UK - Death and Disability Trends for Malignant Neoplasms (15-44)
UK - Death and Disability Trends for Malignant Neoplasms, Ages 15-44

Date: 10 October 2023

Carlos Alegria

Summary

In this study we investigate the UK trends in death rates and disabilities for malignant neoplasms for individuals
aged 15 to 44 by computing excess death rates and excess disability claims, which are the difference between
observed deaths/disability rates and a given baseline for expected death rates/disabilities. We measure changes
in the behaviour of morbidity and mortality before the Covid-19 pandemic with the post-pandemic period, formalignant neoplasms.
We show a large increase in morbidity (disabilities) and mortality due malignant neoplasms that started in 2021
and accelerated substantially in 2022. The increase in disability claims is consistent with the increase in excess
deaths in 2022, and both are highly statistically significant (extreme events). The results indicate that from late
2021 a novel phenomenon leading to increased malignant neoplasm deaths and disabilities appears to be present
in individuals aged 15 to 44 in the UK.

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Contents
1.

Introduction ................................................................................................................................................................ 3

2.

Data .............................................................................................................................................................................. 4

3.

4.

2.1.

Cause of Death Data ........................................................................................................................................ 4

2.2.

Registered Deaths (All Deaths) ...................................................................................................................... 4

2.3.

Disability Claims ............................................................................................................................................... 4

Methodology............................................................................................................................................................... 5
3.1.

Method 2C for Estimating Excess Death Rates .......................................................................................... 5

3.2.

ICD10 Code List of Selected Causes of Death for: Malignant Neoplasms ............................................ 5

Yearly Analysis of Excess Death Rates .................................................................................................................. 6
4.1.

Deaths for All Causes Versus Registered Deaths........................................................................................ 6

4.2.

Death Rates for Age Group 15-44 ................................................................................................................ 7

4.2.1.

Unadjusted (Raw) Death Rates for Age Group 15-44 from Malignant Neoplasms (C00-C99). 7

4.2.2.

Registered Deaths .................................................................................................................................... 8

4.2.3.

Adjusted Deaths from ICD10 Codes C00 to C99 (Malignant Neoplasms). ................................. 8

4.2.4.

Relative Deaths from ICD10 Codes C00 to C99 (Malignant Neoplasms) Versus All Causes. .. 9

4.3.

4.3.1.

Excess Adjusted Deaths from ICD10 Codes C00 to C99 (Malignant Neoplasms). .................. 10

4.3.2.
Causes.

Excess Relative Deaths from ICD10 Codes C00 to C99 (Malignant Neoplasms) Versus All
11

4.3.3.

Excess Adjusted Deaths for Malignant Neoplasms for Males and Females. .............................. 12

4.4.
5.

6.

Summary of the Analysis of Death Rates ................................................................................................... 12

Analysis of UK Disabilities (PIP System) ............................................................................................................ 14
5.1.

Methodology ................................................................................................................................................... 14

5.2.

Baseline PIP Clearances for New Claims for Oncological Causes. ........................................................ 14

5.3.

Excess Yearly PIP Clearances for New Claims for Oncological Causes............................................... 15

5.4.

Summary of the Analysis of PIP Clearances for New Claims................................................................. 15

Concluding Remarks ............................................................................................................................................... 17
6.1.

7.

Excess Death Rates for Age Group 15-44 ................................................................................................. 10

The Overall Scenario for Malignant Neoplasms ....................................................................................... 17

Appendixes ............................................................................................................................................................... 20
7.1.

Appendix 1 – ICD10 Code List for Malignant Neoplasms (C00-C99) ................................................. 20

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1. Introduction
Beginning in early 2020, the world changed due to the emergence of a global pandemic caused by the SARSCov2 virus which, in some individuals, manifested in the form of Covid-19 viral disease. The Covid-19 crisis
led to alterations in individuals’ lifestyles and perceptions of relative and absolute risk, which impacted their
day-to-day decision-making. To add to the social changes, governments added to the hysteria with theintroduction of unprecedented measures of social engineering such as control of media communications, theintroduction of pandemic lockdowns for healthy individuals, and from 2021, mass inoculations based upon
experimental mRNA-based vaccine technology. All these factors led to a break in individuals’ behaviours from2020 onwards.
In this context, Phinance Technologies researchers performed several analyses showing excess mortality (allcause) since 2020, from Europe to the US. We published a methodology report to explain our estimates forexcess mortality, which is based on measuring excess death rates instead of excess deaths1. By accurately
measuring, and then tracking excess mortality trends, we can have a clearer picture of the implications of thedifferent stages of Covid-19 pandemic, as mentioned above.
The purpose of this study is to go into more detail and measure the changes in death rates and morbidity due
to malignant neoplasms. We focus our research on younger individuals, aged 15-44, currently a topic ofparticular interest due to the rise in anecdotal evidence of many unexplained aggressive and unusual cancers(turbo cancers) occurring in the population, particularly in younger individuals. The focus of this study is not
to examine individual claims and anecdotes, but instead to provide a statistical analysis at a population level andclarify if the anecdotal evidence is abnormal or not.
The relationships that we uncover in our analysis offers a basis for a reality check for health professionals tounderstand underlying trends in individuals’ health.

1

https://phinancetechnologies.com/HumanityProjects/Resources/Report%20on%20measuring%20death%20rates%20%20V4%20-%20UK.pdf

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2. Data
2.1.

