Estimation in semiparametric transition measurement error models for longitudinal data

We consider semiparametric transition measurement error models for longitudinal data, where one of the covariates is measured with error in transition models, and no distributional assumption is made for the underlying unobserved covariate. An estimating equation approach based on the pseudo conditional score method is proposed. We show the resulting estimators of the regression coefficients are consistent and asymptotically normal. We also discuss the issue of efficiency loss. Simulation studies are conducted to examine the finite-sample performance of our estimators. The longitudinal AIDS Costs and Services Utilization Survey data are analyzed for illustration.

Proper analysis of secondary phenotype data in case-control association studies

Case-control association studies often collect extensive information on secondary phenotypes, which are quantitative or qualitative traits other than the case-control status. Exploring secondary phenotypes can yield valuable insights into biological pathways and identify genetic variants influencing phenotypes of direct interest. All publications on secondary phenotypes have used standard statistical methods, such as least-squares regression for quantitative traits. Because of unequal selection probabilities between cases and controls, the case-control sample is not a random sample from the general population. As a result, standard statistical analysis of secondary phenotype data can be extremely misleading. Although one may avoid the sampling bias by analyzing cases and controls separately or by including the case-control status as a covariate in the model, the associations between a secondary phenotype and a genetic variant in the case and control groups can be quite different from the association in the general population. In this article, we present novel statistical methods that properly reflect the case-control sampling in the analysis of secondary phenotype data. The new methods provide unbiased estimation of genetic effects and accurate control of false-positive rates while maximizing statistical power. We demonstrate the pitfalls of the standard methods and the advantages of the new methods both analytically and numerically. The relevant software is available at our website.

Mammographic findings of partial breast irradiation

RATIONALE AND OBJECTIVES

The aim of this study was to determine if patients who underwent partial-breast irradiation followed by segmental mastectomies had fewer mammographic changes on the first post-treatment mammogram than those who underwent segmental mastectomies followed by whole-breast irradiation.

MATERIALS AND METHODS

Subjects enrolled in a study of partial-breast irradiation therapy after segmental mastectomy (intraoperative radiation therapy) plus a random sample of patients who underwent segmental mastectomies followed by conventional whole-breast radiation therapy were identified through the institution's breast cancer database from March 2003 through February 2006. A radiologist specializing in breast imaging reviewed and recorded each patient's pretreatment mammogram for breast density and tumor location and the first post-treatment mammogram, obtained within the first year of treatment, for three common types of mammographic change seen after breast surgery and radiation treatment (breast edema, skin thickening, and surgical scarring), which when severe make it difficult to use mammography for continuing follow-up of the conserved breast. The extent of mammographic change was noted by the radiologist as minimal, moderate, or marked. The data were entered into a database, and statistical analysis was conducted using logistic regression models and chi(2) tests. The effect of breast density on mammographic change was also assessed.

RESULTS

The severity of edema was lower with decreasing breast density (P < .006). There was no apparent effect of breast density on the severity of skin thickening. The extent of surgical scarring decreased as breast density increased (P < .026). Analysis of the data from the cumulative logistic regression models demonstrated that even after controlling for breast density, patients who underwent whole-breast radiation therapy had significantly more edema (P = .003), skin thickening (P = .003), and surgical scarring than those who underwent intraoperative radiation therapy (P < .001).

CONCLUSION

Patients have a higher probability of having fewer post-treatment mammographic changes after partial-breast irradiation followed by segmental mastectomy than after breast conservation surgery followed by whole-breast irradiation.

Gamma frailty transformation models for multivariate survival times

We propose a class of transformation models for multivariate failure times. The class of transformation models generalize the usual gamma frailty model and yields a marginally linear transformation model for each failure time. Nonparametric maximum likelihood estimation is used for inference. The maximum likelihood estimators for the regression coefficients are shown to be consistent and asymptotically normal, and their asymptotic variances attain the semiparametric efficiency bound. Simulation studies show that the proposed estimation procedure provides asymptotically efficient estimates and yields good inferential properties for small sample sizes. The method is illustrated using data from a cardiovascular study.

Adjustment for missingness using auxiliary information in semiparametric regression

In this article, we study the estimation of mean response and regression coefficient in semiparametric regression problems when response variable is subject to nonrandom missingness. When the missingness is independent of the response conditional on high-dimensional auxiliary information, the parametric approach may misspecify the relationship between covariates and response while the nonparametric approach is infeasible because of the curse of dimensionality. To overcome this, we study a model-based approach to condense the auxiliary information and estimate the parameters of interest nonparametrically on the condensed covariate space. Our estimators possess the double robustness property, i.e., they are consistent whenever the model for the response given auxiliary covariates or the model for the missingness given auxiliary covariate is correct. We conduct a number of simulations to compare the numerical performance between our estimators and other existing estimators in the current missing data literature, including the propensity score approach and the inverse probability weighted estimating equation. A set of real data is used to illustrate our approach.

