prevalence and outcome of covid-19 infection in cancer ... · 21/08/2020 · cancer patients are...

Prevalence and outcome of Covid-19 infection in cancer patients: a national VA study

Nathanael R. Fillmore, PhD1,2,3,*; Jennifer La, PhD1,*; Raphael E. Szalat, MD1,3,4*; David P.

Tuck1,4, MD; Vinh Nguyen, MS1; Cenk Yildirim, MS1; Nhan V. Do, MD1,4,

Mary T. Brophy, MD1,4; Nikhil C. Munshi; MD1,2,3

1. VA Boston Healthcare System, Boston, MA

2. Harvard Medical School, Boston, MA

3. Dana-Farber Cancer Institute, Boston, MA

4. Boston University School of Medicine, Boston, MA

* These authors contributed equally

Corresponding author:

Nikhil C. Munshi, MD

450 Brookline Ave, Boston, MA 02215

617-632-5272

[email protected]

Text: 2664 words

Abstract: 248 words

Figures: 4

Tables: 0

References: 25

for use under a CC0 license. This article is a US Government work. It is not subject to copyright under 17 USC 105 and is also made available

(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted August 24, 2020. ; https://doi.org/10.1101/2020.08.21.20177923doi: medRxiv preprint

NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice.

https://doi.org/10.1101/2020.08.21.20177923

Abstract

Background

Emerging data suggest variability in susceptibility and outcome to Covid-19 infection. Identifying

the risk-factors associated with infection and outcomes in cancer patients is necessary to develop

healthcare recommendations.

Methods

We analyzed electronic health records of the US National Veterans Administration healthcare

system and assessed the prevalence of Covid-19 infection in cancer patients. We evaluated the

proportion of cancer patients tested for Covid-19 and their confirmed positivity, with clinical

characteristics, and outcome, and stratified by demographics, comorbidities, cancer treatment

and cancer type.

Results

Of 22914 cancer patients tested for Covid-19, 1794 (7.8%) were positive. The prevalence of

Covid-19 was similar across all ages. Higher prevalence was observed in African-American (AA)

(15%) compared to white (5.5%; P<.001), in Hispanic vs non-Hispanic population and in patients

with hematologic malignancy compared to those with solid tumors (10.9% vs 7.7%; P<.001).

Conversely, prevalence was lower in current smoker patients, patients with other co-morbidities

and having recently received cancer therapy (<6 months). The Covid-19 attributable mortality was

10.9%. Highest mortality rates were observed in older patients, those with renal dysfunction,

higher Charlson co-morbidity score and with certain cancer types. Recent (<6 months) or past

treatment did not influence mortality. Importantly, AA patients had 3.5-fold higher Covid-19

attributable hospitalization, however had similar mortality rate as white patients.

Conclusion

Pre-existence of cancer affects both susceptibility to Covid-19 infection and eventual outcome.

The overall Covid-19 attributable mortality in cancer patients is affected by age, co-morbidity and

specific cancer types, however, race or recent treatment including immunotherapy does not

impact outcome.

Fundings:

VA Office of Research and Development and National Institutes of Health.



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Introduction

The Covid-19 infection first reported in China, in December 20191, has now spread worldwide

affecting all demographics and regions. The emerging data suggests variability in susceptibility to

the infection and ultimately outcome. A number of patient related factors, socio economic

conditions, racial and ethnic differences and several comorbidities including obesity, diabetes

and cardiovascular diseases have been associated with higher susceptibility and/or risk of

mortality.2–5 The relatively higher transmission rate and associated greater risk of adverse

outcome has highlighted the need to understand the epidemiologic characteristics of Covid-19

prevalence, and the risk factors associated with poor outcome and death, in order to establish the

best possible public health policies. Cancer patients are considered to be at a higher risk of

infections. This risk varies with functional status of the patient, the cancer type, and/or treatment

modalities utilized.6,7 Thus, along with reducing exposure to the virus, other prophylactic as well

as cancer-related risk factors may need to be addressed to decrease susceptibility to Covid-19

infection or to mitigate related complications in cancer patients. Small epidemiologic studies

mainly from China and USA have also reported increased rates of death in cancer patients related

to Covid-19.8,9 These observations have informed some changes and re-organization of cancer

care worldwide10 but larger studies are needed to understand the comprehensive cancer-related

issues with Covid-19 infection. Here we investigated the prevalence and outcome of Covid-19

infection among cancer patients in a large cohort of patients from the nationwide Veterans Affairs

(VA) healthcare system. Our report, besides suggesting that cancer patients are more vulnerable

to Covid-19 infection,11,12 also highlights the prevalence of Covid-19 and outcome of the disease

based on racial characteristics, comorbidities, type of cancer and related treatment in a cohort of

22914 cancer patients.

Methods

Patients

This analysis was conducted using data from the VA Corporate Data Warehouse (CDW), which

centralizes EHR data for patients seen at VA facilities nationwide. The study population is defined

as veterans with cancer who were tested for Covid-19 at the VA. Cancer patients were identified

as patients with at least one occurrence of an International Classification of Diseases (ICD) code

for cancer between January 1, 2010 and May 4, 2020.26 Non-melanoma skin cancer and benign



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tumors were excluded. This study was performed under a protocol approved by the VA Boston

Healthcare System Research and Development Committee.

