Clinical characteristics and risk factors for mortality in cancer patients with COVID-19

doi:10.1007/s11684-021-0845-6

Front. Med.

2021, Vol. 15

Issue (2) : 264-274 https://doi.org/10.1007/s11684-021-0845-6

RESEARCH ARTICLE

Clinical characteristics and risk factors for mortality in cancer patients with COVID-19

Junnan Liang¹, Guannan Jin², Tongtong Liu³, Jingyuan Wen¹, Ganxun Li¹, Lin Chen^1,³, Wei Wang¹, Yuwei Wang¹, Wei Liao¹, Jia Song¹, Zeyang Ding^1,³(

), Xiao-ping Chen^1,³(

), Bixiang Zhang^1,³(

)

¹. Hepatic Surgery Center, Liver Cancer Institute, and Hubei Key Laboratory of HPB Diseases, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
². Department of Internal Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
³. Tongji Multidisciplinary Team for Treating COVID-19 (TTTC), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China

Download: PDF(523 KB) HTML
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks

Abstract

Patients with cancer are at increased risk of severe infections. From a cohort including 3060 patients with confirmed COVID-19, 109 (3.4%) cancer patients were included in this study. Among them, 23 (21.1%) patients died in the hospital. Cancer patients, especially those with hematological malignancies (41.6%), urinary carcinoma (35.7%), malignancies of the digestive system (33.3%), gynecological malignancies (20%), and lung cancer (14.3%), had a much higher mortality than patients without cancer. A total of 19 (17.4%) cancer patients were infected in the hospital. The clinical characteristics of deceased cancer patients were compared with those of recovered cancer patients. Multivariate Cox regression analysis indicated that a Nutritional Risk Screening (NRS2002) score≥3 (adjusted hazard ratio (HR) 11.00; 95% confidence interval (CI) 4.60–26.32; P <0.001), high-risk type (adjusted HR 18.81; 95% CI 4.21–83.93; P <0.001), tumor stage IV (adjusted HR 4.26; 95% CI 2.34–7.75; P <0.001), and recent adjuvant therapy (<1 month) (adjusted HR 3.16; 95% CI 1.75–5.70; P <0.01) were independent risk factors for in-hospital death after adjusting for age, comorbidities, D-dimer, and lymphocyte count. In conclusion, cancer patients showed a higher risk of COVID-19 infection with a poorer prognosis than patients without cancer. Cancer patients with high-risk tumor, NRS2002 score≥3, advanced tumor stage, and recent adjuvant therapy (<1 month) may have high risk of mortality.

Keywords cancer COVID-19 SARS-CoV-2 risk factor mortality

Corresponding Author(s): Zeyang Ding,Xiao-ping Chen,Bixiang Zhang

Just Accepted Date: 03 March 2021 Online First Date: 22 March 2021 Issue Date: 23 April 2021

Cite this article:

Junnan Liang,Guannan Jin,Tongtong Liu, et al. Clinical characteristics and risk factors for mortality in cancer patients with COVID-19[J]. Front. Med., 2021, 15(2): 264-274.

URL:

https://academic.hep.com.cn/fmd/EN/10.1007/s11684-021-0845-6
https://academic.hep.com.cn/fmd/EN/Y2021/V15/I2/264