Cause of Death Data

The data used in this analysis is the number of deaths that occurred in England and Wales between 2010 and
2022, by underlying cause code (ICD-10), sex, and age group (up to 90+). The source is the UK Office for
National Statistics (ONS). The direct links to the mortality data by cause for 2010 to 2021 and 2022 are listed
below:
Link to the 2022 data source: Death occurrences by sex, five year age group and underlying cause (ICD-10code) England and Wales: 2022 - Office for National Statistics (ons.gov.uk)
Direct link to the source file:https://www.ons.gov.uk/file?uri=/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/adho
cs/1050deathoccurrencesbysexfiveyearagegroupandunderlyingcauseicd10codeenglandandwales2022/deathoccsengwal2022final.xlsx
Link to the 2010-2021 data source: Death occurrences by sex, five year age group and underlying cause(ICD-10 code) England and Wales: 2010 to 2021 - Office for National Statistics (ons.gov.uk)
Direct link to the source file:https://www.ons.gov.uk/file?uri=/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/adho
cs/1017deathoccurrencesbysexfiveyearagegroupandunderlyingcauseicd10codeenglandandwales2010to2021/d
eathsoccsengwal20102021finalnew.xlsx

2.2.

Registered Deaths (All Deaths)

Registered deaths are all the deaths registered in England and Wales, independently whether a cause of deathhas been attributed. The investigation of deaths and attribution of ICD10 codes with a cause of death cantake up to 2 years to be performed.
UK Monthly Registered Deaths (All Cause): Deaths registered monthly in England and Wales - Office for
National Statistics (ons.gov.uk)

2.3.

Disability Claims

For investigating the changes in disability claims, we use data from the Personal Independence Payment (PIP)system of the Department of Work and Pensions (DWP). We analyse changes in PIP clearances for new claims
to the system, as explained in our previous analysis, published on our website2.
Source for PIP data (from DWP): Personal Independence Payment statistics
Stat-Xplore system for DWP data: Stat-Xplore databases

2 https://phinancetechnologies.com/HumanityProjects/PIP%20Analysis-Systems.htm

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3. Methodology
In this study, we investigate the trends in death rates and disability claims for the selected cause: malignant
neoplasm (or oncologic causes for PIP disability claims). We investigate these trends using yearly data andtherefore we do not have to perform a seasonal adjustment to the data.
In general terms, to measure trends in these variables we use a methodology of computing excess rates, which
are the difference between the actual observed rates and a given baseline (expected rates). Because we wantto measure the impact of the Covid-19 pandemic and post-pandemic periods relative to the prior state of theworld, our baselines are based upon the estimation of the trend for a period prior to the pandemic.
In this study we will use method 2C, as described in our report on methodologies for measuring excess deaths3
in the population. Method 2C is based on computing the trends in death rates (deaths adjusted by the
population) instead of deaths, as the baseline for estimating excess mortality. This method significantly reduces
the noise of the estimation (as it adjusts for population growth or decline) and considers the prior trend indeath rates, which tend to decline over time (over the last 100 years) as the population grows healthier anddifferent risk factors are better managed.

3.1.

Method 2C for Estimating Excess Death Rates

𝐸𝑥𝑐𝑒𝑠𝑠𝐷𝑒𝑎𝑡ℎ𝑠𝑡𝑖𝐴𝐺 = 𝐷𝑒𝑎𝑡ℎ𝑠𝑡𝑖𝐴𝐺 − 𝐵𝑎𝑠𝑒𝑙𝑖𝑛𝑒𝑡𝑖𝐴𝐺

Eq. 1

Equation (1) is a general expression for estimating the excess absence rates relative to a given baseline. We use
the subscript “AG” to indicate a given population age cohort which could refer to an age range, region, sex, orunderlying cause of death.
For estimating the baseline for “normal or expected” death rates we use a simple linear fit:
𝐵𝑎𝑠𝑒𝑙𝑖𝑛𝑒(𝑡𝑖 ) = 𝑏̂ + 𝑎̂(𝑡𝑖 − 𝑡0 )Eq. 2

Where 𝑎̂ and 𝑏̂ are the estimated coefficients of the death rate trendline from 2010 to 2019. It should be notedthat for the UK disability data (Personal Independence Payment (PIP) system) the estimation period we use isfrom 2016 to 2019. The data before 2016 is unreliable due to the transition from a prior system Disability Living
Allowance (DLA) to the PIP system in 2013, which only stabilised after 2015.

3.2.

ICD10 Code List of Selected Causes of Death for: Malignant Neoplasms

For this analysis we selected all the ICD10 codes from category I, namely C00 to C99 which refer to deaths
attributed to malignant neoplasms.
The detailed list that was extracted from the ONS cause of death database shows the codes and descriptionthat were aggregated for the purpose of our analysis. The list is shown in Appendix 7.1.
Some ICD10 codes, such as C27 with the generic description of “Malignant neoplasms” refer to ICD10 codesthat were not used in the UK from 2010 to 2022.

3

Https://phinancetechnologies.com/HumanityProjects/Resources/Report%20on%20measuring%20death%20rates%20-%20V4%20-%20UK.pdf

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4. Yearly Analysis of Excess Death Rates
In this section we perform a yearly analysis of the death rates for England and Wales, using the ONS cause ofdeath data. In this analysis we use the 2010-2019 trend in death 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.
The analysis is performed for all the deaths from a particular range of underlying causes of death, as describedby the list of ICD10 codes in section 3.2, which refer to all deaths from malignant neoplasms.

4.1.

