: 55–70)
RT-PCR
non-specific
cancer patients with no treatment
Gonzalez-cao M [45]
2020
Retrospective
Spain
50
27
69 (6–94)
clinical or RT-PCR
melanoma
cancer patients with no treatment
De Melo AC [46]
2020
Retrospective
Brazil
181
71
55 (2–88)
RT-PCR
non-specific
cancer patients with no active antitumor treatment
Albiges L [47]
2020
Retrospective
France
178
76
61 (52–71)
RT-PCR and/or CT
non-specific
cancer patients with no treatment
Martínez-López J [48]
2020
Retrospective
Spain
167
95
71 (IQR: 62–78)
RT-PCR
multiple myeloma (MM)
cancer patients with no treatment
Martín-Moro F [49]
2020
Retrospective
Spain
34
19
72.5 (35–94)
RT-PCR and/or CT
hematological malignancies
cancer patients with no treatment
Lattenist R [50]
2021
Retrospective
Belgium
13
10
70 (IQR: 59–79)
RT-PCR and/or CT
hematological malignancies
cancer patients with no treatment
Nakamura S [51]
2020
Retrospective
Japan
32
22
74.5 (24–90)
RT-PCR
non-specific
cancer patients with no treatment
Rogiers A [52]
2021
Retrospective
multi-national
110
72
63 (27–86)
RT-PCR
non-specific
cancer patients with no treatment
Glenthøj A [16]
2021
Prospective
Denmark
66
40
66.7 (25–91)
 
hematological malignancies
cancer patients with no treatment
Song C [17]
2020
Retrospective
China
223
116
63 (56–71)
RT-PCR
non-specific
cancer patients with discontinous treatment
Lunski MJ [18]
2020
Retrospective
USA
312
142
NA
RT-PCR
non-specific
cancer patients with no treatment
Nie L [53]
2020
Retrospective
China
45
31
66 (58–74)
RT-PCR
lung cancer
cancer patients with no treatment
Larfors G [54]
2020
Retrospective
Sweden
NA
NA
NA
RT-PCR
non-specific
cancer patients with no treatment
H€ollein A [55]
2020
Retrospective
Germany
17
8
73 (27–82)
RT-PCR
non-specific
cancer patients with no treatment
Garnett C [56]
2020
Retrospective
UK
32
21
72.5 (46–96)
RT-PCR
hematological malignancies
cancer patients with no treatment
Hanna GJ [57]
2020
Retrospective
USA
32
20
70 (38–91)
RT-PCR
head and neck cancer
cancer patients with no treatment
Lie’vre A [58]
2020
Retro-prospective
France
1289
795
67 (19–100)
RT-PCR
solid tumor
cancer patients with no treatment
Smith M [59]
2020
Retrospective
USA
86
NA
69 (mean)
RT-PCR
solid tumor
cancer patients with no treatment
Wu YG [60]
2020
Retrospective
China
14
9
37 (14–68)
RT-PCR
hematological malignancies
cancer patients with no treatment
Yang F [12]
2020
Retrospective
China
52
28
63 (34–98)
RT-PCR
solid tumor
cancer patients with no treatment
Author
Number of the control
Anti-tumor therapy
Chemotherapy
Immunotherapy
Targeted therapy
Endocrine therapy
Surgery
Radiotherapy
Outcome
Required mechanical ventilation
Severe COVID-19
Death
Kuderer NM [6]
553
366
160
38
75
85
32
12
death
116
242
121
Lee LYW [19]
272
528
281
44
72
64
29
76
death
NA
360
226
Zhang L [14]
22
6
3
1
2
NA
NA
1
sever COVID-19
10
15
8
Stroppa EM [20]
13
12
8
4
NA
NA
NA
NA
death
NA
NA
9
Yang K [7]
128
54
31
4
12
NA
4
9
death
32
52
40
Zhang H [21]
70
37
NA
6
NA
NA
NA
NA
death
NA
56
23
Robilotti EV [22]
NA
NA
191
31
NA
NA
31
NA
sever COVID-19
40
85
51
Yarza R [23]
NA
NA
36
8
7
10
NA
NA
sever COVID-19; death
NA
24
16
Li Q [24]
43
16
12
NA
6
NA
1
1
death
27
35
16
Jee J [25]
43
170
102
18
49
NA
NA
NA
sever COVID-19
NA
120
31
Sanchez-Pina JM [26]
15
24
4
NA
5
NA
NA
NA
death
NA
18
NA
Pinato DJ [15]
403
479
206
56
93
92
NA
33
sever COVID-19; death
97
565
299
Assaad S [27]
26
29
16
3
14
NA
NA
NA
death
NA
NA
30
Garassino MC [28]
58
142
48
34
28
NA
NA
NA
death
9
NA
66
Liang WH [29]
14
4
NA
NA
NA
NA
NA
NA
sever COVID-19
NA
9
NA
Ma J [30]
24
13
NA
NA
NA
NA
NA
NA
sever COVID-19
NA
20
5
Mehta V [11]
NA
NA
42
5
NA
NA
NA
49
death
45
NA
61
Yu J [31]
5
7
5
2
1
NA
1
4
sever COVID-19; death
NA
3
3
Tian J [4]
NA
NA
NA
NA
NA
NA
119
NA
sever COVID-19
NA
148
NA
Fox TA [32]
NA
NA
29
25
NA
NA
NA
NA
sever COVID-19; death
NA
25
19
Booth S [33]
29
37
NA
NA
NA
NA
NA
NA
death
NA
NA
34
Cattaneo C [34]
43
59
20
28
NA
NA
NA
NA
death
NA
NA
40
Lara OD [35]
NA
NA
NA
NA
NA
NA
NA
NA
death
NA
20
NA
Liu C [36]
138
78
NA
NA
NA
NA
NA
NA
death
NA
NA
37
Luo J [37]
48
54
NA
NA
NA
NA
NA
NA
sever COVID-19; death
18
NA
25
Mato AR [38]
79
119
51
NA
NA
NA
NA
NA
death
53
NA
66
Rogado J [39]
15
30
19
1
2
NA
NA
NA
death
NA
29
19
Russell B [40]
18
81
45
7
5
NA
NA
NA
sever COVID-19; death
NA
28
34
Scarfò L [41]
73
116
NA
NA
NA
NA
NA
NA
sever COVID-19; death
NA
151
56
Vuagnat P [42]
NA
NA
29
NA
19
19
3
36
sever COVID-19
NA
NA
4
Wang BO [43]
11
47
NA
NA
28
NA
NA
NA
death
NA
NA
14
Wang J [44]
188
95
46
NA
12
NA
23
NA
sever COVID-19; death
NA
NA
50
Gonzalez-cao M [45]
12
38
NA
22
16
NA
NA
NA
sever COVID-19; death
NA
34
13
De Melo AC [46]
16
165
63
NA
NA
20
12
10
death
34
NA
60
Albiges L [47]
61
117
66
19
30
16
NA
NA
sever COVID-19; death
NA
47
31
Martínez-López J [48]
NA
NA
83
NA
NA
NA
NA
NA
death
15
141
56
Martín-Moro F [49]
NA
19
NA
NA
NA
NA
NA
NA
death
4
17
11
Lattenist R [50]
6
7
3
NA
NA
NA
NA
NA
death
NA
NA
6
Nakamura S [51]
19
13
10
3
NA
4
13
NA
death
3
NA
11
Rogiers A [52]
NA
NA
25
NA
NA
NA
NA
NA
sever COVID-19; death
NA
35
18
Glenthøj A [16]
10
9
NA
NA
NA
NA
NA
NA
sever COVID-19
NA
33
NA
Song C [17]
19
204
NA
NA
NA
NA
NA
NA
sever COVID-19
NA
159
NA
Lunski MJ [18]
256
56
12
4
9
44
5
2
death
NA
NA
66
Nie L [53]
34
11
4
4
NA
NA
3
NA
death
3
23
11
Larfors G [54]
NA
NA
NA
NA
NA
NA
NA
NA
sever COVID-19; death
NA
NA
NA
H€ollein A [55]
2
15
14
1
2
NA
NA
1
death
3
NA
6
Garnett C [56]
10
22
NA
NA
NA
NA
NA
NA
death
NA
NA
18
Hanna GJ [57]
26
6
3
1
0
NA
4
1
death
NA
NA
NA
Lie’vre A [58]
NA
NA
577
110
181
57
56
133
death
49
NA
370
Smith M [59]
47
39
NA
NA
NA
NA
NA
NA
sever COVID-19
NA
29
NA
Wu YG [60]
NA
NA
7
NA
NA
NA
NA
NA
death
NA
NA
6
Yang F [12]
NA
NA
6
1
NA
NA
2
NA
sever COVID-19
NA
19
11
Abbreviations: ICIs Immune checkpoint inhibitors, RT-PCR Reverse transcription-polymerase chain reaction, NA Not available, ICU Intensive Care Unit