Variables	All patients (n = 109)	Recovered (n = 86)	Deceased (n = 23)	P value
Age (year, median (IQR))	65.00 (56.00, 71.00)	64.00 (56.00, 70.00)	68.00 (53.50, 76.50)	0.33
Age≥65 years	55 (50.5)	42 (48.8)	13 (56.5)	0.675
Sex
Female	52 (47.7)	43 (50.0)	9 (39.1)	0.489
Male	57 (52.3)	43 (50.0)	14 (60.9)	0.489
Source of infection
Nosocomial transmission*	19 (17.5)	11 (12.8)	8 (34.8)	0.014
Community infection**	90 (82.5)	75 (87.2)	15 (65.2)	0.014
During out-of-hospital treatment	6 (5.5)	2 (2.3)	4 (17.4)	< 0.001
Follow-up period	84 (77.0)	73 (84.9)	11 (47.8)	< 0.001
Signs and symptoms at admission
Fever	86 (78.9)	68 (79.1)	18 (78.3)	1
Cough	75 (68.8)	59 (68.6)	16 (69.6)	1
Expectoration	49 (45.0)	37 (43.0)	12 (52.2)	0.584
Shortness of breath	51 (46.8)	39 (45.3)	12 (52.2)	0.728
Pharyngalgia	5 (4.6)	4 (4.7)	1 (4.3)	1
Rhinorrhoea	3 (2.8)	2 (2.3)	1 (4.3)	1
Fatigue	25 (22.9)	18 (20.9)	7 (30.4)	0.494
Chest pain	8 (7.3)	7 (8.1)	1 (4.3)	0.866
Diarrhea	26 (23.9)	20 (23.3)	6 (26.1)	0.994
Abdominal pain	5 (4.6)	3 (3.5)	2 (8.7)	0.618
Anorexia	26 (23.9)	21 (24.4)	5 (21.7)	1
Nausea or vomiting	10 (9.2)	7 (8.1)	3 (13.0)	0.751
Myalgia	14 (12.8)	11 (12.8)	3 (13.0)	1
Headache	9 (8.3)	7 (8.1)	2 (8.7)	1
Dizziness	8 (7.3)	7 (8.1)	1 (4.3)	0.866
Respiratory rate, breath per minute Pulse, beat per minute Median arterial pressure, mmHg Percutaneous oxygen saturation, %	20.00 (20.00, 22.00) 86.00 (76.00, 98.00) 96.33 (90.67, 103.33) 96.00 (92.00, 99.00)	20.00 (20.00, 22.00) 85.00 (76.00, 97.75) 96.83 (92.17, 103.58) 96.50 (94.25, 99.00)	20.00 (20.00, 22.50) 89.00 (78.00, 105.50) 93.00 (83.83, 101.00) 89.00 (75.00, 97.00)	0.661 0.296 0.127 0.005
Chronic comorbidities
Hypertension	38 (34.9)	33 (38.4)	5 (21.7)	0.215
Diabetes	18 (16.5)	15 (17.4)	3 (13.0)	0.85
Cardiovascular disease	10 (9.2)	9 (10.5)	1 (4.3)	0.62
Cerebrovascular disease	4 (3.7)	4 (4.7)	0 (0.0)	0.668
Chronic pulmonary disease	19 (17.4)	17 (19.8)	2 (8.7)	0.35
Chronic kidney disease	3 (2.8)	3 (3.5)	0 (0.0)	0.849
Chronic liver disease	10 (9.2)	6 (7.0)	4 (17.4)	0.258
Clinical type on admission
Severe pneumonia	60 (55.0)	44 (51.2)	16 (69.6)	0.18
Days from illness onset to outcome	41.28 (29.00, 54.50)	45.50 (33.00, 56.26)	25.52 (15.00, 33.00)	< 0.001
Days from admission to outcome	23.72 (13.24, 36.63)	26.67 (17.51, 41.12)	7.62 (4.44, 17.25)	< 0.001

