US -Death Trends for Neoplasms ICD codes: C00-D48, Ages 15-44

Abstract

In this study we investigate trends in death rates from neoplasms (ICD-10 codes C00-D48) in the USA using crude data from the CDC (Centers for Disease Control and Prevention). We limit our investigation to individuals aged 15 to 44 and for the period of 2010 to 2022. We investigate both trends in neoplasms where these appear on multiple causes (MC) of death, or as the underlying cause (UC), as well as the trends in the ratio of multiple cause to underlying cause death rates. Using different metrics, we compare mortality trends due to neoplasms before the COVID-19 pandemic with the pandemic period. We show a rise in excess mortality from neoplasms reported as underlying cause of death, which started in 2020 (1.7%) and accelerated substantially in 2021 (5.6%) and 2022 (7.9%). The increase in excess mortality in both 2021 (Z-score of 11.8) and 2022 (Z-score of 16.5) are highly statistically significant (extreme events). When looking at neoplasm death reported as one of multiple cause of death, we observe a similar trend with excess mortality of 3.3% (Z-score of 5.1) in 2020, 7.9% (Z-score of 12.1) in 2021, and 9.8% (Z-score of 15.0) in 2022, which were also highly statistically significant. The results indicate that from 2021 a novel phenomenon leading to increased neoplasm deaths appears to be present in individuals aged 15 to 44 in the US. The greater rise in deaths due to neoplasms in multiple causes compared to underlying cause indicates that some deaths from neoplasms are being brought forward by other causes. The rise in cancer-death rates as underlying cause might be the result of an unexpected rise in the incidence of rapidly growing fatal cancers and/or a reduction in survival in existing cancer cases. Further stratification is underway, for example by age and cancer type to understand these trends and their relationship to pandemic related factors such as access to or utilization of cancer screening and treatment, changes in health-related behaviors such as exercise or smoking, exposure to COVID-19 disease or COVID-19 vaccines.

Full text

US - Death Trends for Neoplasms ICD codes:
C00-D48, Ages 15-44
C. Alegria 1,∗and D. Wiseman 2and Y. Nunes 1,3
1RiskMath Lda.*
, Portugal
2Synechion, Inc.†
, Dallas, TX, USA
3LibPhys‡
, Department of Physics, FCT-NOVA, Portugal
Correspondence*:
Corresponding Author
calegria@phinancetech.com
ABSTRACT
In this study we investigate trends in death rates from neoplasms (ICD-10 codes C00-D48) in
the USA using crude data from the CDC (Centers for Disease Control and Prevention). We limit
our investigation to individuals aged 15 to 44 and for the period of 2010 to 2022. We investigate
both trends in neoplasms where these appear on multiple causes (MC) of death, or as the
underlying cause (UC), as well as the trends in the ratio of multiple cause to underlying cause
death rates. Using different metrics, we compare mortality trends due to neoplasms before the
COVID-19 pandemic with the pandemic period.
We show a rise in excess mortality from neoplasms reported as underlying cause of death,
which started in 2020 (1.7%) and accelerated substantially in 2021 (5.6%) and 2022 (7.9%).
The increase in excess mortality in both 2021 (
Z
-score of 11.8) and 2022 (
Z
-score of 16.5) are
highly statistically significant (extreme events). When looking at neoplasm death reported as one
of multiple cause of death, we observe a similar trend with excess mortality of 3.3% (
Z
-score
of 5.1) in 2020, 7.9% (
Z
-score of 12.1) in 2021, and 9.8% (
Z
-score of 15.0) in 2022, which
were also highly statistically significant. The results indicate that from 2021 a novel phenomenon
leading to increased neoplasm deaths appears to be present in individuals aged 15 to 44 in the
US. The greater rise in deaths due to neoplasms in multiple causes compared to underlying
cause indicates that some deaths from neoplasms are being brought forward by other causes.
The rise in cancer-death rates as underlying cause might be the result of an unexpected rise in
the incidence of rapidly growing fatal cancers and/or a reduction in survival in existing cancer
cases. Further stratification is underway, for example by age and cancer type to understand
these trends and their relationship to pandemic related factors such as access to or utilization
of cancer screening and treatment, changes in health-related behaviors such as exercise or
smoking, exposure to COVID-19 disease or COVID-19 vaccines.
Keywords: neoplasms, excess mortality, mortality trends
*Phinance Technologies - Humanity Projects
†Synechion, Inc.
‡LibPhys
1

US - Death Trends for Neoplasms ICD codes: C00-D48, Ages 15-44
1 INTRODUCTION
Beginning in early 2020, the world changed due
to the emergence of a global pandemic caused
by the SARS-CoV-2 virus which, in some indi-
viduals, manifested in the form of COVID-19
disease. A short-term increase in mortality rates
was anticipated due to the impact of this novel virus.
However, excess mortality has continued in many
countries despite milder variants of the virus being
in circulation, and the introduction of COVID-19
vaccination programmes. For example, CDC’s data
tracker
1
shows peaks of COVID-19 ascribed deaths
in September 2021 and January 2022 with smaller
peaks in August 2022, and January and September
2023. Various possible explanations have been pro-
posed for this, including lasting effects of the virus,
lockdowns and the resulting impact on healthcare
delivery and adverse effects of COVID-19 vaccines,
some of which are based on newly-implemented
viral vector DNA or mRNA technology. In this
context, we have performed several analyses sho-
wing excess mortality (all cause) since 2020, from
Europe to the USA
2
. We published a methodology
report to explain our estimates for excess mortality,
which is based on determining excess death rates
instead of excess deaths (Alegria, et al., 2024)[
1
].
