Wednesday, July 24, 2013

Facts do not need clarification. - Kendrick

     

Proving that black is white

Last week I was going through some old files, and presentations, in a vague effort to clean up my computer. Whilst looking a one of many thousands of studies I had filed away I came across this paper: ‘Clarifying the direct relation between total cholesterol levels and death from coronary heart disease in older persons1.’

I read it, and immediately recalled why I kept it. For it came to the following, final, conclusion:

 ‘Elevated total cholesterol level is a risk factor for death from coronary heart disease in older adults.’

I remember when I first read this paper a few years ago. My initial thought was to doubt that it could be true. Most of the evidence I had seen strongly suggested that, in the elderly, a high cholesterol level was actually protective against Coronary Heart Disease (CHD).

However, when a bunch of investigators state unequivocally that elevated cholesterol is a risk factor for heart disease, I try to give them the benefit of the doubt. So I read the damned thing. Always a potentially dangerous waste of precious brainpower.

Now, I am not going to dissect all the data in detail here, but one sentence that jumped out of the paper was the following:

‘Persons (Over 65) with the lowest total cholesterol levels ≤4.15 mmol/L had the highest rate of death from coronary heart disease, whereas those with elevated total cholesterol levels ≥ or = 6.20 mmol/L seemed to have a lower risk for death from coronary heart disease. ‘

Now, I can hardly blame you if you struggled to fit those two quotes together. On one hand, the conclusion of the paper was that .. ‘Elevated total cholesterol level is a risk factor for death from coronary heart disease in older adults.’ On the other hand, the authors reported that those with the lowest total cholesterol levels had the highest rate of CHD; whilst those with the highest cholesterol levels had the lowest rate of CHD.

Taken at face value, this paper seems to be contradicting itself…. utterly. However, the key word here, as you may have already noted, is seemed. As in… those with elevated total cholesterol levels ≥ or = 6.20 mmol/L seemed to have a lower risk for death from coronary heart disease. ‘

Now you may think that this is a strange word to use in a scientific paper. Surely those with elevated total cholesterol levels either did, or did not, have a lower risk of death from CHD? Dying is not really something you can fake, and once a cause of death has been recorded it cannot be changed at a later date. So how can someone seem to die of something – yet not die of it?

The answer is that you take the bare statistics, then you stretch them and bend them until you get the answer you want. Firstly, you adjust your figures for established risk factors for coronary heart disease – which may be justified (or may not be). Then you adjust for markers of poor health – which most certainly is not justified – as you have no idea if you are looking at cause, effect, or association.
Then, when this doesn’t provide the answer you want, you exclude a whole bunch of deaths, for reasons that are complete nonsense. I quote:

‘After adjustment for established risk factors for coronary heart disease and markers of poor health and exclusion of 44 deaths from coronary heart disease that occurred within the first year, (my bold text) elevated total cholesterol levels predicted increased risk for death from coronary heart disease, and the risk for death from coronary heart disease decreased as cholesterol levels decreased.’

Why did they exclude 44 deaths within the first year?  Well, they decided that having a low cholesterol levels was a marker for poor health, and so it was the poor health that killed them within the first year.

The reason why they believed they could do this is that, a number of years ago, a man called Iribarren decreed that the raised mortality always seen in those with low cholesterol levels is because people with low cholesterol have underlying diseases. And it is these underlying diseases that kill them. (What, even dying from CHD. And how, exactly does CHD cause a low cholesterol levels….one might ask).

In truth, there has never been a scrap of evidence to support Iribarren’s made-up ad-hoc hypothesis. [A bottle of champagne for anyone who can find any evidence]. However, it is now so widely believed to be true, that no-one questions it.

Anyway, without chasing down too many completely made-up ad-hoc hypotheses, the bottom line is that this paper stands a perfect example of how you can take a result you don’t like and turn it through one hundred and eighty degrees. At which point you have a conclusion that you do like.

Young researcher: (Bright and innocent)  ‘Look, this is really interesting, elderly people with low cholesterol levels are at greater risk of dying of heart disease.’