Tab.1 Clinical characteristics of cancer patients with COVID-19

Variables	All patients (n = 109)	Recovered (n = 86)	Deceased (n = 23)	P value
Tumor type
Lung cancer	14 (12.8)	12 (13.9)	2 (8.2)	0.503
Malignancy of the digestive system	24 (22.0)	16 (18.6)	8 (34.8)	0.096
Gastric carcinoma	8 (7.3)	5 (5.8)	3 (13.0)	0.237
Colorectal cancer	5 (4.6)	4 (4.7)	1 (4.3)	0.949
Esophagus cancer	4 (3.7)	2 (2.3)	2 (8.7)	0.149
Rectal cancer	2 (1.8)	2 (2.3)	0	0.460
Liver cancer	5 (4.6)	3 (3.5)	2 (8.7)	0.289
Head and neck cancer	21 (19.3)	21 (24.4)	0	0.008
Laryngeal carcinoma	1 (0.9)	1 (1.2)	0	0.603
Oral cancer	1 (0.9)	1 (1.2)	0	0.603
Nasopharyngeal carcinoma	3 (2.7)	3 (3.5)	0	0.363
Thyroid cancer	16 (14.7)	16 (18.6)	0	0.025
Hematological malignancies	12 (11.0)	7 (8.1)	5 (21.7)	0.064
Leukemia	7 (6.4)	4 (4.7)	3 (13.0)	0.144
Lymphoma	4 (3.7)	3 (3.5)	1 (4.3)	0.845
Multiple myeloma	1 (0.9)	0	1 (4.3)	0.052
Urinary carcinoma	14 (12.8)	9 (10.5)	5 (21.7)	0.151
Bladder cancer	8 (7.3)	4 (4.7)	4 (17.4)	0.037
Prostate cancer	4 (3.7)	3 (3.5)	1 (4.3)	0.845
Renal carcinoma	2 (1.8)	2 (2.3)	0	0.460
Breast cancer	11 (10.1)	11 (12.8)	0	0.070
Gynecological malignancies	10 (9.2)	8 (9.3)	2 (8.7)	0.928
Uterine malignancy	4 (3.7)	3 (3.5)	1 (4.3)	0.845
Cervical cancer	5 (4.6)	4 (4.7)	1 (4.3)	0.949
Ovarian cancer	1 (0.9)	1 (1.2)	0	0.603
Others	3 (2.7)	2 (2.3)	1 (4.3)	0.312
Spinal tumor	1 (0.9)	1 (1.2)	0	0.598
Bronchial tumor	1 (0.9)	1 (1.2)	0	0.603
Liposarcoma	1 (0.9)	0	1 (4.3)	0.052
Condition grading
Karnofsky performance score (≥70)	8 (7.3)	5 (5.8)	3 (13.0)	0.237
ECOG performance status score (>2)	3 (2.7)	1 (1.2)	2 (8.7)	0.049
NRS2002 score (≥3)	39 (35.7)	19 (22.1)	20 (86.9)	< 0.001
Tumor stage
Stage I/II/III	86 (78.8)	75 (87.2)	11 (47.8)	< 0.001
Stage IV	23 (21.2)	11 (12.3)	12 (52.1)	< 0.001
History of prior treatment
Operation	65 (59.6)	55 (64.0)	10 (43.4)	0.075
a. Operation (<1 month)	4 (3.7)	4 (4.7)	0	0.291
Adjuvant therapy	59 (54.1)	40 (46.5)	19 (82.6)	0.002
Recent adjuvant therapy	20 (18.3)	8 (9.3)	12 (52.1)	< 0.001
Chemo-/radiotherapy	54 (49.5)	38 (44.2)	16 (69.5)	0.031
b. Recent chemo-/radiotherapy (<1 month)	17 (15.6)	7 (8.1)	10 (43.4)	< 0.001
Targeted/immunotherapy	9 (8.2)	4 (4.7)	5 (21.7)	0.008
c. Recent targeted/immunotherapy (<1 month)	3 (2.7)	1 (1.2)	2 (8.7)	0.049