By accurately estimating, and then tracking excess
mortality trends, we can have a clearer picture
of the implications of the different stages of the
COVID-19 pandemic, as mentioned above.
After the all-cause mortality trends were under-
stood, our research efforts focused on changes in
death rates for particular causes of death, focu-
sing on cancer given the emergence of anecdotal
reports of unusually aggressive cancers, particularly
in younger individuals. There have been several
case reports of rapidly growing malignant neo-
plasms in humans following COVID-19 vaccine
administration. Such examples include cases of
haematologic malignancies following administra-
tion of the mRNA COVID-19 vaccine produced by
Pfizer-BioNTech: A diffuse large B-cell lymphoma
1COVID Data Tracker
2Phinance Technologies - Humanity Projects - Excess Mortality Project
and NK/T-cell lymphoma (Zamfir, et al., 2022)[
2
];
and B-cell (Sekizawa, et al., 2022)[
3
] (Mizutani, et
al., 2022)[
4
] and T cell (Goldman, et al., 2021)[
5
]
lymphomas.
There is a report of a subcutaneous panniculitis-
like T-cell lymphoma following an adenovirus type
26 (Ad26) viral vector–based COVID-19 vaccina-
tion produced by Janssen Pharmaceuticals (Kreher,
et al., 2022)[
6
]. Lastly, there is a case report of
B-cell lymphoblastic lymphoma occurring after
injection of the Pfizer COVID-19 vaccine in one
of 14 mice that were part of a study to establish a
model of vaccine-induced myocarditis (Eens, et al.,
2023)[7].
Evidence of a possible relationship between the
novel COVID-19 vaccinations and the development
of malignant neoplasms is not available in the form
of population-based studies where vaccinated and
unvaccinated individuals are compared. However,
reports of cancers following the COVID-19 vacci-
nations made to CDC’s VAERS
3
were found to
be more numerous than for all previous vaccines
combined since 1990 (Section 4.10 in Wiseman et
al.)[8].
Additionally, CDC’s Disproportionality Signal
Analysis using the Proportional Reporting Ratio
(PRR) method conducted in July 2022 disclosed
under the Freedom of Information Act. shows safety
signals for cancers in 11 MedDRA codes (Wiseman,
et al., 2023)[
8
]. As far as we know, an analysis of
this signal has not been published by CDC or FDA.
The possibility of an association between excess
cancers and the SARS-Cov2 virus itself must also
be considered based on work showing that SARS-
Cov2 viral RNA can be reverse transcribed with
genomic integration (Zhang, et al., 2021)[
9
] and
(Zhang, et al., 2023)[10].
There may also have been adverse consequences
of the COVID-19 pandemic on cancer rates due
to delays in diagnosis and treatment (Siegel, et al,
2022)[11].
3Vaccine Adverse Events Recording System
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US - Death Trends for Neoplasms ICD codes: C00-D48, Ages 15-44
These effects may have persisted at least into 2021
(Siegel, et al, 2023)[12].
The COVID-19 pandemic may have resulted in
changes in health-related behaviors with consequ-
ences on all-cause and cancer mortality, including
physical activity and cigarette smoking (Tseng, et
al., 2021)[
13
] (Almeda, et al., 2022)[
14
] (Gaffney,
et al., 2022)[15].
The aggregate effects of the COVID-19 pandemic
on mortality rates in general, and cancer deaths
rates in particular may not be fully appreciated for
several years. (Siegel, et al, 2023)[12].
In a previous study (Alegria, et al., 2024)[
1
] of
15-44 year olds in England and Wales we observed
increases in all-cause mortality in 2020-2022 and
cancer-associated mortality in 2021 and 2022. In
the present study we investigate if the USA has simi-
lar trends. The analysis of US cause of death data
provides further clarity in corroborating and under-
standing the phenomenon of rising cancer deaths.
In particular, the US data does not have the same
problems of missing datapoints in 2021 and 2022,
as we noticed in the UK data. Also, the US data pro-
vides the opportunity to analyze trends in cancers
both as the underlying cause of death, or as con-
tributing causes of death. Lastly, as the US has a
population that is about 6 times larger than the UK,
statistically significant signals are easier to identify.
Cancers tend to be slowly-developing diseases
with remarkably stable death rates and only small
variations over time. This makes any temporal asso-
ciation between a possible explanatory factor (such
as COVID-19, the novel COVID-19 vaccines, or
other factor) difficult to establish. However, the pur-
pose of this paper is not to explain the mechanisms
behind the rise in cancer-related deaths. Rather, our
work provides a statistical analysis at a population
level, which offers insight for health professionals
regarding current trends in population health, and
raises questions for further investigation.