Regression splines in the time-dependent coefficient rates model for recurrent event data

Many epidemiologic studies involve the occurrence of recurrent events and much attention has been given for the development of modeling techniques that take into account the dependence structure of multiple event data. This paper presents a time-dependent coefficient rates model that incorporates regression splines in its estimation procedure. Such methods would be appropriate in situations where the effect of an exposure or covariates changes over time in recurrent event data settings. The finite sample properties of the estimators are studied via simulation. Using data from a randomized community trial that was designed to evaluate the effect of vitamin A supplementation on recurrent diarrheal episodes in small children, we model the functional form of the treatment effect on the time to the occurrence of diarrhea. The results describe how this effect varies over time. In summary, we observed a major impact of the vitamin A supplementation on diarrhea after 2 months of the dosage, with the effect diminishing after the third dosage. The proposed method can be viewed as a flexible alternative to the marginal rates model with constant effect in situations where the effect of interest may vary over time.

Computerized assessment of vessel morphological changes during treatment of glioblastoma multiforme: report of a case imaged serially by MRA over four years

A patient with glioblastoma multiforme underwent serial computerized analysis of tumor-associated vasculature defined from magnetic resonance angiographic (MRA) scans obtained over almost a four year period. The clinical course included tumor resection with subsequent radiation therapy, a long symptom-free interval, emergence of a new malignant focus, resection of that focus, a stroke, and treatment with chemotherapy and anti-angiogenic therapy. Image analysis methods included segmentation of vessels from each MRA and statistical comparison of vessel morphology over 4 regions of interest (the initial tumor site, the second tumor site, a distant control region, and the entire brain) to the same 4 regions of interest in 50 healthy volunteers (26 females and 24 males; mean age 39 years). Results suggested that following completion of focal radiation therapy (RT) vessel shape abnormalities, if elevated at the time of RT completion, may progressively normalize for months in focal regions, that progressively severe vessel shape abnormalities can precede the emergence of a gadolinium enhancing lesion by months, that lesion resection can produce a dramatic but highly transient drop in abnormal vessel tortuosity both focally and globally, and that treatment with anti-angiogenic agents does not necessarily normalize vessel shape. Quantitative measurements of vessel morphology as defined from MRA may provide useful insights into tumor development and response to therapy.

Insurance status and the severity of breast cancer at the time of diagnosis

RATIONALE AND OBJECTIVES

To evaluate how the insurance status of women diagnosed with breast cancer correlates with size and stage at the time of diagnosis.

METHODS AND MATERIALS

The age-adjusted incidence of early- and late-stage breast cancer as determined by the tumor node metastasis classification system of stages in situ, local, regional, or distant was calculated for insured and uninsured women from our institution's database between 2002 and 2004. Late-stage breast cancer was defined as present when patients had either regional or distant disease. Statistical analysis was conducted using generalized linear models and chi(2) tests.

RESULTS

There were a total of 617 patients in our retrospective study. Of these, 564 (91.4%) had insurance and 53 (8.6%) were uninsured. Four hundred forty-seven (72.4%) patients were Caucasian and 170 (27.6%) patients were non-Caucasian. Of the 463 patients with early-stage breast cancer (0, I, or II), 433 (93.5%) had insurance and 30 (6.5%) were uninsured. Of the 154 patients with late-stage breast cancer (III or IV), 131 (85.1%) had insurance and 23 (14.9%) patients were uninsured. Analysis demonstrated that there was a significant effect in the insurance status on cancer stage (P = .006) and tumor size (P = .010). Compared to insured patients, uninsured patients had a 66% higher likelihood of presenting with a late-stage cancer and larger tumor. The analysis from the chi(2) test also supports the above with a significant association between patients' cancer stage and insurance status (P = .001) and also between tumor size and insurance status (P = .001). Patients' ages and geographic locations were not significant correlated with size and stage, but non-Caucasians had a significantly higher risk of larger tumors and more advanced stage than Caucasians (P < .005).

CONCLUSIONS

Uninsured, non-Caucasian patients have a higher probability of presenting with a more advanced stage of breast cancer and larger tumor size than patients with insurance in a large university multidisciplinary breast cancer population.

Semiparametric transformation models with random effects for joint analysis of recurrent and terminal events

We propose a broad class of semiparametric transformation models with random effects for the joint analysis of recurrent events and a terminal event. The transformation models include proportional hazards/intensity and proportional odds models. We estimate the model parameters by the nonparametric maximum likelihood approach. The estimators are shown to be consistent, asymptotically normal, and asymptotically efficient. Simple and stable numerical algorithms are provided to calculate the parameter estimators and to estimate their variances. Extensive simulation studies demonstrate that the proposed inference procedures perform well in realistic settings. Applications to two HIV/AIDS studies are presented.

