Day: 07/28/2010

Total cholesterol and LDL levels decrease before rheumatoid arthritis

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Introduction

An increasing number of studies world wide provide compelling evidence for the excess cardiovascular (CV) risk in patients with rheumatoid arthritis (RA) compared with the general population.1 2 The interplay of two major contributors (traditional CV risk factors and inflammation) is being investigated to better understand the mechanisms underlying the high CV morbidity and mortality in RA. The contribution of inflammation to atherogenesis is supported by epidemiological evidence on the independent predictive value of inflammatory markers for subclinical and clinical atherosclerosis and for associated CV events.3,–,5 However, the impact of lipids on CV risk in the chronic autoimmune inflammatory setting of RA is unclear and the literature on lipid profile in patients with RA is contradictory. A number of studies have demonstrated a proatherogenic profile in RA.6,–,9 Some authors did not find a significant difference between lipid levels in patients with RA and in the general population.10 On the other hand, growing evidence suggests that patients with active untreated RA have reduced total cholesterol (TC), low-density lipoprotein (LDL) and high-density lipoprotein (HDL) cholesterol.11,–,13 These conflicting results can be attributed to confounding by indication and, possibly, to the effect of inflammation and treatment. Comprehensive analyses of trends in lipids both before and after RA incidence are lacking and the impact of RA onset on lipids is unknown. To examine this subject, we performed a longitudinal study of changes in lipid profile during the period surrounding RA incidence in a population-based cohort of patients with RA and a comparison cohort of non-RA subjects.

The aim of this study was to compare lipid profiles in patients with RA and non-RA subjects during the 5 years before and 5 years after the RA incidence/index date.

Methods

This retrospective longitudinal cohort study was performed using the population-based resources of the Rochester Epidemiology Project (REP) medical records linkage system. The unique features of the REP with respect to epidemiological studies are described in a number of publications.14,–,16 Briefly, this records linkage system allows ready access to the complete medical records from all healthcare providers from the Mayo Clinic and its affiliated hospitals, the Olmsted Medical Center, the Olmsted Community Hospital, local nursing homes and the few private practitioners. The potential of this data system for population-based studies has been described elsewhere.16 This system ensures virtually complete ascertainment of all clinically recognised cases of RA among the residents of Olmsted County, Minnesota, USA.

The study population comprised a retrospectively identified incidence cohort of patients with RA who were Olmsted County, Minnesota residents ≥18 years of age and first met the 1987 American College of Rheumatology (ACR) criteria17 between 1 January 1988 and 1 January 2008 and had at least one lipid measurement during the time period from 5 years before to 5 years after the RA incidence date. Subjects with only one lipid measure do not contribute to the estimation of trends (ie, slopes), but they do contribute information to the mean lipid levels and thus were included. The RA incidence date was defined as the earliest date at which the patient fulfilled four or more ACR criteria for RA.

For each patient with RA, a non-RA subject of similar age, sex, calendar year and length of medical history before the index date was selected from the same population. Every person in the community ≥18 years of age who qualified during the defined period regardless of race, ethnicity or socioeconomic status was equally eligible for inclusion. Each non-RA subject was assigned an index date corresponding to the RA incidence date of the designated patient with RA.

The original and complete medical records of all subjects were reviewed longitudinally by trained nurse abstractors, supervised by the principal investigator. Information about demographics (age and sex) and RA disease characteristics (disease duration and rheumatoid factor seropositivity) was collected.

All lipid measures (TC, HDL, LDL and triglycerides (TGs)) obtained from 5 years before the RA incidence/index date to the last follow-up were abstracted. In accordance with Adult Treatment Panel III guidelines,18 abnormal lipid levels were defined as TC ≥6.2 mmol/l (≥240 mg/dl), LDL ≥4.1 mmol/l (≥160 mg/dl), TGs ≥2.3 mmol/l (≥200 mg/dl) or HDL <1.0 mmol/l (<40 mg/dl). Data on prescription of lipid-lowering drugs (ie, statins and other lipid-lowering drugs) were available for 1017/1117 (91%) subjects from 1997 to the present. Extensive height and weight data were also available from 1997 to the present and were used to calculate body mass index (BMI). The study protocol was approved by the Institutional Review Boards from Mayo Clinic and Olmsted Medical Center.