2 DATA
2.1 Cause of Death Data
In this study we analyzed the number of dea-
ths that occurred in the USA between 2010 and
2022, by underlying cause code (ICD-10), sex, and
10-year age groups, obtained using the CDC WON-
DER system (National Center for Health Statistics
of the Centers for Disease Control and Prevention
- CDC)
4
. The mortality data is final up to 2021 but
provisional from 2022 onwards. Additionally, for
comparing multiple cause (MC)
5
of death trends
from neoplasms with underlying cause (UC)
6
of
death trends, we downloaded data from both the
multiple cause of death databases and underlying
cause of death databases.
Query parameters:
For underlying cause of death data, select variable
grouped by: 1. Ten-year-age-groups, 2. Gender, 3.
Year, 4. UCD – ICD Chapter
(Link to the underlying cause of death databases)
.
For multiple cause of death data, select variable
grouped by: 1. Ten-year-age-groups, 2. Gender, 3.
Year, 4. MCD – ICD Chapter
(Link to the multiple cause of death databases)
2.2 Definition of MC of Death and UC of
Death
The Centers for Disease Control and Prevention
(CDC) classifies deaths based on cause into two
primary categories: ”Underlying Cause of Death”
and ”Multiple Causes of Death.” The definitions
are:
Underlying Cause (UC) of Death: The underl-
ying cause of death is defined as ”the disease or
injury which initiated the train of morbid events
leading directly to death, or the circumstances of
the accident or violence which produced the fatal
4CDC Wonder
5CDC Wonder Multiple Cause of Death 1999 - 2020
6CDC Wonder Underliyng Cause of Death 1999 - 2020
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US - Death Trends for Neoplasms ICD codes: C00-D48, Ages 15-44
injury,” according to the World Health Organization
(WHO).
Multiple Causes (MC) of Death: Multiple causes
of death include all causes and conditions reported
on the death certificate that contributed to death,
not just the underlying cause. This includes the
underlying cause, immediate cause, and any other
significant conditions contributing to death. Each
death certificate contains a single underlying cause
of death, and up to twenty additional multiple
causes.
2.3 Data Use Restrictions
In this research paper we abide by the CDC’s
restrictions on data use which are7:
“The Public Health Service Act (42 U.S.C. 242m(d))
provides that the data collected by the National Cen-
ter for Health Statistics (NCHS) may be used only
for the purpose for which they were obtained; any
effort to determine the identity of any reported cases,
or to use the information for any purpose other
than for health statistical reporting and analysis, is
against the law. Therefore, users will:
•
Use these data for health statistical reporting
and analysis only.
•
Do not present or publish death counts of 9 or
fewer or death rates based on counts of nine or
fewer (in figures, graphs, maps, tables, etc.).
•
Make no attempt to learn the identity of any
person or establishment included in these data.
•
Make no disclosure or other use of the identity
of any person or establishment discovered ina-
dvertently and advise the NCHS Confidentiality
Officer of any such discovery.”
2.4 Population data
Crude death rate (deaths per 100,000) were obtai-
ned by selecting the “crude rates” option on the
WONDER interface that uses CDC’s estimates of
7CDC Wonder - Data Use Restrictions
population data. We chose to use the CDC popula-
tion data instead of data from the US Census Bureau
for consistency with other researchers’ analyses.
2.5 All-cause deaths data
All cause deaths were retrieved from CDC WON-
DER, by using the following query parameters:
1.Ten-year-age-groups, 2. Gender, 3. Year
2.6 Data verification and limitations
The CDC WONDER system provides two sepa-
rate databases from which to query underlying
cause of death data and multiple cause of death
data. Additionally, each is separated into two data-
sets comprising of different time periods, so that
in order to obtain time series from 2010 to 2022,
multiple queries were performed.
Within the multiple cause of death databases, it is
also possible to obtain the underlying cause of death
data. We downloaded all the available yearly data
(for MC of death and UC of death) and compared
the different datasets for consistency, whenever the
time periods overlapped.
From 2010 to 2021 the MC and UC of death data
is final while for 2022 it is provisional. The data for
2023 was not used as apart from being provisional
it was also incomplete. Details on provisional CDC
deaths data can be found here.8
3 METHODOLOGY
In this study, we analyze the trends in death rates for
neoplasms (both malignant and benign). We investi-
gate these trends using yearly data and therefore a
seasonal adjustment to the data is unnecessary.
In general terms, to estimate trends in these vari-
ables we use a methodology of computing excess
rates, which is the difference between the actual
observed rates and a given baseline (expected rates).
Because we want to describe the impact of the
COVID-19 pandemic and post-pandemic periods
relative to the prior state of the world, our baselines
8CDC Wonder Technical Notes for Provisional Mortality
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US - Death Trends for Neoplasms ICD codes: C00-D48, Ages 15-44
are based upon the estimation of the trend for the
period prior to the pandemic.
In this study we will use method 2C, as descri-
bed in our report on methodologies for measuring
excess deaths in the population (Alegria, et al.,
2024)[
16
]. Method 2C is based on computing the
trends in death rates (deaths adjusted by the popula-
tion) instead of deaths, as the baseline for estimating
excess mortality. This method significantly reduces
the noise of the estimation as it adjusts for popu-
lation growth or decline, and by also providing
different rates for each age category, we adjust for
changes in population age distribution. The method
also considers the prior trend in death rates, which
tends to decline over time as the population grows
healthier and risk factors are better managed.