Professor: (Smoothly threatening) ‘I think you will find…. if you were to look more carefully, that this is not what you actually found….. Is it? By the way, how is your latest grant application going?’

Young researcher: (Flushing red at realising his blunder) ‘Yes, by golly, how silly of me. I think I really found that elderly people with high cholesterol levels are at a greater risk of dying of heart disease.’

Professor: ‘Yes, excellent. Be a good lad, find a good statistician to make sure the figures make sense, and write it up.’

For those who wonder at my almost absolute cynicism with regard to the current state of Evidence Based Medicine, I offer this paper as a further example of the way that facts are beaten into submission until they fit with current medical scientific dogma.

As a final sign off I would advise that any paper that has the word ‘clarifying’ in its title, should be treated with the utmost suspicion. I think George Orwell would know exactly what the word clarifying means in this context. Facts do not need clarification.

1: Corti MC et al: Clarifying the direct relation between total cholesterol levels and death from coronary heart disease in older persons. Ann Intern Med. 1997 May 15;126(10):753-60
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Friday, July 12, 2013

Statin = substantial increase in diabetes risk in postmenopausal women

Statin Use and Risk of Diabetes Mellitus in Postmenopausal Women in the Women's Health Initiative

ABSTRACT

Background  This study investigates whether the incidence of new-onset diabetes mellitus (DM) is associated with statin use among postmenopausal women participating in the Women's Health Initiative (WHI).


Methods  The WHI recruited 161 808 postmenopausal women aged 50 to 79 years at 40 clinical centers across the United States from 1993 to 1998 with ongoing follow-up. The current analysis includes data through 2005. Statin use was captured at enrollment and year 3. Incident DM status was determined annually from enrollment. Cox proportional hazards models were used to estimate the risk of DM by statin use, with adjustments for propensity score and other potential confounding factors. Subgroup analyses by race/ethnicity, obesity status, and age group were conducted to uncover effect modification.

Results  This investigation included 153 840 women without DM and no missing data at baseline. At baseline, 7.04% reported taking statin medication. There were 10 242 incident cases of self-reported DM over 1 004 466 person-years of follow-up. Statin use at baseline was associated with an increased risk of DM (hazard ratio [HR], 1.71; 95% CI, 1.61-1.83). This association remained after adjusting for other potential confounders (multivariate-adjusted HR, 1.48; 95% CI, 1.38-1.59) and was observed for all types of statin medications. Subset analyses evaluating the association of self-reported DM with longitudinal measures of statin use in 125 575 women confirmed these findings.

Conclusions  Statin medication use in postmenopausal women is associated with an increased risk for DM. This may be a medication class effect. Further study by statin type and dose may reveal varying risk levels for new-onset DM in this population.
 
Given the success of statins in both primary and secondary prevention of cardiovascular morbidity and mortality,16 their use is progressively increasing, especially among older Americans.7 With such widespread use, even small risks are apparent alongside benefits. One emerging risk is an increased incidence of diabetes mellitus (DM). There is evidence that incident DM associated with statin use may be more common in the elderly, in women, and in Asians.812 A recent analysis suggests that preexisting metabolic risk factors control incident DM rate with statin medication.13 It is unclear if this risk varies with individual statins or if this is a dose-driven class effect.9,14 Although experimental and clinical studies find that individual statins act differently on glucose homeostasis as a function of relative lipophilicity and/or potency of action,15 other findings differ. A recent meta-analysis of 17 randomized controlled trials by Mills et al16 found a class effect increase of new-onset DM with statins (odds ratio [OR], 1.09; 95% CI, 1.02-1.16) similar to that reported by Sattar et al.9 Possibly, the grouping of statins masks the effect variation of individual statins. Still, at some given dose threshold, differences may be overcome, as implied by a meta-analysis of 5 trials comparing intensive to moderate dosing regimens using mainly atorvastatin and simvastatin.13,17 Notably, meta-analysis results display intertrial and intratrial variability in diagnostic and statistical methods and do not consistently consider confounding factors. Moreover, contributing sample sizes do not permit balanced comparison by statin type, sex, race/ethnicity, and age. Similarly, single studies may uncover only part of a greater topography.
 