Assessment of study quality and publication bias

Refer to Additional file 3: Appendix 3 for quality assessment of 52 recruited studies. Furthermore, no publication bias was defined via Egger’s tests in the pooled analyses for various anti-tumor approaches (see Additional file 4: Appendix 4) and supernumerary prognostic factors (see Additional file 5: Appendix 5).

Data analysis

In this study, regarding cancer patients treated with anti-tumor therapy before COVID-19 diagnosis, the pooled OR was 1.21 (95%CI: 1.07–1.36, P = 0.0026) (Fig. 2A) for death without publication bias (Fig. 2C, Egger’s test: P = 0.5516), and 1.19 (95%CI: 1.01–1.40, P = 0.0412) (Fig. 2B) for severe COVID-19 without publication bias (Fig. 2D, Egger’s test: P = 0.3930).

The impact of anti-tumor therapy on death and severe disease of cancer patients with COVID-19

As for cancer patients with COVID-19, compared with patients without anti-tumor approaches, the incidence of death appeared to be higher in patients treated with chemotherapy (OR = 1.22, 95%CI: 1.08–1.38, P = 0.0013) (Fig. 3A) and surgery (OR = 1.27, 95%CI: 1.00–1.61, P = 0.0472) (Fig. 3B), but not in patients receiving radiotherapy (OR = 0.90, 95%CI: 0.75–1.09, P = 0.2817), targeted therapy (OR = 0.97, 95%CI: 0.76–1.23, P = 0.7914), endocrine therapy (OR = 0.95, 95%CI: 0.80–1.12, P = 0.5097), and immunotherapy (OR = 1.05, 95%CI: 0.90–1.22, P = 0.5412) (Additional file 6: Appendix 6).
Compared with cancer patients without anti-tumor approaches, the incidence of severe COVID-19 was higher in patients receiving chemotherapy (OR = 1.10, 95%CI: 1.02–1.18, P = 0.0165) (Fig. 3C) and targeted therapy (OR = 1.14, 95%CI: 1.01–1.30, P = 0.0357) (Fig. 3D), but not in patients treated with surgery (OR = 1.15, 95%CI: 0.89–1.47, P = 0.2888) and immunotherapy (OR = 1.18, 95%CI: 0.97–1.45, P = 0.1034) (Additional file 6: Appendix 6).

Subgroup analysis

Patients were further divided into groups of solid tumor and haematological malignancy depending on the type of cancer, as listed in Table 2. Compared with patients without anti-tumor approaches, solid tumor patients with COVID-19 witnessed higher incidence of death after receiving chemotherapy (OR = 1.17, 95%CI: 1.03–1.34, P = 0.0158), but not the case in haematological malignancy patients with COVID-19 (OR = 1.41, 95%CI: 0.74–2.68, P = 0.2964).
Table 2
Subgroup analysis of the impact of anti-tumor therapy on death and severe disease of cancer patients with COVID-19
Anti-tumor therapy
Solid tumour
Haematological malignancy
death
severe COVID-19
death
severe COVID-19
OR (95%CI)
P
OR (95%CI)
P
OR (95%CI)
P
OR (95%CI)
P
Chemotherapy
1.17 (1.03–1.34)
0.0158
1.16 (0.81–1.66)
0.4072
1.41 (0.74–2.68)
0.2964
NA
NA
Radiotherapy
NA
NA
NA
NA
NA
NA
NA
NA
Targeted therapy
NA
NA
NA
NA
NA
NA
NA
NA
Surgery
NA
NA
NA
NA
NA
NA
NA
NA
Endocrine therapy
NA
NA
NA
NA
NA
NA
NA
NA
Immunotherapy
0.91 (0.47–1.76)
0.7705
NA
NA
NA
NA
NA
NA
Antitumor therapy
1.15 (0.94–1.42)
0.1815
1.08 (0.88–1.32)
0.4643
1.26 (0.91–1.75)
0.1597
NA
NA
Abbreviations NA Not available, OR Odds ratio, CI Confidence interval

Supernumerary prognostic factors for death and severe disease of cancer patients with COVID-19

