Haitao Chu

Quantitating the Multiplicity of Infection with Human Immunodeficiency Virus Type 1 Subtype C Reveals a Non-Poisson Distribution of Transmitted Variants

ABSTRACT Identifying the specific genetic characteristics of successfully transmitted variants may prove central to the development of effective vaccine and microbicide interventions. Although human immunodeficiency virus transmission is associated with a population bottleneck, the extent to which different factors influence the diversity of transmitted viruses is unclear. We estimate here the number of transmitted variants in 69 heterosexual men and women with primary subtype C infections. From 1,505 env sequences obtained using a single genome amplification approach we show that 78% of infections involved single variant transmission and 22% involved multiple variant transmissions (median of 3). We found evidence for mutations selected for cytotoxic-T-lymphocyte or antibody escape and a high prevalence of recombination in individuals infected with multiple variants representing another potential escape pathway in these individuals. In a combined analysis of 171 subtype B and C transmission events, we found that infection with more than one variant does not follow a Poisson distribution, indicating that transmission of individual virions cannot be seen as independent events, each occurring with low probability. While most transmissions resulted from a single infectious unit, multiple variant transmissions represent a significant fraction of transmission events, suggesting that there may be important mechanistic differences between these groups that are not yet understood.

Illustrating bias due to conditioning on a collider

That conditioning on a common effect of exposure and outcome may cause selection, or collider-stratification, bias is not intuitive. We provide two hypothetical examples to convey concepts underlying bias due to conditioning on a collider. In the first example, fever is a common effect of influenza and consumption of a tainted egg-salad sandwich. In the second example, case-status is a common effect of a genotype and an environmental factor. In both examples, conditioning on the common effect imparts an association between two otherwise independent variables; we call this selection bias.

Basic Concepts and Methods for Joint Models of Longitudinal and Survival Data

Joint models for longitudinal and survival data are particularly relevant to many cancer clinical trials and observational studies in which longitudinal biomarkers (eg, circulating tumor cells, immune response to a vaccine, and quality-of-life measurements) may be highly associated with time to event, such as relapse-free survival or overall survival. In this article, we give an introductory overview on joint modeling and present a general discussion of a broad range of issues that arise in the design and analysis of clinical trials using joint models. To demonstrate our points throughout, we present an analysis from the Eastern Cooperative Oncology Group trial E1193, as well as examine some operating characteristics of joint models through simulation studies.

Network Meta-analysis of Margin Threshold for Women With Ductal Carcinoma In Situ

BACKGROUND Negative margins are associated with reduced risk of ipsilateral breast tumor recurrence (IBTR) for women with ductal carcinoma in situ (DCIS) treated with breast-conserving surgery (BCS). However, there is no consensus about the best minimum margin width. METHODS We searched the PubMed database for studies of DCIS published in English between January 1970 and July 2010 and examined the relationship between IBTR and margin status after BCS for DCIS. Women with DCIS were stratified into two groups, BCS with or without radiotherapy. We used frequentist and Bayesian approaches to estimate the odds ratios (OR) of IBTR for groups with negative margins and positive margins. We further examined specific margin thresholds using mixed treatment comparisons and meta-regression techniques. All statistical tests were two-sided. RESULTS We identified 21 studies published in 24 articles. A total of 1066 IBTR events occurred in 7564 patients, including BCS alone (565 IBTR events in 3098 patients) and BCS with radiotherapy (501 IBTR events in 4466 patients). Compared with positive margins, negative margins were associated with reduced risk of IBTR in patients with radiotherapy (OR = 0.46, 95% credible interval [CrI] = 0.35 to 0.59), and in patients without radiotherapy (OR = 0.34, 95% CrI = 0.24 to 0.47). Compared with patients with positive margins, the risk of IBTR for patients with negative margins was smaller (negative margin >0 mm, OR = 0.45, 95% CrI = 0.38 to 0.53; >2 mm, OR = 0.38, 95% CrI = 0.28 to 0.51; >5 mm, OR = 0.55, 95% CrI = 0.15 to 1.30; and >10 mm, OR = 0.17, 95% CrI = 0.12 to 0.24). Compared with a negative margin greater than 2 mm, a negative margin of at least 10 mm was associated with a lower risk of IBTR (OR = 0.46, 95% CrI = 0.29 to 0.69). We found a probability of .96 that a negative margin threshold greater than 10 mm is the best option compared with other margin thresholds. CONCLUSIONS Negative surgical margins should be obtained for DCIS patients after BCS regardless of radiotherapy. Within cosmetic constraint, surgeons should attempt to achieve negative margins as wide as possible in their first attempt. More studies are needed to understand whether margin thresholds greater than 10 mm are warranted.