Statistical methods

Descriptive statistics (means, percentages, etc) were used to summarise the lipid measures in the patients with RA and non-RA subjects. Demographics of patients with RA and non-RA subjects, as well as subjects with and without lipid measures, were compared using χ2 tests and t tests. Random-effects models adjusting for age, sex and calendar year of the RA incidence/index date were used to analyse the trends in lipid profiles during the time period from 5 years before to 5 years after the RA incidence/index date. These models account for multiple measurements for each subject using random effects to fit individual intercepts and slopes for each subject. Furthermore, these models were used to estimate the percentage of patients with RA and non-RA subjects with abnormal lipid measures before and after the RA incidence/index date, as well as to examine the trends in BMI over the time period. Generalised additive models with smoothing splines were used to illustrate the trends in lipid levels over time.

Sensitivity analyses, in which the original analyses were repeated under slightly different conditions, were performed to examine the change in results when (a) using the date of first joint swelling instead of the date of fourth criteria as the index date and (b) excluding patients using statins.

Results

A total of 650 Olmsted County, Minnesota residents first met the ACR criteria for RA between 1 January 1988 and 1 January 2008. Of these, 577 patients had at least one lipid measure during the time period from 5 years before to 5 years after the RA incidence date and thus were included in the study. The total number of lipid measurements in patients with RA was 3088 (median four measurements for each patient). Patients with RA without lipid measures during the time period of interest (n=73)had similar sex and rheumatoid factor status to those with lipid measures. However, patients with RA without lipid measures were younger (mean age 47.9 years, p<0.001) than patients with RA with lipid measures. Within the same time period, lipid measurements were also available for 540 non-RA subjects with a total of 3048 lipid measurements (median four measurements for each subject). The spread of measurements was similar for both groups (mean 5.4 years, SD 3.0 years for RA and mean 5.8 years, SD 3.2 years for non-RA (p=0.49)). Non-RA subjects had similar age and sex characteristics to those of patients with RA with lipid measures.

Demographic characteristics and the length of follow-up were similar in both RA and non-RA subjects (table 1). The median follow-up was 5 years in each cohort as the follow-up was truncated at 5 years for these analyses. A full 5 years of follow-up after the RA incidence/index date was available in 373 (65%) patients with RA and 377 (70%) non-RA subjects. In addition, 531 (92%) RA and 496 (92%) non-RA subjects had 5 years of available information before the RA incidence/index date. The mean time before the RA incidence/index date was 4.8 years in both groups with a median of 5 years.

Table 1

Characteristics of patients with RA and non-RA subjects

Figure 1 shows the trends in lipids during the 5 years before and 5 years after the RA incidence/index date in the RA and non-RA cohorts. There was a significant decline in TC and LDL levels during the 5 years before the RA incidence/index date in the RA, but not in the non-RA cohort. During the 5 years after the RA incidence/index date, the trends in TC and LDL levels were similar in RA and non-RA cohorts. HDL and TG levels in patients with RA and non-RA subjects did not change significantly during the entire study period of 5 years before and 5 years after the RA incidence/index date (figure 1).

Figure 1

Trends in lipid levels in patients with rheumatoid arthritis (RA) and non-RA subjects during the time period from 5 years before to 5 years after the RA incidence/index date adjusting for age, sex and calendar year of RA diagnosis. HDL, high-density lipoprotein; LDL, low-density lipoprotein; Tch, total cholesterol; TG, triglycerides.

Table 2 summarises the mean changes in lipid levels in the RA and non-RA cohorts. These results are derived from the random-effects models. During the 5 years before the RA incidence/index date, mean TC and LDL levels in the RA cohort decreased significantly (from 5.61 to 5.03 mmol/l and from 3.58 to 2.97 mmol/l, respectively) as compared with the non-RA cohort where the mean TC and LDL levels decreased minimally (table 2). Decreases in TC and LDL levels in the RA cohort (by −0.58 mmol/l and −0.61 mmol/l, respectively) were significantly larger than those in non-RA cohort (p<0.001). The mean changes in lipid levels were otherwise similar in the RA and non-RA cohorts during the study period. Patients with RA experienced a larger decline in TC:HDL ratio than non-RA subjects during the 5 years before RA (table 2).