Deaths for All Causes Versus Registered Deaths

When analysing the ONS data for cause of death we noticed that there are discrepancies between the numberof deaths which have a cause of death and the number of registered deaths for a year. This is particularly thecase for deaths in 2022 (the most recent year) and younger individuals where there are significant discrepancies
between both these datasets.
The reason for the discrepancy is that death certificates for younger individuals take longer as each death is
thoroughly examined and, on many occasions, post-mortems need to be performed. For older individuals, thediscrepancies are small. In this report we only investigate deaths for individuals aged from 15 to 44. For thisage group, we show the differences between registered deaths and all the causes of deaths in Figure 1.

Figure 1- England and Wales, registered deaths versus deaths from all causes in the ONS deaths by cause data table for age group 15 to 44. Left: Yearly
numbers. Right: % missing cause of death relative to registered deaths.

We can observe that the discrepancy between registered deaths and the sum of all deaths by cause ranges
between -3% to +3% from 2010 to 2020. We consider these normal discrepancies between these databases as
there are many factors that could lead to these discrepancies, including if the deaths occurred within Englandand Wales or abroad, or if they occurred with individuals that were temporary stays in England and Wales.
For 2021, however, we observe about 8% more registered deaths than the sum of the deaths from all causes.
In 2022, there are still about 32% of registered deaths without a final cause of death. This is a large discrepancy
that needs to be corrected.
To correct for the discrepancies in registered deaths compared to deaths from all causes, we scale the deaths
for each ICD10 code by the ratio R=(registered/all cause deaths). This adjustment is significant for 2022 andwww.phinancetechnologies.com

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assumes that the proportion of deaths from the different ICD10 codes will remain the same after the final
figures are published (in 1 or 2 years). This may not be the case and, therefore, the results need to be taken witha degree of caution.
In summary, to estimate the trends in death rates for different causes, we use Adjusted Deaths (Adj-deaths)
which refers to the deaths from a particular cause or range of causes adjusted by the ratio defined above.
Adjusted death rates are computed based on adjusted deaths.

4.2.

Death Rates for Age Group 15-44

In this section we investigate the trends in death rates in England and Wales for the 15-44 age group. We
compare all-cause mortality (registered deaths) with deaths from malignant neoplasms, with ICD10 codes
ranging from C00 to C99. When computing death rates, we chose to show the numbers as deaths per 100,000
as death rates for younger age groups are very low.

4.2.1. Unadjusted (Raw) Death Rates for Age Group 15-44 from Malignant Neoplasms (C00-C99)
The first analysis that we perform is the analysis of the unadjusted (raw) deaths from malignant neoplasms.
Before starting the analysis, it needs to be reiterated that as mentioned in section 4.1, there are a significant
number of missing records for recorded causes of death relative to registered deaths in 2021 and 2022. This isbecause younger individuals are not expected to die from natural causes and, consequently, those deaths need
to be investigated to understand the underlying causes.
In section 4.1 we observed that for the 15-44 age group, there are about 8.3% of missing records in 2021 in the
ONS cause of death dataset, and 32% for 2022. The missing records for 2022 are about a third, which meansthat when analysing the raw numbers of deaths (without adjustment) for malignant neoplasms, they will likely
underreport actual deaths by that amount.
With these caveats in mind, Figure 2 shows the deaths (right) and death rate per 100,000 individuals (left) for
malignant neoplasm deaths in England and Wales from 2010 to 2022. Even with a large number of missing
records, we can already observe a clear signal in above-trend malignant neoplasm deaths in both 2021 and 2022.

Figure 2 - Yearly unadjusted (raw) deaths from malignant neoplasms in England and Wales. The red dashed line shows the average from 2010 to 2019.
The dotted line shows the 2015-2019 average death rate. Left: Deaths per 100,000. Right: Deaths (number).

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4.2.2. Registered Deaths
The analysis of the registered deaths allows us to have a context by which we can then compare the death rates
for malignant neoplasms. Figure 3 shows the death rate per 100,000 individuals for all registered deaths in
England and Wales from 2010 to 2022. We can observe that registered deaths per year had been trending
slightly lower from 2010 to 2019.

Figure 3 - Yearly registered deaths per 100,000 for England and Wales. The red dashed line shows the average from 2010 to 2019. The dotted line shows
the 2015-2019 average death rate.

In 2019, the death rate was about 67 per 100,000 individuals aged 15 to 44. The death rate increased in 2020
to about 69 per 100,000 and then again in 2021 to 75 per 100,000. In 2022 the death rate dropped slightly toabout 71 per 100,000, the same level as observed in 2010 and still above the 2020 level.

4.2.3. Adjusted Deaths from ICD10 Codes C00 to C99 (Malignant Neoplasms).
We now investigate adjusted4 deaths for all malignant neoplasms (ICD10 codes C00 to C99). Figure 4 (left)
shows the death rate per 100,000 individuals for malignant neoplasms deaths (adjusted for under-reporting) in
England and Wales from 2010 to 2022. We can observe that deaths per year from malignant neoplasms havebeen trending lower from 2010 to 2019, with a significant downward slope. In 2010 the deaths rate was 15 per
100,000 and in 2019 it was around 12.8 per 100,000, a 14.7% drop.

4 Deaths adjusted for the missing causes of death relative to registered deaths.

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Figure 4 - Yearly adjusted deaths for diseases by malignant neoplasms in England and Wales. The red dashed line shows the average from 2010 to 2019. The
dotted line shows the 2015-2019 average death rate. Left: Adj-Deaths per 100,000. Right: Adj-Deaths (Number).