The potential prognostic factors for the death of cancer patients with COVID-19 were as follows: age (OR = 1.15, 95%CI: 1.12–1.19, P < 0.0001) (Fig. 4A), gender (OR = 1.22, 95%CI: 1.11–1.34, P < 0.0001) (Fig. 4B), hypertension (OR = 1.32, 95%CI: 1.22–1.41, P < 0.0001) (Fig. 4C), diabetes (OR = 1.31, 95%CI: 1.20–1.42, P < 0.0001) (Fig. 4D), COPD (OR = 1.24, 95%CI: 1.08–1.41, P = 0.0016) (Fig. 4E), cardiovascular disease (OR = 1.33, 95%CI: 1.15–1.55, P = 0.0001) (Fig. 4F), smoking (OR = 1.29, 95%CI: 1.14–1.47, P < 0.0001) (Fig. 4G), ECOG PS (OR = 1.73, 95%CI: 1.47–2.03, P < 0.0001) (Fig. 4H), lung cancer (OR = 1.38, 95%CI: 1.05–1.81, P = 0.0200) (Fig. 4I), white blood cell count (OR = 1.86, 95%CI: 1.17–2.97, P = 0.0093) (Fig. 4J), and CRP (OR = 1.03, 95%CI: 1.00–1.05, P = 0.0298) (Fig. 4K). Nevertheless, obesity status (OR = 1.02, 95%CI: 0.91–1.15, P = 0.6827), lymphocyte count (OR = 1.24, 95%CI: 0.57–2.68, P = 0.5868), D-dimer (OR = 1.01, 95%CI: 0.98–1.05, P = 0.3981) and NLR (OR = 1.30, 95%CI: 0.64–2.64, P = 0.4763) were not highly correlated to the death of cancer patients with COVID-19 (Additional file 7: Appendix 7).
Furthermore, the potential prognostic factors for severe disease of cancer patients with COVID-19 included age (OR = 1.10, 95%CI: 1.05–1.15, P < 0.0001) (Fig. 5A), gender (OR = 1.12, 95%CI: 1.04–1.21, P = 0.0017) (Fig. 5B), hypertension (OR = 1.22, 95%CI: 1.02–1.45, P = 0.0286) (Fig. 5C), COPD (OR = 1.20, 95%CI: 1.01–1.43, P = 0.0416) (Fig. 5D), smoking (OR = 1.21, 95%CI: 1.08–1.35, P = 0.0008) (Fig. 5E), and lung cancer (OR = 1.30, 95%CI: 1.08–1.56, P = 0.0055) (Fig. 5F). However, such factors as diabetes (OR = 1.03, 95%CI: 0.88–1.20, P = 0.7415), obesity status (OR = 1.00, 95%CI: 0.92–1.10, P = 0.9254), ECOG PS (OR = 1.39, 95%CI: 0.93–2.07, P = 0.1119), white blood cell count (OR = 1.90, 95%CI: 0.88–4.11, P = 0.1026), CRP (OR = 1.39, 95%CI: 0.77–2.50, P = 0.2735), lymphocyte count (OR = 1.02, 95%CI: 0.76–1.36, P = 0.9093), D-dimer (OR = 1.05, 95%CI: 0.98–1.13, P = 0.1387), and creatine kinase (OR = 1.52, 95%CI: 0.83–2.77, P = 0.1762) did not obviously influence the severe disease of cancer patients with COVID-19 (Additional file 7: Appendix 7).

Subgroup analysis

Depending on the type of cancer, patients were further assigned into groups of solid tumor and haematological malignancy, as listed in Additional file 8: Appendix 8.
The potential prognostic factors for the death of solid tumor patients with COVID-19 included age (OR = 1.01, 95%CI: 1.00–1.01, P = 0.0168), gender (OR = 1.22, 95%CI: 1.09–1.36, P = 0.0006), hypertension (OR = 1.20, 95%CI: 1.00–1.42, P = 0.0446), and smoking (OR = 1.19, 95%CI: 1.04–1.35, P = 0.0110).
Furthermore, age (OR = 1.37, 95%CI: 1.20–1.57, P < 0.0001), hypertension (OR = 1.20, 95%CI: 1.02–1.41, P = 0.0246) and diabetes (OR = 1.26, 95%CI: 1.03–1.53, P = 0.0245) ranked as the potential prognostic factors for the death of haematological malignancy patients with COVID-19.

Discussion

A meta-analysis involving 15 studies demonstrated that chemotherapy could increase the risk of death from COVID-19 in cancer patients [61]. To our best knowledge, this study composed of 52 cohorts involving 9231 cancer patients with COVID-19, was so far the largest-scale investigation with respect to the impact of anti-tumor approaches on clinical outcomes of cancer patients with COVID-19, indicating that cancer patients with recent anti-tumor therapy (especially chemotherapy) were generally susceptible to develop into severe COVID-19, or even death.
Firstly, cancer patients with COVID-19 receiving chemotherapy were more likely to confront with severe disease and death, probably because patients treated with chemotherapy were susceptible to suffer from bone marrow suppression (including severe neutropenia or lymphocytopenia) and impaired immunity [62, 63], even respiratory infections (involving viral etiology) [64]. Furthermore, the recovery of immune system might take a long time after the weakening of immune functions by chemotherapy [65]. As a result, cancer patients with COVID-19 failed to effectively activate the immune system to eliminate the virus in a timely manner [66], that’s why they were more likely to trigger severe disease or even death.
Secondly, recent surgery might lead to increasing risk of death and a trend of severe disease in cancer patients with COVID-19, partially attributable to their frequent visits to hospital and postoperative negative nitrogen balance. Moreover, the stress and trauma caused by surgery could be clinically manifested as decreased immunity, since numerous studies revealed that the immunity of patients would reduce to a certain extent in a period of time after surgery [67].
Thirdly, patients administered with targeted therapy before COVID-19 diagnosis faced with elevated risk of severe disease. Despite targeted therapy seldomly impaired the immunity system of cancer patients, all those receiving maintenance targeted therapy suffered from advanced disease and many complications in general, giving rise to clinical worsening as a result.
Finally, tumor immunotherapy has played an increasingly crucial role in the field of anti-tumor treatment over the past decade [68]. As shown in our study, cancer patients with COVID-19 who received immunotherapy recently did not generate a higher rate of severe disease or death when comparing to those without immunotherapy.
In summary, this study aimed at providing clinicians with preliminary evidence for the safety of anti-tumor approaches during COVID-19. As to patients with COVID-19 who received anti-tumor approaches recently, especially chemotherapy, surgery and targeted therapy, clinicians should focus on disease progression and make intervention in a timely manner when necessary. Furthermore, intensive nursing and positive measures shall be taken to improve the prognosis and reduce the risk of death in practice.