Study Variables and Outcomes

Patient demographics, Covid-19 laboratory tests, comorbidities, cancer type, cancer treatment,

and outcomes were identified through structured data in the EHR. Patients were considered

positive for Covid-19 if they had at least one positive test result, and negative if all Covid-19 test

results were negative. Covid-19 tests that were cancelled or did not have a positive or negative

result recorded were excluded from consideration. The Charlson comorbidity index and presence

of individual comorbidities were derived from ICD codes in the year prior to each patient’s first

Covid-19 test using the comorbidity package in R.13 BMI was calculated from each patient’s most

recently recorded weight and height prior to their first Covid-19 test. Smoking status was defined

using health factors.14 The geographical region of the VA hospital each patient was tested in, was

extracted from structured data, with regions defined using the mapping in Supplementary

Methods in Supplement 1. Cancer type was determined based on ICD codes in the study period,

and patients may have multiple cancer types. Only cancer types with at least 200 patients are

shown. The systemic therapies for cancer considered in this study were based on a list of

approved cancer drugs tabulated by the NCI.15 Patients were identified as being on active or

recent treatment for cancer at the time of Covid-19 testing if they received systemic therapy for

cancer in the 6 months prior to their first test for Covid-19, and only treatments in this time frame

were considered to determine the type of therapy received. As regards to outcomes,

hospitalization was defined as any inpatient visit after the patient’s first Covid-19 test, and ICU

admission was defined as a subset of hospitalizations where the specialty ward is either “Surgical

ICU” or “Medical ICU”. Respiratory support was determined based on the presence of a current

procedural terminology (CPT) or ICD procedure code for intubation (CPT 94002, 94003, 94004,

94005, ICD-10 Z99.1, Z99.11, Z99.12) or mechanical ventilation (CPT 31500, ICD-10 J95.851)

after the patient’s first Covid-19 test. Missing data existed for race, ethnicity, and smoking status

and was coded as a separate level in all analyses.

Statistical Analysis

We evaluated the proportion of Covid-19 positive patients among those tested, along with 95%

confidence intervals, and stratified by demographics, comorbidities, cancer treatment and cancer

type. We also evaluated the proportion of patients experiencing each outcome among Covid-19

positive and negative patients, and defined the Covid-19 attributable risk of each outcome as the



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difference of these two proportions. We used chi-squared tests to assess differences in

proportion. Odds ratio (OR) as to Covid-19 positive status by cancer type was assessed using

univariate and multivariate logistic regression, adjusting for race, ethnicity, and smoking status in

the multivariate models.

Results

Susceptibility to Covid-19 infection in cancer patients We identified 22914 patients with history of cancer who were tested for Covid-19 infection on or

before May 4, 2020, of whom 1794 patients (7.8%) reported positive (Figure 1A). The prevalence

of Covid-19 among those tested was similar across all ages (<50 years to ≥80years; P=.158),

although older patients with cancer were tested for Covid-19 more frequently (eTable 1 in

Supplement 1). Importantly, there was a significant difference in prevalence of infection across

race and ethnicity, with 14.95% of African Americans (AA) but only 5.49% of white patients testing

positive for Covid-19 (P<.001), and 10.87% of Hispanic/Latino patients vs 7.71% of non-

Hispanic/Latino patients testing positive (P<.001). We also observed a significantly lower

prevalence in cancer patients who were current smokers compared to former smokers or those

who never smoked (5.26% vs 9.49%; P<.001). Compared to the overall sample (7.8% positive),

there was a small but statistically significant negative association between susceptibility to Covid-

19 and concomitant congestive heart failure (6.68% positive; P<0.001), peripheral vascular

disease (6.51%; P<0.001), chronic obstructive pulmonary disease (6.27%; P<.001), and

moderate/severe liver disease (5.15%; P=.023). Higher body mass index (BMI) was associated

with increased prevalence of infection (P<.001).During the period of observation, Covid-19 was

much more frequent in the North Atlantic (14.77%) than other regions (6.25% Continental, 7.85%

Midwest, 2.37% Pacific, 3.21% Southeast; P<.001). Differences in susceptibility across race

persisted within each region (eTable 6).