3.1 Method 2C for Estimating Excess
Death Rates
Excess
DeathsAG
ti
=DeathsAG
ti
−BaselineAG
ti(1)
Equation 1 is a general expression for estimating
the excess absence rates relative to a given base-
line. We use the superscript
AG
to indicate a given
population age range, as this is the primary focus
of the current analysis. Other cohorts which this
equation could apply to include a specific region,
sex, or underlying cause of death. The subscript
ti
refers to time, that is, the corresponding year for
which the excess deaths are computed.
For estimating the baseline for “normal or expe-
cted” death rates we use a simple linear fit:
Baseline(ti) = ˆ
b+ ˆa(ti−t0)(2)
Where
ˆa
and
ˆ
b
are the estimated coefficients of
the death rate trendline from 2010 to 2019. We also
compute a
Z
-score that estimates the normalized
deviation from trend:
Z=hDeathsiAG
ti
−hBaselineiAG
ti
σ2010−2019
(3)
Where
σ
is the standard deviation of the excess
deaths during the pre-pandemic period 2010-2019.
3.2 ICD-10 Code List of Selected Causes
of Death for: Neoplasms
For this analysis we selected all the ICD-10 codes
from the CDC aggregated chapter lists (Letters C00
to D48), of which C00 to C99 refer to deaths attri-
buted to malignant neoplasms and D00 to D48 refer
to benign neoplasms.
4 YEARLY ANALYSIS OF EXCESS
DEATH RATES
In this section we analyzed the trend in yearly death
rates for individuals aged 15 to 44 in the USA. In
this analysis we use the 2010-2019 trend in deaths
per 100,000 (death rates) as the baseline estimate for
excess death rates. Excess death rates for the 2010-
2019 period are in-sample while the rates for 2020,
2021, and 2022 are out of sample computations.
4.1 Deaths from All Causes
The analysis of deaths from all causes allows us
to have a context by which we can then compare the
death rates from neoplasms. Figure 1 (top) shows
the death rate per 100,000 individuals for all deaths
in the US from 2010 to 2022, for the 15 to 44 age
group. Figure 1 (bottom) shows the actual number
of deaths during the period.
We note two differences in these US data compa-
red with those we found from England and Wales[
1
].
Firstly, the all-cause death rate for this relatively
young age group is substantially higher in the US
data. The all-cause death rate for the US was about
130 deaths per 100,000 in 2019, while for the
England and Wales it was about 67 deaths per
100,000. Secondly, all-cause death rates had been
trending higher from 2010 to 2019, compared with
the downward trend in the data from England and
Wales. While investigating these differences is not
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US - Death Trends for Neoplasms ICD codes: C00-D48, Ages 15-44
the topic of this paper, we believe they merit further
investigation.
Figure 1. Yearly registered deaths per 100,000 for
the US for individuals aged 15 to 44. The red dashed
line shows the average from 2010 to 2019. The
dotted line shows the extrapolation of the trend from
2020 until 2022. Top: Deaths per 100,000. Bottom:
Deaths (Number)
In 2019, the all-cause death rate was about 130
per 100,000 individuals and increased in 2020 to
about 162 per 100,000 in 2020 and again in 185 per
100,000 in 2021. In 2022 the death rate dropped
slightly to about 170 per 100,000.
4.1.1 Excess all-cause death rates
Figure 2 shows the excess death rate for all-cause
deaths in the USA from 2010 to 2022. Figure 2 (top)
refers to relative deviations from the 2010-2019
trend, while Figure 2 (bottom) shows the
Z
-score
(signal strength) for the deviations from trend.
Figure 2 shows that excess deaths in 2020 were
19.9%, with a
Z
-score of 6.5 which is a high level
of statistical significance. In 2021 excess deaths
jumped to 33.8% with a
Z
-score above 11.0 indica-
ting very high statistical significance. Excess deaths
in 2022 remained abnormally high at 18.2% with
a
Z
-score of 5.9 indicating very high statistical
significance.
Figure 2. Excess all-cause death rates for both
sexes with ages 15 to 44 in the USA. Top: Relative
deviation from trend, percent. Bottom: Deviation
from trend Z-Score.
4.2 Trends in UC Death Rates for ICD-10
codes C00 to D48 (Neoplasms)
In this section we investigate the trends in death
rates from 2010 to 2022 where neoplasms (ICD-10
codes C00 to D48) were classified as the underlying
cause of death, for the 15-44 age group of both
sexes.
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US - Death Trends for Neoplasms ICD codes: C00-D48, Ages 15-44
4.2.1 UC Death Rates
Figure 3 (top) shows that the death rate per
100,000 individuals for neoplasm deaths as underl-
ying cause in the US trended significantly downw-
ards with a reduction of 12.1% from 14 per 100,000
in 2010 to around 12.3 per 100,000 in 2019.
Figure 3. Yearly deaths from neoplasms as underl-
ying cause in the US. The red dashed line shows
the average from 2010 to 2019. The dotted line
shows the extrapolation of the trend from 2020 until
2022. Top: Deaths per 100,000. Bottom: Deaths
(Number).
The death rate dropped slightly in 2020 to about
12.2 per 100,000 and then rose to 12.6 per 100,000
in 2021 and again to about 12.7 per 100,000, similar
to that observed in 2017.