Tab.2 Oncological characteristics of cancer patients with COVID-19

Tab.3 Treatment and complications in cancer patients with COVID-19

Patient characteristics and findings	Univariate
Patient characteristics and findings	HR (95% CI)	P value
Age, >65 years	1.528 (0.668–3.493)	0.315
Sex, male	1.399 (0.605–3.234)	0.433
Chronic comorbidities
Chronic pulmonary disease	0.396 (0.093–1.689)	0.211
Signs and symptoms at admission
Percutaneous oxygen saturation,≤93%	3.345 (1.473–7.599)	0.004
Tumor type
High-risk type	11.094 (1.495–82.35)	0.019
Tumor stage
Tumor stage IV	6.025 (2.647–13.713)	< 0.001
Condition grading
Karnofsky performance score (≥70)	0.512 (0.152–1.724)	0.28
ECOG performance status score (> 2)	4.95 (1.152–53.191)	0.032
NRS2002 score (≥3)	14.53 (4.31–48.91)	< 0.001
History of prior treatment
Operation	0.566 (0.248–1.292)	0.176
a. Operation (<1 month)	1.304 (0.174–9.757)	0.796
Adjuvant therapy	5.137 (1.743–15.139)	0.003
Recent adjuvant therapy (<1 month)	4.194 (1.845–9.534)	< 0.001
Chemo-/radiotherapy	2.589 (1.064–6.301)	0.036
b. Recent chemo-/radiotherapy (<1 month)	4.834 (2.116–11.043)	< 0.001
Targeted/immunotherapy	3.662 (1.352–9.914)	0.011
c. Recent targeted/immunotherapy (<1 month)	3.458 (0.803–14.898)	0.096
Combined (a+ b or a+ c)	3.786 (0.507–28.29)	0.195
Source of infection
Nosocomial infection	2.501 (1.56–5.923)	0.037
Chest computed tomography scan features
Bilateral	1.071 (0.134–8.568)	0.948
Laboratory findings
Lymphocyte count, <1.1 × 10⁹/L	2.874 (0.976–8.468)	0.055
Platelet count, <125 × 10⁹/L	6.752 (2.859–15.951)	< 0.001
Hemoglobin, <120 g/L	2.006 (0.868–4.638)	0.104
D-dimer, >1 µg/mL	4.018 (1.365–11.828)	0.012
Aspartate aminotransferase, > 40 U/L	2.516 (1.1–5.751)	0.029
Total bilirubin, > 21.1 µmol/L	5.000 (1.96–12.5)	0.001
Direct bilirubin, > 8 µmol/L	2.85 (1.204–6.666)	0.018
Albumin, <35 g/L	3.823 (1.411–10.25)	0.008
Lactose dehydrogenase, >214 U/L	2.394 (0.879–6.521)	0.088
High-sensitivity cardiac troponin I, >15.6 pg/mL	7.081 (2.782–18.026)	< 0.001
N-terminal pro-brain natriuretic peptide, > 486 pg/mL	6.329 (2.409–16.666)	< 0.001
Highly sensitive C-reactive protein, >10 mg/L	10.11 (1.362–75.072)	0.024
Serum ferritin, > 400 µg/L	7.173 (0.942–54.639)	0.057
IL-6, > 62 U/mL	0 (0-Inf)	0.998
Procalcitonin, > 0.05 ng/mL	8.268 (1.105–61.874)	0.04
IL-10, > 9.1 pg/mL	8.242 (2.751–24.7)	< 0.001

Tab.4 Univariate Cox regression analysis of risk factors associated with death in cancer patients with COVID-19

Fig.1 Risk factors for death according to the multivariate Cox proportional hazards regression model. Shown in the figure are the hazards ratio (HR) and the 95% confidence interval (95% CI) associated with the endpoint. The HRs of each variable were obtained using separate proportional hazard Cox models after adjusting for age, comorbidities, D-dimer, and lymphocyte count. Comorbidities included chronic obstructive pulmonary disease, hypertension, diabetes, and cardiovascular disease.

Fig.2 Adjusted Kaplan–Meier survival curves of cancer patients with COVID-19 stratified by risk factors. (A) NRS2002 score, (B) tumor type, (C) tumor stage, and (D) recent adjuvant therapy. NRS2002, Nutritional Risk Screening 2002.