We further investigated cancer types and prevalence of Covid-19 (Figure 1B) and observed

higher prevalence in patients with hematologic malignancy (10.9%) in comparison to patients with

solid tumors (7.8%, P<.001). Among specific cancer type, we observed significantly higher

frequency of Covid-19 among patients with prostate cancer (10.0%, P<0.001), while significantly

lower frequency among patients with esophagus (3.3%, P=.003), hepatocellular carcinoma (HCC)

(4.2%, P<.001), lung (4.3%, P<.001), cutaneous squamous cell carcinoma (CSSC) (4.7%,

P<.001), lymphoma (5.2%, P<.001), squamous cell head and neck cancer (SCCHN) (5.5%,



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P<.001), bone cancer (6.3%, P=.004), and urothelial cancer (6.46%, P=.013), among others. To

understand the relationship of race and cancer type, we assessed the odds of Covid-19 infection

by cancer type, adjusting for race, ethnicity and smoking status (eTable 2). Although the

univariate analysis showed that patients with prostate cancer had a higher risk of Covid-19

infection, this was no longer the case after adjustment, suggesting the higher prevalence

observed in prostate cancer may be affected by race, ethnicity, and/or smoking status. On the

other hand, patients with esophageal cancer, HCC, lung cancer, lymphoma, SCCHN, bone

cancer, melanoma, and other cancers continued to have a lower risk of Covid-19 infection even

after adjusting for these factors.

Next, we evaluated the impact of active cancer treatment on susceptibility to Covid-19 infection

and observed that patients receiving cancer therapy within the last 6 months had significantly

lower prevalence (6.23%) of Covid-19 compared to those who received therapy >6 months ago

(7.81%) or never received therapy (8.13%; P=.002). Moreover, compared to the overall cohort

(7.8%), patients receiving immune checkpoint inhibitors (2.70%, P<.001) or chemotherapy

(4.61%, P<.001) within the last 6 months had significantly lower prevalence of Covid-19 while

patients on hormonal therapy (8.14%, P=.763) or targeted therapy (6.55%, P=.114) did not have

significantly different prevalence.

Outcome of Covid-19 infection in cancer patients We next evaluated the impact of Covid-19 infection on outcome in cancer patients and calculated

the difference between frequency in positive vs negative as the Covid-19 attributable contribution.

Overall, compared to Covid-19 negative cancer patients, Covid-19 positive cancer patients have

higher frequency of hospitalizations (31.5% versus 43.8% respectively; an excess of 12.3%

Covid-19 attributable), ICU admissions (7.8% vs 19.7% respectively; 11.9% Covid-19

attributable), respiratory support (1.3% vs 7.9% respectively; 6.6% Covid-19 attributable). Covid-

19 attributable death was 10.9% with 14% death in Covid-19 positive compared to 3.1% in Covid-

19 negative patients (Figure 2).

To further assess the impact of patient and disease-related features on Covid-19 attributable

outcomes, we evaluated each of the demographic and comorbidity strata described above

(Figure 3A and Figure 4A). In general outcomes occur more frequently among Covid-19 positive

cancer patients, however the difference attributable to Covid-19 infection varies widely across

strata. Covid-19 attributable mortality is strongly associated with age, ranging from 0.23% among



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patients <50 years old to 20.51% among patients ≥80 years old (P<.001). Presence of other

comorbidities is also associated with increased Covid-19 attributable death, ranging from 3.07%

among patients with Charlson score 0, to 14.96% among patients with Charlson score ≥5

(P<.001). Covid-19 attributable ICU admissions were more common in obese patients (14.34%)

than in patients with normal BMI (5.87%, P<.001), as is need for respiratory support (8.94% vs

4.78%, P=.014); however mortality was not higher (10.45% in obese, 13.47% in normal; P=.21).

Interestingly, Covid-19 attributable mortality was lower in current smokers (6.45%) compared to

former/never smokers (11.99%; P=.002).

African Americans have increased Covid-19 attributable hospitalization (20.9%) compared to

white patients (5.9%), a 3.5 fold difference (P<.001) (Figure 4 and eTable 3). However, despite

the higher Covid-19 prevalence as well as increased Covid-19 attributable hospitalization, we do

not observe a significant difference in any of the other more serious Covid-19 attributable

outcomes, including mortality (12.0% in AA vs 10.8% in white; P=.498), respiratory support (6.0%

in AA vs 7.6% in white; P=.233), or ICU admissions (13.7% in AA vs 10.2% in white; P=.081).

Similarly, we do not observe a significant difference in Covid-19 attributable outcomes for

Hispanic/Latino compared to Non-Hispanic/Latino (eTable 4).

Outcomes were variable based on type of cancer (Figure 3B and Figure 4B). Covid-19

attributable deaths were observed in most but not all cancer types, with the highest attributable

mortality in acute leukemia (25.64%), male genital (20.79%), and thyroid cancer (19.88%). Covid-

19 attributable mortality is similar in patients recently treated for cancer (≤6 months ago, 14.17%)

compared to those treated >6 months ago (13.06%) or never treated with systemic therapy

(10.09%; P=.250). There is a suggestive relationship between type of treatment and outcome

attributable to Covid-19 infection. In patients receiving ICI within the last 6 months, Covid-19

attributable mortality (7.10%) is less than half that observed in patients receiving chemotherapy

(14.02%), hormone therapy (16.21%), or targeted therapy (14.13%), though significance is not

reached because of fewer observed deaths.

