#2597

Don’t think so. CGM seems similar before and after (I use Dexcom). My HbA1c are mentioned above. My last two fasting glucose levels were 83 and 86. My insulin was lower than ever, but I want to re check that again.

But note that I am generally very metabolically healthy, with a “low glucose / glycemic index” diet and a good exercise routine. So only an N=1 in that context.

(The range below is “normal” is lower than 18.4)

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#2598

I thought most of what is found in these forums is a bit controversial. As an example, I am taking acarbose (based on these forums) and doctor said I shouldn’t since I have no need for it. And when I dare mentioned that I am taking RAPA he was petrified. the only way to calm him down was to tell him I was joking but a friend of mine is doing it, not me. So, I’m not sure about your sophists comment.

As far as deleting a post, i have only deleted one post and the reason for that was the info I provided on the post was literally posted three posts earlier and I didn’t see it. So, my friendly advice is, save yourself time and don’t write something you know you’ll be deleting immediately. BTW, I clicked at some of your deleted post and did NOT see any useful information, rather I saw satire, or some form of bullying.
Fine by me, (nothing was even directed at me) but I don’t see how that would be beneficial or adds any value to the conversation on these boards. If anything, it might discourage some “cultured” participants in participating even if they had something valuable to add.

4 Likes
#2599

There’s a difference with what was posted. It is like arguing that 1+1 isn’t 2.
People make mistakes.

As far as deleted posts, I try to keep a nice tone and a sarcastic comment isn’t that.

#2600

:rofl: :rofl: :rofl: :rofl: :rofl: :rofl: :rofl: :rofl: :rofl: :rofl:

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#2601

I do agree that more safety data is needed for PCSK9i. Though the JUPITER trials does show a 20% reduction in all cause mortality after just 2 years with rosuvastatin which reduces LDL-C by 40-55% so perhaps evolocumab increased the risk of other diseases or it lacked the inflammation lowering effect of statins?

1 Like
#2602

I’m happy to share my opinion, but it will not be popular here. I also don’t know the specific problem you’re trying to solve, but I’m thinking it’s a bad CAC such as happened to me.

After age 60 I think the more cholesterol you have the better, unless you’ve had a heart attack. I don’t know if you follow the LPS, LL-37, microbial burden part of the forum, but cholesterol helps clear out the LPS. Basically people die because of the effects of inflammation caused by microbial burden. That includes the plaque caused by inflammation and microbial burden. So I think LDL plays an important role in helping clean up the mess and plug the holes after the battle.

The problem is that the only nasty part of the LDL is the small dense glycated form. It doesn’t get recycled because of the sugar stuck to it or because it’s size makes it not fit as easy. Macrophages gobble these up because they become a problem, then the macrophages turn into foam cells and start inflamming. From this you get plaque. Repatha, which I used for a while, increases the number of stations where LDL can be recycled and sent back out which will lower your cholesterol and make your doctor feel better. If you believe LDL is killing you then you may feel better too. But actually the extra stations are just as bad at recycling sLDL and oxidized LDL as the ones you already have.

Enter beta cyclodextrin. Cavadex or RemChol or CholRem. It binds to the cholesterol crystals and carries them away. It turns foam cells back into macrophages and shrinks the plaque. This stuff can actually solve the problem without causing more problems. I think. There are probably problems we don’t even know about. It doesn’t even lower your cholesterol numbers. Alpha does.

This stuff is all too expensive for my taste. I think what I’m doing will keep me alive till the really good stuff comes. This is my opinion. Take what you like and leave the rest.

3 Likes
#2603

Thank you for your explanation. Yes, you are right, it was a bad calcium score that I’m trying to reduce without creating more problems.

#2604

Do you have any clinical trial showing that a higher LDL in older people is beneficial for all-cause mortality? Because otherwise this all just sounds like keto meme science.