1	N Zhu, D Zhang, W Wang, X Li, B Yang, J Song, X Zhao, B Huang, W Shi, R Lu, P Niu, F Zhan, X Ma, D Wang, W Xu, G Wu, GF Gao, W Tan; China Novel Coronavirus Investigating and Research Team. A novel coronavirus from patients with pneumonia in china, 2019. N Engl J Med 2020; 382(8): 727–733 https://doi.org/10.1056/NEJMoa2001017 pmid: 31978945
2	E Dong, H Du, L Gardner. An interactive web-based dashboard to track COVID-19 in real time. Lancet Infect Dis 2020; 20(5): 533–534 https://doi.org/10.1016/S1473-3099(20)30120-1 pmid: 32087114
3	M Kamboj, KA Sepkowitz. Nosocomial infections in patients with cancer. Lancet Oncol 2009; 10(6): 589–597 https://doi.org/10.1016/S1470-2045(09)70069-5 pmid: 19482247
4	JY Li, XF Duan, LP Wang, YJ Xu, L Huang, TF Zhang, JY Liu, F Li, Z Zhang, DL Yue, F Wang, B Zhang, Y Zhang. Selective depletion of regulatory T cell subsets by docetaxel treatment in patients with nonsmall cell lung cancer. J Immunol Res 2014; 2014: 286170 https://doi.org/10.1155/2014/286170 pmid: 24868562
5	A Sica, M Massarotti. Myeloid suppressor cells in cancer and autoimmunity. J Autoimmun 2017; 85: 117–125 https://doi.org/10.1016/j.jaut.2017.07.010 pmid: 28728794
6	W Liang, W Guan, R Chen, W Wang, J Li, K Xu, C Li, Q Ai, W Lu, H Liang, S Li, J He. Cancer patients in SARS-CoV-2 infection: a nationwide analysis in China. Lancet Oncol 2020; 21(3): 335–337 https://doi.org/10.1016/S1470-2045(20)30096-6 pmid: 32066541
7	L Zhang, F Zhu, L Xie, C Wang, J Wang, R Chen, P, Jia HQ Guan, L Peng, Y, Chen P Peng, P Zhang, Q Chu, Q Shen, Y Wang, SY Xu, JP, Zhao M Zhou. 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 https://doi.org/10.1016/j.annonc.2020.03.296 pmid: 32224151
8	C Huang, Y Wang, X Li, L Ren, J Zhao, Y Hu, L Zhang, G Fan, J Xu, X Gu, Z Cheng, T Yu, J Xia, Y Wei, W Wu, X Xie, W Yin, H Li, M Liu, Y Xiao, H Gao, L Guo, J Xie, G Wang, R Jiang, Z Gao, Q Jin, J Wang, B Cao. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet 2020; 395(10223): 497–506 https://doi.org/10.1016/S0140-6736(20)30183-5 pmid: 31986264
9	D Wang, B Hu, C Hu, F Zhu, X Liu, J Zhang, B Wang, H Xiang, Z Cheng, Y Xiong, Y Zhao, Y Li, X Wang, Z Peng. Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China. JAMA 2020; 323(11): 1061–1069 https://doi.org/10.1001/jama.2020.1585 pmid: 32031570
10	X Yang, Y Yu, J Xu, H Shu, J Xia, H Liu, Y Wu, L Zhang, Z Yu, M Fang, T Yu, Y Wang, S Pan, X Zou, S Yuan, Y Shang. Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study. Lancet Respir Med 2020; 8(5): 475–481 https://doi.org/10.1016/S2213-2600(20)30079-5 pmid: 32105632