Table 2

Mean changes in lipid levels in patients with RA and non-RA subjects from 5 years before to 5 years after the RA incidence/index date based on random effects models

Figure 2 shows the changes in the proportion of patients with RA and non-RA subjects with abnormal lipid measures during the 5 years before and 5 years after the RA incidence/index date. As seen from the figure, the proportion of patients with RA with elevated TC or LDL measures decreased significantly (p<0.001) during the 5 years before RA. No change in the proportion of subjects with abnormal TC or LDL was seen in the non-RA cohort during the corresponding time period. During the 5 years after the RA incidence/index date the proportions of both patients with RA and non-RA subjects with elevated TC and LDL measures remained essentially unchanged. The proportions of patients with RA and non-RA subjects with abnormal HDL and TG measures did not change significantly over the study period (figure 2).

Figure 2

Trends in the proportion of patients with abnormal lipid measures in patients with rheumatoid arthritis (RA) and non-RA subjects during the time period from 5 years before to 5 years after the RA incidence/index date adjusting for age, sex and calendar year of RA diagnosis. HDL, high-density lipoprotein; LDL, low-density lipoprotein; Tch, total cholesterol; TG, triglycerides.

We also examined the potential role of BMI and lipid-lowering drug use on these trends. There were no clinically significant changes in BMI in the RA cohort over the time period (mean BMI 27.7 kg/m2 5 years before RA incidence; 28.4 kg/m2 at RA incidence; 28.4 kg/m2 5 years after RA incidence). Non-RA subjects were more likely to have prescriptions for statins and other lipid-lowering drugs than patients with RA. Among those for whom prescription data were available, 165 (32%) patients with RA and 194 (39%) non-RA subjects had a prescription for statins (p=0.02). Similarly, 174 (34%) patients with RA and 203 (41%) non-RA subjects had a prescription for any lipid-lowering treatment (p=0.02). To explore the impact of statins on the lipid changes we performed a sensitivity analysis excluding statin users. The trends in TC, LDL, HDL and TGs in patients with RA not receiving statins were similar to those reported for the whole RA cohort (data not shown). However, the mean TG levels were considerably lower when statin users were removed, indicating that patients with the higher TG levels were probably taking statins.

To further investigate the nature of lipid changes in RA, we tested the hypothesis that the results would not change if we defined the index date as the date of the first joint swelling. We found that the time from first joint swelling to fulfilment of the fourth criteria for RA was minimal in the majority of patients (median: 4.5 days; 25th centile: 0 days; 75th centile: 108 days). In fact, 73% of patients met criteria within 90 days of the first joint swelling and 80% met within 6 months of the first joint swelling. Sensitivity analyses were performed using the date of the first joint swelling in place of the fourth criteria date as the index date for these analyses, and the results were identical (data not shown).

Discussion

This retrospective cohort study illustrates the longitudinal trends in lipids in a population-based cohort of patients with RA and non-RA subjects from the same underlying community during the period from 5 years before to 5 years after the RA incidence/index date. There was a significant decrease in TC and LDL levels, and a significant decrease in the TC:HDL ratio during the 5-year period before RA incidence. Lipid trends were otherwise similar in the RA and non-RA cohorts during the period from 5 years before to 5 years after RA. During the 5 years before the RA incidence/index date, the proportion of patients with RA with elevated TC or LDL measures was significantly less than for non-RA subjects.

To the best of our knowledge, this is the first longitudinal population-based study reporting long-term lipid trends in RA and non-RA populations both before and after the RA incidence/index date. The major finding of our study is the significant decline in TC and LDL levels occurring during the 5 years before the RA incidence/index date in patients with RA as compared with non-RA subjects. Consistent with the dynamics of TC and HDL changes (ie, decrease in TC levels and unchanged HDL levels), patients with RA also experienced a larger decline in the TC:HDL ratio than non-RA subjects during the 5 years before RA. The declines in TC and LDL levels were similar when using the date of the first joint swelling as an index date.We also found a significant reduction of the proportion of patients with lipid abnormalities (elevated TC or LDL measures) during the 5 years before the incidence/index date in the RA cohort, but not in non-RA subjects.