Discussion

We investigated a large cohort of cancer patients evaluated for Covid-19 at the VA Healthcare

System from across the United States in order to identify risk factors for Covid-19 susceptibility



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and outcomes in cancer patients. The overall frequency of Covid-19 positivity was 7.8% of tested

patients. As of May 16th, 2020, according to the United States Center for Disease Control, the

national positivity rate for Covid-19 infection in the US among patients aged of 18 and older is

13.5% with 126,627 positive patients out of 928,366 tested patients.16 Thus, the prevalence of

Covid-19 among cancer patients appeared to be lower than in the general population. However,

the real prevalence of Covid-19 remains uncertain, as a significant number of patients are not or

have not been tested, particularly in the context of asymptomatic disease. Nevertheless, the

observed lower prevalence of Covid-19 in cancer patients might be explained either by higher

access to testing within the VA healthcare system and/or higher rates of testing in cancer patients

in general.

Perhaps the most striking observation in our data is the significant racial and ethnic disparity in

prevalence of Covid-19 infection. African-American (15%) and Hispanic (10.9%) cancer patients

had significantly higher rates of Covid-19 infection in comparison to white cancer patients (5.5%),

and also had higher rates of hospitalization. The biological and/or social basis for this observation,

also recently reported in the general population,17–19 remains unclear. Overall, the observation of

this disparity across all the regions of the country (eTable 6) rules out the possible role of regional

conditions in explaining this difference. Covid-19 was more frequent among patients with prostate

cancer which is also more frequent in African-American patients.20 Although after adjusting for

race, ethnicity, and smoking status, this difference is no longer observed. The possible

explanations requiring further investigation include socio-economic factors or genetic

predisposition. Importantly, although AA cancer patients were more frequently admitted to the

hospital, with equal access to care in the VA healthcare system, similar mortality rate was

observed between AA and white cancer patients. Similar trend was also observed in

Hispanic/Latino population. These results suggest distinct factors modulating Covid-19

susceptibility and the related-outcome.

The significantly reduced prevalence of Covid-19 infection in cancer patients with current smoking

history, compared to those who have quit smoking or never smoked, is intriguing. This observation

is also confirmed by observed reduced frequency of Covid-19 infection among patients with lung

(4.31%, P<0.001), SCCHN (5.52%, P<0.001), and urothelial (6.46, P=0.013) cancers, all

malignancies associated with smoking. These differences might also be related to race or

ethnicity (eTables 3 and 4), or to socio-economics factors. An earlier preliminary report has also

suggested association of active smoking with significantly lower rates of Covid-19 infections.21



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This negative association requires further investigation. The role of nicotine, local epithelial cell

changes or inflammatory environment may play a role.22,23 We did not observe significant impact

of cardiopulmonary and other comorbidities as well as age of patients on rate of infection (Figure

1). The lack of significant impact of the well-described influence of comorbidities on Covid-19 in

our patients may suggest that pre-existence of cancer may outweigh the other comorbidities in

regard to susceptibility to Covid-19. Moreover, it is possible that sick patients and patients under

active cancer treatment may have been more cautious and thus less exposed to Covid-19, and

this may affect the vulnerability. While we are unable to directly quantify severity of cancer illness

in our dataset, we included two proxies for severity of disease that are available: (1) whether or

not each patient was recently treated for cancer (≤6 months ago), treated >6 months ago, or never

treated with systemic therapy, which serves to some extent as a proxy for severity; and (2) the

Charlson score which reflects severity of overall health condition prior to Covid-19 diagnosis. Our

analysis does reveal significantly lower rate of infection in patients treated ≤6 months ago, though

no significant difference in Covid-19 attributable mortality or other outcomes, and higher rates of

infection in patients with higher Charlson score was observed.

Outcome of cancer patients infected by Covid-19 was characterized by higher rates of mortality.

Although the frequency of Covid-19 positivity was lower in patients receiving cancer related

therapy within 6 months of the Covid-19 infection, the overall mortality was not significantly

different in comparison to no treatment or treatment prior to 6 months groups. These mortality

rates are higher than the mortality rates reported in the global population8,24 and confirm higher

vulnerability of cancer patients to Covid-19 infection. Therapies including conventional

chemotherapy, targeted therapies with small molecules or monoclonal antibodies were

associated with higher mortality rates in this study. Immune checkpoint inhibitor treatment was

associated with a lower rate of infection however, only a small number of patients are in this group

suggesting both caution in interpreting this data and also a need for further focused investigation

in patients receiving ICI therapy and with Covid-19 positivity. The lower mortality rate in patients

receiving this treatment confirms the recent report about the impact of this therapy on Covid-19

outcome.25 Although frequency of Covid-19 infection was not significantly different, higher rates

of mortality were observed in elderly patients (19.5% in patients > 70 y.o.), patients with low

Charlson score, underweight patients and patients with comorbidities, mainly cardio-vascular and

renal disease (Figure 3). While hematological malignancies were associated with higher rates of

infection, similar Covid-19 attributable mortality was observed in comparison to solid

malignancies. Fatality rate related to each cancer type was variable with breast, male genital,



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acute leukemia and thyroid cancer being associated with highest rate of Covid-19 related mortality

(Figure 3).

Our study has several limitations. First, the veteran population is primarily male and hence the

study represents various trends and associations whose interpretations are restricted to male.