Cumulative life course and adult socioeconomic status and markers of inflammation in adulthood

OBJECTIVE

To examine the association between cumulative life course and adult socioeconomic status (SES) and adult levels of inflammatory risk markers (fibrinogen, white blood cell count (WBC), C-reactive protein (CRP), von Willebrand factor (vWF) and an overall inflammatory score).

DESIGN

Retrospective cohort study.

SETTING

12,681 white and African-American participants in the Atherosclerosis Risk in Communities (ARIC) study and two ancillary studies.

METHODS

Participants provided information on SES and place of residence in childhood and young (30-40 years) and mature (45+) adulthood. Residences were linked to census data for neighbourhood SES information. Multiple imputation (MI) was used for missing data. Linear regression and adjusted geometric means were used to estimate the effects of SES on inflammatory risk marker levels.

RESULTS

Graded, statistically significant associations were observed between greater cumulative life-course exposure to low education and social class and elevated levels of fibrinogen and WBC among white participants. Stronger graded, statistically significant associations were observed between low adult education, social class and neighbourhood SES and elevated inflammatory levels. Associations were weaker and less consistent in African-Americans. Covariate adjustment attenuated results but many associations remained strong.

CONCLUSIONS

Our results suggest that cumulative exposure to adverse SES conditions across the life course and low adult SES are associated with an elevated systemic inflammatory burden in adulthood. Chronic systemic inflammation may be one pathway linking low life-course SES and elevated cardiovascular disease risk.

SEMIPARAMETRIC TRANSFORMATION MODELS WITH RANDOM EFFECTS FOR CLUSTERED FAILURE TIME DATA

We propose a general class of semiparametric transformation models with random effects to formulate the effects of possibly time-dependent covariates on clustered or correlated failure times. This class encompasses all commonly used transformation models, including proportional hazards and proportional odds models, and it accommodates a variety of random-effects distributions, particularly Gaussian distributions. We show that the nonparametric maximum likelihood estimators of the model parameters are consistent, asymptotically normal and asymptotically efficient. We develop the corresponding likelihood-based inference procedures. Simulation studies demonstrate that the proposed methods perform well in practical situations. An illustration with a well-known diabetic retinopathy study is provided.

Blood vessel morphologic changes depicted with MR angiography during treatment of brain metastases: a feasibility study

PURPOSE

To prospectively determine if magnetic resonance (MR) angiography can depict intracranial vascular morphologic changes during treatment of brain metastases from breast cancer and if serial quantitative vessel tortuosity measurements can be used to predict tumor treatment response sooner than traditional methods.

MATERIALS AND METHODS

Institutional review board approval and informed consent were obtained for this HIPAA-compliant study. Twenty-two women aged 31-61 years underwent brain MR angiography prior to and 2 months after initiation of lapatinib therapy for brain metastases from breast cancer. Vessels were extracted from MR angiograms with a computer program. Changes in vessel number, radius, and tortuosity were calculated mathematically, normalized with values obtained in 34 healthy control subjects (19 women, 15 men; age range, 19-72 years), and compared with subsequent assessments of tumor volume and clinical course.

RESULTS

All patients exhibited abnormal vessel tortuosity at baseline. Nineteen (86%) patients did not exhibit improvement in vessel tortuosity at 2-month follow-up, and all patients demonstrated tumor growth at 4-month follow-up. Vessel tortuosity measurements enabled us to correctly predict treatment failure 1-2 months earlier than did traditional methods. Three (14%) patients had quantitative improvement in vessel tortuosity at 2-month follow-up, with drop out of small abnormal vessels and straightening of large vessels. Each of the two patients for whom further follow-up data were available responded to treatment for more than 6 months.

CONCLUSION

Study results established the feasibility of using MR angiography to quantify vessel shape changes during therapy. Although further research is required, results suggest that changes in vessel tortuosity might enable early prediction of tumor treatment response.