Longitudinal changes in serum lipids among HIV‐infected men on highly active antiretroviral therapy

The aim of the study was to describe longitudinal changes in serum lipids among HIV‐infected men receiving highly active antiretroviral therapy (HAART) with long‐term follow‐up.

A statistical framework for Illumina DNA methylation arrays

MOTIVATION The Illumina BeadArray is a popular platform for profiling DNA methylation, an important epigenetic event associated with gene silencing and chromosomal instability. However, current approaches rely on an arbitrary detection P-value cutoff for excluding probes and samples from subsequent analysis as a quality control step, which results in missing observations and information loss. It is desirable to have an approach that incorporates the whole data, but accounts for the different quality of individual observations. RESULTS We first investigate and propose a statistical framework for removing the source of biases in Illumina Methylation BeadArray based on several positive control samples. We then introduce a weighted model-based clustering called LumiWCluster for Illumina BeadArray that weights each observation according to the detection P-values systematically and avoids discarding subsets of the data. LumiWCluster allows for discovery of distinct methylation patterns and automatic selection of informative CpG loci. We demonstrate the advantages of LumiWCluster on two publicly available Illumina GoldenGate Methylation datasets (ovarian cancer and hepatocellular carcinoma). AVAILABILITY R package LumiWCluster can be downloaded from http://www.unc.edu/∼pfkuan/LumiWCluster.

Comparison of Viral Env Proteins from Acute and Chronic Infections with Subtype C Human Immunodeficiency Virus Type 1 Identifies Differences in Glycosylation and CCR5 Utilization and Suggests a New Strategy for Immunogen Design

ABSTRACT Understanding human immunodeficiency virus type 1 (HIV-1) transmission is central to developing effective prevention strategies, including a vaccine. We compared phenotypic and genetic variation in HIV-1 env genes from subjects in acute/early infection and subjects with chronic infections in the context of subtype C heterosexual transmission. We found that the transmitted viruses all used CCR5 and required high levels of CD4 to infect target cells, suggesting selection for replication in T cells and not macrophages after transmission. In addition, the transmitted viruses were more likely to use a maraviroc-sensitive conformation of CCR5, perhaps identifying a feature of the target T cell. We confirmed an earlier observation that the transmitted viruses were, on average, modestly underglycosylated relative to the viruses from chronically infected subjects. This difference was most pronounced in comparing the viruses in acutely infected men to those in chronically infected women. These features of the transmitted virus point to selective pressures during the transmission event. We did not observe a consistent difference either in heterologous neutralization sensitivity or in sensitivity to soluble CD4 between the two groups, suggesting similar conformations between viruses from acute and chronic infection. However, the presence or absence of glycosylation sites had differential effects on neutralization sensitivity for different antibodies. We suggest that the occasional absence of glycosylation sites encoded in the conserved regions of env, further reduced in transmitted viruses, could expose specific surface structures on the protein as antibody targets.

Meta-analysis of diagnostic accuracy studies accounting for disease prevalence: alternative parameterizations and model selection.

In a meta-analysis of diagnostic accuracy studies, the sensitivities and specificities of a diagnostic test may depend on the disease prevalence since the severity and definition of disease may differ from study to study due to the design and the population considered. In this paper, we extend the bivariate nonlinear random effects model on sensitivities and specificities to jointly model the disease prevalence, sensitivities and specificities using trivariate nonlinear random-effects models. Furthermore, as an alternative parameterization, we also propose jointly modeling the test prevalence and the predictive values, which reflect the clinical utility of a diagnostic test. These models allow investigators to study the complex relationship among the disease prevalence, sensitivities and specificities; or among test prevalence and the predictive values, which can reveal hidden information about test performance. We illustrate the proposed two approaches by reanalyzing the data from a meta-analysis of radiological evaluation of lymph node metastases in patients with cervical cancer and a simulation study. The latter illustrates the importance of carefully choosing an appropriate normality assumption for the disease prevalence, sensitivities and specificities, or the test prevalence and the predictive values. In practice, it is recommended to use model selection techniques to identify a best-fitting model for making statistical inference. In summary, the proposed trivariate random effects models are novel and can be very useful in practice for meta-analysis of diagnostic accuracy studies.