The only previous longitudinal study describing lipid levels in the pre-RA period was performed using the samples of blood donors in the Netherlands during 1984–99 who later developed RA.19 These authors showed a more atherogenic lipid profile in the preclinical phase of RA. However, owing to differences in study population and design, as well as different time periods under study, these findings cannot be directly compared with ours. The declining trend in TC and LDL levels is concordant with studies showing lower TC and LDL levels in active RA.8 11 This observation is also consistent with the concept of lowering of the plasma cholesterol concentrations in acute (particularly, inflammatory) conditions.20,–,23 In fact, this decrease in TC and LDL levels might result from their increased catabolism or increased retention (ie, subendothelial deposition) rather than decreased lipid production.24 25 Subendothelial lipid deposition might explain the paradox of lower cholesterol levels and increased CV risk in RA. Indeed, low cholesterol concentrations have been previously associated with high mortality risk26 27 and a poor response to tissue stress.28 29

Given that the major declines in TC and LDL occurred during the pre-RA period, even before the first joint swelling, these changes were unlikely to have been affected by antirheumatic treatment. The decreases in TC and LDL levels in RA in our study are unlikely to be solely due to the use of lipid-lowering treatment either, since use of lipid-lowering drugs was lower in RA than in non-RA subjects and the lipid trends in patients with RA were similar when statin users were excluded from the analysis. Hence, the lipid changes in the RA cohort occurring during the 5 years before RA are likely to be associated with the ongoing preclinical inflammation rather than the effect of antirheumatic and lipid-lowering drugs. Lipid changes in non-RA subjects are consistent with the major lipid trends in the US population (studies NHANES and ARIC), suggesting that the non-RA cohort reflects the general population.30 31 These lipid changes can be explained by increasing usage of lipid-lowering drugs in the general population during recent decades.31 A similar explanation might be suggested for the changes in HDL and TG levels in non-RA subjects over time. Although trends in HDL and TG levels in the RA cohort were not significantly different from those in non-RA subjects, the possibility of RA-specific mechanisms for these changes in patients with RA cannot be excluded. However, from this observational study, it is impossible to make inferences about the pathophysiological and clinical implications of lipid profile changes in RA. Thus, the reasons for these lipid changes in the RA population and the association of these trends with excess CV risk in RA are uncertain.

Strengths of the study include the population-based study design and the comprehensive data collection. The unique record linkage system allowed ascertainment of all RA cases from Olmsted County within the study period and provided comprehensive data on RA and non-RA subjects for the study. Our study takes advantage of the longitudinal design and parallel analysis of the lipid trends in patients with RA and the non-RA comparison cohort within the same calendar period.

This study has a number of potential limitations. First, patients with RA may have visited the doctor more often and consequently, may be more likely to have had more lipid measurements than non-RA subjects. Similarly, patients with abnormal lipid values are more likely to have repeat measurements. However, the number of lipid measurements was similar in the RA and non-RA cohorts. Further, this weakness was minimised during the statistical analysis by accounting for multiple lipid measurements per subject. In this observational study, we did not analyse the role of traditional CV risk factors, inflammatory characteristics and antirheumatic drugs in lipid profile changes in RA. The impact of these three potential contributors on the lipid profile in RA was shown previously7 9 19 32,–,34 and is beyond the scope of this study.

While data on lipid-lowering drugs were not available before 1997, this was unlikely to bias the results as the limitation applied equally to both the RA and non-RA cohorts. Although quantitative change in body weight in patients with RA during the study period was not significant, there may have been changes in body composition which were not measured and thus may have been missed. A decrease in muscle mass and an increase in fat mass are common in patients with RA and have been shown to be associated with dyslipidaemia.34,–,36 However, increased, not decreased TC and LDL levels would be expected in patients with RA with rheumatoid cachectic obesity,34 so these metabolic changes are unlikely to explain the observed lipid changes in patients with RA. Finally, during the calendar period of investigation the population of Olmsted County, Minnesota was predominantly white. Thus, the results may not be generalisable to non-white subjects. Except for the higher proportion of the population with higher educational levels, other sociodemographic characteristics of Olmsted County, Minnesota residents are similar to those of US white subjects.

