Background

Although studies have reported a high prevalence of end-stage renal disease in human immunodeficiency virus (HIV)-infected individuals, little is known about moderate impairments in kidney function. Cystatin C measurement may be more sensitive than creatinine for detecting impaired kidney function in persons with HIV.

Methods

We evaluated kidney function in the Fat Redistribution and Metabolic Change in HIV Infection (FRAM) cohort, a representative sample of 1008 HIV-infected persons and 290 controls from the Coronary Artery Risk Development in Young Adults (CARDIA) study in the United States.

Results

Cystatin C level was elevated in HIV-infected individuals; the mean±SD cystatin C level was 0.92±0.22 mg/L in those infected with HIV and 0.76±0.15 mg/L in controls (P<.001). In contrast, both mean creatinine levels and estimated glomerular filtration rates appeared similar in HIV-infected individuals and controls (0.87±0.21 vs 0.85±0.19 mg/dL [to convert to micromoles per liter, multiply by 88.4] [P=.35] and 110±26 vs 106±23 mL/min/1.73 m2 [P=.06], respectively). Persons with HIV infection were more likely to have a cystatin C level greater than 1.0 mg/L (OR, 9.8; 95% confidence interval, 4.4-22.0 [P<.001]), a threshold demonstrated to be associated with increased risk for death and cardiovascular and kidney disease. Among participants with HIV, potentially modifiable risk factors for kidney disease, hypertension, and low high-density lipoprotein concentration were associated with a higher cystatin C level, as were lower CD4 lymphocyte count and coinfection with hepatitis C virus (all P<.001).

Conclusions

Individuals infected with HIV had substantially worse kidney function when measured by cystatin Clevel compared with HIV-negative controls, whereas mean creatinine levels and estimated glomerular filtration rates were similar. Cystatin C measurement could be a useful clinical tool to identify HIV-infected persons at increased risk for kidney and cardiovascular disease.

Summary

Visceral obesity is associated with insulin resistance, but the association of other regional adipose depots with insulin resistance is not understood. In HIV infection, buffalo hump (upper trunk fat) is associated, but the association of upper trunk fat with insulin resistance has not been examined in controls. To determine the independent association of adipose depots other than visceral with insulin resistance, we performed a cross-sectional analysis of controls and HIV-infected subjects in the Fat Redistribution and Metabolic Change in HIV Infection (FRAM) study, who had measurements of glucose, insulin, and adipose tissue volumes by whole-body magnetic resonance imaging. We studied 926 HIV-positive persons from 16 academic medical center clinics and trials units with demographic characteristics representative of US patients with HIV infection and 258 FRAM controls from the population-based Coronary Artery Risk Development in Young Adults study. We measured visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) volume in the legs, arms, lower trunk (back and abdomen), and upper trunk (back and chest) and assessed their association with the homeostasis model of assessment (HOMA) and HOMA >4 by stepwise multivariable analysis. The prevalence of HOMA >4 as a marker of insulin resistance was 28% among controls compared with 37% among HIV-infected subjects (P = 0.005). Among controls, those in the highest tertile of upper trunk SAT volume had an odds ratio (OR) of 9.0 (95% confidence interval [CI]: 2.4 to 34; P = 0.001) for having HOMA >4 compared with the lowest tertile, whereas in HIV-positive subjects, the OR was lower (OR = 2.09, 95% CI: 1.36 to 3.19; P = 0.001). Among controls, the highest tertile of VAT volume had an OR of 12.1 (95% CI: 3.2 to 46; P = 0.0002) of having HOMA >4 compared with the lowest tertile, whereas in HIV-positive subjects, the OR was 3.12 (95% CI: 2.0 to 4.8; P < 0.0001). After adjusting for VAT and upper trunk SAT, the association of other SAT depots with HOMA >4 did not reach statistical significance. Thus, VAT and upper trunk SAT are independently associated with insulin resistance in controls and in HIV-infected persons.