Ps: If you post u-shaped observational trials you’ll be cursed with lower LDL-C from now on :smiley:

3 Likes
#2605

“if you wanted to pick up a signal on that with statical confidence”

#2606

The thing is that you have to state that hypothesis before the trial (and for each hypothesis you state you have less “p value” left to use for any other hypothesis).

Is similar (kind of the inverse) to the feeling when you randomly bump into a friend you haven’t seen in a decade at a random location and random time

Most people (and human intuition is) - wow what a coincidence.

But the actual question to just whether one should feel “wow what a coincidence” should be - how many people have I ever met (including but way beyond this one person) that if I randomly bumped into - not just today, but any time this year or couple of years and not just at this location but at almost any location I have been - would I feel “wow what a coincidence”.

The integral or sum of all those probabilities - ie all those different people and the all those times and all those locations - is such a massively larger number that it not longer is crazy small,

In the case with a clinical trial, the question should be how many random things could happen that if that one thing happens someone will call out as an example of the medicine having a negative effect, when in fact is just randomness

Eg if you have two groups, by normal chance there will be some things that occur more in one of the groups

  • there 100s of cancers
  • dozens of automobile idease’s
  • dozens of psychiatric conditions
  • etc, etc
  • etc,
  • etc

Now it’s enough that one of them is randomly higher in the treatment group than in the control group for someone to say “Hang on, it’s looks likes the medicine causes X”.

But X was just one hundred of potential things and given randomness something whether X or Y and P or Q or A or B would naturally randomly occur.

Can you perhaps explain what it wrong with the logic and math and way the world works in the paper that @AnUser referred to that was published in a top journal?

1 Like
#2608

I read this site and others related to health as a hobby. I spent 8 hours in a skid loader today. So this may not be up to your standards, but I do read. First an article written in 2015, references are at the bottom:

http://www.ravnskov.nu/2015/12/27/myth-9/

I’m going to throw in 2 studies confirming that LDL has work to do and is not just glue to gum up your arteries. First on humans from 1992:

https://www.ahajournals.org/doi/abs/10.1161/01.atv.12.3.341

Then on mice done in 1996:

https://www.jci.org/articles/view/118556

3 Likes
#2609

Anuser you seem to struggle debating this rationally and logically. Maybe think about why, because getting personal on a board like this can seem a little pathetic. I have an Msc, so no, not an artist. And yes I fully understand the statistics. I’ve also studied logic, which I recommend.

BUT the facts about the fourier trial that you seem to struggle with are as follows. I’m interested if you disagree with any of these:

  1. It used subjects with pre-existing cvd. So it may not be generalizable to cardiovascularly healthy people like you and me.
  2. After independent review, investigators found a 41.4% inconsistency rate between FOURIER clinical events and those noted by the local clinical investigator for the CSR. This equates to a different cause of death in 360 of 870 instances.
  3. halfway through the trial, the sample size changed from 22,500 to 27,500, even though the accrual of the targeted number of events was on track.
  4. The rate of all-cause mortality had started to diverge in favor of placebo after 2 years of follow-up. It was 4.8% for evolocumab and 4.3% for placebo in participants with > 2.5 years of follow-up. A long-term follow-up would have yielded more events and thus more power to evaluate the effect of evolocumab on all-cause mortality.
  5. A team of Restoring Invisible and Abandoned Trials (RIAT) investigators was formed for a review of the FOURIER data in 2018. After readjudication, deaths of cardiac origin were numerically higher in the evolocumab group than in the placebo group in the FOURIER trial, suggesting possible cardiac harm.

I would be surprised if you disagreed with any of the above. My interpretation, given the above, is that the Fourier trial is not convincing as to whether a cardiovascularly healthy person with sub 70 mg/dl apoB should target sub 40 mg/dl using pcsk9 inhibitors or indeed any other pharma.

I am going to experiment with v low dow dose statin + ezetimibe however. My results are in the 50s and 60s and id like to be consistently in the 50s based on the research I’ve seen.

