It’s been a little while since the release of our April 7th paper for the Keto-CTA study and news on
our documentary around it, The Cholesterol Code. I wanted to wait until all four analyses were in before doing a full update here on the blog.
INITIAL CONTROVERSY
Interestingly, since April, critics have asserted our study wasn’t detecting an association
between LDL cholesterol and plaque progression because “everyone had high LDL.” As
one prominent critic put it, “All of these people had high LDL and high ApoB.”
This criticism assumes we had a narrow range of LDL levels—something like a
standard deviation of, say, 10 mg/dL clustered tightly around our mean of 253 mg/dL. If
that were true, I’d agree the criticism would be valid.
But our actual spread was already published in Table 1 of our paper. That table points
out that we had a standard deviation of 84.7 mg/dL and an interquartile range of 202 to
308 mg/dL. Our participants’ LDL cholesterol levels ranged from 49 mg/dL at the lowest
to 591 mg/dL at the highest—a spread of 542 mg/dL.
I’m going to make what some might consider an audacious statement: I’m confident we
have the largest spread of LDL cholesterol of any prospective imaging study ever
conducted. I wasn’t able to find anything even close to comparable.
This matters because the lipid hypothesis itself is built on dose-dependent relationships.
As the 2017 European Atherosclerosis Society consensus statement puts it: the
probability of plaque development “increases in a dose dependent manner” and is
“proportional to both the absolute magnitude and duration of exposure to elevated LDL
cholesterol.”
The dose-dependent, log-linear relationship between LDL and atherosclerosis isn’t a
movable goalpost—it IS the lipid hypothesis. We had the dose variation. We had the
range. The association simply wasn’t there.
THE CLEERLY SITUATION
So why weren’t we more vocal about defending our work? The answer lies in what was
happening behind the scenes with our data analyses.
Remember: the scans are the scans are the scans. All our analyses—semi-quantitative,
Cleerly, HeartFlow, and QAngio—looked at the exact same 200 CT scans from our 100
participants.
When I received access to the raw Cleerly data on April 18th, eleven days after
publication, I found several concerning issues. I brought these to the attention of both
Lundquist and Cleerly immediately. In an April 24th meeting, Cleerly’s then-CMO, who was also a co-author on our paper, agreed these were important concerns and
committed to running a blinded quality control pass to confirm or disconfirm the results.
However, what followed surprised us. The previous commitment was disregarded, and Cleerly asserted they would not follow through on the blinded quality control pass.
At that point, we knew we needed to engage another independent, AI-guided CTA analysis service. This is what brought us to look into Heartflow.
MULTIPLE INDEPENDENT CONFIRMATIONS
Under normal circumstances, when two analyses disagree, adding a third to break the tie would be fairly standard. But these weren’t normal circumstances. Many long time critics had become quite attached to the Cleerly analysis, and thus we wanted to add an additional blinded, independent confirmation to help us all get a stronger redundancy for confirmation.
Now, here are the results. For absolute change in non-calcified plaque volume—the
numbers that matter most—Cleerly showed 18.8 mm³, while HeartFlow showed 5.5
mm³ and QAngio showed 5.6 mm³. HeartFlow and QAngio were in close agreement
with each other, but both disagreed substantially with Cleerly.
VERIFIED REGRESSION
Here’s the exciting part. Both HeartFlow and QAngio showed substantial numbers of
participants with non-calcified plaque regression—33 regressors for HeartFlow and 15
for QAngio in non-calcified plaque volume. More importantly, Dr. Budoff and his team at
Lundquist have independently verified this regression in a subset of these participants
by direct visual inspection of the scans.
This slides was taken directly from my presentation:
FINAL THOUGHTS
Needless to say, it’s been exciting to see all these data come together.
Across multiple independent analyses—and with direct confirmation from one of the world’s leading cardiology imaging teams—the results have remained consistent: the predicted dose-dependent relationship between LDL cholesterol and plaque progression simply did not appear.
It’s worth underscoring that, yes, there is a subset of rapid progressors, as you’d expect in any middle-aged population. But even here, progression shows no association to LDL cholesterol; in fact, some progressors had levels lower than the cohort average.
Conversely, we observed clear evidence of regression in another subset of participants, including some with much higher than average LDL cholesterol—indeed, some with extremely high levels. (We’ll expand more on this in our upcoming paper.)
There’s still much more work ahead, and I look forward to sharing future announcements. For now, I want to thank each and every one of you for your tremendous support—it’s been essential to moving this research forward.