11	F Zhou, T Yu, R Du, G Fan, Y Liu, Z Liu, J Xiang, Y Wang, B Song, X Gu, L Guan, Y Wei, H Li, X Wu, J Xu, S Tu, Y Zhang, H Chen, B Cao. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet 2020; 395(10229): 1054–1062 https://doi.org/10.1016/S0140-6736(20)30566-3 pmid: 32171076
12	C Sohrabi, Z Alsafi, N O’Neill, M Khan, A Kerwan, A Al-Jabir, C Iosifidis, R Agha. World Health Organization declares global emergency: a review of the 2019 novel coronavirus (COVID-19). Int J Surg 2020; 76: 71–76 https://doi.org/10.1016/j.ijsu.2020.02.034 pmid: 32112977
13	RS Zheng, KX Sun, SW Zhang, HM Zeng, XN Zou, R Chen, XY Gu, WW Wei, J He. Report of cancer epidemiology in China, 2015. Chin J Oncol (Zhonghua Zhong Liu Za Zhi) 2019; 41(1): 19–28 (in Chinese) pmid: 30678413
14	J Cao, WJ Tu, W Cheng, L Yu, YK Liu, X Hu, Q Liu. Clinical features and short-term outcomes of 102 patients with corona virus disease 2019 in Wuhan, China. Clin Infect Dis 2020; 71(15): 748–755 https://doi.org/10.1093/cid/ciaa243 pmid: 32239127
15	T Chen, D Wu, H Chen, W Yan, D Yang, G Chen, K Ma, D Xu, H Yu, H Wang, T Wang, W Guo, J Chen, C Ding, X Zhang, J Huang, M Han, S Li, X Luo, J Zhao, Q Ning. Clinical characteristics of 113 deceased patients with coronavirus disease 2019: retrospective study. BMJ 2020; 368: m1091 https://doi.org/10.1136/bmj.m1091 pmid: 32217556
16	M Berdasco, M Esteller. Clinical epigenetics: seizing opportunities for translation. Nat Rev Genet 2019; 20(2): 109–127 https://doi.org/10.1038/s41576-018-0074-2 pmid: 30479381
17	C Röllig, S Knop, M Bornhäuser. Multiple myeloma. Lancet 2015; 385(9983): 2197–2208 https://doi.org/10.1016/S0140-6736(14)60493-1 pmid: 25540889
18	F Xiao, M Tang, X Zheng, Y Liu, X Li, H Shan. Evidence for gastrointestinal infection of SARS-CoV-2. Gastroenterology 2020; 158(6): 1831–1833.e3 https://doi.org/10.1053/j.gastro.2020.02.055 pmid: 32142773
19	KS Cheung, IFN Hung, PPY Chan, KC Lung, E Tso, R Liu, YY Ng, MY Chu, TWH Chung, AR Tam, CCY Yip, KH Leung, AY Fung, RR Zhang, Y Lin, HM Cheng, AJX Zhang, KKW To, KH Chan, KY Yuen, WK Leung. Gastrointestinal manifestations of SARS-CoV-2 infection and virus load in fecal samples from a Hong Kong cohort: systematic review and meta-analysis. Gastroenterology 2020; 159(1): 81–95 https://doi.org/10.1053/j.gastro.2020.03.065 pmid: 32251668
20	H Chen, J Guo, C Wang, F Luo, X Yu, W Zhang, J Li, D Zhao, D Xu, Q Gong, J Liao, H Yang, W Hou, Y Zhang. Clinical characteristics and intrauterine vertical transmission potential of COVID-19 infection in nine pregnant women: a retrospective review of medical records. Lancet 2020; 395(10226): 809–815 https://doi.org/10.1016/S0140-6736(20)30360-3 pmid: 32151335