In conclusion, patients with RA experienced a significant decrease in TC and LDL levels during the 5 years before RA incidence as compared with non-RA subjects. Lipid trends were otherwise similar in RA and non-RA cohorts during the 5 years before and 5 years after RA. The prevalence of abnormal TC or LDL measures significantly decreased in the RA, but not in the non-RA cohort, during the 5 years before the RA incidence/index date. These lipid changes in RA are unlikely to be solely due to lipid-lowering treatment or changes in BMI. The reasons and the clinical significance for the apparent changes in lipid profile before RA are uncertain. Further studies of the association of RA characteristics and antirheumatic drugs with lipid profile and CV outcomes in RA over time are underway.

The Evolving Science of Cancer Stem Cells

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A diagram showing stem cells and progenitor cells Stem cells can both self-replicate, as well as produce progenitors that differentiate into other, more mature cell types, such as endothelial cells. Similarly, a cancer stem cell is thought to self-replicate and produce progenitors that generate all of the cell types that make up a tumor. Click to Enlarge.

The theory of the cancer stem cell (CSC) has generated as much excitement and optimism as perhaps any area of cancer research over the last decade. Biologically, the theory goes, these cells are distinct from the other cells that form the bulk of a tumor in that they can self-perpetuate and produce progenitor cells, the way that traditional stem cells do. The progenitors’ job is then to repopulate tumor cells eradicated by treatments such as chemotherapy or radiation.

But for all the attention and fanfare CSC research has received, the findings reported to date are far from clear-cut, investigators acknowledge. For example, most of the studies that have identified human CSCs have used mouse xenograft assays and cells from only a small number of human tumor samples, making it difficult to draw firm conclusions. In addition, other researchers haven’t always been able to replicate initially reported findings. (See the sidebar: “Tools of the CSC Trade: Markers and Xenografts.”) And while these tumor-initiating cells, as they are also called, have been described as being a rare class, several studies have found that the number of cells that can form tumors in these mouse experiments is actually quite large, suggesting that perhaps CSCs aren’t such a privileged breed.

In other words, the idea of just what cancer stem cells are, and their role in different cancers, appears to be changing.

“The [stem cell] model has not been adequately tested in most cancers,” said Dr. Sean Morrison, who directs the Center for Stem Cell Biology at the University of Michigan. “I think that there are some cancers that do clearly follow a cancer stem cell model…But it will be more complicated than what’s been presented so far.”

An Evolving Idea

Unlike the random or “stochastic” model dominant in cancer research, which holds that nearly any cancer cell has the potential to form a tumor, the cancer stem cell model is one of a hierarchical organization, with the pluripotent cancer stem cell sitting ready and able to amass all of the components of the original tumor.

It’s also thought, with some experimental evidence to support it, that CSC pluripotency allows these cells to adapt and to resist chemotherapy, radiation therapy, and even current molecularly targeted therapies. If true, then these treatments may not harm the most lethal tumor cells, those that can lead to a recurrence with the production of a new set of progenitors.

Despite numerous studies published in the last 16 years that identified CSCs for different cancers—including colon, brain, pancreatic, and breast cancer—the consensus among researchers seems to be that the evidence is strongest for the first cancer in which a population of tumor-initiating cells was discovered, acute myeloid leukemia (AML), as well as for other blood cancers.

“The reason why it’s so much stronger for hematologic malignancies is because hematopoiesis research goes back 40 or 50 years and it’s very stem cell-based,” said Dr. Jean Wang, a stem cell researcher at the University of Toronto. “Whereas in solid tumors, there’s less of a foundation for identifying the normal cellular hierarchies and for [cell-surface] markers that identify different populations of cells like stem cells and progenitors.”

Even so, Dr. Wang believes the existence of CSCs is pretty well demonstrated for breast and brain cancers. But, she cautioned, “I don’t know if it applies to all cancers. In a lot [of cancers] it does seem to apply. But most of the markers we have right now are still very rough.”

Despite the evidence for CSC-like cells in a growing number of cancers, the theory clearly has its skeptics, who point to problems such as shortcomings in the mouse xenograft assay and the variable specificity of the cell-surface markers used to demarcate a CSC from a non-CSC.

“I still feel that it’s a concept yet to be proven,” said Dr. Barbara Vonderhaar, who, along with colleagues in NCI’s Center for Cancer Research, recently published a study identifying a population of CSC-like cells in estrogen receptor-negative breast cancer. “It’s certainly a good idea, but it’s only a hypothesis at this point. We still don’t have definitive proof that cancer stem cells exist.”