The death rate dropped in 2020 to about 12.5 per 100,000 and then rose to 14 per 100,000 in 2021. In 2022 thedeath rate increased again to about 17.5 per 100,000, a level that is 11.7% higher than observed in 2010. The
death rate in 2022 was about 4.7 deaths per 100,000 above the 2015-2019 average.
When translating these numbers into the absolute number of deaths for diseases from malignant neoplasms,
shown in Figure 4 (right), we can observe that the 5-year average deaths from 2015 to 2019 was about 3000
deaths. In 2020, malignant neoplasm deaths were about 2,800, 200 less than the prior 5-year average. In 2021
there were about 3200 deaths, which was 200 more than the 2015-2019 average. In 2022, the number increased
to 4000, 1000 more than the 2015-2019 average.

4.2.4. Relative Deaths from ICD10 Codes C00 to C99 (Malignant Neoplasms) Versus All Causes.
In our study we also analyse the trends in the relative incidence of malignant neoplasm deaths relative to allother causes, which provides a different type of information related to breaks in the normal pattern of deathsin this age group.
For this purpose, in Figure 5 we plot the fraction of deaths from all causes that are attributed to malignant
neoplasms. We observe that there was a slightly declining trend in deaths due to malignant neoplasms from2010 to 2019. In 2010, deaths attributed to malignant neoplasms accounted for 21% of total deaths, while in2019, the fraction was only 19.5%.
In 2020 the fraction of deaths due to malignant neoplasms dropped to about 17.5% of total deaths. The fraction
then increased to 18.5% in 2021 (on top of the 2010-2019 trendline) and then jumped to about 24.5% in 2022,
which is significantly above the 2010 level.

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Figure 5 – Fraction of all causes for yearly deaths attributed to malignant neoplasms, for England and Wales. The red dashed line shows the average from2010 to 2019.

4.3.

Excess Death Rates for Age Group 15-44

In this section we investigate the trends in excess death rates in England and Wales for the 15-44 age group.
We compare excess all-cause mortality (registered deaths) with excess deaths from malignant neoplasms, with
ICD10 codes ranging from C00 to C99. We also compare excess deaths for males and females.

4.3.1. Excess Adjusted Deaths from ICD10 Codes C00 to C99 (Malignant Neoplasms).
Figure 6 compares the excess death rate for malignant neoplasms (adjusted for under-reporting) and excess
registered deaths in England and Wales from 2010 to 2022. The figure on the Figure 6 (left) refers to relative
deviations from the 2010-2019 trend, while Figure 6 (right) shows the Z-score (signal strength) for thedeviations from trend.

Figure 6 - Excess adjusted deaths rates for diseases by malignant neoplasms versus excess death rates for all registered deaths in England and Wales. Left:
Relative deviation from trend, percent. Right: Deviation from trend Z-Score.

In Figure 6 (left) we can observe that the excess deaths rates from malignant neoplasms were close to zero in2020, rose by about 13% in 2021, and about 43% in 2022. The excess mortality for all registered deaths was
about 5% in 2020, 15% in 2021, and 10% in 2022. Interestingly, the drop in excess mortality for all registeredwww.phinancetechnologies.com

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deaths from 2021 to 2022 was not mirrored in a drop in malignant neoplasm deaths. In fact, the opposite
occurred, with a sharp acceleration in excess deaths due to malignant neoplasms.
In terms of statistical significance of the excess deaths, we observe from Figure 6 (right) that for all registereddeaths, the Z-score in 2020 was only about 2, which is not a strong signal. However, in 2021, the Z-score wasslightly above 5.0 which is a very strong signal. In 2022 the Z-score dropped to about 3.5, which still indicatesthat the excess deaths are statistically significant deviations from the 2010-2019 trend.
When looking at excess deaths from malignant neoplasms, the Z-score in 2020 was around 0, indicating thatprior to the start of the vaccinations there was no signal pointing to an increase in malignant neoplasm deaths.
That trend however accelerated substantially in 2021 and 2022 where we observe Z-scores of around 5 and 16,
respectively. These are extreme events that we believe need a thorough investigation. Our previous work on
measuring excess mortality and disabilities in the UK5 points to the Covid-19 vaccines likely playing a significant
role in the rise of mortality and morbidity. However, the pandemic rules, lockdowns, and Covid-19 could haveplayed a role in the rise of malignant neoplasm deaths.

4.3.2. Excess Relative Deaths from ICD10 Codes C00 to C99 (Malignant Neoplasms) Versus All
Causes.
A different perspective is to analyse the fraction of deaths from all causes that are attributed to malignant
neoplasms and compare them with the absolute changes in death rates due to malignant neoplasms, as shownin Figure 7.
We observe that in 2020 and 2021 the fraction of malignant neoplasm deaths relative to all other causes did notdeviate significantly from the 2010-2019 trend. In 2021, both registered deaths and malignant neoplasm deaths
increased by similar amounts so that the fraction of neoplasm deaths remained unchanged. For 2022, weobserve that in similarity with excess death rates, the fraction of neoplasm deaths jumped substantially, by about
30%.
When looking at the statistical significance of the signals, in 2022, the fraction of excess deaths due to malignant
neoplasms had a Z-score of about 16, similar in magnitude than that for excess adjusted deaths rates. This
reinforces the fact that deaths related to the malignant neoplasms are of particular concern for this age group
and needs further investigation.

5 See our work on excess deaths in the UK:(https://phinancetechnologies.com/HumanityProjects/yearly%20Excess%20Death%20Rate%20Analysis%20%20UK.htm).
and the analysis of PIP clearances: (https://phinancetechnologies.com/HumanityProjects/PIP%20AnalysisSystems.htm)

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Figure 7 – Excess adjusted deaths rates for malignant neoplasms versus excess fraction of all deaths that were from malignant neoplasms, in England andWales. Left: Relative deviation from trend, percent. Right: Deviation from trend Z-Score.