Second, patients tested outside the VA system would not be included in this analysis. However,

this number is likely to be very small as most patients who get cancer care in the VA do return for

their healthcare needs to the VA. Third, it is possible that analyses are confounded by indication

for testing. However, we believe that our comparison of those who tested positive to those who

tested negative remains relevant, especially because Covid-19 testing criteria at VA hospitals was

informed by centralized guidance from the VA Central Office, increasing consistency of testing

criteria nationally.27

In conclusion, the presence of cancer changes the susceptibility to Covid-19 infection and affects

overall outcome. The overall disease behavior is modulated by patient-related as well as cancer-

related factors which needs to be considered in development of Covid-19 preventative strategies

as well as modulation of cancer therapies to optimize the patient care. Importantly, having equal

access to care is an important component to improving overall outcome.

Acknowledgements

This work was supported by the VA Office of Research and Development, Cooperative Studies

Program (NRF, NVD, MTB), the VA Merit Review Award 1I01BX001584 (NCM), and NIH grants

P01-155258-07 and P50-100707 (NCM). The views expressed are those of the authors and do

not necessarily reflect the position or policy of the Department of Veterans Affairs or the United

States government.

Disclosure of Conflicts of Interest

NCM is consultant for BMS, Janssen, OncoPep, Amgen, Abbvie and Takeda and on the board of

directors for OncoPep. The remaining authors declare no competing financial interests.



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Figures legends

Figure 1: Covid-19 prevalence among cancer patients.

Percent of Covid-19 positive patients among cancer patients tested for Covid-19, stratified by

demographics, comorbidities, cancer type, and cancer therapy are represented. The dashed line

indicates the overall percent positive (7.8%). The two rows at top show the number of Covid-19

positive patients, and the total number of cancer patients tested. In addition to the percent positive

in each group, a 95% confidence interval and P value are shown. (* = P < .05; ** = P < .01; *** =

P < .001).

Figure 2: Outcome of cancer patients with Covid-19.

Percent of patients experiencing hospitalization, ICU visits, respiratory support, and death in

Covid-19 positive (blue) and negative (red) cancer patients are represented. The Covid-19

attributable risk of experiencing each outcome, i.e., the difference of the percent experiencing

each outcome in Covid-19 positive compared to negative patients is also shown (darker red),

along with 95% confidence intervals.

Figure 3: Covid-19 attributable mortality among cancer patients.

Covid-19 attributable mortality defined as the difference in the percent mortality in Covid-19

positive compared to negative patients, is shown, along with 95% confidence intervals. The

dashed line shows the Covid-19 attributable mortality in the overall cohort (14.4%), and the dotted

line marks 0, the point where there is no Covid-19 attributable mortality. The four rows at top show

the number of Covid-19 positive patients who died, the total number of Covid-19 positive patients,



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the number of Covid-19 negative patients who died, and the total number of Covid-19 negative

patients.

Figure 4: Covid-19 attributable hospitalizations, ICU admissions, and respiratory support

among cancer patients.

Covid-19 attributable hospitalizations, ICU admissions, and respiratory support defined as the

difference in the percent of Covid-19 positive patients experiencing each outcome minus the

percent of Covid-19 negative patients experiencing each outcome are shown. 95% confidence

intervals are shown. The dashed line shows the Covid-19 attributable contribution in the overall

cohort, and the dotted line marks 0, the point where there is no Covid-19 attributable contribution.



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Figure 1. Covid-19 prevalence among cancer patients. Percent of Covid-19 positive patients among cancer patients tested for Covid-19, stratified by demographics, comorbidities, cancer type, and cancer therapy are represented. The dashed line indicates the overall percent positive (7.8%). The two rows at top show the number of Covid-19 positive patients, and the total number of cancer patients tested. In addition to the percent positive in each group, a 95% confidence interval and P value are shown. (* = P < .05; ** = P < .01; *** = P < .001).

A

B



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Figure 2. Outcome of cancer patients with Covid-19. Percent of patients experiencing hospitalization, ICU visits, respiratory support, and death in Covid-19 positive (blue) and negative (red) cancer patients are represented. The Covid-19 attributable risk of experiencing each outcome, i.e., the difference of the percent experiencing each outcome in Covid-19 positive compared to negative patients is also shown (darker red), along with 95% confidence intervals.



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Figure 3. Covid-19 attributable mortality among cancer patients. Covid-19 attributable mortality defined as the difference in the percent mortality in Covid-19 positive compared to negative patients, is shown, along with 95% confidence intervals. The dashed line shows the Covid-19 attributable mortality in the overall cohort (14.4%), and the dotted line marks 0, the point where there is no Covid-19 attributable mortality. The four rows at top show the number of Covid-19 positive patients who died, the total number of Covid-19 positive patients, the number of Covid-19 negative patients who died, and the total number of Covid-19 negative patients.

