Editor
Due to the restriction caused by the COVID-19 epidemic, the cancer community currently faces many difficulties1. First, tumor patients had to risk the chances of exposure when they went to the cancer clinic. Second, cancer treatment could predispose patients to more serious effects of COVID-19. Third, infection of COVID-19 after tumor surgeries could lead to higher levels of comorbidity2,3. Thus, the surgeons and oncologists have to weigh the risk of COVID-19 infection against the magnitude of benefit of cancer treatments. Especially, along with the restoration of the medic order in the hospitals in Wuhan, the effects of those delayed treatments are now showing up in the following months4.
In this study, the medical records of patients from gastrointestinal department, Wuhan Union hospital, were collected and analyzed. Information recorded included demographic data, tumor clinical and pathological TNM stages, levels of hemoglobin and albumin on admission. We retrospectively analyzed 137 tumor patients admitted to our department on March and April, 2020 and 351 patients in the same period in 2019 (Table 1). A special group of patients, who were diagnosed before the epidemic (2020 January) but had been suspended for 2 months were specially studied to identify the progression (Table S1, supporting information). We expressed descriptive data as mean (SD) or median (IQR) for continuous variables and number (%) for categorical variables. Student's t test was used for continuous variables.
Table 1.
Clinical characteristics of patients admitted on March and April in 2019 and 2020
| Gastric cancer | Colorectal cancer | |||
|---|---|---|---|---|
| 2019 | 2020 | 2019 | 2020 | |
| Number of cases | 150 | 51 | 201 | 86 |
| Age (y) | 61·0 (54·0-66·0) | 58·0 (51·0-67·5) | 61·0 (53·8-69·0) | 62·0 (49·0-67·0) |
| Gender, female | 63 (42·0%) | 13 (25·5%) | 83 (41·3%) | 44 (51·2%) |
| Time from symptom onset to admission (days) | 30·0 (20·2-60·0) | 60·0 (21·0-120·0) | 30·0 (15·0-90·0) | 60·0 (30·0-90·0) * |
| BMI on admission | 22·1 ± 3·1 | 22·3 ± 3·4 | 23·3 ± 3·4 | 21·6 ± 3·5 * |
| Hb on admission | 113·2 ± 24·7 | 103·5 ± 39·1 | 119·3 ± 22·1 | 108·1 ± 29·5 * |
| Alb on admission | 38·3 ± 6·1 | 34·3 ± 11·0 | 40·1 ± 5·0 | 36·5 ± 8·9 * |
| Patient Category | * p = 0·049 | |||
| Surgery | 121 (80·7%) | 32 (62·7%) | 172 (85·6%) | 64 (74·4%) |
| Chemoradiotherapy | 23 (15·3%) | 15 (29·4%) | 22 (11·0%) | 15 (17·5%) |
| Giving up treatment | 6 (4·0%) | 4 (7·8%) | 7 (3·5%) | 7 (8·1%) |
| Pathology type | * p = 0·001 | |||
| G0 | 2 (1·7%) | 0 (0·0%) | 3 (1·7%) | 4 (6·2%) |
| G1 | 5 (4·1%) | 1 (3·1%) | 11 (6·4%) | 0 (0·0%) |
| G2 | 25 (20·7%) | 3 (9·4%) | 134 (77·9%) | 40 (62·5%) |
| G3 | 88 (72·7%) | 28 (87·5%) | 24 (14·0%) | 19 (29·7%) |
| G4 | 1 (0·8%) | 0 (0·0%) | 0 (0·0%) | 1 (1·6%) |
| Depth of tumor invasion | ||||
| pT1 | 23 (19·1%) | 2 (6·2%) | 18 (10·5%) | 7 (10·9%) |
| pT2 | 13 (10·7%) | 3 (9·4%) | 22 (12·8%) | 4 (6·2%) |
| pT3 | 33 (27·3%) | 8 (25·0%) | 101 (58·7%) | 37 (57·8%) |
| pT4 | 52 (43·0%) | 19 (59·4%) | 31 (18·0%) | 16 (25·0%) |
| Lymph node metastasis | * p = 0·006 | * p = 0·04 | ||
| pN0 | 46 (38·0%) | 6 (18·8%) | 98 (57·0%) | 35 (54·7%) |
| pN1 | 14 (11·6%) | 9 (28·1%) | 46 (26·7%) | 15 (23·4%) |
| pN2 | 25 (20·7%) | 2 (6·2%) | 28 (16·3%) | 14 (21·9%) |
| pN3 | 36 (29·8%) | 15 (46·9%) | ||
| Distant metastasis | * p = 0·016 | |||
| cM0 | 118 (97·5%) | 28 (87·5%) | 167 (97·1%) | 61 (95·3%) |
| cM1 | 3 (2·5%) | 4 (12·5%) | 5 (2·9%) | 3 (4·7%) |
| Vessels invasion, + | 60 (49·6%) | 18 (56·2%) | 40 (23·3%) | 16 (25·0%) |
| Nerves invasion, + | 70 (57·9%) | 21 (65·6%) | 44 (25·6%) | 18 (28·1%) |
| Adjuvant chemotherapy, yes | 8 (6·6%) | 4 (12·5%) | 2 (1·2%) | 6 (9·4%) * |
A continuous variables were presented as mean ± SD or median (IQR), categorical variables were showed as n (%). P-values were from t test for normally distributed continuous data and from Mann–Whitney U test for abnormally distributed continuous data. P-values were from χ2 test for categorical data.