Limitations

This study came up with four drawbacks as follows: firstly, limited studies related to radiotherapy, surgery and endocrine therapy might affect the accuracy of pooled results to some degree; secondly, 23 included studies failed to separate solid tumor from haematological malignancy for investigating the impact of anti-tumor approaches on the clinical outcomes, which might influence the accuracy of results; thirdly, bias might exist to some extent for excluding relevant studies published in non-English language; lastly, other forms of bias should be taken into account as follows: position bias (e.g. different health care systems and national policies in managing COVID-19) and time lag bias (time of study: start of pandemic vs. later phase of pandemic), which were not available in the included studies.

Conclusions

Anti-tumor therapy, especially chemotherapy, augmented the risk of severe disease and death for cancer patients with COVID-19, so did surgery for the risk of death and targeted therapy for the incidence of severe COVID-19.

Acknowledgments

None.

Code availability

Not applicable.

Registration and protocol

The review was not registered and the protocol was not prepared.

Declarations

Not applicable.
Not applicable.

Competing interests

The authors declare no competing interests.
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Literatur
1.
Zurück zum Zitat Coronaviridae Study Group of the International Committee on Taxonomy of Viruses. The species severe acute respiratory syndrome-related coronavirus: classifying 2019-nCoV and naming it SARS-CoV-2. Nat Microbiol. 2020;5(4):536–44. CrossRef Coronaviridae Study Group of the International Committee on Taxonomy of Viruses. The species severe acute respiratory syndrome-related coronavirus: classifying 2019-nCoV and naming it SARS-CoV-2. Nat Microbiol. 2020;5(4):536–44. CrossRef
2.
Zurück zum Zitat Atzrodt CL, Maknojia I, McCarthy RDP, et al. A guide to COVID-19: a global pandemic caused by the novel coronavirus SARS-CoV-2. FEBS J. 2020;287(17):3633–50. PubMedCrossRef Atzrodt CL, Maknojia I, McCarthy RDP, et al. A guide to COVID-19: a global pandemic caused by the novel coronavirus SARS-CoV-2. FEBS J. 2020;287(17):3633–50. PubMedCrossRef
3.
Zurück zum Zitat Giannakoulis VG, Papoutsi E, Siempos II. Effect of cancer on clinical outcomes of patients with COVID-19: a meta-analysis of patient data. JCO Glob Oncol. 2020;6(6):799–808. PubMedCrossRef Giannakoulis VG, Papoutsi E, Siempos II. Effect of cancer on clinical outcomes of patients with COVID-19: a meta-analysis of patient data. JCO Glob Oncol. 2020;6(6):799–808. PubMedCrossRef
4.
Zurück zum Zitat Tian J, Yuan X, Xiao J, et al. Clinical characteristics and risk factors associated with COVID-19 disease severity in patients with CANCER in Wuhan, China: a multicentre, retrospective, cohort study. Lancet Oncol. 2020;21(7):893–903. PubMedPubMedCentralCrossRef Tian J, Yuan X, Xiao J, et al. Clinical characteristics and risk factors associated with COVID-19 disease severity in patients with CANCER in Wuhan, China: a multicentre, retrospective, cohort study. Lancet Oncol. 2020;21(7):893–903. PubMedPubMedCentralCrossRef
5.
Zurück zum Zitat Dai M, Liu D, Liu M, et al. Patients with cancer appear more vulnerable to SARS-CoV-2: a multicenter study during the COVID-19 outbreak. Cancer Discov. 2020;10(6):783–91. PubMedPubMedCentral Dai M, Liu D, Liu M, et al. Patients with cancer appear more vulnerable to SARS-CoV-2: a multicenter study during the COVID-19 outbreak. Cancer Discov. 2020;10(6):783–91. PubMedPubMedCentral
6.
Zurück zum Zitat Kuderer NM, Choueiri TK, Shah DP, et al. COVID-19 and Cancer consortium. Clinical impact of COVID-19 on patients with Cancer (CCC19): a cohort study. Lancet. 2020;395(10241):1907–18. PubMedPubMedCentralCrossRef Kuderer NM, Choueiri TK, Shah DP, et al. COVID-19 and Cancer consortium. Clinical impact of COVID-19 on patients with Cancer (CCC19): a cohort study. Lancet. 2020;395(10241):1907–18. PubMedPubMedCentralCrossRef
7.
Zurück zum Zitat Yang K, Sheng Y, Huang C, et al. Clinical characteristics, outcomes, and risk factors for mortality in patients with Cancer and COVID-19 in Hubei, China: a multicentre, retrospective, cohort study. Lancet Oncol. 2020;21(7):904–13. PubMedPubMedCentralCrossRef Yang K, Sheng Y, Huang C, et al. Clinical characteristics, outcomes, and risk factors for mortality in patients with Cancer and COVID-19 in Hubei, China: a multicentre, retrospective, cohort study. Lancet Oncol. 2020;21(7):904–13. PubMedPubMedCentralCrossRef
8.
Zurück zum Zitat Jazieh AR, Akbulut H, Curigliano G, et al. International research network on COVID-19 impact on cancer care. Impact of the COVID-19 pandemic on cancer care: a global collaborative study. JCO Glob Oncol. 2020;6:1428–38. PubMedCrossRef Jazieh AR, Akbulut H, Curigliano G, et al. International research network on COVID-19 impact on cancer care. Impact of the COVID-19 pandemic on cancer care: a global collaborative study. JCO Glob Oncol. 2020;6:1428–38. PubMedCrossRef
9.
Zurück zum Zitat Balogun OD, Bea VJ, Phillips E. Disparities in cancer outcomes due to COVID-19 – a tale of 2 cities. JAMA Oncol. 2020;6(10):1531. PubMedCrossRef Balogun OD, Bea VJ, Phillips E. Disparities in cancer outcomes due to COVID-19 – a tale of 2 cities. JAMA Oncol. 2020;6(10):1531. PubMedCrossRef
10.
Zurück zum Zitat Pathania AS, Prathipati P, Abdul BA, et al. COVID-19 and Cancer comorbidity: therapeutic opportunities and challenges. Theranostics. 2021;11(2):731–53. PubMedPubMedCentralCrossRef Pathania AS, Prathipati P, Abdul BA, et al. COVID-19 and Cancer comorbidity: therapeutic opportunities and challenges. Theranostics. 2021;11(2):731–53. PubMedPubMedCentralCrossRef