The absolute numbers of deaths with neoplasms
as underlying cause (Figure 3 bottom), were about
16,000 in both 2019 and 2020 rising to about 16,580
16,670 deaths in 2021 and 2022 respectively.
4.2.2 Excess UC Death Rates
Figure 4 shows the excess death rates for neopla-
sms as underlying cause in the USA, for the 15 to
44 age group from 2010 to 2022 with the excess
all-cause deaths (from Figure 2) for comparison.
The upper figure refers to relative deviations from
the 2010-2019 trend, while the lower figure shows
the
Z
-score (signal strength) for the deviations from
trend.
Figure 4. Excess UC death rates from neopla-
sms from 2010 to 2022 for both sexes of ages 15
to 44 in the USA. Top: Relative deviation from
trend, percent. Bottom: Deviation from trend
Z
-
Score. Excess deaths from all causes are shown for
comparison.
The excess death rates from neoplasms as the
underlying cause were 1.7% in 2020, rose to 5.6%
in 2021, and 7.9% in 2022. By comparison, the
excess all-cause mortality was 19.9% in 2020,
33.8% in 2021, and 18.2% in 2022. Noteworthy
is that the drop in all-cause excess mortality from
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US - Death Trends for Neoplasms ICD codes: C00-D48, Ages 15-44
2021 to 2022 was not mirrored in a drop in neo-
plasm deaths. In fact, the opposite occurred, with
an increase in excess deaths due to neoplasms as
the underlying cause.
In terms of statistical significance of the excess
deaths, we observe from Figure 4 (bottom) that the
Z
-score in 2020 was 6.5, which is a very strong
signal. In 2021, the
Z
-score was 11.0 which is an
extreme signal. In 2022 the
Z
-score dropped to
5.9, which still indicates that the excess deaths are
a statistically significant deviation from the 2010-
2019 trend.
When looking at excess deaths from neoplasms,
while the excess death rate from neoplasms as the
underlying cause was only 1.7% in 2020, the
Z
-
score was 3.5 which increased substantially in 2021
and 2022 where we observe
Z
-scores of 11.8 and
16.5, respectively. These are extreme events that we
believe require thorough investigation. The investi-
gation of trends in cancer rates in individuals aged
15 to 44 from the UK (Alegria, et al., 2024)[
1
],
showed much larger deviations from trend in 2021
and 2022, albeit with similar levels of statistical
significance as those found in the US data. (The
US population is about 6 times larger than the UK
population, which provides a much larger sample
size. Consequently, a smaller deviation from trend
can produce a similar level of statistical significa-
nce.) Additionally, the larger increments in death
rates from cancers in the UK are more uncertain
estimates as they are based upon incomplete data-
sets where deaths are adjusted using the assumption
of proportional deaths for the missing data points.
This makes the corroboration of increased death
rates from neoplasms in the US data of particular
interest.
4.3 Trends in Multiple Cause Death Rates
and Excess Deaths for ICD-10 Codes
C00 to D48 (Neoplasms)
In this section we investigate the trends in death
rates and excess deaths from 2010 to 2022 where
neoplasms are reported as one of the multiple causes
of death (either underlying or secondary cause of
death), for the 15-44 age group of both sexes.
4.3.1 Deaths MC (Multiple Cause) from
ICD-10 Codes C00 to D48
(Neoplasms)
In this section we analyze the trends in MC death
rates from neoplasms where they were either the
underlying cause of death or were recorded as a
secondary cause of death. This analysis provides
additional information in understanding the pheno-
menon of increased deaths from cancer during the
pandemic years, for this age group.
Figure 5 (top) shows the death rate per 100,000
individuals aged 15 to 44, from neoplasms deaths
in the US from 2010 to 2022, where neoplasms
are listed as one of multiple causes of death (either
underlying or contributing). We can observe that
MC deaths per year from neoplasms trended lower
from 2010 to 2019, with a significant downward
slope. In 2010 the death rate was 14.5 per 100,000
and in 2019 it was around 13.1 per 100,000, a 9.65%
drop.
The death rate rose slightly in 2020 to 13.2 per
100,000 and then rose to 13.7 per 100,000 in 2021
where it remained steady in 2022 at a level similar
to that observed in 2014.
4.3.2 Excess MC Death Rates
As previously mentioned, MC deaths rates need
to be taken with caution as they refer to death rates
for a given disease where it is either the underlying
cause or a contributing factor towards death. Some
diseases, such as respiratory diseases, are mostly
attributed as contributing factors for death while
other causes are the underlying cause. This means
that MC death rates from respiratory diseases could
amount to several times the UC death rate. On the
other hand, by analyzing both MC death rates and
UC death rates, we can have a better understanding
of the underlying phenomena that lead to death.
When excess death rates are computed (either MC
death rates or UC cause death rates), they adjust
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US - Death Trends for Neoplasms ICD codes: C00-D48, Ages 15-44
Figure 5. Yearly deaths from neoplasms as one of
multiple causes (underlying or contributing factor)
in the USA. The red dashed line shows the average
from 2010 to 2019. The dotted line shows the extra-
polation of the trend from 2020 until 2022. Top:
Deaths per 100,000. Bottom: Deaths (Number).
for prior trends in death rates which are also scale-
adjusted when relative deviation from trends are
computed. Excess death rates are also adjusted by
the volatility in deviations from trend (dispersion
around the trend), which allows for a direct com-
parison of excess MC death rates with excess UC
death rates.
