statins

oldie28 posted:

I stopped Crestor for 33 days. my lipids were: [br>TC 139 [br>HDL 35 [br>TRG 126 [br>LDL/HDL 2.3 [br>GLU 88 [br>[br>Now they are: [br>TC 211 [br>HDL 29 [br>TRG 164 [br>LDL/HDL 5 [br>GLU 96 [br>[br>I did not relax my strict Mediterrean diet nor hard daily exercise. Now I take the side of statins in the on-going controversy on whether they do any good or not. I'm 84, one stent RCA, May 2010 [br>(I dropped Crestor to see if i twas the cause of my two-year bout of night sweats. I still have them.)

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*I stopped Crestor for 33 days. my lipids were: [br>TC 139 [br>HDL 35 [br>TRG 126 [br>LDL/HDL 2.3 [br>GLU 88 [br>[br>Now they are: [br>TC 211 [br>HDL 29 [br>TRG 164 [br>LDL/HDL 5 [br>GLU 96 [br>[br>I did not relax my strict Mediterrean diet nor hard daily exercise. Now I take the side of statins in the on-going controversy on whether they do any good or not. I'm 84, one stent RCA, May 2010 [br>(I dropped Crestor to see if i twas the cause of my two-year bout of night sweats. I still have them.)*
iride6606 responded:

Wow, that sure illustrates the effectiveness of statins. It's interesting to see the effect the statin had on your HDL. Many people don't realize that statins have been shown to increase HDL up to 15%. Your numbers show that as well.

I hope you get past the night sweats!

I hope you get past the night sweats!

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*Wow, that sure illustrates the effectiveness of statins. It's interesting to see the effect the statin had on your HDL. Many people don't realize that statins have been shown to increase HDL up to 15%. Your numbers show that as well.*

I hope you get past the night sweats!I hope you get past the night sweats!

bobby75703 replied to iride6606's response:

It illustrates the effectiveness of statins on blood lipids.

However its impossible to prove a would-be heart attack was prevented, nor do the numbers prove any benefit against the progression of CVD.

The good news is today's imaging of arteries can show clearly the progression of CVD, regardless of lipid counts.

The association of cholesterol levels with risk for cardiac events is deeply ingrained in consumer's minds. Yet cholesterol remains one of the poorest predictors of a cardiac event.

However its impossible to prove a would-be heart attack was prevented, nor do the numbers prove any benefit against the progression of CVD.

The good news is today's imaging of arteries can show clearly the progression of CVD, regardless of lipid counts.

The association of cholesterol levels with risk for cardiac events is deeply ingrained in consumer's minds. Yet cholesterol remains one of the poorest predictors of a cardiac event.

Thanks for your Reply!

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*It illustrates the effectiveness of statins on blood lipids.*

However its impossible to prove a would-be heart attack was prevented, nor do the numbers prove any benefit against the progression of CVD.

The good news is today's imaging of arteries can show clearly the progression of CVD, regardless of lipid counts.

The association of cholesterol levels with risk for cardiac events is deeply ingrained in consumer's minds. Yet cholesterol remains one of the poorest predictors of a cardiac event.

However its impossible to prove a would-be heart attack was prevented, nor do the numbers prove any benefit against the progression of CVD.

The good news is today's imaging of arteries can show clearly the progression of CVD, regardless of lipid counts.

The association of cholesterol levels with risk for cardiac events is deeply ingrained in consumer's minds. Yet cholesterol remains one of the poorest predictors of a cardiac event.

iride6606 responded:

So I'm a numbers guy, I live numbers. It's my way of earning a living and a hobby. People get all worked up with trial results, they want to over analyze the meanings and findings when it's really much more simple than that.

All a trial is designed to do is determine the likelihood of an outcome with a given premise. In other words is it more or less likely to produce a given result, that's really all there is to it.

One thing that statin trials have shown us is that a lower cholesterol level is related to as much as a 42% reduction in death by heart disease. The numbers in every trial point to the same relative risk reduction so why not go with the odds? If I can reduce my risk of dying from a heart attack by 42% by having a lower cholesterol level, I'm in. The probability based on all the data collected eerily point to the same number, 42%, I like those odds.

All a trial is designed to do is determine the likelihood of an outcome with a given premise. In other words is it more or less likely to produce a given result, that's really all there is to it.

One thing that statin trials have shown us is that a lower cholesterol level is related to as much as a 42% reduction in death by heart disease. The numbers in every trial point to the same relative risk reduction so why not go with the odds? If I can reduce my risk of dying from a heart attack by 42% by having a lower cholesterol level, I'm in. The probability based on all the data collected eerily point to the same number, 42%, I like those odds.

Thanks for your Reply!