4.3.3. Excess Adjusted Deaths for Malignant Neoplasms for Males and Females.
When looking at deaths attributed to malignant neoplasms for males and females, shown in Figure 8, we observethat in 2020 neither group had any noticeable excess mortality (slightly negative), with respective Z-scores close
to zero (low statistical significance).
However, we also observe that in 2021 men suffered slightly worse outcomes than women, with men
experiencing a 16% deviation from trend, compared to about 10% for women. In 2022 men suffered muchworse outcomes than women, with men experiencing a 52% deviation from trend, compared to about 31% forwomen. The signal strengths for both men and women were highly statistically significant, as shown in Figure
8 (right).

Figure 8 - Excess adjusted deaths rates by malignant neoplasms for males and females, in England and Wales. Left: Relative deviation from trend, percent.
Right: Deviation from trend Z-Score.

4.4.

Summary of the Analysis of Death Rates

We started our analysis of excess death rates due to malignant neoplasms by showing that the analysis needs tobe performed with caution as not all deaths had a classified cause up to the time of publication of the ONS
dataset. This issue is particularly relevant in younger age groups, which is the case of the present analysis, where
we observe that in 2022 about 32% of registered deaths were still not classified with a cause (Figure 1).

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We perform a correction to this problem by extrapolating the deaths in each year as if the proportion of eachcause of death remained the same when the missing deaths are finally classified. This is an assumption thatmust be taken with care. To make sure that we are identifying an actual trend in the data, we also analyse thedeaths from malignant neoplasms relative to all classified causes of death (Figure 7). The results show that therise in deaths from malignant neoplasms in 2022 was similar to the relative rise in malignant neoplasms in
relation to all other causes. We also analyse raw unadjusted deaths (Figure 2) which show that even without
accounting for the missing records, 2022 already shows significant above-trend deaths.
Our analysis shows that the excess death rates from malignant neoplasms were close to zero in 2020, rose by
about 13% in 2021, and about 43% in 2022. On the other hand, the excess mortality for all registered deaths
was about 5% in 2020, 15% in 2021, and 10% in 2022. The drop in excess mortality for all registered deaths
from 2021 to 2022 was not mirrored in a drop in malignant neoplasm deaths. The opposite occurred, with asharp acceleration in excess deaths due to malignant neoplasms.
The excess mortality from malignant neoplasm deaths in 2021 and 2022 are highly statistically significant with
Z-scores of 5 and 16, respectively. These are very strong signals. As mentioned above, these signals arecorroborated by similar findings when measuring rises in the fraction of deaths from malignant neoplasms
relative to all other deaths with classified causes.
When translating these numbers into the absolute number of deaths from malignant neoplasm, shown in Figure
4 (right) we can observe that in 2020, malignant neoplasm deaths were about 2,800, 200 less than the prior 5year average. In 2021 there were about 3200 deaths, 200 more than the 2015-2019 average, and in 2022, 4000
(1000 more than the 2015-2019 average).
When comparing outcomes for men and women, shown in Figure 8, we observe that both had no significant
changes in deaths from malignant neoplasms in 2020. However, in 2021 men suffered slightly worse outcomesthan women, with men experiencing a 16% deviation from trend, compared to about 10% for women. In 2022
men suffered much worse outcomes than women, with men experiencing a 52% deviation from trend,
compared to about 31% for women. The signal strengths for both men and women were highly statisticallysignificant, as shown in Figure 8 (right).
In the future, we plan to expand our analysis to identify the individual causes of death (ICD10 codes) within
the malignant neoplasms (ICD10 codes C00-C99) that were responsible for the acceleration in these deaths.

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5. Analysis of UK Disabilities (PIP System)
In this section we investigate the trends in disability claims in the UKs Department of Work and Pension(DWP) Personal Independence Payment (PIP) system that replaced the previous Disability Living Allowance(DLA) system from 2013 onwards.
The analysis we present here refers to clearances from new claims to the system. It should be noted thatclearances refer to decisions made, which can be positive or negative. The fraction of positive clearances (thatlead to a grant allowance) is shown to be stable over time at a rate of about 40%.
One must be aware that PIP replaced the UK’s previous Disability Living Allowance (DLA) system in 2013
and therefore we observe sharp increase in cases/claims in the few years following the initiation of PIP, which
has been explained as “capacity issues” by the DWP. For this reason, only cases after January 2016 are includedin this set of analyses.
We perform the analysis for PIP clearances related to oncologic causes to compare these trends with theprevious chapter on excess mortality due to the malignant neoplasms. On our website, we present the analysisof trends in PIP clearances for the different body systems6 which include interactive charts where theuser/researcher can change body system, age of the individuals and trend metric.

5.1.

Methodology

The methodology we use to estimate excess clearances of new claims in the PIP system is similar to that on
measuring excess mortality, described previously in section 3. We compare the 2016 to 2019 trendline in PIP
clearances with actual claims and compute the deviation from trend in relative terms (percentage deviation).

5.2.

Baseline PIP Clearances for New Claims for Oncological Causes.

Figure 9 shows the monthly PIP clearances for oncologic causes from January of 2016 to January of 2023. The
dotted line refers to the cumulative Covid-19 vaccine doses as a percentage of the 16-44 age group.