Figure 6 compares the excess MC and UC death
rates from neoplasms from 2010 to 2022 showing
the relative deviations (top) and the
Z
-score (signal
strength) for the deviations (bottom) from the 2010-
2019 trend.
In Figure 6 (top) we observe that the excess MC
death rates from neoplasms were 3.3% in 2020,
then rose to 7.9% in 2021, and 9.8% in 2022. By
comparison, the excess UC death rates were 1.7%
Figure 6. Excess MC death rates from neoplasms
from 2010 to 2022 for both sexes of ages 15 to
44 in the USA. Top: Relative deviation from trend,
percent. Bottom: Deviation from trend
Z
-Score.
Excess UC death rates are shown for comparison.
in 2020, 5.6% in 2021, and 7.9% in 2022. Of note is
that the excess mortality for MC deaths from cancer
was greater than for UC deaths in all three pandemic
years, particularly in 2020.
The
Z
-score for excess deaths with neoplasm as
a multiple cause in 2020 was 5.1, indicating a very
strong signal. A trend emerged with substantial
increases in
Z
-scores of 12.1 and 15.0 for 2021
and 2022, respectively. These are extreme events,
akin to those observed for UC cancer deaths.
4.4 Comparison of MC and UC Death
Rates for ICD-10 Codes C00 to D48
(Neoplasms)
In this section we compare the trends in death
rates from MC and UC deaths from neoplasms,
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US - Death Trends for Neoplasms ICD codes: C00-D48, Ages 15-44
attempting to determine whether the increase in
neoplasm MC deaths in 2020 represents an increase
in cancers per se, or a consequence of the pandemic
on mortality for people with existing cancers.
Figure 7 (top) plots together the UC and MC death
rates from neoplasms in the US, from 2010 to 2022
previously plotted in Figures 3 and 5, respectively.
Figure 7 (bottom) shows the ratio of MC/UC death
rates and illustrates that the fraction of cancer deaths
recorded as a secondary cause was relatively stable,
at 4% to 5% of the number of deaths with cancer as
the underlying cause, from 2010 to 2016.
However, a departure from this existing trend
emerged in 2017 when this fraction trended upw-
ards reaching 1.08 in 2020, indicating that for an
increasing proportion of decedents for whom cancer
was listed as a multiple cause, the underlying cause
of death was attributed to another cause. In 2020,
this could be explained by deaths from COVID-19
or other health effects of the pandemic lockdowns
on individuals suffering from cancer. In 2021 the
fraction of MC to UC cancer deaths rose to close to
1.09 and remained at a similar level in 2022.
4.5 Trends in UC Death Rates for Males
and Females.
In this section we analyze the trends in UC death
rates from neoplasms in males and females.
4.5.1 UC Death Rates for Males and
Females from ICD-10 Codes C00 to
D48 (Neoplasms)
Figure 8 shows the death rates per 100,000 indivi-
duals for males and females, where neoplasms were
the underlying cause of death. We can observe that
UC death rates have been trending lower from 2010
to 2019, with significant downward slopes, for both
males and females in the 15-44 age group.
For females, in 2010 the death rate was 14.9 per
100,000 and in 2019 it was 13.2 per 100,000, an
11.4% drop. The death rate dropped slightly in 2020
to 13 per 100,000 and then rose to 13.4 per 100,000
in 2021, remaining at this level in 2022.
Figure 7. Yearly deaths from neoplasms as multi-
ple cause (underlying or contributing factor) in the
USA. The red dashed line shows the average from
2010 to 2019. The dotted line shows the extrapola-
tion of the trend from 2020 until 2022. Top: Deaths
per 100,000. Bottom: Deaths (Number).
Figure 8. Yearly UC death rates from neoplasms
in the USA for males and females of ages 15-44.
The red dashed line shows the average from 2010
to 2019. The dotted line shows the extrapolation of
the trend from 2020 until 2022.
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US - Death Trends for Neoplasms ICD codes: C00-D48, Ages 15-44
For males, in 2010 the death rate was 13 per
100,000 and in 2019 it was 11 per 100,000, a 15.4%
drop. The death rate rose slightly in 2020 to 11.1
per 100,000 and then rose to 11.4 per 100,000 in
2021 and 11.5 per 100,000 in 2022.
4.5.2
Excess UC Death Rates for Males and
Females
When comparing excess UC death rates attributed
to neoplasms for males and females (Figure 9) we
observe that in 2020, while females had no signi-
ficant excess mortality, males experienced about
3% excess mortality, with a
Z
-score of about 3.5
indicating a statistically significant deviation from
trend.
Figure 9. Excess deaths rates by neoplasms for
males and females, in the US. Top: Relative devia-
tion from trend, percent. Bottom: Deviation from
trend Z-Score.
In 2021 excess UC death rates from neoplasms for
males was 7.2% while only 4.2% for females, both
having
Z
-scores close to 8, indicating very high
statistical significance (Figure 9 bottom). Males
experienced about a 70% higher excess mortality
from neoplasms compared with females in 2021.