11.
Zurück zum Zitat Mehta V, Goel S, Kabarriti R, et al. Case fatality rate of cancer patients with COVID-19 in a New York hospital system. Cancer Discov. 2020;10(7):935–41. PubMedPubMedCentralCrossRef Mehta V, Goel S, Kabarriti R, et al. Case fatality rate of cancer patients with COVID-19 in a New York hospital system. Cancer Discov. 2020;10(7):935–41. PubMedPubMedCentralCrossRef
12.
Zurück zum Zitat Yang F, Shi S, Zhu J, et al. Clinical characteristics and outcomes of Cancer patients with COVID-19. J Med Virol. 2020;92(10):2067–73. PubMedCrossRef Yang F, Shi S, Zhu J, et al. Clinical characteristics and outcomes of Cancer patients with COVID-19. J Med Virol. 2020;92(10):2067–73. PubMedCrossRef
14.
Zurück zum Zitat Zhang L, Zhu F, Xie L, et al. Clinical characteristics of COVID-19-infected Cancer patients: a retrospective case study in three hospitals within Wuhan, China. Ann Oncol. 2020;31(7):894–901. PubMedCrossRef Zhang L, Zhu F, Xie L, et al. Clinical characteristics of COVID-19-infected Cancer patients: a retrospective case study in three hospitals within Wuhan, China. Ann Oncol. 2020;31(7):894–901. PubMedCrossRef
15.
Zurück zum Zitat Pinato DJ, Zambelli A, Aguilar-Company J, et al. Clinical portrait of the SARS-CoV-2 epidemic in European cancer patients. Cancer Discov. 2020;10(10):1465–74. PubMedCentralCrossRef Pinato DJ, Zambelli A, Aguilar-Company J, et al. Clinical portrait of the SARS-CoV-2 epidemic in European cancer patients. Cancer Discov. 2020;10(10):1465–74. PubMedCentralCrossRef
16.
Zurück zum Zitat Glenthøj A, Jakobsen LH, Sengeløv H, et al. SARS-CoV-2 infection among patients with Haematological disorders: severity and one-month outcome in 66 Danish patients in a Nationwide cohort study. Eur J Haematol. 2021;106(1):72–81. PubMedCrossRef Glenthøj A, Jakobsen LH, Sengeløv H, et al. SARS-CoV-2 infection among patients with Haematological disorders: severity and one-month outcome in 66 Danish patients in a Nationwide cohort study. Eur J Haematol. 2021;106(1):72–81. PubMedCrossRef
17.
Zurück zum Zitat Song C, Dong Z, Gong H, et al. An online tool for predicting the prognosis of Cancer patients with SARS-CoV-2 infection: a multi-center study. J Cancer Res Clin Oncol. 2021;147(4):1247–57. PubMedCrossRef Song C, Dong Z, Gong H, et al. An online tool for predicting the prognosis of Cancer patients with SARS-CoV-2 infection: a multi-center study. J Cancer Res Clin Oncol. 2021;147(4):1247–57. PubMedCrossRef
18.
Zurück zum Zitat Lunski MJ, Burton J, Tawagi K, et al. Multivariate mortality analyses in COVID-19: comparing patients with Cancer and patients without Cancer in Louisiana. Cancer. 2021;127(2):266–74. PubMedCrossRef Lunski MJ, Burton J, Tawagi K, et al. Multivariate mortality analyses in COVID-19: comparing patients with Cancer and patients without Cancer in Louisiana. Cancer. 2021;127(2):266–74. PubMedCrossRef
19.
Zurück zum Zitat Lee LY, Cazier JB, Angelis V, 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. PubMedPubMedCentralCrossRef Lee LY, Cazier JB, Angelis V, 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. PubMedPubMedCentralCrossRef
20.
Zurück zum Zitat Stroppa EM, Toscani I, Citterio C, et al. Coronavirus Disease-2019 in Cancer patients. A report of the first 25 Cancer patients in a Western country (Italy). Future Oncol. 2020;16(20):1425–32. PubMedCrossRef Stroppa EM, Toscani I, Citterio C, et al. Coronavirus Disease-2019 in Cancer patients. A report of the first 25 Cancer patients in a Western country (Italy). Future Oncol. 2020;16(20):1425–32. PubMedCrossRef
21.
Zurück zum Zitat Zhang H, Wang L, Chen Y, et al. Outcomes of novel coronavirus disease 2019 (COVID-19) infection in 107 patients with cancer from Wuhan, China. Cancer. 2020;126(17):4023–31. PubMedCrossRef Zhang H, Wang L, Chen Y, et al. Outcomes of novel coronavirus disease 2019 (COVID-19) infection in 107 patients with cancer from Wuhan, China. Cancer. 2020;126(17):4023–31. PubMedCrossRef
22.
Zurück zum Zitat Robilotti EV, Babady NE, Mead PA, et al. Determinants of COVID-19 disease severity in patients with cancer. Nat Med. 2020;26(8):1218–23. Robilotti EV, Babady NE, Mead PA, et al. Determinants of COVID-19 disease severity in patients with cancer. Nat Med. 2020;26(8):1218–23.
23.
Zurück zum Zitat Yarza R, Bover M, Paredes D, et al. SARS-CoV-2 infection in Cancer patients undergoing active treatment: analysis of clinical features and predictive factors for severe respiratory failure and death. Eur J Cancer. 2020;135:242–50. PubMedPubMedCentralCrossRef Yarza R, Bover M, Paredes D, et al. SARS-CoV-2 infection in Cancer patients undergoing active treatment: analysis of clinical features and predictive factors for severe respiratory failure and death. Eur J Cancer. 2020;135:242–50. PubMedPubMedCentralCrossRef
24.
Zurück zum Zitat Li Q, Chen L, Li Q, et al. Cancer increases risk of in-hospital death from COVID-19 in persons <65 years and those not in complete remission. Leukemia. 2020;34(9):2384–91. PubMedPubMedCentralCrossRef Li Q, Chen L, Li Q, et al. Cancer increases risk of in-hospital death from COVID-19 in persons <65 years and those not in complete remission. Leukemia. 2020;34(9):2384–91. PubMedPubMedCentralCrossRef
26.
Zurück zum Zitat Sanchez-Pina JM, Rodríguez Rodriguez M, Castro Quismondo N, et al. Clinical course and risk factors for mortality from COVID-19 in patients with Haematological malignancies. Eur J Haematol. 2020;105(5):597–607. PubMedCrossRef Sanchez-Pina JM, Rodríguez Rodriguez M, Castro Quismondo N, et al. Clinical course and risk factors for mortality from COVID-19 in patients with Haematological malignancies. Eur J Haematol. 2020;105(5):597–607. PubMedCrossRef