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*So I'm a numbers guy, I live numbers. It's my way of earning a living and a hobby. People get all worked up with trial results, they want to over analyze the meanings and findings when it's really much more simple than that.*

All a trial is designed to do is determine the likelihood of an outcome with a given premise. In other words is it more or less likely to produce a given result, that's really all there is to it.

One thing that statin trials have shown us is that a lower cholesterol level is related to as much as a 42% reduction in death by heart disease. The numbers in every trial point to the same relative risk reduction so why not go with the odds? If I can reduce my risk of dying from a heart attack by 42% by having a lower cholesterol level, I'm in. The probability based on all the data collected eerily point to the same number, 42%, I like those odds.All a trial is designed to do is determine the likelihood of an outcome with a given premise. In other words is it more or less likely to produce a given result, that's really all there is to it.

One thing that statin trials have shown us is that a lower cholesterol level is related to as much as a 42% reduction in death by heart disease. The numbers in every trial point to the same relative risk reduction so why not go with the odds? If I can reduce my risk of dying from a heart attack by 42% by having a lower cholesterol level, I'm in. The probability based on all the data collected eerily point to the same number, 42%, I like those odds.

bobby75703 replied to iride6606's response:

*"42%, I like those odds."*This is where marketing hype paints an unrealistic picture of statins, shining the spotlight on Relative Risk Reduction, and not the Absolute Risk Reduction, which is closer to 1%.

**"All the trial is designed to do is determine an outcome with a given premise"**

There is a lot of bias with that given premise. The entire reason the drug companies spend billions of dollars on studies of their own product is in hopes of boosting sales,

and no other reason.

Again in the real world, serum cholesterol is a lousy predictor of a heart attack.

If we become too focused on the promotion of industry funded numbers, we lose sight of the real world.

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This is where marketing hype paints an unrealistic picture of statins, shining the spotlight on Relative Risk Reduction, and not the Absolute Risk Reduction, which is closer to 1%.

There is a lot of bias with that given premise. The entire reason the drug companies spend billions of dollars on studies of their own product is in hopes of boosting sales,

and no other reason.

Again in the real world, serum cholesterol is a lousy predictor of a heart attack.

If we become too focused on the promotion of industry funded numbers, we lose sight of the real world.*"42%, I like those odds."*This is where marketing hype paints an unrealistic picture of statins, shining the spotlight on Relative Risk Reduction, and not the Absolute Risk Reduction, which is closer to 1%.

**"All the trial is designed to do is determine an outcome with a given premise"**

There is a lot of bias with that given premise. The entire reason the drug companies spend billions of dollars on studies of their own product is in hopes of boosting sales,

and no other reason.

Again in the real world, serum cholesterol is a lousy predictor of a heart attack.

If we become too focused on the promotion of industry funded numbers, we lose sight of the real world.

iride6606 responded:

So I'm a numbers guy and I go by what the numbers tell me. Most researchers and medical professionals are moving away from ARR and NNT numbers as a way to interpret the results of a study. The reason is simple; there are too many calculations for these numbers so compared to each other they mean nothing. For instance, the position of the NIH;

**Absolute risk reductions and consequent NNT values associated with statin therapy among those with elevated high-sensitivity C-reactive protein and low low-density lipoprotein cholesterol are comparable if not superior to published NNT values for several widely accepted interventions for primary cardiovascular prevention, including the use of statin therapy among those with overt hyperlipidemia.**

Now let's consider NNT which many assume is that inverse of ARR or;

**NNT**= 1/ARR.

The problem is that is just one way to calculate NNT and is not commonly used by statisticians but is usually used to look for flaws in a trial or to minimize the results as it's an easy target. The real question is what NNT calculation was used? Was it:

Choen's d or Kreamer & Kupher?

http://www.plosone.org/article/info:doi/10.1371/journal.pone.0019070

**Strauss Survival method;**

*NNT*

*1/Arr-1St-Sc***i**s it one of these with certain co=variables introduced;

**NNT [risk difference> = 1 / RD**

**` NNT [relative risk of event> = 1 / (pc*RRR)**

**` NNT [relative risk of no event> = 1 / ((1-pc)*(RRne-1))**

**` NNT [odds ratio> = (1-(pc*(1-OR)) / ((1-pc)*pc*(1-OR))**

Or how about confidence factors, any added;

**Confidence Interval Methods**

*Confidence intervals for odds ratios were calculated using the methods described by Martin and Autsin (1991).*

*Confidence intervals for relative risk are calculated using Koopman's likelihood-based approach advocated by Gart and Nam (Gart and Nam, 1988; Koopman, 1984).*