Objective

Coinfection with hepatitis C virus (HCV) is reported to be associated with a higher prevalence of lipodystrophy than HIV infection alone. We examine the association between HCV and adipose tissue volume in HIV-infected men and women.

Methods

Cross-sectional analysis of HIV-infected subjects from the study of Fat Redistribution and Metabolic Change in HIV Infection. MRI measured regional adipose tissue volume. Detectable HCV RNA defined HCV infection.

Results

Twenty percent of 792 men and 26% of 329 women were HIV/HCV-coinfected. HIV/HCV-coinfected and HIV-monoinfected women had similar amounts of subcutaneous adipose tissue (SAT) in the leg, lower trunk, upper trunk, and arm and similar amounts of visceral adipose tissue (VAT). Similar findings were seen in men, except in the leg and VAT. After adjustment, HCV infection remained associated with more leg fat in men (12.2%, 95% confidence interval [CI]: 0.3 to 25.3; P = 0.043). Among those on stavudine, HIV-monoinfected men had less leg fat (−7% effect per year of stavudine use, 95% CI: −9 to −5; P < 0.001); a weaker association was seen in HIV/HCV-coinfected men (−2% effect, 95% CI: −7 to 3; P = 0.45). Indinavir was associated with less leg fat (−4% in HIV-monoinfected men, 95% CI: −6 to −1; P = 0.002; −5% in HIV/HCV-coinfected men, 95% CI: −11 to 2; P = 0.14).

Conclusions

Our findings suggest that HIV/HCV coinfection is not associated with less SAT in men and women. HCV infection seems to mitigate the loss of leg fat seen in HIV-infected men on stavudine.

Background

Chronic hepatitis C virus infection is prevalent and often causes hepatic fibrosis, which can progress to cirrhosis and cause liver cancer or liver failure. Study of fibrosis progression often relies on imputing the time of infection, often as the reported age of first injection drug use. We sought to examine the accuracy of such imputation and implications for modeling factors that influence progression rates.

Methods

We analyzed cross-sectional data on hepatitis C antibody status and reported risk factor histories from two large studies, the Women's Interagency HIV Study and the Urban Health Study, using modern survival analysis methods for current status data to model past infection risk year by year. We compared fitted distributions of past infection risk to reported age of first injection drug use.

Results

Although injection drug use appeared to be a very strong risk factor, models for both studies showed that many subjects had considerable probability of having been infected substantially before or after their reported age of first injection drug use. Persons reporting younger age of first injection drug use were more likely to have been infected after, and persons reporting older age of first injection drug use were more likely to have been infected before.

Conclusion

In cross-sectional studies of fibrosis progression where date of HCV infection is estimated from risk factor histories, modern methods such as multiple imputation should be used to account for the substantial uncertainty about when infection occurred. The models presented here can provide the inputs needed by such methods. Using reported age of first injection drug use as the time of infection in studies of fibrosis progression is likely to produce a spuriously strong association of younger age of infection with slower rate of progression.

Background

High-throughput mutagenesis of the mammalian genome is a powerful means to facilitate analysis of gene function. Gene trapping in embryonic stem cells (ESCs) is the most widely used form of insertional mutagenesis in mammals. However, the rules governing its efficiency are not fully understood, and the effects of vector design on the likelihood of gene-trapping events have not been tested on a genome-wide scale.

Methodology/Principal Findings

In this study, we used public gene-trap data to model gene-trap likelihood. Using the association of gene length and gene expression with gene-trap likelihood, we constructed spline-based regression models that characterize which genes are susceptible and which genes are resistant to gene-trapping techniques. We report results for three classes of gene-trap vectors, showing that both length and expression are significant determinants of trap likelihood for all vectors. Using our models, we also quantitatively identified hotspots of gene-trap activity, which represent loci where the high likelihood of vector insertion is controlled by factors other than length and expression. These formalized statistical models describe a high proportion of the variance in the likelihood of a gene being trapped by expression-dependent vectors and a lower, but still significant, proportion of the variance for vectors that are predicted to be independent of endogenous gene expression.