Remember, it’s ok to disagree. And it’s ok to change your mind. 🫨

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#2610

That’s my point - That a more convincing trial design would have included all cause mortality in its design. Given that there was a massive 41.4% disagreement between the local clinicians and the researchers as to the cause of death. And given that the independent reviewers disagreed with the research team too…

The problem with the Fourier trial is that three different groups all disagreed on what constituted a death from cvd. If the independent review team are right in their assessment (and they had the same data as the researchers) then the intervention wasn’t beneficial.

So the Fourier trial isn’t convincing to me, not because the stats are bad mathematically, but because the data relies too much on judgment for classification.

Also the trial isn’t convincing for me personally to lower my ldl-c more extremely because it used subjects with pre-existing cvd. And I don’t have cvd.

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#2611

It is consistent with all other evidence of LDL lowering from people with and without pre-existing CVD.

Yeah I have already addressed this before, those rogue doctors are doing a post-hoc analysis unblinded with less information than the original, blinded people, judging the cause of death. I already told you to read about this so it seems you just want to argue for the sake of arguing like @scta123 likes to do and which he admits.

How do you know?

What does diverge mean? Two faces on the moon rather than one?

See response to #2.

#2612

You are not reading what is being posted in this thread, which tells me you are here to argue and not learn.
See this paper.

Should a Reduction in All-Cause Mortality Be the Goal When Assessing Preventive Medical Therapies?

https://www.ahajournals.org/doi/10.1161/CIRCULATIONAHA.116.023359

#2613

Gosh this is getting long;

  1. We’re not talking about “all other evidence” just the Fourier trial, and whether it’s convincing. Happy to assess your other evidence too. But this was the biggest trial that you said “convinced” you, so I started here.

  2. “Rogue doctors”? Where is your evidence of that? And no you’ve misunderstood - this is the deviation between the local clinicians and the research team. The independent reviewers calculated this 41.4% deviation based on the data provided by the research team.

3.I know because I read the paper appraising the Fourier trial. I’ve linked it twice above but you seem unwilling to read it. You can check against the original trial protocol. But no one else is disputing this, including the lead author of the Fourier trial.

  1. Diverge means " to move or extend in different directions from a common point : draw apart"

  2. These are different Doctors. There were 3 sets of doctors who all disagreed on classification. The local clinicians, the research team and the Independent reviewers. You seem to be saying that two of these groups were “rogue doctors”. Do you have any evidence for this? The independent reviewers had the same data as the research team. The local clinicians may have had other knowledge because they treated the patients.

1 Like
#2614

I read it, but it makes a general and obvious point
There’s a lot of noise with all cause mortality. My points are:

  1. That when clinicians disagree over 41.4% of the classifications (between cvd death and non-cvd deaths) that also creates a massive amount of noise.
    So much so that the independent review team who had access to the same data, couldn’t find any significant benefit for cvd related mortality.

  2. When you are limiting a study to elderly people with preexisting cvd, there is less noise. Because a large proportion of all cause deaths will be cvd related.

  3. The Fourier trial was terminated early, if it had been allowed to continue, there is a chance a statistically significant result re all cause mortality would have emerged.

None of these points should be controversial.

1 Like
#2615

No you don’t know because a paper says, in a somewhat vague manner, so.

I am not disputing the fact that the sample size changed, but the reason for the change, you don’t have evidence or know whether that claim is true.

What does diverge mean in this context, like is it about seeing two faces on the moon rather than one?

I see what you mean now, we are talking about different things. And it appears you did not listen to me long ago when I told you to search for FOURIER in this thread or you somehow managed to not find the response to that paper.

In response to the study, Sabatine highlighted the different ways the TIMI study group collected and analyzed data compared with the RIAT researchers.

“Anytime there is a cardiovascular event, that triggers the collection of a dossier containing all the relevant and available source documents,” he said. “If somebody had a heart attack, we need to see discharge summary, the lab data for the troponin values, the ECGs, the angiograms—we get all the source documents. If there’s been a death, we get the autopsy reports.”