*Confidence intervals for risk difference and number needed to treat are based on the iterative method of Miettinen and Nurminen (Newcombe, 1998a; Gart and Nam 1990; Miettinen and Nurminen, 1985) for constructing confidence intervals for differences between independent binomial proportions.*

*Confidence intervals for individual risks are calculated by the Clopper-Pearson method for binomial proportions (Newcombe, 1998b).*

*The notation of harm/benefit suggested by Altman (1988) is used here instead of quoting negative estimates and confidence limits.*Again, the best number to look at is simple, relative risk reduction which is very basic and based on the data collected, people with low cholesterol are 42% less likely of dying of heart disease. It's not all about ARRs or NNTs, it really is this simple and not part of any hype by the drug companies. As a researcher who does this every day I can tell you this with total confidence.

Thanks for your Reply!

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So I'm a numbers guy and I go by what the numbers tell me. Most researchers and medical professionals are moving away from ARR and NNT numbers as a way to interpret the results of a study. The reason is simple; there are too many calculations for these numbers so compared to each other they mean nothing. For instance, the position of the NIH;

Now let's consider NNT which many assume is that inverse of ARR or;

The problem is that is just one way to calculate NNT and is not commonly used by statisticians but is usually used to look for flaws in a trial or to minimize the results as it's an easy target. The real question is what NNT calculation was used? Was it:

Choen's d or Kreamer & Kupher?

http://www.plosone.org/article/info:doi/10.1371/journal.pone.0019070

Or how about confidence factors, any added;

Again, the best number to look at is simple, relative risk reduction which is very basic and based on the data collected, people with low cholesterol are 42% less likely of dying of heart disease. It's not all about ARRs or NNTs, it really is this simple and not part of any hype by the drug companies. As a researcher who does this every day I can tell you this with total confidence.

So I'm a numbers guy and I go by what the numbers tell me. Most researchers and medical professionals are moving away from ARR and NNT numbers as a way to interpret the results of a study. The reason is simple; there are too many calculations for these numbers so compared to each other they mean nothing. For instance, the position of the NIH;

**Absolute risk reductions and consequent NNT values associated with statin therapy among those with elevated high-sensitivity C-reactive protein and low low-density lipoprotein cholesterol are comparable if not superior to published NNT values for several widely accepted interventions for primary cardiovascular prevention, including the use of statin therapy among those with overt hyperlipidemia.**Now let's consider NNT which many assume is that inverse of ARR or;

**NNT**= 1/ARR.The problem is that is just one way to calculate NNT and is not commonly used by statisticians but is usually used to look for flaws in a trial or to minimize the results as it's an easy target. The real question is what NNT calculation was used? Was it:

Choen's d or Kreamer & Kupher?

http://www.plosone.org/article/info:doi/10.1371/journal.pone.0019070

**Strauss Survival method;***NNT**1/Arr-1St-Sc***i**s it one of these with certain co=variables introduced;**NNT [risk difference> = 1 / RD****` NNT [relative risk of event> = 1 / (pc*RRR)****` NNT [relative risk of no event> = 1 / ((1-pc)*(RRne-1))****` NNT [odds ratio> = (1-(pc*(1-OR)) / ((1-pc)*pc*(1-OR))**Or how about confidence factors, any added;

**Confidence Interval Methods***Confidence intervals for odds ratios were calculated using the methods described by Martin and Autsin (1991).**Confidence intervals for relative risk are calculated using Koopman's likelihood-based approach advocated by Gart and Nam (Gart and Nam, 1988; Koopman, 1984).**Confidence intervals for risk difference and number needed to treat are based on the iterative method of Miettinen and Nurminen (Newcombe, 1998a; Gart and Nam 1990; Miettinen and Nurminen, 1985) for constructing confidence intervals for differences between independent binomial proportions.**Confidence intervals for individual risks are calculated by the Clopper-Pearson method for binomial proportions (Newcombe, 1998b).**The notation of harm/benefit suggested by Altman (1988) is used here instead of quoting negative estimates and confidence limits.*Again, the best number to look at is simple, relative risk reduction which is very basic and based on the data collected, people with low cholesterol are 42% less likely of dying of heart disease. It's not all about ARRs or NNTs, it really is this simple and not part of any hype by the drug companies. As a researcher who does this every day I can tell you this with total confidence.

iride6606 replied to bobby75703's response:

Bobby, I wasn't responding to you, I have no desire to have one of your circular discussions. I am responding to the OP,nothing more so please leave me out of your discussion.

Thanks for your Reply!

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*Bobby, I wasn't responding to you, I have no desire to have one of your circular discussions. I am responding to the OP,nothing more so please leave me out of your discussion.*
bobby75703 replied to iride6606's response:

I have every right to post a comment.

Thanks for your Reply!