A

B



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Figure 4. Covid-19 attributable hospitalizations, ICU admissions, and respiratory support among cancer patients. Covid-19 attributable hospitalizations, ICU admissions, and respiratory support, defined as the difference in the percent of Covid-19 positive patients experiencing each outcome minus the percent of Covid-19 negative patients experiencing each outcome are shown. In addition, 95% confidence intervals are shown. The dashed line shows the Covid-19 attributable contribution in the overall cohort, and the dotted line marks 0, the point where there is no Covid-19 attributable contribution.

A

B

B



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Supplement 1 Supplementary Methods Geographical Region The geographical region of the VA hospital each patient was tested in was extracted from structured data, with regions defined using the following mapping from the Corporate Data Warehouse:

• Continental (Arkansas, Colorado, Louisiana, Mississippi, Montana, Oklahoma, Texas, Utah, Wyoming)

• Midwest (Illinois, Indiana, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, Wisconsin)

• North Atlantic (Connecticut, Delaware, District Of Columbia, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, North Carolina, Pennsylvania, Rhode Island, Vermont, Virginia, West Virginia)

• Pacific (Alaska, Arizona, California, Hawaii, Idaho, Nevada, New Mexico, Oregon, Washington)

• Southeast (Alabama, Florida, Georgia, Kentucky, Puerto Rico, South Carolina, Tennessee)



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Supplementary Results eTable 1. Patient characteristics in the full cohort of cancer patients tested for Covid-19, and stratified by patients who were negative or positive for Covid-19.

Overall, n (%) Negative, n (%) Positive, n (%) p n 22914 21120 1794 Age (%) 0.158 <50 1542 ( 6.7) 1416 ( 6.7) 126 ( 7.0) 50-59 2506 (10.9) 2307 (10.9) 199 (11.1) 60-64 2691 (11.7) 2480 (11.7) 211 (11.8) 65-69 3335 (14.6) 3108 (14.7) 227 (12.7) 70-79 8714 (38.0) 8035 (38.0) 679 (37.8) >=80 4126 (18.0) 3774 (17.9) 352 (19.6) Race (%) <0.001 White 15856 (69.2) 14986 (71.0) 870 (48.5) Black 5430 (23.7) 4618 (21.9) 812 (45.3) Other or Unknown 1628 ( 7.1) 1516 ( 7.2) 112 ( 6.2) Ethnicity (%) <0.001 Not Hispanic or Latino 20942 (91.4) 19327 (91.5) 1615 (90.0) Hispanic or Latino 1288 ( 5.6) 1148 ( 5.4) 140 ( 7.8) Unknown 684 ( 3.0) 645 ( 3.1) 39 ( 2.2) Smoking (%) <0.001 Current 8589 (37.5) 8137 (38.5) 452 (25.2) Former 9315 (40.7) 8416 (39.8) 899 (50.1) Never 3549 (15.5) 3227 (15.3) 322 (17.9) Unknown 1461 ( 6.4) 1340 ( 6.3) 121 ( 6.7) BMI (%) <0.001 Underweight 603 ( 2.6) 564 ( 2.7) 39 ( 2.2) Normal 5189 (22.6) 4864 (23.0) 325 (18.1) Overweight 7124 (31.1) 6573 (31.1) 551 (30.7) Obese 9824 (42.9) 8956 (42.4) 868 (48.4) Unknown 174 ( 0.8) 163 ( 0.8) 11 ( 0.6) Charlson (%) <0.001 0 2962 (12.9) 2692 (12.7) 270 (15.1) 1-2 8215 (35.9) 7512 (35.6) 703 (39.2) 3-4 6544 (28.6) 6085 (28.8) 459 (25.6) >=5 5193 (22.7) 4831 (22.9) 362 (20.2) AMI 2231 ( 9.7) 2079 ( 9.8) 152 ( 8.5) 0.066