Figure 9 –Monthly clearances (decisions) for new claims to the Personal Independence Payment (PIP) system in the UK, for oncological causes. The red line
shows the 2016-2019 trend and the dotted line refers to the cumulative vaccinations for the 15-44 age group.

6 https://phinancetechnologies.com/HumanityProjects/PIP%20Analysis-Systems.htm

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From 2016 to 2019 we observe that there was an average of about 200 new PIP clearances per month. During
2020, there was no noticeable change in new claims. However, from early 2021, we observe a systematic rise in
the PIP clearances, reaching a peak of 600 in January of 2023.
The results above seem to corroborate the prior findings of increases deaths attributed to malignant neoplasms.
However, the results can be better compared by performing a yearly analysis of the PIP clearances.

5.3.

Excess Yearly PIP Clearances for New Claims for Oncological Causes.

When we compute the yearly PIP clearances from new claims for oncologic causes, shown in Figure 10, we
observe that PIP clearances were very stable from 2016-2019, at around 5478 per year.

Figure 10 - Yearly excess clearances for new claims to the Personal Independence Payment (PIP) system in the UK for oncologic causes for ages 16 to 44. The
dotted line refers to the 2016 to 2019 average yearly number of new claims.

In 2020 PIP claims increased by about 1.7%, which was a slight increase from the 2016-2019 average. In 2021,
PIP clearances were 0.1% below the baseline. However, in 2022, PIP clearances jumped by about 39.4%,
relative to the baseline. We should recall that for excess deaths from malignant neoplasms, we observed
deviations from trend of -6.7% in 2020, +6.7% in 2021, and +33.3% in 2022.
We should note that there was a backlog in PIP clearances peaking in August of 2021 which led to claims taking
up to 26 weeks to clear. The DWP mentions that the situation was normalised from early 2022 with PIP claims
clearing in about 14 weeks7. Consequently, we must observe caution when directly comparing the timing ofexcess deaths with excess disability claims. However, on a yearly basis, these differences are smoothed out, as
observed by the similarity of the trends in both excess deaths and excess disability claims for oncological causes.

5.4.

Summary of the Analysis of PIP Clearances for New Claims

The analysis of PIP clearances for new claims where the underlying causes were oncological, is consistent withthe analysis of excess deaths.
We observe that in 2020 and 2021 the fraction of malignant neoplasm deaths relative to all other causes did notdeviate significantly from the 2010-2019 trend. We also show that in 2022 the rise in percentage terms, fordisability claims was of similar magnitude to the equivalent rise in excess adjusted death rates.

7 https://www.gov.uk/government/statistics/personal-independence-payment-statistics-to-january-2023/personal-

independence-payment-statistics-april-2013-to-january-2023#clearance-and-outstanding-times

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The results suggest that there is an underlying phenomenon that is causing large rises in mortality and morbidity
due to malignant neoplasms. The explosion in malignant neoplasm deaths and disabilities occurred from late
2021 and accelerated in 2022, with a few months lag relative to the rollout of the Covid-19 vaccines.
The paper from Fraiman et al8, shows that the combined rate of serious adverse events during the 2 to 3 months
unblinded period of the Pfizer and Moderna clinical trials was 13.2 in 10,000 (vaccine arm relative to placebo
arm of the clinical trial)9. This translates to vaccinated individuals having a rate of serious adverse events ofabout 1 per 760. This is an extraordinary signal which was present in the original clinical trials, and that we’veshown in our US disabilities research10, is on the scale of the rise in disabilities we observe at the populationlevel.
Fraiman et al.’s paper does not account for serious adverse events that might have originated some time after
the Covid-19 inoculations. For instance, in our previous report on Cardiovascular deaths for 15 to 44 year-olds
in the UK11, we show that cardiovascular deaths increased over time and in 2022 reached its highest levels. Thisoccurred more than 6 months after the main vaccination rollout for the 15-44 age group.
Similarly, it is possible that the rise in disabilities and deaths from malignant neoplasms has an underlying
pattern that leads to a lag between the Covid-19 inoculations and the manifestation of the effect. Our results
show that malignant neoplasms shot up later than cardiovascular deaths, mainly in 2022, while cardiovasculardeaths had started to rise in 2021.
We have plans to research the trends in the main types of deaths and disabilities from individual ICD10 codes
within malignant neoplasms, to have insights into the underlying phenomenon of action.

8 J. Fraiman et al, "Serious adverse events of special interest following mRNA COVID-19 vaccination in randomized

trials in adults", Vaccine, Vol. 40, Issue 40, 22 September 2022, pp 5798-5805.
9 We analyse the paper on our website:
https://phinancetechnologies.com/HumanityProjects/SAE%20mRNA%20Clinical%20Trials.htm
10 https://phinancetechnologies.com/HumanityProjects/US%20Disabilities%20-%20Part5.htm
11 https://phinancetechnologies.com/HumanityProjects/UK%20Cause%20of%20death%20Project%20%20Cardiovascular%20Deaths%2015-44.htm

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6. Concluding Remarks
Table 1 summarises the yearly excess PIP claims for the oncologic system and compares them with theequivalent numbers of excess deaths. In the absolute number of deaths for diseases of the oncologic system,
shown in Figure 4 (right) we can observe that the 5-year average deaths from 2015 to 2019 was about 3000
deaths. In 2020, malignant neoplasm deaths were about 2,800, 200 less than the prior 5-year average. In 2021,
there were about 3200 deaths (200 more than the 2015-2019 average), and in 2022, 4000 deaths, which were1000 more than the 2015-2019 average.