27.
Zurück zum Zitat Assaad S, Avrillon V, Fournier ML, et al. High mortality rate in Cancer patients with symptoms of COVID-19 with or without detectable SARS-COV-2 on RT-PCR. Eur J Cancer. 2020;135:251–9. PubMedPubMedCentralCrossRef Assaad S, Avrillon V, Fournier ML, et al. High mortality rate in Cancer patients with symptoms of COVID-19 with or without detectable SARS-COV-2 on RT-PCR. Eur J Cancer. 2020;135:251–9. PubMedPubMedCentralCrossRef
28.
Zurück zum Zitat Garassino MC, Whisenant JG, Huang LC, et al. COVID-19 in patients with thoracic malignancies (TERAVOLT): first results of an international, registry-based, cohort study. Lancet Oncol. 2020;21(7):914–22. PubMedPubMedCentralCrossRef Garassino MC, Whisenant JG, Huang LC, et al. COVID-19 in patients with thoracic malignancies (TERAVOLT): first results of an international, registry-based, cohort study. Lancet Oncol. 2020;21(7):914–22. PubMedPubMedCentralCrossRef
29.
30.
Zurück zum Zitat Ma J, Yin J, Qian Y, Wu Y. Clinical characteristics and prognosis in cancer patients with COVID-19: a single center’s retrospective study. J Inf Secur. 2020;81(2):318–56. Ma J, Yin J, Qian Y, Wu Y. Clinical characteristics and prognosis in cancer patients with COVID-19: a single center’s retrospective study. J Inf Secur. 2020;81(2):318–56.
31.
Zurück zum Zitat Yu J, Ouyang W, Chua MLK, Xie C. SARS-CoV-2 transmission in patients with cancer at a tertiary care Hospital in Wuhan, China. JAMA Oncol. 2020;6(7):1108–10. PubMedPubMedCentralCrossRef Yu J, Ouyang W, Chua MLK, Xie C. SARS-CoV-2 transmission in patients with cancer at a tertiary care Hospital in Wuhan, China. JAMA Oncol. 2020;6(7):1108–10. PubMedPubMedCentralCrossRef
32.
Zurück zum Zitat Fox TA, Troy-Barnes E, Kirkwood AA, et al. Clinical outcomes and risk factors for severe COVID-19 in patients with Haematological disorders receiving chemo-or immunotherapy. Br J Haematol. 2020;191(2):194–206. PubMedCrossRef Fox TA, Troy-Barnes E, Kirkwood AA, et al. Clinical outcomes and risk factors for severe COVID-19 in patients with Haematological disorders receiving chemo-or immunotherapy. Br J Haematol. 2020;191(2):194–206. PubMedCrossRef
33.
Zurück zum Zitat Booth S, Willan J, Wong H, et al. Regional outcomes of severe acute respiratory syndrome coronavirus 2 infection in hospitalised patients with Haematological malignancy. Eur J Haematol. 2020;105(4):476–83. PubMedCrossRef Booth S, Willan J, Wong H, et al. Regional outcomes of severe acute respiratory syndrome coronavirus 2 infection in hospitalised patients with Haematological malignancy. Eur J Haematol. 2020;105(4):476–83. PubMedCrossRef
34.
Zurück zum Zitat Cattaneo C, Daffini R, Pagani C, et al. Clinical characteristics and risk factors for mortality in Dematologic patients affected by COVID-19. Cancer. 2020;126(23):5069–76. PubMedCrossRef Cattaneo C, Daffini R, Pagani C, et al. Clinical characteristics and risk factors for mortality in Dematologic patients affected by COVID-19. Cancer. 2020;126(23):5069–76. PubMedCrossRef
35.
Zurück zum Zitat Lara OD, O'Cearbhaill RE, Smith MJ, et al. COVID-19 outcomes of patients with gynecologic cancer in New York City. Cancer. 2020;126(19):4294–303. PubMedCrossRef Lara OD, O'Cearbhaill RE, Smith MJ, et al. COVID-19 outcomes of patients with gynecologic cancer in New York City. Cancer. 2020;126(19):4294–303. PubMedCrossRef
36.
Zurück zum Zitat Liu C, Li L, Song K, et al. A nomogram for predicting mortality in patients with COVID-19 and solid tumors: a multicenter retrospective cohort study. J Immunother Cancer. 2020;8(2):e001314. PubMedPubMedCentralCrossRef Liu C, Li L, Song K, et al. A nomogram for predicting mortality in patients with COVID-19 and solid tumors: a multicenter retrospective cohort study. J Immunother Cancer. 2020;8(2):e001314. PubMedPubMedCentralCrossRef
37.
Zurück zum Zitat Luo J, Rizvi H, Preeshagul IR, et al. COVID-19 in patients with lung Cancer. Ann Oncol. 2020;31(10):1386–96. PubMedCrossRef Luo J, Rizvi H, Preeshagul IR, et al. COVID-19 in patients with lung Cancer. Ann Oncol. 2020;31(10):1386–96. PubMedCrossRef
38.
Zurück zum Zitat Mato AR, Roeker LE, Lamanna N, et al. Outcomes of COVID-19 in patients with CLL: a multicenter international experience. Blood. 2020;136(10):1134–43. PubMedCrossRef Mato AR, Roeker LE, Lamanna N, et al. Outcomes of COVID-19 in patients with CLL: a multicenter international experience. Blood. 2020;136(10):1134–43. PubMedCrossRef
39.
Zurück zum Zitat Rogado J, Obispo B, Pangua C, et al. Covid-19 transmission, outcome and associated risk factors in cancer patients at the first month of the pandemic in a Spanish hospital in Madrid. Clin Transl Oncol. 2020;22(12):2364–8. PubMedCrossRef Rogado J, Obispo B, Pangua C, et al. Covid-19 transmission, outcome and associated risk factors in cancer patients at the first month of the pandemic in a Spanish hospital in Madrid. Clin Transl Oncol. 2020;22(12):2364–8. PubMedCrossRef
40.
Zurück zum Zitat Russell B, Moss C, Papa S, et al. Factors affecting COVID-19 outcomes in cancer patients: a first report from Guy’s cancer center in London. Front Oncol. 2020;10:1279. PubMedPubMedCentralCrossRef Russell B, Moss C, Papa S, et al. Factors affecting COVID-19 outcomes in cancer patients: a first report from Guy’s cancer center in London. Front Oncol. 2020;10:1279. PubMedPubMedCentralCrossRef
41.
Zurück zum Zitat Scarfò L, Chatzikonstantinou T, Rigolin GM, et al. COVID-19 severity and mortality in patients with chronic lymphocytic leukemia: a joint study by ERIC, the European research initiative on CLL, and CLL campus. Leukemia. 2020;34(9):2354–63. PubMedCrossRef Scarfò L, Chatzikonstantinou T, Rigolin GM, et al. COVID-19 severity and mortality in patients with chronic lymphocytic leukemia: a joint study by ERIC, the European research initiative on CLL, and CLL campus. Leukemia. 2020;34(9):2354–63. PubMedCrossRef