These dossiers are reviewed independently by two board-certified clinicians—a cardiologist for the cardiovascular outcomes and a neurologist for the cerebrovascular outcomes—who are blinded to treatment. The criteria for clinical outcomes, including the type of death, are based on standard FDA definitions, said Sabatine. At the end of a large cardiovascular outcomes trial, the FDA even audits the adjudication process and results, which they did in FOURIER. The agency, he said, found nothing of concern.

Clinical trials also require the CSR narrative, which is generated 24 hours after a patient has a serious adverse event, such as death. These narratives describe the event but may be incomplete, said Sabatine, noting they may be based solely on information in the death certificate. For this reason, it’s not surprising to have the initial cause of death listed in the CSR narrative by the local investigator differ from the CEC-adjudicated cause of death. The CEC has much more information on which to base their decision, said Sabatine.

“That process will naturally result in reclassification,” said Sabatine. “That’s the very purpose. There’s nothing nefarious that it doesn’t perfectly agree with the investigators.”

It’s annoying to argue with people who just want to argue, like as if sample size change reason is a hill to die on… When you CLEARLY do not know why that sample size change happened (basing it on two sentences from a paper from an author with a total of 22 citations in his research career). And because they do not want to read information from other sides to try and find the truth. It’s arguing with someone who is playing an ideologue.

#2616
  1. “No you don’t know because a paper says, in a somewhat vague manner, so.”
    I’m not exactly sure what that means, but yes I think, without getting too epistemological about it, that we can say “I know something” because it was in a respected peer reviewed journal. The quote is : “halfway through the trial, the sample size changed from 22,500 to 27,500” Not sure why you’re trying to argue that I don’t ‘know’ a fact, when you then go onto say that you “don’t dispute it”.

I make no claims as to why the sample size was changed. It’s merely a yellow flag for me. It’s well appreciated that adaptations part way through lead to risks of false of results. (Your logic mistake here is to assume I’m claiming something that I’m not)

  1. Not sure what the Moon has to do with this. Diverge is the term used in the paper i was quoting. They are saying that the difference in the all cause death rate between the evolocumab group v placebo was getting bigger (diverging) over the time period immediately before the trial was stopped early.

  2. I have read Sabatine’s response, it does go some way to explaining the 41.4% deviation between local clinicians and the research team, but that 41.4% still seems high to me. He also doesn’t explain why the independent reviewers (RIAT) came to a different finding to his team. If the classifications are based on clear “standard definitions” why would the RIAT come to assessments so different that the positive finding for evolocumab disappears? (Your logic mistake here is that you’ve been reassured by Sabatine’s explanation for the deviation between the research team and the local clinicians, but forgotten that there needs to be some explanation as to why the research team classifications deviated from the independent reviewers’)

I’m not trying to argue ideologically. You stated that you were “convinced” by the Fourier trial. Which means, logically, you must be "convinced’ the independent reviewers (RIAT) made mistakes. Nothing you’ve said explains why you’re “convinced” they got it wrong, or why and how the RIAT team were mistaken.

I’m merely saying that when an independent team review the same data and come to the opposite conclusion, it raises doubts. And so I’m not “convinced” by this trial. I’m very happy to be convinced in the future, just not yet.

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#2617

This is a direct quote, without cutting it in half like you are doing. Are you dishonest?:

halfway through the trial, the sample size changed from 22,500 to 27,500, even though the accrual of the targeted number of events was on track.

You are claiming that they changed the sample size for a reason other than the one they could change the sample size for. That is conspiratorial tinfoil hat theory since you don’t have evidence for that claim other than the authors in your paper saying so.

Because you haven’t proven it’s not diverging from one point of noise to another point of noise.

Did you miss the part in his response where he explained the RIAT team is not blinded, while those who did the adjudication process in the study was? Or that the RIAT team has less data as it is basing their adjucation on CSR? You are “conveniently” missing the most important parts. Read the quote I posted.

If you believe in the adjudication process by a team, post-hoc, with less data, and without being blinded… so be it.