PIP Clearances

Baseline(Av 2015-2019)
N=5,478

Excess Deaths

N=3,000

2020

2021

2022

N=5,574(+96)(+1.7%)

N=5,474(-4)(-0.1%)

N=2,800(-200)(-6.7%)

N=3,200(+200)(+6.7%)

N=7,636(+2,158)(+39.4%)(Z=17.9)
N=4,000(+1,000)(+33.3%)(Z=16.1)

Table 1 - Summary for excess deaths and disabilities for malignant neoplasms in England and Wales (deaths) and the UK (PIP claims).

The results shown in Table 1 indicate that there was a significant rise in both disability claims and deaths in the
15-44 age group in the UK.
We also observe that the relative changes in disabilities were more than double the equivalent rises in deaths,
which points towards the risk of higher malignant neoplasm deaths in the coming years as these conditions
remain unresolved.
The previous statement is furthermore supported by our analysis of excess mortality in the UK by analysing
the time series of weekly registered deaths12. The current annualised excess mortality for 2023 is around 20%
for the 15-44 age group, a substantial rise from the prior level in 2022, which was slightly above 10%. To us,
this is a warning sign that we will observe yet another rise in excess mortality due to malignant neoplasms whenthe 2023 numbers are released.
We are currently in the process of pursuing further investigations into this issue in more detail. In particular,
we will analyse the trends in deaths and disabilities for the most common individual ICD10 causes withinmalignant neoplasms, to gain insights into the underlying phenomenon of action.

6.1.

The Overall Scenario for Malignant Neoplasms

In addition to finding a relationship between disability claims and deaths related to malignant neoplasms, it isof interest to build an image of the whole phenomenon to be able to understand the coming challenges to theresources of the health sector and to the risks for the overall population health.

12 https://phinancetechnologies.com/HumanityProjects/yearly%20Excess%20Death%20Rate%20Analysis%20-%20UK.htm

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For this purpose, in similarity to our macro analysis of all-cause excess mortality, disabilities and injuries, which
we denominate as the V-Damage Project, in Table 2 we try to map the landscape of damage from malignant
neoplasms, this is, V-Damage Project – Malignant Cancers.
Unlike cardiovascular diseases, where several papers have reported incidence rates of myocarditis and otherheart conditions at a population level, we do not find equivalent surveys for malignant neoplasms, andconsequently the “target” population for malignant neoplasms is unknown.
To obtain a rough estimate of the population under risk, we speculate that recipients of the Covid-19
inoculations who suffered (vaccine-related) adverse events could be more susceptible for experiencing
malignant neoplasms in the future. The paper by Stephen J. Thomas et al.13 that establishes the Pfizer vaccine
efficacy based on the clinical trial data also provides us an estimate of the rate of adverse events in individuals
who took the vaccines versus the placebo group.
The paper reports that the rate of adverse events related to the inoculations was 23,903 per 100,000 in thevaccine group versus 5,981 per 100,000 in the placebo group. We assume that the difference was the rate ofindividuals who had some adverse reaction due to the Covid-19 inoculation, which is (23,903-5,981)=17,922
per 100,000, which corresponds to 17.92% of the vaccinated group. For the 15 to 44 age group in the UK, thevaccination rate for individuals that took at least 1 dose is estimated to be about 68.8%14. Consequently, thepopulation at risk is estimated at 17.92x0.688=12.3% or 12,330 per 100,000.
We understand that this is not a precise estimate, and there are reasons to believe it is an underreporting as well
as over-reporting of the true estimate for the population aged 15-44 “at risk”.
Possible pool

Excess events in 2021

Excess events in 2022

N=-4(-0.018 per 100,000)
N=+200(0.88 per 100,000)

N=+2,158(9.5 per 100,000)***
N=+1000(4.4 per 100,000)***

12.3%

Possible pool for
malignant neoplasms15(12,330 per 100,000)
PIP Clearances
Excess Deaths

Table 2 – Overall picture for damage from malignant neoplasms. Estimated rates for excess deaths and disabilities from malignant neoplasms in Englandand Wales (deaths) and the UK (PIP claims). Incidence rates are under investigation. ***Very high statistical significance.

We observe that there were close to zero excess rate of disability claims in 2021, and only a rate of 0.88 per
100,000 excess deaths in 2021.
These rates shot up in 2022 with 9.5 per 100,000 excess disability claims and 4.4 per 100,000 excess deaths.
When comparing the rise in malignant neoplasms deaths and disabilities with those for the cardiovascularsystem16, we observe that both showed an extremely strong signal in 2022. However, in 2021 while
13 Stephen J. Thomas et al, “Safety and Efficacy of the BNT162b2 mRNA Covid-19 Vaccine through 6 Months”, New

England Journal of Medicine, 9/2021.
Link to paper: https://www.nejm.org/doi/full/10.1056/NEJMoa2110345#article_supplementary_material
Reviewed here: Humanity Project - US Disabilities - Part 6 (phinancetechnologies.com)
14 https://coronavirus.data.gov.uk/
15 We emphasise that this is not a precise estimate. There are reasons to believe it underreports the true population atrisk, as well as there are arguments to affirm that this number is an over-reporting for the population aged 15-44 “atrisk”.
16 https://phinancetechnologies.com/HumanityProjects/UK%20Cause%20of%20death%20Project%20%20Cardiovascular%20Deaths%2015-44.htm

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cardiovascular deaths were already high, malignant neoplasm deaths were not. We hypothesise that the medium
to longer-term negative effects of the Covid-19 vaccine are starting to surface, first in the form of risingcardiovascular events and later with the rise of malignant neoplasms.
The observations above point to a worrying picture that we might see an even greater acceleration of malignant
neoplasm deaths and disabilities in the coming years, which makes the investigation of the underlying causesof upmost importance.