Conclusions/Significance

The findings of significant expression and length effects reported here further the understanding of the determinants of vector insertion. Results from this analysis can be applied to help identify other important determinants of this important biological phenomenon and could assist planning of large-scale mutagenesis efforts.

Background

Published pharmaceutical industry–sponsored trials are more likely than non-industry-sponsored trials to report results and conclusions that favor drug over placebo. Little is known about potential biases in drug–drug comparisons. This study examined associations between research funding source, study design characteristics aimed at reducing bias, and other factors that potentially influence results and conclusions in randomized controlled trials (RCTs) of statin–drug comparisons.

Methods and Findings

This is a cross-sectional study of 192 published RCTs comparing a statin drug to another statin drug or non-statin drug. Data on concealment of allocation, selection bias, blinding, sample size, disclosed funding source, financial ties of authors, results for primary outcomes, and author conclusions were extracted by two coders (weighted kappa 0.80 to 0.97). Univariate and multivariate logistic regression identified associations between independent variables and favorable results and conclusions. Of the RCTs, 50% (95/192) were funded by industry, and 37% (70/192) did not disclose any funding source. Looking at the totality of available evidence, we found that almost all studies (98%, 189/192) used only surrogate outcome measures. Moreover, study design weaknesses common to published statin–drug comparisons included inadequate blinding, lack of concealment of allocation, poor follow-up, and lack of intention-to-treat analyses. In multivariate analysis of the full sample, trials with adequate blinding were less likely to report results favoring the test drug, and sample size was associated with favorable conclusions when controlling for other factors. In multivariate analysis of industry-funded RCTs, funding from the test drug company was associated with results (odds ratio = 20.16 [95% confidence interval 4.37–92.98], p < 0.001) and conclusions (odds ratio = 34.55 [95% confidence interval 7.09–168.4], p < 0.001) that favor the test drug when controlling for other factors. Studies with adequate blinding were less likely to report statistically significant results favoring the test drug.

Conclusions

RCTs of head-to-head comparisons of statins with other drugs are more likely to report results and conclusions favoring the sponsor's product compared to the comparator drug. This bias in drug–drug comparison trials should be considered when making decisions regarding drug choice.

Lisa Bero and colleagues found published trials comparing one statin with another were more likely to report results and conclusions favoring the sponsor's product than the comparison drug.

Editors' Summary

Background.

Randomized controlled trials are generally considered to be the most reliable type of experimental study for evaluating the effectiveness of different treatments. Randomization involves the assignment of participants in the trial to different treatment groups by the play of chance. Properly done, this procedure means that the different groups are comparable at outset, reducing the chance that outside factors could be responsible for treatment effects seen in the trial. When done properly, randomization also ensures that the clinicians recruiting participants into the trial cannot know the treatment group to which a patient will end up being assigned. However, despite these advantages, a large number of factors can still result in bias creeping in. Bias comes about when the findings of research appear to differ in some systematic way from the true result. Other research studies have suggested that funding is a source of bias; studies sponsored by drug companies seem to more often favor the sponsor's drug than trials not sponsored by drug companies

Why Was This Study Done?

The researchers wanted to more precisely understand the impact of different possible sources of bias in the findings of randomized controlled trials. In particular, they wanted to study the outcomes of “head-to-head” drug comparison studies for one particular class of drugs, the statins. Drugs in this class are commonly prescribed to reduce the levels of cholesterol in blood amongst people who are at risk of heart and other types of disease. This drug class is a good example for studying the role of bias in drug–drug comparison trials, because these trials are extensively used in decision making by health-policy makers.

What Did the Researchers Do and Find?