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CHF 5632 (24.6) 5256 (24.9) 376 (21.0) <0.001 PVD 4808 (21.0) 4495 (21.3) 313 (17.4) <0.001 COPD 8889 (38.8) 8332 (39.5) 557 (31.0) <0.001 MLD 2976 (13.0) 2757 (13.1) 219 (12.2) 0.323 DIAB 8949 (39.1) 8226 (38.9) 723 (40.3) 0.271 DIABWC 5999 (26.2) 5543 (26.2) 456 (25.4) 0.461 REND 5876 (25.6) 5382 (25.5) 494 (27.5) 0.060 MSLD 544 ( 2.4) 516 ( 2.4) 28 ( 1.6) 0.023 Treatment Time (%) 0.002 Never Treated 16396 (71.6) 15063 (71.3) 1333 (74.3) Treated <= 6 Months Ago 3034 (13.2) 2845 (13.5) 189 (10.5) Treated > 6 Months Ago 3484 (15.2) 3212 (15.2) 272 (15.2) Esophagus 331 ( 1.4) 320 ( 1.5) 11 ( 0.6) 0.003 HCC 1092 ( 4.8) 1046 ( 5.0) 46 ( 2.6) <0.001 Lung 2806 (12.2) 2685 (12.7) 121 ( 6.7) <0.001 CSCC 1188 ( 5.2) 1132 ( 5.4) 56 ( 3.1) <0.001 Other Gastrointestinal 353 ( 1.5) 336 ( 1.6) 17 ( 0.9) 0.043 Pancreas 331 ( 1.4) 315 ( 1.5) 16 ( 0.9) 0.052 Brain 522 ( 2.3) 495 ( 2.3) 27 ( 1.5) 0.028 Lymphoma 2370 (10.3) 2247 (10.6) 123 ( 6.9) <0.001 Acute Leukemia 288 ( 1.3) 273 ( 1.3) 15 ( 0.8) 0.120 SCCHN 2209 ( 9.6) 2087 ( 9.9) 122 ( 6.8) <0.001 Melanoma 902 ( 3.9) 851 ( 4.0) 51 ( 2.8) 0.016 Neuroendocrine 344 ( 1.5) 324 ( 1.5) 20 ( 1.1) 0.193 Bone 2251 ( 9.8) 2110 (10.0) 141 ( 7.9) 0.004 Breast 462 ( 2.0) 433 ( 2.1) 29 ( 1.6) 0.243 Gastric 698 ( 3.0) 654 ( 3.1) 44 ( 2.5) 0.146 Connective and Soft Tissue 470 ( 2.1) 440 ( 2.1) 30 ( 1.7) 0.275 Hodgkin 202 ( 0.9) 189 ( 0.9) 13 ( 0.7) 0.542 Urothelial 2198 ( 9.6) 2056 ( 9.7) 142 ( 7.9) 0.013 Ill Defined Site 2397 (10.5) 2238 (10.6) 159 ( 8.9) 0.024 Thyroid 275 ( 1.2) 256 ( 1.2) 19 ( 1.1) 0.647 Rectum 405 ( 1.8) 377 ( 1.8) 28 ( 1.6) 0.549 Skin 8961 (39.1) 8331 (39.4) 630 (35.1) <0.001 RCC 1245 ( 5.4) 1151 ( 5.4) 94 ( 5.2) 0.747 Chronic Leukemia 504 ( 2.2) 465 ( 2.2) 39 ( 2.2) 1.000 Myeloid Malignancy 1210 ( 5.3) 1116 ( 5.3) 94 ( 5.2) 0.979 Endocrine Glands 949 ( 4.1) 872 ( 4.1) 77 ( 4.3) 0.786 Colon 1299 ( 5.7) 1188 ( 5.6) 111 ( 6.2) 0.349



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MDS 374 ( 1.6) 342 ( 1.6) 32 ( 1.8) 0.667 Multiple Myeloma 1081 ( 4.7) 980 ( 4.6) 101 ( 5.6) 0.066 Male Genital 341 ( 1.5) 309 ( 1.5) 32 ( 1.8) 0.329 Prostate 4910 (21.4) 4417 (20.9) 493 (27.5) <0.001



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eTable 2. Odds ratio (OR) as to Covid-19 positive status by cancer type, in univariate logistic regression analysis and multivariate logistic regression, adjusting for race, ethnicity and smoking status. In addition to the odds ratio, the 95% confidence interval (lower, upper) and p value is shown.

Multivariate Analysis Univariate Analysis Cancer Type OR Lower Upper P OR Lower Upper P

Esophagus 0.484 0.264 0.888 0.019 0.401 0.22 0.733 0.003 HCC 0.5 0.37 0.677 <0.001 0.505 0.374 0.681 <0.001 Lung 0.546 0.451 0.661 <0.001 0.497 0.411 0.6 <0.001 CSCC 0.759 0.575 1 0.05 0.569 0.433 0.747 <0.001 Other Gastrointestinal 0.574 0.35 0.942 0.028 0.592 0.363 0.966 0.036 Pancreas 0.574 0.345 0.955 0.033 0.594 0.359 0.984 0.043 Brain 0.661 0.445 0.982 0.04 0.637 0.431 0.941 0.023 Lymphoma 0.638 0.528 0.772 <0.001 0.618 0.512 0.746 <0.001 Acute Leukemia 0.59 0.348 1 0.05 0.644 0.382 1.085 0.098 SCCHN 0.734 0.606 0.89 0.002 0.665 0.551 0.804 <0.001 Melanoma 0.969 0.724 1.296 0.832 0.697 0.523 0.928 0.014 Neuroendocrine 0.731 0.461 1.158 0.181 0.724 0.459 1.14 0.163 Bone 0.816 0.681 0.977 0.027 0.769 0.643 0.918 0.004 Breast 0.674 0.459 0.991 0.045 0.785 0.537 1.147 0.211 Gastric 0.794 0.58 1.087 0.15 0.787 0.578 1.072 0.128 Connective and Soft Tissue 0.769 0.527 1.123 0.174 0.799 0.55 1.161 0.239 Hodgkin 0.896 0.506 1.587 0.707 0.808 0.46 1.421 0.46 Urothelial 0.83 0.693 0.994 0.043 0.797 0.668 0.952 0.012 Ill Defined Site 0.836 0.705 0.993 0.041 0.82 0.693 0.971 0.021 Thyroid 0.858 0.534 1.38 0.528 0.872 0.546 1.394 0.568 Rectum 0.891 0.602 1.319 0.563 0.872 0.592 1.285 0.489 Skin 1.125 1.01 1.253 0.032 0.831 0.751 0.919 <0.001 RCC 0.875 0.702 1.09 0.232 0.959 0.773 1.191 0.706 Chronic Leukemia 1.009 0.721 1.411 0.96 0.987 0.709 1.374 0.939 Myeloid Malignancy 1.034 0.83 1.289 0.763 0.991 0.798 1.23 0.936 Endocrine Glands 0.941 0.738 1.2 0.625 1.041 0.821 1.321 0.739 Colon 1.058 0.862 1.298 0.591 1.107 0.905 1.353 0.323 MDS 1.024 0.705 1.486 0.901 1.103 0.766 1.59 0.598 Multiple Myeloma 0.981 0.791 1.217 0.86 1.226 0.993 1.514 0.058 Male Genital 1.185 0.815 1.725 0.374 1.223 0.847 1.766 0.282