As a large part of the aging population, postmenopausal women have not been fully represented in past clinical trials.16 Sex differences in DM pathogenesis are well recognized.1819 Using the Women's Health Initiative (WHI) data, we evaluated the overall effect of statin medication use on incident DM risk and examined these associations by specific statin agent. We stratified analyses by race/ethnicity, body mass index (BMI) (calculated as weight in kilograms divided by height in meters squared) category, and age group to determine if any associations were modified by these factors. In addition, we conducted subgroup analysis in women with and without self-reported cardiovascular disease (CVD) at baseline to address potential confounding and selection bias.

METHODS

The WHI recruited 161 808 postmenopausal women aged 50 to 79 years at 40 clinical centers across the United States from 1993 to 1998 and followed consenting participants. Of these women, 68 132 were enrolled in 1, 2, or all 3 of the clinical trial (CT) arms: the Dietary Modification Trial, the Hormone Trial, and the Calcium and Vitamin D Trial. Another 93 676 women were enrolled into a prospective observational study (OS).2023 The WHI eligibility criteria included the ability to complete study visits with expected survival and local residency for at least 3 years. Original exclusion criteria addressed conditions that would limit full participation in the study. This analysis used WHI data through 2005. After exclusion for prevalent DM, missing data, and use of cerivastatin (this medication was withdrawn from the market in 2001 for safety reasons), a total of 153 840 women were included (Figure).
 
Figure. Flowchart for statin users and diabetes mellitus (DM) analyses using data sets from the Women's Health Initiative.                    
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MEASUREMENT AND CLASSIFICATION OF STATIN MEDICATIONS
The current medication regimens of all CT participants were inventoried at baseline and at years 1, 3, 6, and 9. In the OS, medication data were inventoried at baseline and year 3. At each inventory, the brand or generic name on the medication label was matched to the corresponding item in the Master Drug Data Base (Medi-Span, Indianapolis, Indiana). We sorted for statin use as users or nonusers at baseline and year 3. Given that Sattar et al9 found a null effect of lipophilicity among statins, and in the absence of dose information, we determined statin categories by relative potency of action to decrease low-density lipoprotein cholesterol. Accordingly, statins were designated as low (fluvastatin, lovastatin, pravastatin) or high (simvastatin, atorvastatin) potency.2425
IDENTIFICATION OF DM
At baseline and at each semiannual (CT) or annual (OS) contact, incident treated DM was identified by questionnaire and was defined as a self-report of a new physician diagnosis of treated DM. This method of identification of prevalent and incident DM has been used in prior publications by the WHI investigators.18,2628 The accuracy of self-reported DM in the WHI trials has been assessed using medication and laboratory data, and self-reported DM was found to be reliable.29
COVARIATES
Baseline questionnaires ascertained demographic and health history information, including race/ethnicity, age, educational attainment, family history of DM, family history of depression, self-report of CVD, hormone therapy use, and smoking status. Baseline self-report for CVD has been previously validated in the WHI3031 and found to have reasonable agreement with hospital discharge International Classification of Diseases, Ninth Revision (ICD-9) codes.
 