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7. Appendixes
7.1.

Appendix 1 – ICD10 Code List for Malignant Neoplasms (C00-C99)

ICD10
Code

Cause

C00

Malignant neoplasm of lip

C01

Malignant neoplasm of base of tongue

C02

Malignant neoplasm of other and unspecified parts of tongue

C03

Malignant neoplasm of gum

C04

Malignant neoplasm of floor of mouth

C05

Malignant neoplasm of palate

C06

Malignant neoplasm of other and unspecified parts of mouth

C07

Malignant neoplasm of parotid gland

C08

Malignant neoplasm of other and unspecified major salivary glands

C09

Malignant neoplasm of tonsil

C10

Malignant neoplasm of oropharynx

C11

Malignant neoplasm of nasopharynx

C12

Malignant neoplasm of pyriform sinus

C13

Malignant neoplasm of hypopharynx

C14

Malignant neoplasm of other and ill-defined sites in the lip, oral cavity and pharynx

C15

Malignant neoplasm of esophagus

C16

Malignant neoplasm of stomach

C17

Malignant neoplasm of small intestine

C18

Malignant neoplasm of colon

C19

Malignant neoplasm of rectosigmoid junction

C20

Malignant neoplasm of rectum

C21

Malignant neoplasm of anus and anal canal

C22

Malignant neoplasm of liver and intrahepatic bile ducts

C23

Malignant neoplasm of gallbladder

C24

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C25

Malignant neoplasm of pancreas

C26

Malignant neoplasm of other and ill-defined digestive organs

C27

Malignant neoplasms

C28

Malignant neoplasms

C29

Malignant neoplasms

C30

Malignant neoplasm of nasal cavity and middle ear

C31

Malignant neoplasm of accessory sinuses

C32

Malignant neoplasm of larynx

C33

Malignant neoplasm of trachea

C34

Malignant neoplasm of bronchus and lung

C35

Malignant neoplasms

C36

Malignant neoplasms

C37

Malignant neoplasm of thymus

C38

Malignant neoplasm of heart, mediastinum and pleura

C39

Malignant neoplasm of other and ill-defined sites in the respiratory system and intrathoracic
organs

C40

Malignant neoplasm of bone and articular cartilage of limbs

C41

Malignant neoplasm of bone and articular cartilage of other and unspecified sites

C42

Malignant neoplasms

C43

Malignant melanoma of skin

C44

Other and unspecified malignant neoplasm of skin

C45

Mesothelioma

C46

Kaposi's sarcoma

C47

Malignant neoplasm of peripheral nerves and autonomic nervous system

C48

Malignant neoplasm of retroperitoneum and peritoneum

C49

Malignant neoplasm of other connective and soft tissue

C4A

Merkel cell carcinoma

C50

Malignant neoplasm of breast

C51

Malignant neoplasm of vulva

C52

Malignant neoplasm of vagina

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C53

Malignant neoplasm of cervix uteri

C54

Malignant neoplasm of corpus uteri

C55

Malignant neoplasm of uterus, part unspecified

C56

Malignant neoplasm of ovary

C57

Malignant neoplasm of other and unspecified female genital organs

C58

Malignant neoplasm of placenta

C59

Malignant neoplasms

C60

Malignant neoplasm of penis

C61

Malignant neoplasm of prostate

C62

Malignant neoplasm of testis

C63

Malignant neoplasm of other and unspecified male genital organs

C64

Malignant neoplasm of kidney, except renal pelvis

C65

Malignant neoplasm of renal pelvis

C66

Malignant neoplasm of ureter

C67

Malignant neoplasm of bladder

C68

Malignant neoplasm of other and unspecified urinary organs

C69

Malignant neoplasm of eye and adnexa

C70

Malignant neoplasm of meninges

C71

Malignant neoplasm of brain

C72

Malignant neoplasm of spinal cord, cranial nerves and other parts of central nervous system

C73

Malignant neoplasm of thyroid gland

C74

Malignant neoplasm of adrenal gland

C75

Malignant neoplasm of other endocrine glands and related structures

C76

Malignant neoplasm of other and ill-defined sites

C77

Secondary and unspecified malignant neoplasm of lymph nodes

C78

Secondary malignant neoplasm of respiratory and digestive organs

C79

Secondary malignant neoplasm of other and unspecified sites

C7A

Malignant neuroendocrine tumors

C7B

Secondary neuroendocrine tumors

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C80

Malignant neoplasm without specification of site

C81

Hodgkin lymphoma

C82

Follicular lymphoma

C83

Non-follicular lymphoma

C84

Mature T/NK-cell lymphomas

C85

Other specified and unspecified types of non-Hodgkin lymphoma

C86

Other specified types of T/NK-cell lymphoma

C87

of which malignant neoplasm of lymph/haematopoietic tissue

C88

Malignant immunoproliferative diseases and certain other B-cell lymphomas

C89

of which malignant neoplasm of lymph/haematopoietic tissue

C90

Multiple myeloma and malignant plasma cell neoplasms

C91

Lymphoid leukemia

C92

Myeloid leukemia

C93

Monocytic leukemia

C94

Other leukemias of specified cell type

C95

Leukemia of unspecified cell type

C96

Other and unspecified malignant neoplasms of lymphoid, hematopoietic and related tissue

C97

Malignant neoplasms

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