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Prostate 1.089 0.972 1.219 0.141 1.433 1.285 1.598 <0.001



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eTable 3. Outcomes by Race and Covid-19 Result

Outcome in Covid-19 Negative patients

n (%)

Outcome in Covid-19 Positive patients

n (%)

Covid-19 attributable outcome %

Ratio of Covid-19

attributable outcome in AA/White White AA White AA White AA

Hospitalization 4835 (32.3) 1365 (29.6) 332 (38.2) 410 (50.5) 5.9 20.9 3.5 ICU 1204 (8.0) 350 (7.6) 159 (18.3) 173 (21.3) 10.3 13.7 1.3 Respiratory Support 191 (1.3) 60 (1.3) 63 (7.2) 72 ( 8.9) 5.9 7.6 1.3 Death 482 (3.2) 129 (2.8) 122 (14.0) 120 (14.8) 10.8 12 1.1



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eTable 4. Outcomes by Ethnicity and Covid-19 Result

Outcome in Covid-19 Negative patients

n (%)

Outcome in Covid-19 Positive patients

n (%) Covid-19 attributable

outcome %

Ratio of Covid-19 attributable

outcome in Hispanic or Latino/Not Hispanic or

Latino Not Hispanic or Latino

Hispanic or Latino

Not Hispanic or Latino

Hispanic or Latino

Not Hispanic or Latino

Hispanic or Latino

Hospitalization 6123 (31.7) 324 (28.2) 715 (44.3) 54 (38.6) 12.6 10.4 0.8 ICU 1518 ( 7.9) 86 ( 7.5) 322 (19.9) 24 (17.1) 12 9.6 0.8 Respiratory Support 244 ( 1.3) 20 ( 1.7) 133 ( 8.2) 7 ( 5.0) 6.9 3.3 0.5 Death 604 ( 3.1) 34 ( 3.0) 237 (14.7) 13 ( 9.3) 11.6 6.3 0.5



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eTable 5. Outcomes by Tumor Type and Covid-19 Result

Outcome in Covid-19 Negative patients n (%)

Outcome in Covid-19 Positive patients n (%)

Covid-19 attributable outcome %

Solid Heme Solid and Heme Solid Heme

Solid and Heme Solid Heme

Solid and Heme

17610 1439 2071 1484 176 134

Hospitalization 5211 (29.6) 548 (38.1) 886 (42.8) 626 (42.2) 95 (54.0) 65 (48.5) 12.6 15.9 5.7 ICU 1283 (7.3) 135 (9.4) 237 (11.4) 283 (19.1) 43 (24.4) 27 (20.1) 11.8 15 8.7 Respiratory Support 206 (1.2) 23 (1.6) 41 (2.0) 117 ( 7.9) 19 (10.8) 6 (4.5) 6.7 9.2 2.5 Death 520 (3.0) 45 (3.1) 98 (4.7) 200 (13.5) 30 (17.0) 21 (15.7) 10.5 13.9 11



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eTable 6. Regional data on Covid-19 prevalence and race. Higher prevalence is observed in black patients across all regions.

Demographics of Cancer Patients Tested for Covid-19 across Regions Region Overall, n Black, n (% of Overall) White, n (% of Overall) Continental 3525 826 (23.43%) 2418 (68.6%) Midwest 4581 1076 (23.49%) 3267 (71.32%) North Atlantic 5768 1778 (30.83%) 3736 (64.77%) Pacific 4464 627 (14.05%) 3222 (72.18%) Southeast 4576 1123 (24.54%) 3213 (70.21%) All Regions 22914 5430 (23.7%) 15856 (69.2%)

Prevalence of Covid-19 across Regions Region % Positive in Overall % Positive in Black % Positive in White Continental 7.06 15.25 4.30 Midwest 8.64 19.42 5.17 North Atlantic 14.77 20.70 11.51 Pacific 2.82 3.35 2.79 Southeast 3.74 7.84 2.40 All Regions 7.83 14.95 5.49



https://doi.org/10.1101/2020.08.21.20177923

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