The metabolic equivalents of physical activities and average daily nutrient intake were computed, using detailed methods described elsewhere.3233 Trained and certified clinic staff measured height using a fixed stadiometer and weight by a calibrated balance-beam scale. Relative weight as BMI was calculated from these values. Blood was analyzed for glucose and insulin for the random 6% WHI-CT blood subsample at baseline, year 1, year 3, year 6, and year 9. Fasting glucose was analyzed using the hexokinase method with interassay coefficients of variation less than 2%.26 Insulin was measured by enzyme-linked immunosorbent assay. The WHI used the homeostasis model assessment of insulin resistance (HOMA-IR), which was developed for application in large epidemiologic investigations as an alternative to the glucose clamp. HOMA-IR = fasting plasma insulin (μIU/mL) × fasting plasma glucose (mmol/L)/22.5.34
STATISTICAL ANALYSIS
Cox proportional hazards (PH) models were used to estimate hazard ratios (HRs) of DM by statin medication use. The dependent variable was time to occurrence of DM determined by self-report (ie, time to event). The time to event was calculated as the interval between enrollment date and the earliest of the following: (1) date of annual medical history update when new DM was ascertained (observed outcome) and (2) date of the last annual medical update during which DM status was ascertained (censored outcome). The primary independent variable in these analyses was statin use at baseline, coded as a binary variable. We present 3 Cox PH models to examine the association between baseline statin use and DM: model 1 estimates the unadjusted HRs (and associated 95% CIs) of the effects of statin use on incident DM; model 2 presents age- and race/ethnicity–adjusted HRs; and model 3 presents HRs adjusted for all potential confounding variables at baseline (age, race/ethnicity, education, cigarette smoking, BMI, physical activity, alcohol intake, energy intake, family history of DM, hormone therapy use, study arm, and self-report of CVD). Similar analyses were conducted for specific type of statin medication use at baseline, categorized as low vs high potency.
 
Since individuals using statins may have different underlying conditions that could put them at elevated risk for DM, we conducted several subgroup analyses to control confounding by indication. First, we conducted subgroup analyses by age, race/ethnicity, and BMI categories to examine whether the associations of statin use and onset of DM differed by categories of these variables. Age was categorized into 3 groups (50-59 years, 60-69 years, and ≥70 years). Race/ethnicity was assessed according to 4 major groups (white, African American, Hispanic, Asian). Body mass index was categorized into 3 groups (<25 .0="" 25.0-29.9="" 2="" analyses="" analysis="" at="" baseline.="" conducted="" cvd="" either="" finally="" in="" of="" or="" propensity="" score="" second="" self-reported="" similar="" subgroups="" sup="" we="" with="" without="" women="">35
was performed to reduce the confounding effects of other factors in the evaluation of the association between statin use and DM risk within an observational study setting. Participant-specific propensity scores were estimated from a logistic regression model to predict the probability of statin prescription. Covariates considered for inclusion into the logistic regression model included age, BMI, self-report of hypertension, self-report of CVD, family history of DM, smoking status, and physical activity. The final propensity score model retained all covariates noted herein with the exception of physical activity, which was an insignificant predictor of statin use. The association between statin use and DM risk was evaluated in Cox PH models after adjusting for the estimated propensity score.
 
After exclusion for cases of DM before year 3 (146 women), use of cerivastatin (651 women), and missing medication data at year 3 (2 women), our longitudinal analyses were conducted in a subset of 125 575 women from the OS and the CT arm at baseline and year 3 visits. Statin use was sorted into 4 categories: (1) never took statin; (2) use at both baseline and at the year 3 visit, (3) use only at baseline; and (4) use only at the year 3 visit. The HRs for DM by statin use were estimated similarly based on Cox PH models.

RESULTS

Participant characteristics are listed in Table 1. At baseline, the mean (SD) age of women included in our sample was 63.2 (7.3) years. Approximately 16.30% of the women were from racial/ethnic groups other than white, of which the largest representation was African American (8.32%). Only 2.56% (3922 women) were Asian. At baseline, 7.04% of participants took statin medication. Of these, 30.29% took simvastatin; 27.29%, lovastatin; 22.52%, pravastatin; 12.15%, fluvastatin; and 7.74%, atorvastatin. Comparison between statin users and nonusers showed significant differences in baseline characteristics.
 