The CSC concept is “a work in transition,” said Dr. William Matsui, from the Johns Hopkins School of Medicine, whose lab studies the role of stem cells in hematologic cancers. “To me, as a clinical person, the ideal model is one where you can find something that is going to work in humans. We’re far from that.”

Case Study: Melanoma

One of the most well-known studies in the CSC literature came from Dr. Morrison’s lab in 2008. Earlier studies had suggested that, consistent with the CSC model, there was only a rare population of cells from human melanoma tumors that, when injected into mice with compromised immune systems (called NOD/SCID mice), could form new tumors.

But in a study published in Nature, Dr. Morrison’s team tweaked the common experimental approach: they used mice with immune systems that were even more impaired than NOD/SCID mice and waited longer to assess tumor growth. The result: approximately one in four randomly selected single cells taken from a human melanoma sample could form a tumor.

The results “made clear that estimates of the frequency of tumorigenic cells are far more assay-dependent than we realized,” Dr. Morrison said. In addition to factors such as the status of the mouse’s immune system in the experiments, he continued, “there are probably other variables that have a much bigger influence that we still haven’t discovered.”  (In AML, it’s worth noting, use of more immunocompromised mice does not significantly increase the number of cells that can form tumors.)

Researchers from Stanford University earlier this month reported in Nature that they had found a marker, CD271, that identified a somewhat unique population of cells that could produce melanoma in highly immunocompromised mice; anywhere from 2.5 percent to 41 percent of cells in their human tumor samples expressed the marker. In additional experiments using similar mice on which human skin was engrafted, only tumor cells with the marker could produce tumors and metastases in the mice. (In his lab, Dr. Morrison noted, the same marker did not differentiate tumor-forming from nontumor-forming cells.)

The fact that a fairly large percentage of the cells from the nine human melanoma tumors used in the study could initiate a tumor reflects a number of things, wrote lead author Dr. Andrew Boiko and colleagues in the Nature paper. Among them, an evolutionary type process selects for the survival of tumor cells that fail to normally differentiate during tumor development.

That might mean that a cancer stem cell isn’t necessarily part of the original tumor, but due to various factors or influences—such as interactions with the immune system or hypoxia—certain tumor cells, maybe many of them, can activate a stem cell-like “program.”

“I’m a firm believer that the microenvironment, the stem cell ‘niche,’ is every bit as important as the cell itself,” Dr. Vonderhaar said. “I don’t know if just any cell can become [a CSC], but there is a hierarchy of cells, and some may be able to function in a stem cell-like manner, and others may not.”

The CSC field itself, Dr. Matsui noted, needs to move more quickly beyond just determining whether these cells can grow tumors on their own, “and ask what other properties they might have that contribute to clinical outcomes.” Those might include their role in problems such as drug resistance or metastasis.

Some of the controversy surrounding CSCs “is a good thing,” Dr. Matsui said, “because it forces us to be more rigorous in our work. The more rigor we can get in the research, the more clinically applicable all of the ideas are going to be.”

source:NCI

Brain Cancer Incidence Trends Do Not Support Link to Cell Phones

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A new analysis by NCI researchers has turned up no evidence to support a link between cell phone use and brain cancer in the United States. The analysis was carried out in view of concerns about a possible link between widespread use of cell phones and brain cancer risk. With more than 279 million U.S. wireless subscribers today, the researchers reasoned that it should be possible to detect an increase in brain cancer rates over time if, in fact, cell phone use does contribute to risk of this particular cancer. The caveat would be that no effect would be expected if the induction period for brain tumors is very long or increased risk is limited to long-term users.

Dr. Peter Inskip and his colleagues in NCI’s Division of Cancer Epidemiology and Genetics used NCI’s SEER database to examine brain cancer incidence trends between 1992 and 2006. In almost all age groups and in both men and women, the trends for brain cancer during these years were, if anything, slightly downward.

The one exception was a statistically significant increasing trend among females in their twenties, but not males. This increase, however, was driven by cancers in the frontal lobe of the brain, which is not where the researchers would have expected to see an effect from cell phones. Studies have shown that other parts of the brain are more highly exposed to the radiofrequency radiation from cell phones.