DNA‐methylation profiling distinguishes malignant melanomas from benign nevi

DNA methylation, an epigenetic alteration typically occurring early in cancer development, could aid in the molecular diagnosis of melanoma. We determined technical feasibility for high‐throughput DNA‐methylation array‐based profiling using formalin‐fixed paraffin‐embedded tissues for selection of candidate DNA‐methylation differences between melanomas and nevi. Promoter methylation was evaluated in 27 common benign nevi and 22 primary invasive melanomas using a 1505 CpG site microarray. Unsupervised hierarchical clustering distinguished melanomas from nevi; 26 CpG sites in 22 genes were identified with significantly different methylation levels between melanomas and nevi after adjustment for age, sex, and multiple comparisons and with β‐value differences of ≥0.2. Prediction analysis for microarrays identified 12 CpG loci that were highly predictive of melanoma, with area under the receiver operating characteristic curves of >0.95. Of our panel of 22 genes, 14 were statistically significant in an independent sample set of 29 nevi (including dysplastic nevi) and 25 primary invasive melanomas after adjustment for age, sex, and multiple comparisons. This first report of a DNA‐methylation signature discriminating melanomas from nevi indicates that DNA methylation appears promising as an additional tool for enhancing melanoma diagnosis.

Propensity-weighted Long-term Risk of Urinary Adverse Events After Prostate Cancer Surgery, Radiation, or Both

BACKGROUND Prostate cancer is the second most common cancer in men and has high survivorship, yet little is known about the long-term risk of urinary adverse events (UAEs) after treatment. OBJECTIVE To compare the long-term UAE incidence across treatment and control groups. DESIGN, SETTING, AND PARTICIPANTS Using a matched-cohort design, we identified elderly men treated with external-beam radiotherapy (EBRT; n=44 318), brachytherapy (BT; n=14 259), EBRT+BT (n=11 835), radical prostatectomy (RP; n=26 970), RP+EBRT (n=1557), or cryotherapy (n=2115) for non-metastatic prostate cancer and 144 816 non-cancer control individuals from the population-based Surveillance, Epidemiology, and End Results-Medicare linked data from 1992-2007 with follow-up through 2009. OUTCOME MEASURES AND STATISTICAL ANALYSIS The incidence of treated UAEs and time from cancer treatment to first UAE were analyzed in terms of propensity-weighted survival. RESULTS Median follow-up was 4.14 yr. At 10 yr, all treatment groups experienced higher propensity-weighted cumulative UAE incidence than the control group (16.1%; hazard risk [HR] 1.0), with the highest incidence for RP+EBRT (37.8%; HR 3.19, 95% confidence interval [CI] 2.79-3.66), followed by BT+EBRT (28.4%; HR 1.97, CI 1.85-2.10), RP (26.6%; HR 2.44, CI 2.34-2.55), cryotherapy (23.4%; HR 1.56, CI 1.30-1.87), BT (19.8%; HR 1.43, CI 1.33-1.53), and EBRT (19.7%; HR 1.11, CI 1.07-1.16). Bladder outlet obstruction was the most common event. CONCLUSIONS Men undergoing RP, RP+EBRT, and BT+EBRT experienced the highest UAE risk at 10 yr, although UAEs accrued differently over extended follow-up. The significant background UAE rate among non-cancer control individuals yields a risk attributable to prostate cancer treatment that is 17% lower than prior estimates. PATIENT SUMMARY We show that treatment for prostate cancer, especially combinations of two treatments such as radiation and surgery, carries a significant risk of urinary adverse events such as urethral stricture. This risk increases with time since treatment, emphasizing that treatments have long-term effects.