In 2022 the excess UC death rate from neoplasms
for males was about 10.7%, almost double that for
5.8% for females, both having
Z
-scores above 10,
indicating extreme occurrences.
5 SUMMARY OF FINDINGS AND
COMMENTARY
In our study we analyze trends in death rates
from neoplasms in individuals aged 15-44 in the
USA. We compare excess death rates for neoplasms
where they are classified as the underlying cause of
death (UC) or with cancers as MC of death (either
underlying cause or contributing cause).
UC deaths from neoplasms
When analyzing UC death rates from neoplasms,
our computations show that the excess death rates
from neoplasms for the 15-44 age group were 1.7%
in 2020, 5.6% in 2021, and 7.9% in 2022 (Figure 4).
Even though the deviation from trend was small, the
excess death rate in 2020 was statistically significant
with a
Z
-score of 3.5. The excess UC death rates
in 2021 and 2022 can be considered extreme events
with respective Z-scores of 11.8 and 16.5.
For comparison, excess mortality for all-cause
deaths was 19.9% in 2020, 33.8% in 2021, and
18.2% in 2022. It should be noted that as excess
mortality for all-cause deaths dropped from 2021 to
2022, this was not associated with a drop in excess
UC death rates from neoplasms; rather, the reverse
occurred.
When comparing UC death rates for males and
females we observe that while death rates for fema-
les did not show a significance increase in 2020,
males experienced a statistically significant 3%
excess mortality from neoplasms. In 2021 excess
UC death rates from neoplasms for males was 7.2%
while only 4.2% for females, both having
Z
-scores
ResearchGate PrePrint 11

US - Death Trends for Neoplasms ICD codes: C00-D48, Ages 15-44
close to 8, indicating very high statistical signifi-
cance (Figure 9 bottom). In 2022 excess UC death
rates from neoplasms for males was about 10.7%
while about 5.8% for females, both having
Z
-scores
above 10, indicating extreme occurrences.
Males experienced an approximately 70% incre-
ase in excess deaths from neoplasms compared with
females in 2021, doubling in 2022. These results
are corroborated by the findings of our previous
work (Alegria, et al., 2024)[
1
] on cancer rates in
individuals aged 15 to 44 from the UK.
MC deaths from neoplasms
When analyzing MC death rates we found that
the excess death rate from neoplasms was 3.3% in
2020, then rose to 7.9% in 2021, and 9.8% in 2022
(Figure 6). The excess death rate in 2020 was highly
statistically significant with a
Z
-score of 5.1. The
excess MC death rates in 2021 and 2022 can be
considered extreme events with respective
Z
-scores
of 12.1 and 15.0.
The rise in MC cancer deaths in 2020 may be due
at least in part to other causes such as COVID-19
or the effect of the lockdowns, which may have
limited access to diagnosis or treatment. In 2021
and 2022 we observe larger rises in deviations from
trend in MC death rates from neoplasms, compared
to deviations from trend in UC death rates. In 2021
the ratio of MC to UC cancer deaths rose to 1.09
and remained at that level in 2022.
Comments
Our observations are consistent with those (all
ages) published by the American Cancer Soci-
ety (ACS) in their two most recent summaries of
cancer statistics. Their 2023 report (Siegel, et al.,
2023)[
12
] noted “Despite the pandemic, and in con-
trast with other leading causes of death, the cancer
death rate continued to decline from 2019 to 2020”
Although their 2024 paper (Siegel, et al., 2024)[
17
]
reported that cancer mortality (all age) continued to
decline through 2021, they noted that cancer-related
mortality (i.e., cancer as an underlying or contribu-
ting cause) increased from 2019 to 2020 and again
in 2021. Citing Fedeli, et al.(2024)[
18
] the ACS
contrasted these increases with the two decades
of decline in mortality rates, speculating that this
was a “secondary consequence of the COVID-19
pandemic.” Fedeli et al. [
18
] drew particular atten-
tion to increases in mortality related to prostate and
hematologic cancers.
To explain the observed trends in rising cancer-
related death rates from 2020, we propose two
general hypotheses:
a)
Individuals aged 15-44 with existing cancers
died at higher rates, from multiple underlying
causes, during 2020, 2021, and 2022. This
hypothesis implies that a certain number of
individuals would have died at a later date, of
the neoplasm itself or other incidental illnesses,
but that COVID-19 infection or other pandemic
impacts ”brought forward” their deaths. Causes
unrelated to COVID-19 have also contributed
to the pre-pandemic rise in the MC/UC ratio
that began in 2017. (Fedeli, et al., 2024)[18]
b)
Cancer rates and/or the severity of cancers
within the 15-44 age group rose significantly
during 2020, 2021 and 2022, leading to rises
in cancers as the underlying cause of death and
also rates of death with cancers as secondary
causes.
And finally, we have a situation where a combi-
nation of the above hypotheses occurred simultane-
ously.
c)
Combinations of both previous hypotheses.
Increased cancer rates and/or severity in the
15-44 age group, combined with earlier dea-
ths from cancer and/or other illnesses (bring-
forward effect), resulted in higher neoplasm
deaths from 2020.
