REP: The Elusive Cancer Signal

Vaccination campaigns and neoplasm signals (C00-D48) in population-level data for ages 12-17 and 75+

Introduction

There has been a lot of talk about “turbo-cancer”. The way I see it, using such terms will only lower our credibility. Terms like “Rapidly progressing malignancies” or REP (Rapid Early Progression) are much closer to conventional medical language and can be understood by anyone in the field.

For this article I tried to isolate cancer signals from U.S. population level data for the two vaccination age tiers of children 12 or older (12-17) and adults 75 or older (75+). If there is a signal, I want to know when it manifests and whether this coincides with the onset of the “COVID vaccination” campaign.

Methods

Deaths are based on UCOD (Underlying Cause Of Death). If a decedent had COVID (U07.1), then its death is unlikely to show up in neoplasm deaths, because the WHO advised examiners to prioritize U07.1 (COVID-19) over other underlying causes of death.

Monthly (2015-2017) and weekly (2018-2022) data are available through CDC Wonder. I stretch these to pseudo-daily data to get continuous time series that are better suited for being visualized as line graphs. The time series are smoothed by a period of +-15 days, so they should be treated as figures with monthly precision.

Data for all 50 states are available through the download section of my “Summer Deaths” article. I am using the same methodology to calculate rates per 100k residents outlined in the methods section of that article.

In order to isolate the signal I am performing a correction of linear trends which is explained in more detail in the results section.

Results

First I will show you how the trend-correction works, then we will proceed to look at excess mortality for both age tiers next to vaccine doses.

Finally I will show you a scatter chart, which displays cumulative doses per capita and all-age excess neoplasm mortality across 50 states in 2022.

Trend-correction

Trend-correction is very straight-forward. I calculate rates of deaths per 100k using annual population estimates released by the Census Bureau for all deaths where one of the ICD-10 codes from the Neoplasms chapter (C00-D48) was specified as the UCOD (Underlying Cause Of Death), perform a linear regression on the mortality data between 2015 and 2019 and then correct the entire time series for the slope determined by the regression.

Before trend-correction the mortality rates in 2021 and 2022 were roughly on the same level as they were in 2017 and 2018. If we tried to calculate excess mortality using 2015-2019 as reference, we would only find a very weak signal or none at all.

After trend-correction we can see the cancer rate shoot up right upon introduction of COVID shots in December 2021.

I did the same thing for ages 12-17. In both age tiers, neoplasm mortality was apparently trending downwards throughout 2015-2019, possibly due to improvements in cancer therapy and diagnostics.

Excess mortality and doses per capita

The neoplasm signal manifested as soon as vaccines started to be administered to the population.

Again, the neoplasm signal for children 12 or older manifested as soon as this age group started receiving their COVID shots, but five months later than the signal for individuals aged 75 or older.

So rising neoplasm excess mortality coincided with the onsets of vaccination campaigns.

Regressions

I applied the above process to state-level all-age neoplasm mortality, calculated relative excess mortality for 2022, plotted it against cumulative vaccine doses and performed a regression across the 50 states.

As you can see, you’re seeing nothing. There is no significant (p<0.5) correlation between doses administered per capita and excess neoplasm mortality.

Bummer.

Discussion

Correcting for linear trends is only semi-legit. We basically created new time series that do not represent reality. Climatologists and other scammers are doing it all the time to adjust the data to their needs - their needs being whatever they want to convince you of.

In the case of neoplasm mortality however, I would say it is justified, because cancer screenings and therapies have been improving for some time. We should expect to see negative trends in the data.

In both the youngest and highest age tier these negative trends were broken when COVID shots started to be administered to the respective age group. The signal in adults 75 or older precedes the signal in children 12 or older by around 5 months.

This is suggestive of the vaccines being responsible for the rise in cancer deaths.

Strangely there is no correlation across states between the number of doses administered per capita by the end of 2022 and cancer excess mortality in 2022.

Possible reasons for this could be:

• The vaccines aren’t what’s causing neoplasm deaths

• Another factor is increasing neoplasm mortality in regions with low vaccination coverage, e.g. mistrust in the medical establishment leading to less cancer screenings being performed

  • We should control for changes in the number of screenings per capita in a multivariate regression, but I do not have the required state-level data available

• Only some vaccine products are causing neoplasm deaths and a higher proportion of these products was used in states where demand was lower (states with lower “vaccine” coverage)

  • This is not unlikely. Only Pfizer’s shots are known to contain linearized plasmids coding for SV40 thought to have an impact on cancer growth

  • Regressions should be performed after stratifying doses per capita by manufacturer (Moderna, Johnson, Pfizer). Maybe I will get around to this.

Looking forward to your input!