This research study was based on searching PubMed, a biomedical literature database, with the aim of finding all randomized controlled trials of statins carried out between January 1999 and May 2005 (reference lists also were searched). Only trials which compared one statin to another statin or one statin to another type of drug were included. The researchers extracted the following information from each article: the study's source of funding, aspects of study design, the overall results, and the authors' conclusions. The results were categorized to show whether the findings were favorable to the test drug (the newer statin), inconclusive, or not favorable to the test drug. Aspects of each study's design were also categorized in relation to various features, such as how well the randomization was done (in particular, the degree to which the processes used would have prevented physicians from knowing which treatment a patient was likely to receive on enrollment); whether all participants enrolled in the trial were eventually analyzed; and whether investigators or participants knew what treatment an individual was receiving.

One hundred and ninety-two trials were included in this study, and of these, 95 declared drug company funding; 23 declared government or other nonprofit funding while 74 did not declare funding or were not funded. Trials that were properly blinded (where participants and investigators did not know what treatment an individual received) were less likely to have conclusions favoring the test drug. However, large trials were more likely to favor the test drug than smaller trials. When looking specifically at the trials funded by drug companies, the researchers found various factors that predicted whether a result or conclusion favored the test drug. These included the impact of the journal publishing the results; the size of the trial; and whether funding came from the maker of the test drug. However, properly blinded trials were less likely to produce results favoring the test drug. Even once all other factors were accounted for, the funding source for the study was still linked with results and conclusions that favored the maker of the test drug.

What Do These Findings Mean?

This study shows that the type of sponsorship available for randomized controlled trials of statins was strongly linked to the results and conclusions of those studies, even when other factors were taken into account. However, it is not clear from this study why sponsorship has such a strong link to the overall findings. There are many possible reasons why this might be. Some people have suggested that drug companies may deliberately choose lower dosages for the comparison drug when they carry out “head-to-head” trials; this tactic is likely to result in the company's product doing better in the trial. Others have suggested that trials which produce unfavorable results are not published, or that unfavorable outcomes are suppressed. Whatever the reasons for these findings, the implications are important, and suggest that the evidence base relating to statins may be substantially biased.

Additional Information.

Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.0040184.

The James Lind Library has been created to help people understand fair tests of treatments in health care by illustrating how fair tests have developed over the centuries

The International Committee of Medical Journal Editors has provided guidance regarding sponsorship, authorship, and accountability

The CONSORT statement is a research tool that provides an evidence-based approach for reporting the results of randomized controlled trials

Good Publication Practice guidelines provide standards for responsible publication of research sponsored by pharmaceutical companies

Information from Wikipedia on Statins. Wikipedia is an internet encyclopedia anyone can edit

Background

The citation rate for articles is viewed as a measure of their importance and impact; however, little is known about what features of articles are associated with higher citation rate.

Methodology/Principal Findings

We conducted a cohort study of all original articles, regardless of study methodology, published in the Lancet, JAMA, and New England Journal of Medicine, from October 1, 1999 to March 31, 2000. We identified 328 articles. Two blinded, independent reviewers extracted, in duplicate, nine variables from each article, which were analyzed in both univariable and multivariable linear least-squares regression models for their association with the annual rate of citations received by the article since publication. A two-way interaction between industry funding and an industry-favoring result was tested and found to be significant (p = 0.02). In our adjusted analysis, the presence of industry funding and an industry-favoring result was associated with an increase in annual citation rate of 25.7 (95% confidence interval, 8.5 to 42.8) compared to the absence of both industry funding and industry-favoring results. Higher annual rates of citation were also associated with articles dealing with cardiovascular medicine (13.3 more; 95% confidence interval, 3.9 to 22.3) and oncology (12.6 more; 95% confidence interval, 1.2 to 24.0), articles with group authorship (11.1 more; 95% confidence interval, 2.7 to 19.5), larger sample size and journal of publication.

Conclusions/Significance

Large trials, with group authorship, industry-funded, with industry-favoring results, in oncology or cardiology were associated with greater subsequent citations.