21	S Zheng, J Fan, F Yu, B Feng, B Lou, Q Zou, G Xie, S Lin, R Wang, X Yang, W Chen, Q Wang, D Zhang, Y Liu, R Gong, Z Ma, S Lu, Y Xiao, Y Gu, J Zhang, H Yao, K Xu, X Lu, G Wei, J Zhou, Q Fang, H Cai, Y Qiu, J Sheng, Y Chen, T Liang. Viral load dynamics and disease severity in patients infected with SARS-CoV-2 in Zhejiang Province, China, January–March 2020: retrospective cohort study. BMJ 2020; 369: m1443 https://doi.org/10.1136/bmj.m1443 pmid: 32317267
22	L Dong, J Tian, S He, C Zhu, J Wang, C Liu, J Yang. Possible vertical transmission of SARS-CoV-2 from an infected mother to her newborn. JAMA 2020; 323(18): 1846–1848 https://doi.org/10.1001/jama.2020.4621 pmid: 32215581
23	J Kondrup, HH Rasmussen, O Hamberg, Z Stanga; Ad Hoc ESPEN Working Group. Nutritional risk screening (NRS 2002): a new method based on an analysis of controlled clinical trials. Clin Nutr 2003; 22(3): 321–336 https://doi.org/10.1016/S0261-5614(02)00214-5 pmid: 12765673
24	G Liu, S Zhang, Z Mao, W Wang, H Hu. Clinical significance of nutritional risk screening for older adult patients with COVID-19. Eur J Clin Nutr 2020; 74(6): 876–883 https://doi.org/10.1038/s41430-020-0659-7 pmid: 32404899
25	A Vigano, M Piccioni, B Trutschnigg, L Hornby, P Chaudhury, R Kilgour. Male hypogonadism associated with advanced cancer: a systematic review. Lancet Oncol 2010; 11(7): 679–684 https://doi.org/10.1016/S1470-2045(10)70021-8 pmid: 20541464
26	L Zhao, R He, H Long, B Guo, Q Jia, D Qin, SQ Liu, Z Wang, T Xiang, J Zhang, Y Tan, J Huang, J Chen, F Wang, M Xiao, J Gao, X Yang, H Zeng, X Wang, C Hu, PB Alexander, ALJ Symonds, J Yu, Y Wan, QJ Li, L Ye, B Zhu. Late-stage tumors induce anemia and immunosuppressive extramedullary erythroid progenitor cells. Nat Med 2018; 24(10): 1536–1544 https://doi.org/10.1038/s41591-018-0205-5 pmid: 30297899
27	WJM Mulder, J Ochando, LAB Joosten, ZA Fayad, MG Netea. Therapeutic targeting of trained immunity. Nat Rev Drug Discov 2019; 18(7): 553–566 https://doi.org/10.1038/s41573-019-0025-4 pmid: 30967658
28	AC Shaw, DR Goldstein, RR Montgomery. Age-dependent dysregulation of innate immunity. Nat Rev Immunol 2013; 13(12): 875–887 https://doi.org/10.1038/nri3547 pmid: 24157572
29	KD Kim, J Zhao, S Auh, X Yang, P Du, H Tang, YX Fu. Adaptive immune cells temper initial innate responses. Nat Med 2007; 13(10): 1248–1252 https://doi.org/10.1038/nm1633 pmid: 17891146
30	FAM Saner, A Herschtal, BH Nelson, A deFazio, EL Goode, SJ Ramus, A Pandey, JA Beach, S Fereday, A Berchuck, S Lheureux, CL Pearce, PD Pharoah, MC Pike, DW Garsed, DDL Bowtell. Going to extremes: determinants of extraordinary response and survival in patients with cancer. Nat Rev Cancer 2019; 19(6): 339–348 https://doi.org/10.1038/s41568-019-0145-5 pmid: 31076661