Table Graphic Jump Location Table 1. Characteristics of 153 840 Study Participants, Women's Health Initiativea
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A total of 10 242 incident cases of DM were reported over 1 004 466 person-years of follow-up. Table 2 presents results regarding the association between statin use at baseline and risk of incident DM. In unadjusted models, statin use at baseline was significantly associated with an increased DM risk (HR, 1.71; 95% CI, 1.61-1.83) when compared with nonuse. This association was decreased but remained significant after adjusting for potential confounders (HR, 1.48; 95% CI, 1.38-1.59). This association was observed for all types of statin. Similar risk associations were found in use of either high- or low-potency statins, with multivariate-adjusted HRs of 1.45 (95% CI, 1.36-1.61) and 1.48 (95% CI, 1.36-1.61) compared with nonusers, respectively. Table 3 shows subgroup analyses by race/ethnicity, BMI category, and age group. In both unadjusted and adjusted models, statin use was consistently associated with increased risk of DM across subgroups by age. We observed significantly increased risk of DM by statin use within subgroups of white, Hispanic, and Asian women in both unadjusted and adjusted models. In adjusted models, we observed HRs of 1.49 (95% CI, 1.38-1.62), 1.18 (95% CI, 0.96-1.45), 1.57 (95% CI, 1.14-2.17), and 1.78 (95% CI, 1.32-2.40) among whites, African Americans, Hispanics, and Asians, respectively. Statin use was also associated with a significantly increased risk of DM within 3 subgroups according to BMI (<25 .0="" 1.09-1.33="" 1.20="" 1.48-1.87="" 1.57-2.29="" 1.66="" 1.89="" 25.0-29.9="" 25.0="" 29.9="" 30.0="" a="" adjusted="" adjusting="" after="" all="" among="" and="" associated="" bmi="" ci="" compared="" confounders.="" dm="" for="" groups="" higher="" hrs="" in="" increased="" less="" lower="" models="" moreover="" observed="" of="" or="" p="" potential="" respectively.="" risk="" significantly="" statin="" than="" the="" to="" use="" was="" were="" when="" with="" within="" women="">
 
Table Graphic Jump Location Table 2. Association Between Diabetes Mellitus (DM) Risk and Statin Use Status at Baseline in 153840 Participants
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To address potential confounding and selection bias, we conducted subgroup analyses among postmenopausal women with and without a history of CVD (Table 4). Among a subset of 24 842 women who self-reported CVD at baseline, we found that statin use was associated with an increased risk of DM (HR, 1.52; 95% CI, 1.36-1.71). These associations remained significant after adjusting for potential confounders (HR, 1.46; 95% CI, 1.29-1.65). Similar findings were observed among women without CVD at baseline.
 
Table Graphic Jump Location Table 4. Risk of Diabetes Mellitus (DM) by Statin Use Among Women With and Without Medical History of Cardiovascular Disease (CVD) at Baseline                    
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In unadjusted models, statin use was significantly related to DM risk (HR, 1.71; 95% CI, 1.61-1.83). When the propensity score was included, the estimated HR attenuated to 1.38 (95% CI, 1.29-1.47). On inclusion of other confounders in the model, the HR was essentially unaltered (HR, 1.40; 95% CI, 1.31-1.51). Propensity score adjusted models yielded HRs of 1.38 (95% CI, 1.23-1.54) and 1.40 (95% CI, 1.29-1.53) for respective increased risk with either high- or low-potency statin use at baseline compared with nonuse.
LONGITUDINAL MEASURES OF STATIN USE AND RISK OF DM
When compared with those who never received statin therapy, unadjusted HRs of 1.82 (95% CI, 1.65-2.00), 1.75 (95% CI, 1.43-2.14), and 1.81 (95% CI, 1.67-1.97) were observed for the groups of women who reported statin use at both baseline and at the year 3 visit, reported statin use only at baseline, and reported statin use only at the year 3 visit, respectively (Table 5). The risk associations remained significant after adjusting for age, race/ethnicity, other potential confounders, and propensity score. The multivariate adjusted HRs were 1.47 (95% CI, 1.32-1.64), 1.44 (95% CI, 1.15-1.80), and 1.60 (95% CI, 1.47-1.75), respectively.
 