42.
Zurück zum Zitat Vuagnat P, Frelaut M, Ramtohul T, et al. COVID-19 in breast Cancer patients: a cohort at the Institut curie hospitals in the Paris area. Breast Cancer Res. 2020;22(1):55. PubMedPubMedCentralCrossRef Vuagnat P, Frelaut M, Ramtohul T, et al. COVID-19 in breast Cancer patients: a cohort at the Institut curie hospitals in the Paris area. Breast Cancer Res. 2020;22(1):55. PubMedPubMedCentralCrossRef
43.
Zurück zum Zitat Wang B, Van Oekelen O, Mouhieddine TH, et al. A tertiary center experience of multiple myeloma patients with COVID-19: lessons learned and the path forward. J Hematol Oncol. 2020;13(1):94. PubMedPubMedCentralCrossRef Wang B, Van Oekelen O, Mouhieddine TH, et al. A tertiary center experience of multiple myeloma patients with COVID-19: lessons learned and the path forward. J Hematol Oncol. 2020;13(1):94. PubMedPubMedCentralCrossRef
45.
Zurück zum Zitat Gonzalez-Cao M, Carrera C, Rodriguez Moreno JF, et al. COVID-19 in melanoma patients: Results of the Spanish Melanoma Group Registry, GRAVID study. J Am Acad Dermatol. 2021;84(5):1412–5. Gonzalez-Cao M, Carrera C, Rodriguez Moreno JF, et al. COVID-19 in melanoma patients: Results of the Spanish Melanoma Group Registry, GRAVID study. J Am Acad Dermatol. 2021;84(5):1412–5.
46.
Zurück zum Zitat de Melo AC, LCS T, da Silva JL, et al. Brazilian National Cancer Institute COVID-19 task force. Cancer inpatient with COVID-19: a report from the Brazilian National Cancer Institute. Plos One. 2020;15(10):e0241261. PubMedPubMedCentralCrossRef de Melo AC, LCS T, da Silva JL, et al. Brazilian National Cancer Institute COVID-19 task force. Cancer inpatient with COVID-19: a report from the Brazilian National Cancer Institute. Plos One. 2020;15(10):e0241261. PubMedPubMedCentralCrossRef
47.
Zurück zum Zitat Albiges L, Foulon S, Bayle A, et al. Determinants of the outcomes of patients with cancer infected with SARS-CoV-2: results from the Gustave Roussy cohort. Nature Cancer. 2020;1:965–75. PubMedCrossRef Albiges L, Foulon S, Bayle A, et al. Determinants of the outcomes of patients with cancer infected with SARS-CoV-2: results from the Gustave Roussy cohort. Nature Cancer. 2020;1:965–75. PubMedCrossRef
48.
Zurück zum Zitat Martínez-López J, Mateos MV, Encinas Giannakoulis VGC, et al. Multiple myeloma and SARS-CoV-2 infection: clinical characteristics and prognostic factors of inpatient mortality. Blood Cancer J. 2020;10(10):103. PubMedPubMedCentralCrossRef Martínez-López J, Mateos MV, Encinas Giannakoulis VGC, et al. Multiple myeloma and SARS-CoV-2 infection: clinical characteristics and prognostic factors of inpatient mortality. Blood Cancer J. 2020;10(10):103. PubMedPubMedCentralCrossRef
49.
Zurück zum Zitat Martín-Moro F, Núnez-Torrón C, Pérez-Lamas L, et al. Survival study of hospitalised patients with concurrent COVID-19 and Haematological malignancies. Leuk Res. 2021;101:106518. PubMedPubMedCentralCrossRef Martín-Moro F, Núnez-Torrón C, Pérez-Lamas L, et al. Survival study of hospitalised patients with concurrent COVID-19 and Haematological malignancies. Leuk Res. 2021;101:106518. PubMedPubMedCentralCrossRef
50.
Zurück zum Zitat Lattenist R, Yildiz H, De Greef J, Bailly S, Yombi JC. COVID-19 in adult patients with hematological disease: analysis of clinical characteristics and outcomes. Indian J Hematol Blood Transfus. 2020;37(1):1–5. Lattenist R, Yildiz H, De Greef J, Bailly S, Yombi JC. COVID-19 in adult patients with hematological disease: analysis of clinical characteristics and outcomes. Indian J Hematol Blood Transfus. 2020;37(1):1–5.
51.
Zurück zum Zitat Nakamura S, Kanemasa Y, Atsuta Y, et al. Characteristics and outcomes of coronavirus disease 2019 (COVID-19) patients with cancer: a single-center retrospective observational study in Tokyo, Japan. Int J Clin Oncol. 2021;26(3):485–93. PubMedCrossRef Nakamura S, Kanemasa Y, Atsuta Y, et al. Characteristics and outcomes of coronavirus disease 2019 (COVID-19) patients with cancer: a single-center retrospective observational study in Tokyo, Japan. Int J Clin Oncol. 2021;26(3):485–93. PubMedCrossRef
52.
Zurück zum Zitat Rogiers A, Pires da Silva I, Tentori C, et al. Clinical Impact of COVID-19 on Patients with Cancer Treated with Immune Checkpoint Inhibition. J Immunother Cancer. 2021;9(1):e001931. PubMedCrossRef Rogiers A, Pires da Silva I, Tentori C, et al. Clinical Impact of COVID-19 on Patients with Cancer Treated with Immune Checkpoint Inhibition. J Immunother Cancer. 2021;9(1):e001931. PubMedCrossRef
53.
Zurück zum Zitat Nie L, Dai K, Wu J, et al. Clinical characteristics and risk factors for in-hospital mortality of lung cancer patients with COVID-19: a multicenter, retrospective, cohort study. Thorac Cancer. 2021;12(1):57–65. PubMedCrossRef Nie L, Dai K, Wu J, et al. Clinical characteristics and risk factors for in-hospital mortality of lung cancer patients with COVID-19: a multicenter, retrospective, cohort study. Thorac Cancer. 2021;12(1):57–65. PubMedCrossRef
54.
Zurück zum Zitat Larfors G, Pahnke S, State M, Fredriksson K, Pettersson D. Covid-19 intensive care admissions and mortality among Swedish patients with cancer. Acta Oncol. 2021;60(1):32–4. PubMedCrossRef Larfors G, Pahnke S, State M, Fredriksson K, Pettersson D. Covid-19 intensive care admissions and mortality among Swedish patients with cancer. Acta Oncol. 2021;60(1):32–4. PubMedCrossRef
55.