The U.S. findings are consistent with a recent study of brain cancer incidence trends in four European countries. That study found no change in rates from 1998 to 2003, the period when possible associations between mobile phone use and cancer risk would likely be apparent assuming an induction period of 5 to 10 years.


Some Studies Suggest Antirejection Drugs Not Always Needed to Protect Kidney Graft

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Researchers are exploring the tantalizing prospect of identifying patients with kidney transplants who do not need to continue to take antirejection medicines to preserve their donated organ. At the very least, this line of research might enable physicians to recognize those patients with renal allografts who could take less immunosuppressive medicine, reducing the risks of infection and cancer associated with such drugs.

Figure 05071FA
Researchers are hoping to identify the rare patients with kidney transplants who do not need antirejection medicines, allowing them to avoid the adverse effects of such drugs. (Photo credit: AJPhoto/www.sciencesource.com)

Such hopes were raised by researchers in the United States and Europe who identified biological signatures of a small minority of patients who had stopped taking antirejection medicines for a variety of reasons, such as adverse effects or cost, yet still preserved their allograft function.

source:JAMA

The FDA Approves New Higher-Dose Aricept® For The Treatment Of Moderate-To-Severe Alzheimer’s Disease

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Eisai Inc. and Pfizer Inc. announced today that the U.S. Food and Drug Administration (FDA) approved a new once-daily, higher-dose Aricept (donepezil HCl) 23 milligram (mg) tablet for the treatment of moderate-to-severe Alzheimer’s disease (AD). Aricept 23 mg tablet offers another dosing option for patients with moderate-to-severe AD, for whom few treatments are available.

The approval of Aricept 23 mg tablet is based on data from a large head-to-head study of Aricept 23 mg tablet versus Aricept 10 mg tablet in over 1,400 patients with moderate-to-severe AD. The Aricept 23 mg tablet demonstrated a statistically significant improvement in cognition but did not achieve statistically significant improvement in global function, as compared to Aricept 10 mg tablet.

“Slowing the decline of cognitive symptoms is important at all stages of Alzheimer’s disease,” said Dr. Martin R. Farlow, professor and vice-chairman of research, department of neurology, Indiana University School of Medicine and lead author of the pivotal study publication. “Throughout the course of Alzheimer’s disease, caregivers are usually the first to notice changes in cognition. It’s important for families to talk with their doctor when they notice a worsening in cognitive function in their loved ones to reevaluate therapeutic needs.”

Based on the approved label, the recommended starting dose of Aricept is 5 mg once daily and can be increased to Aricept 10 mg once daily after four-to-six weeks. Moderate-to-severe AD patients who are established on a regimen of Aricept 10 mg tablet for at least three months are candidates for dose escalation to Aricept 23 mg tablet.

Nausea, vomiting, diarrhea and anorexia were the most common adverse events noted in the pivotal study of Aricept 23 mg tablet.

“We have a long-standing commitment to the AD community and recognize that there are few treatment options available,” said Lonnel Coats, president and CEO, Eisai Inc. “In drawing upon our heritage, we are proud to offer a new dosing option to caregivers and patients living with this debilitating condition.”

About Aricept (donepezil HCl)

Aricept is the first and only prescription medication approved by the FDA for the treatment of all stages of AD—mild, moderate and severe dementia of the Alzheimer’s type. It is not a cure for AD, but Aricept may help provide symptomatic benefits for some patients. Aricept may work differently for each person. For those who respond, symptoms may improve, they may stabilize or they may progress more slowly than without Aricept. Aricept is currently available in 5 mg tablet, 10 mg tablet, orally disintegrating tablet (5 mg and 10 mg) and now 23 mg tablet. The Aricept 23 mg tablet is expected to be available in U.S. pharmacies in August. Based upon the submission of the Aricept 23 mg tablet clinical trial data to the FDA, Aricept 23 mg tablet is expected to have three years of data exclusivity in the United States. Aricept is co-promoted in the United States by Eisai Inc. and Pfizer Inc.

Important Safety Information

Aricept may not be for everyone. People at risk for stomach ulcers or who take certain other medicines should tell their doctors because serious stomach problems, such as bleeding, may get worse.

People at risk for certain heart conditions should tell their doctor before starting Aricept because they may experience fainting. People with serious lung conditions and difficulty breathing, bladder problems or seizures should tell their doctor before using Aricept. Aricept 23 mg is associated with weight loss. Check with the doctor if this is a concern. Inform the doctor if the patient needs surgery requiring anesthesia while taking Aricept.