Table Graphic Jump Location Table 5. Risk of Diabetes Mellitus (DM) by Statin Use at Baseline and 3-Year Follow-up in 125575 Participants
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SENSITIVITY ANALYSIS
A sensitivity analysis was conducted on a subset of 3706 women without DM at baseline and enrolled in the WHI CT for whom fasting glucose measurements were available at baseline and at least 1 additional follow-up visit. Diabetes mellitus was identified based on fasting glucose levels of 126 mg/dL (6.99 mmol/L) or higher. In unadjusted models, statin use at baseline was not significantly related to DM risk (HR, 1.06; 95% CI, 0.61-1.86). However, using baseline through year 6 data in the CT arm, we found that the statin users had higher fasting glucose levels and HOMA-IR compared with non–statin users, with increasing values from baseline to year 6 follow-up.
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Tuesday, July 2, 2013

Effect Chelation Regimen on Cardiovascular Events in Patients With Previous Myocardial Infarction - JAMA

ABSTRACT 

 
 
Importance  Chelation therapy with disodium EDTA has been used for more than 50 years to treat atherosclerosis without proof of efficacy.

Objective  To determine if an EDTA-based chelation regimen reduces cardiovascular events.

Design, Setting, and Participants  Double-blind, placebo-controlled, 2 × 2 factorial randomized trial enrolling 1708 patients aged 50 years or older who had experienced a myocardial infarction (MI) at least 6 weeks prior and had serum creatinine levels of 2.0 mg/dL or less. Participants were recruited at 134 US and Canadian sites. Enrollment began in September 2003 and follow-up took place until October 2011 (median, 55 months). Two hundred eighty-nine patients (17% of total; n=115 in the EDTA group and n=174 in the placebo group) withdrew consent during the trial.

Interventions  Patients were randomized to receive 40 infusions of a 500-mL chelation solution (3 g of disodium EDTA, 7 g of ascorbate, B vitamins, electrolytes, procaine, and heparin) (n=839) vs placebo (n=869) and an oral vitamin-mineral regimen vs an oral placebo. Infusions were administered weekly for 30 weeks, followed by 10 infusions 2 to 8 weeks apart. Fifteen percent discontinued infusions (n=38 [16%] in the chelation group and n=41 [15%] in the placebo group) because of adverse events.

Main Outcome Measures  The prespecified primary end point was a composite of total mortality, recurrent MI, stroke, coronary revascularization, or hospitalization for angina. This report describes the intention-to-treat comparison of EDTA chelation vs placebo. To account for multiple interim analyses, the significance threshold required at the final analysis was P = .036.

Results  Qualifying previous MIs occurred a median of 4.6 years before enrollment. Median age was 65 years, 18% were female, 9% were nonwhite, and 31% were diabetic. The primary end point occurred in 222 (26%) of the chelation group and 261 (30%) of the placebo group (hazard ratio [HR], 0.82 [95% CI, 0.69-0.99]; P = .035). There was no effect on total mortality (chelation: 87 deaths [10%]; placebo, 93 deaths [11%]; HR, 0.93 [95% CI, 0.70-1.25]; P = .64), but the study was not powered for this comparison. The effect of EDTA chelation on the components of the primary end point other than death was of similar magnitude as its overall effect (MI: chelation, 6%; placebo, 8%; HR, 0.77 [95% CI, 0.54-1.11]; stroke: chelation, 1.2%; placebo, 1.5%; HR, 0.77 [95% CI, 0.34-1.76]; coronary revascularization: chelation, 15%; placebo, 18%; HR, 0.81 [95% CI, 0.64-1.02]; hospitalization for angina: chelation, 1.6%; placebo, 2.1%; HR, 0.72 [95% CI, 0.35-1.47]).

Sensitivity analyses examining the effect of patient dropout and treatment adherence did not alter the results.

Conclusions and Relevance  Among stable patients with a history of MI, use of an intravenous chelation regimen with disodium EDTA, compared with placebo, modestly reduced the risk of adverse cardiovascular outcomes, many of which were revascularization procedures. These results provide evidence to guide further research but are not sufficient to support the routine use of chelation therapy for treatment of patients who have had an MI.
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