Zurück zum Zitat Höllein A, Bojko P, Schulz S, et al. Characteristics and outcomes of patients with cancer and COVID-19: results from a cohort study. Acta Oncol. 2021;60(1):24–7. PubMedCrossRef Höllein A, Bojko P, Schulz S, et al. Characteristics and outcomes of patients with cancer and COVID-19: results from a cohort study. Acta Oncol. 2021;60(1):24–7. PubMedCrossRef
56.
Zurück zum Zitat Garnett C, Foldes D, Bailey C, et al. Outcome of hospitalized patients with hematological malignancies and COVID-19 infection in a large urban healthcare trust in the United Kingdom. Leuk Lymphoma. 2021;62(2):469–72. PubMedCrossRef Garnett C, Foldes D, Bailey C, et al. Outcome of hospitalized patients with hematological malignancies and COVID-19 infection in a large urban healthcare trust in the United Kingdom. Leuk Lymphoma. 2021;62(2):469–72. PubMedCrossRef
57.
Zurück zum Zitat Hanna GJ, Rettig EM, Park JC, et al. Hospitalization rates and 30-day all-cause mortality among head and neck cancer patients and survivors with COVID-19. Oral Oncol. 2021;112:105087. PubMedCrossRef Hanna GJ, Rettig EM, Park JC, et al. Hospitalization rates and 30-day all-cause mortality among head and neck cancer patients and survivors with COVID-19. Oral Oncol. 2021;112:105087. PubMedCrossRef
58.
Zurück zum Zitat Lièvre A, Turpin A, Ray-Coquard I, et al. GCO-002 CACOVID-19 collaborators/investigators. Risk factors for coronavirus disease 2019 (COVID-19) severity and mortality among solid Cancer patients and impact of the disease on anticancer treatment: a French Nationwide cohort study (GCO-002 CACOVID-19). Eur J Cancer. 2020;141:62–81. PubMedPubMedCentralCrossRef Lièvre A, Turpin A, Ray-Coquard I, et al. GCO-002 CACOVID-19 collaborators/investigators. Risk factors for coronavirus disease 2019 (COVID-19) severity and mortality among solid Cancer patients and impact of the disease on anticancer treatment: a French Nationwide cohort study (GCO-002 CACOVID-19). Eur J Cancer. 2020;141:62–81. PubMedPubMedCentralCrossRef
59.
Zurück zum Zitat Smith M, Lara OD, O'Cearbhaill R, et al. Inflammatory markers in gynecologic oncology patients hospitalized with COVID-19 infection. Gynecol Oncol. 2020;159(3):618–22. PubMedPubMedCentralCrossRef Smith M, Lara OD, O'Cearbhaill R, et al. Inflammatory markers in gynecologic oncology patients hospitalized with COVID-19 infection. Gynecol Oncol. 2020;159(3):618–22. PubMedPubMedCentralCrossRef
60.
Zurück zum Zitat Wu Y, Chen W, Li W, et al. Clinical characteristics, therapeutic management, and prognostic factors of adult COVID-19 inpatients with hematological malignancies. Leuk Lymphoma. 2020;61(14):3440–50. PubMedCrossRef Wu Y, Chen W, Li W, et al. Clinical characteristics, therapeutic management, and prognostic factors of adult COVID-19 inpatients with hematological malignancies. Leuk Lymphoma. 2020;61(14):3440–50. PubMedCrossRef
61.
Zurück zum Zitat Yekedüz E, Utkan G, Ürün Y. A systematic review and meta-analysis: the effect of active cancer treatment on severity of COVID-19. Eur J Cancer. 2020;141:92–104. PubMedPubMedCentralCrossRef Yekedüz E, Utkan G, Ürün Y. A systematic review and meta-analysis: the effect of active cancer treatment on severity of COVID-19. Eur J Cancer. 2020;141:92–104. PubMedPubMedCentralCrossRef
62.
Zurück zum Zitat May JE, Donaldson C, Gynn L, Morse HR. Chemotherapy-induced Genotoxic Damage to Bone Marrow Cells: Long-term Implications. Mutagenesis. 2018;33(3):241–51. PubMedCrossRef May JE, Donaldson C, Gynn L, Morse HR. Chemotherapy-induced Genotoxic Damage to Bone Marrow Cells: Long-term Implications. Mutagenesis. 2018;33(3):241–51. PubMedCrossRef
63.
Zurück zum Zitat Gardner RV. Long term hematopoietic damage after chemotherapy and cytokine. Front Biosci. 1999;4:e47–57. PubMedCrossRef Gardner RV. Long term hematopoietic damage after chemotherapy and cytokine. Front Biosci. 1999;4:e47–57. PubMedCrossRef
64.
Zurück zum Zitat Vento S, Cainelli F, Temesgen Z. Lung infections after cancer chemotherapy. Lancet Oncol. 2008;9(10):982–92. PubMedCrossRef Vento S, Cainelli F, Temesgen Z. Lung infections after cancer chemotherapy. Lancet Oncol. 2008;9(10):982–92. PubMedCrossRef
65.
Zurück zum Zitat Kang DH, Weaver MT, Park NJ, Smith B, McArdle T, Carpenter J. Significant impairment in immune recovery after Cancer treatment. Nurs Res. 2009;58(2):105–14. PubMedPubMedCentralCrossRef Kang DH, Weaver MT, Park NJ, Smith B, McArdle T, Carpenter J. Significant impairment in immune recovery after Cancer treatment. Nurs Res. 2009;58(2):105–14. PubMedPubMedCentralCrossRef
67.
Zurück zum Zitat Lord JM, Midwinter MJ, Chen YF, et al. The systemic immune response to trauma: an overview of pathophysiology and treatment. Lancet. 2014;384(9952):1455–65. PubMedPubMedCentralCrossRef Lord JM, Midwinter MJ, Chen YF, et al. The systemic immune response to trauma: an overview of pathophysiology and treatment. Lancet. 2014;384(9952):1455–65. PubMedPubMedCentralCrossRef
68.
Zurück zum Zitat Topalian SL, Drake CG, Pardoll DM. Immune checkpoint blockade: a common denominator approach to Cancer therapy. Cancer Cell. 2015;27(4):450–61. PubMedPubMedCentralCrossRef Topalian SL, Drake CG, Pardoll DM. Immune checkpoint blockade: a common denominator approach to Cancer therapy. Cancer Cell. 2015;27(4):450–61. PubMedPubMedCentralCrossRef
Metadaten
Titel
The impact of anti-tumor approaches on the outcomes of cancer patients with COVID-19: a meta-analysis based on 52 cohorts incorporating 9231 participants
verfasst von
Qing Wu
Shuimei Luo
Xianhe Xie
Publikationsdatum
30.11.2022
Verlag
BioMed Central
Erschienen in
BMC Cancer / Ausgabe 1/2022
Elektronische ISSN: 1471-2407
DOI
https://doi.org/10.1186/s12885-022-09320-x

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