[1]

FMD-20096-OF-CXP_suppl_1

Download

[1]	Guizhen Wang, Qun Zhao, Hui Zhang, Fan Liang, Chen Zhang, Jun Wang, Zhenyin Chen, Ran Wu, Hong Yu, Beibei Sun, Hua Guo, Ruie Feng, Kaifeng Xu, Guangbiao Zhou. Degradation of SARS-CoV-2 receptor ACE2 by the E3 ubiquitin ligase Skp2 in lung epithelial cells[J]. Front. Med., 2021, 15(2): 252-263.
[2]	Shi-Yong Sun. mTOR-targeted cancer therapy: great target but disappointing clinical outcomes, why?[J]. Front. Med., 2021, 15(2): 221-231.
[3]	Wenjie Zhu, Binghe Xu. Overcoming resistance to endocrine therapy in hormone receptor-positive human epidermal growth factor receptor 2-negative (HR⁺/HER2^--) advanced breast cancer: a meta-analysis and systemic review of randomized clinical trials[J]. Front. Med., 2021, 15(2): 208-220.
[4]	Deyu Zhang, Xiaojie Xu, Qinong Ye. Metabolism and immunity in breast cancer[J]. Front. Med., 2021, 15(2): 178-207.
[5]	Xiaowei Zhu, Houfeng Zheng. Factors influencing peak bone mass gain[J]. Front. Med., 2021, 15(1): 53-69.
[6]	Yong Fan, Yan Geng, Lin Shen, Zhuoli Zhang. Advances on immune-related adverse events associated with immune checkpoint inhibitors[J]. Front. Med., 2021, 15(1): 33-42.
[7]	Solmaz Ohadian Moghadam, Seyed Ali Momeni. Human microbiome and prostate cancer development: current insights into the prevention and treatment[J]. Front. Med., 2021, 15(1): 11-32.
[8]	Hongnan Mo, Binghe Xu. Progress in systemic therapy for triple-negative breast cancer[J]. Front. Med., 2021, 15(1): 1-10.
[9]	Zixin Shu, Yana Zhou, Kai Chang, Jifen Liu, Xiaojun Min, Qing Zhang, Jing Sun, Yajuan Xiong, Qunsheng Zou, Qiguang Zheng, Jinghui Ji, Josiah Poon, Baoyan Liu, Xuezhong Zhou, Xiaodong Li. Clinical features and the traditional Chinese medicine therapeutic characteristics of 293 COVID-19 inpatient cases[J]. Front. Med., 2020, 14(6): 760-775.
[10]	Guohua Chen, Wen Su, Jiayao Yang, Dan Luo, Ping Xia, Wen Jia, Xiuyang Li, Chuan Wang, Suping Lang, Qingbin Meng, Ying Zhang, Yuhe Ke, An Fan, Shuo Yang, Yujiao Zheng, Xuepeng Fan, Jie Qiao, Fengmei Lian, Li Wei, Xiaolin Tong. Chinese herbal medicine reduces mortality in patients with severe and critical coronavirus disease 2019: a retrospective cohort study[J]. Front. Med., 2020, 14(6): 752-759.
[11]	Yun Tan, Feng Liu, Xiaoguang Xu, Yun Ling, Weijin Huang, Zhaoqin Zhu, Mingquan Guo, Yixiao Lin, Ziyu Fu, Dongguo Liang, Tengfei Zhang, Jian Fan, Miao Xu, Hongzhou Lu, Saijuan Chen. Durability of neutralizing antibodies and T-cell response post SARS-CoV-2 infection[J]. Front. Med., 2020, 14(6): 746-751.
[12]	Qingwei Li, Han Wang, Xiuyang Li, Yujiao Zheng, Yu Wei, Pei Zhang, Qiyou Ding, Jiaran Lin, Shuang Tang, Yikun Zhao, Linhua Zhao, Xiaolin Tong. The role played by traditional Chinese medicine in preventing and treating COVID-19 in China[J]. Front. Med., 2020, 14(5): 681-688.
[13]	Mian Peng, Xueyan Liu, Jinxiu Li, Di Ren, Yongfeng Liu, Xi Meng, Yansi Lyu, Ronglin Chen, Baojun Yu, Weixiong Zhong. Successful management of seven cases of critical COVID-19 with early noninvasive–invasive sequential ventilation algorithm and bundle pharmacotherapy[J]. Front. Med., 2020, 14(5): 674-680.
[14]	Lingling Tang, Yingan Jiang, Mengfei Zhu, Lijun Chen, Xiaoyang Zhou, Chenliang Zhou, Peng Ye, Xiaobei Chen, Baohong Wang, Zhenyu Xu, Qiang Zhang, Xiaowei Xu, Hainv Gao, Xiaojun Wu, Dong Li, Wanli Jiang, Jingjing Qu, Charlie Xiang, Lanjuan Li. Clinical study using mesenchymal stem cells for the treatment of patients with severe COVID-19[J]. Front. Med., 2020, 14(5): 664-673.
[15]	Zhihang Peng, Wenyu Song, Zhongxing Ding, Quanquan Guan, Xu Yang, Qiaoqiao Xu, Xu Wang, Yankai Xia. Linking key intervention timings to rapid declining effective reproduction number to quantify lessons against COVID-19[J]. Front. Med., 2020, 14(5): 623-629.

Viewed

Full text

Abstract

Cited

Shared

Discussed