Some people may have nausea, diarrhea, difficulty sleeping, vomiting or muscle cramps. Incidence of nausea and vomiting were markedly greater in patients taking Aricept 23 mg/day versus patients taking Aricept 10 mg/day. Some people may feel tired or may have loss of appetite. If they persist, please talk to the doctor.

Why More Education Lowers Dementia Risk

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A  team of researchers from the United Kingdom and Finland has discovered why people who stay in education longer have a lower risk of developing dementia—a question that has puzzled scientists for the past decade.

Examining the brains of 872 people who had been part of three large ageing studies, and who before their deaths had completed questionnaires about their education, the researchers found that more education makes people better able to cope with changes in the brain associated with dementia.

Over the past decade, studies on dementia have consistently showed that the more time you spend in education, the lower your risk of dementia. For each additional year of education there is an 11% decrease in risk of developing dementia, this study reports.

However, these studies have been unable to determine whether or not education—which is linked to higher socioeconomic status and healthier lifestyles—protects the brain against dementia.

This is not the case, the new study lead by Professor Carol Brayne of the University of Cambridge has found. Instead, the study shows people with different levels of education have similar brain pathology but that those with more education are better able to compensate for the effects of dementia.

According to co-author Dr Hannah Keage of the University of Cambridge: “Previous research has shown that there is not a one-to-one relationship between being diagnosed with dementia during life and changes seen in the brain at death. One person may show lots of pathology in their brain while another shows very little, yet both may have had dementia. Our study shows education in early life appears to enable some people to cope with a lot of changes in their brain before showing dementia symptoms.”

Compared with previous research, this study was able to answer the question because of its large size and statistical power.

The studies have assessed participants for up to 20 years and are three of only six such studies in the world.

The results have important implications for public health at a time when populations in many countries are ageing.

“Education is known to be good for population health and equity. This study provides strong support for investment in early life factors which should have an impact on society and the whole lifespan. This is hugely relevant to policy decisions about the importance of resource allocation between health and education,” says Professor Brayne.

The results of this study are published in the journal Brain.

Diphtheria-Tetanus-Pertussis Vaccination and Dravet Syndrome

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Even when the onset of Dravet syndrome immediately followed DTP vaccination, the course and outcome were the same as in patients with onset remote from vaccination.

Recent research has shown that most patients who experience the onset of a severe encephalopathy with seizures after pertussis vaccination have severe myoclonic epilepsy of infancy (Dravet syndrome), a condition that is causally linked to de novo mutations of the sodium-channel gene SCN1A. Although the pertussis vaccination could precipitate the clinical onset of the disease, it cannot be the cause in patients who have the mutation. These researchers aimed to determine whether diphtheria-tetanus-pertussis (DTP) vaccination affects the timing of onset, clinical features, or outcome of Dravet syndrome. They retrospectively studied 40 patients who had (1) Dravet syndrome, (2) a de novo SCN1A mutation, and (3) records documenting the dates of DTP vaccination and seizure onset (to avoid recall bias).

The researchers compared participants who had a first seizure on the day of DTP vaccination or the next day (the vaccination-proximate group) with those who had their first seizure at a different time (the vaccination-distant group). The only difference between the two groups was that the vaccination-proximate group had their first seizure about 2 months earlier (mean age, 18.4 vs. 26.2 weeks). The groups did not differ in terms of SCN1A mutation type, subsequent seizure type, or intellectual outcome (median age at follow-up, 5.4 years).

Comment: This study provides additional, robust evidence against the lingering belief or misperception that vaccinations can cause or aggravate neurological disorders. The findings support the counterargument that vaccinations, like intercurrent infectious illnesses, can lower the seizure threshold and precipitate the first seizure of an epilepsy that the patient was genetically programmed to develop. This study did not involve any comparison of patients with Dravet syndrome who had received DTP vaccination and those who had not.

— Blaise F. D. Bourgeois, MD

Dr. Bourgeois is Professor of Neurology, Harvard Medical School, and Director, Division of Epilepsy and Clinical Neurophysiology, Children’s Hospital, Boston.

Published in Journal Watch Neurology July 27, 2010