p < 0.05 data in 2019 compared to data in 2020.
We compared the TNM stages and nutrient status of the patients in the 2 years. In 2020, patients had lower nutrition state, as there are lower levels of Hb, Alb and BMI. But only in the colorectal cancer group, there are significant differences. In terms of pathology, in 2020, we identified significantly higher levels of lymph node metastasis in both cancers. But in colorectal cancer, there are deeper depths of tumor invasion and in gastric cancer; there are more percentages of distant metastasis. Previously, before the epidemic in Wuhan, few patients received adjuvant chemotherapy before surgery, but due to COVID-19 affection, this situation is promoted in the colorectal cancer patients (Table 1).
We specially focused on progression of the patients who were diagnosed with gastrointestinal tumor on January, 2020. Many of these patients previously planned to spend the spring holiday with the family and come back 7 days later, but ended up with a delay of 2 months on average. The paired t test results proved that 2 months' delay led to advancedd lymph node metastasis stage an worse nutrition status in gastrointestinal tumor patients (Table S1, supporting information).
Previously, the immediately priority was to control the COVID-19 pandemic5. But now Wuhan already entered into the aftermath and recovery phase. At this moment, evaluating the effects of COVID-19 on cancer mortality will be a new priority. Unfortunately, the data presented by our medical center suggested “a long shadow beyond infection”. Still, our experience alerted that surgeons and oncologists in other countries and regions should be prepared ahead of time. For sure we believe that finally we could succeed in fighting against COVID-19. But we could do something more to reduce the sacrifice.
Funding/Support
This study was supported by National Natural Science Foundation of China (81700488, 81874184, 81972881). Natural Science Foundation of Hubei Province of China(2019CFB514).
Supplementary Material
Supplementary Table 1 Tumor progression from the same patient during the epidemic lockdown
Contributor Information
Geng Wang, Email: wangguobinuh@126.com.
Guobing Wang, Email: wangguobinuh@126.com.
Kaixiong Tao, Email: kaixiongtao@hust.edu.cn.
Reference
- 1. Wang H, Zhang L. Risk of COVID-19 for patients with cancer. The Lancet Oncology 2020; 21: e181. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2. Jessop ZM, Dobbs TD, Ali SRet al. Personal Protective Equipment (PPE) for Surgeons during COVID-19 Pandemic: A Systematic Review of Availability, Usage, and Rationing. Br J Surg 2020; 10.1002/bjs.11750 [Epub ahead of print]. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3. Ueda M, Martins R, Hendrie PC, McDonnell T, Crew JR, Wong TLet al. Managing cancer care during the COVID-19 pandemic: agility and collaboration toward a common goal. J Natl Compr Canc Netw 2020; 10.6004/jnccn.2020.7560 [Epub ahead of print]. [DOI] [PubMed] [Google Scholar]
- 4. Spinelli A, Pellino G. COVID-19 pandemic: perspectives on an unfolding crisis. Br J Surg 2020; 107: 785–787. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Søreide K, Hallet J, Matthews JB, Schnitzbauer AA, Line PD, Lai PBSet al. Immediate and long-term impact of the COVID-19 pandemic on delivery of surgical services. Br J Surg 2020; 10.1002/bjs.11670 [Epub ahead of print]. [DOI] [PMC free article] [PubMed] [Google Scholar]
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Supplementary Materials
Supplementary Table 1 Tumor progression from the same patient during the epidemic lockdown