Hypothesis a) is supported by the fact that death
involving cancer as a multiple cause started rising in
2020, when death rates from cancers as the underl-
ying cause did not rise significantly. COVID-19 or
other causes of death, associated with lockdowns
and reduced medical care (Burus, et al., 2024)[
19
]
during the pandemic, are factors that were not
ResearchGate PrePrint 12

US - Death Trends for Neoplasms ICD codes: C00-D48, Ages 15-44
present before 2020 and could have contributed
towards increased MC deaths from cancer in 2022.
On the other hand, the bring-forward effect usu-
ally implies that after a period of higher excess
deaths, there would be an equivalent period of
negative excess deaths that compensates for the
bring-forward effect i.e. deaths that were precipi-
tated by the COVID-19 pandemic would then be
absent from counts of deaths in subsequent time
periods. The opposite has so far occurred, with both
MC and UC cancer death rates accelerating in 2021
and 2022. No period of negative excess neoplasm
deaths has materialized so far for this age group.
Although COVID-19 disease became milder (less
lethal) in 2021 and 2022 with the emergence of the
Omicron variant, the virus became more transmis-
sible leading to a surge in the overall number of
deaths attributed to COVID-19 ”bringing forward”
neoplasm MC deaths.
Hypothesis b) is supported mainly by the rising
trend in both MC and UC cancer excess death
rates. Higher than expected cancer death rates could
originate from higher incidence of cancers, an
acceleration of existing cancer cases, and/or more
rapidly-progressing cancers.
If the initial rise in cancer-related deaths in 2020
is explained by the bring-forward effect, it was
not followed by an expected compensatory period
of negative excess deaths, but by a continued rise
in neoplasm death rates in 2021 and 2022. Thus,
a different phenomenon may be occurring, over-
lapping in timescale, of increased incidence or
severity of cancers, supporting the combination
hypothesis c). Some insight into these observati-
ons might be gained from cancer incidence rates.
However, ACS (Siegel at al, 2024) note difficulty
in analyzing diagnoses data from 2020 because of
the large anomalous drop in apparent incidence
due to COVID-19 health care disruptions. Delays
in diagnosis were not uniformly distributed across
cancer types, age, or severity of cancer, adding to
the complexity of the problem.
Indeed, in the present study, a reduction in cancer
screening and diagnostics during the pandemic
years leading to higher deaths could be a confoun-
ding factor. However, the younger age group of 15
to 44 are not likely to be affected significantly by
this factor, as the majority of cancer screening is
carried out in age groups over 45. This is supported
by the observation by the ACS (Siegel et al 2024)
that the drop in incidence rates in 2020 was lower
for childhood (4%) and adolescent (6.5%) cancers.
Limitations of the study
The main limitation from our analysis is that the
2022 data from the CDC for the different causes of
death is provisional, at the date of the data download
(2023-12-20) which means that it might be sub-
ject to change, particularly in the classification of
underlying cause or when adding secondary causes
of disease. This might lead to some discrepancies
when the final data are released.
Our analysis does not allow us to look in detail at
whether cancer incidence has increased since 2020,
and when this may have occurred. As noted by
(Siegel, et al., 2024)[
17
], incidence and mortality
data may not become publicly available for 2-4
years.
We have reported here trends based on crude rates,
and recognize that a variety of adjustments may be
made, for example for age, and reference to an index
year and using analytical tools such as Joinpoint
and DevCan
9
. However, as ACS notes (Siegel, et
al., 2024)[
17
] these tools may be limited as they
were not designed to accommodate the sorts of data
anomalies occurring between 2019 and 2020 due to
COVID-19 related disruptions in health care. The
very strong signals detected in our analysis based
on crude rates are sufficient justification for further
exploration.
Other limitations are implied by the following
discussion on Future Work.
9
National Cancer Institute - Methods & Tools for Population-based Cancer
Statistics
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US - Death Trends for Neoplasms ICD codes: C00-D48, Ages 15-44
Future work
We concur with Fedeli, et al. (2024)[
18
] that
further research is needed to determine the rela-
tive contributions of what are likely to be multiple
factors affecting the rise in cancer-related death
rates during or after the COVID-19 pandemic.
In particular, cancer trends need to be further
stratified by age, gender and cancer type. Health
disparities during the COVID-19 pandemic related
to race and ethnicity may be particular sources of
confounding. The relationship between cancer dea-
ths as a multiple cause for other underlying causes
must be dissected. Additionally, changes in inci-
dence and survival statistics during the COVID-19
pandemic must be examined, when reliable data are
available.
The possible effect of the modRNA COVID-19
vaccines, which were rolled out from 2021 and pri-
oritized for vulnerable groups such as those with
cancer should be studied. This imperative is based
on a growing body of evidence supporting plausibi-
lity including the case reports and CDC’s cancer
signals derived from VAERS described in our
introduction. Accordingly, future work should com-
pare cancer rates in vaccinated and unvaccinated
individuals.
CONFLICT OF INTEREST STATEMENT
The authors declare that the research was condu-
cted in the absence of any commercial or financial
relationships that could be construed as a potential
conflict of interest.
ACKNOWLEDGMENTS
The authors would like to acknowledge Elizabeth
Walsh for valuable feedback on the manuscript.
FUNDING
There was no funding source associated with this
research. The research was a product of independent
work by the authors.
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