Preventing facial recognition when rendering MR images of the head in three dimensions

In the United States it is not allowed to make public any patient-specific information without the patient's consent. This ruling has led to difficulty for those interested in sharing three-dimensional (3D) images of the head and brain since a patient's face might be recognized from a 3D rendering of the skin surface. Approaches employed to date have included brain stripping and total removal of the face anterior to a cut plane, each of which lose potentially important anatomical information about the skull surface, air sinuses, and orbits. This paper describes a new approach that involves (a) definition of a plane anterior to which the face lies, and (b) an adjustable level of deformation of the skin surface anterior to that plane. On the basis of a user performance study using forced choices, we conclude that approximately 30% of individuals are at risk of recognition from 3D renderings of unaltered images and that truncation of the face below the level of the nose does not preclude facial recognition. Removal of the face anterior to a cut plane may interfere with accurate registration and may delete important anatomical information. Our new method alters little of the underlying anatomy and does not prevent effective registration into a common coordinate system. Although the methods presented here were not fully effective (one subject was consistently recognized under the forced choice study design even at the maximum deformation level employed) this paper may point a way toward solution of a difficult problem that has received little attention in the literature.

Efficient resampling methods for nonsmooth estimating functions

We propose a simple and general resampling strategy to estimate variances for parameter estimators derived from nonsmooth estimating functions. This approach applies to a wide variety of semiparametric and nonparametric problems in biostatistics. It does not require solving estimating equations and is thus much faster than the existing resampling procedures. Its usefulness is illustrated with heteroscedastic quantile regression and censored data rank regression. Numerical results based on simulated and real data are provided.

Drinking water arsenic exposure and blood pressure in healthy women of reproductive age in Inner Mongolia, China

The extremely high exposure levels evaluated in prior investigations relating elevated levels of drinking water arsenic and hypertension prevalence make extrapolation to potential vascular effects at lower exposure levels very difficult. A cross-sectional study was conducted on 8790 women who had recently been pregnant in an area of Inner Mongolia, China known to have a gradient of drinking water arsenic exposure. This study observed increased systolic blood pressure levels with increasing drinking water arsenic, at lower exposure levels than previously reported in the literature. As compared to the referent category (below limit of detection to 20 microg of As/L), the overall population mean systolic blood pressure rose 1.29 mm Hg (95% CI 0.82, 1.75), 1.28 mm Hg (95% CI 0.49, 2.07), and 2.22 mm Hg (95% CI 1.46, 2.97) as drinking water arsenic concentration increased from 21 to 50, 51 to 100, and >100 microg of As/L, respectively. Controlling for age and body weight (n=3260), the population mean systolic blood pressure rose 1.88 mm Hg (95% CI 1.03, 2.73), 3.90 mm Hg (95% CI 2.52, 5.29), and 6.83 mm Hg (95% CI 5.39, 8.27) as drinking water arsenic concentration increased, respectively. For diastolic blood pressure effect, while statistically significant, was not as pronounced as systolic blood pressure. Mean diastolic blood pressure rose 0.78 mm Hg (95% CI 0.39, 1.16), 1.57 mm Hg (95% CI 0.91, 2.22) and 1.32 mm Hg (95% CI 0.70, 1.95), respectively, for the overall population and rose 2.11 mm Hg (95% CI 1.38, 2.84), 2.74 mm Hg (95% CI 1.55, 3.93), and 3.08 mm Hg (95% CI 1.84, 4.31), respectively, for the adjusted population (n=3260) at drinking water arsenic concentrations of 21 to 50, 51 to 100, and >100 microg of As/L. If our study results are confirmed in other populations, the potential burden of cardiovascular disease attributable to drinking water arsenic is significant.

Power calculation for case-cohort studies with nonrare events

Case-cohort design has been advocated in many epidemiologic studies when studying rare diseases or events. In this design, with a rare event, all the events are selected for risk-factor assessment. When the event is not rare, it is desirable to consider a generalized case-cohort design, where only a fraction of events are sampled. We provide a valid test statistic to compare hazards functions between two samples for this generalized design and give a method for calculating power. Our result generalizes the result in Cai and Zeng (2004, Biometrics60, 1015-1024), and it shows numerically that efficiency loss due to sampling only part of the events is very low under nonrare-events situation.

Tumor therapeutic response and vessel tortuosity: preliminary report in metastatic breast cancer

No current non-invasive method is capable of assessing the efficacy of brain tumor therapy early during treatment. We outline an approach that evaluates tumor activity via statistical analysis of vessel shape using vessels segmented from MRA. This report is the first to describe the changes in vessel shape that occur during treatment of metastatic brain tumors as assessed by sequential MRA. In this preliminary study of 16 patients undergoing treatment for metastatic breast cancer we conclude that vessel shape may predict tumor response several months in advance of traditional methods.

Kidney disease in life-course socioeconomic context: the Atherosclerosis Risk in Communities (ARIC) Study

BACKGROUND

Persons belonging to the working class or living in an adverse social environment at particular periods of their life course may have an increased risk of chronic kidney disease (CKD).

METHODS

This hypothesis was examined among participants of the Life Course Socioeconomic Status Study, an ancillary study of the Atherosclerosis Risk in Communities Study, conducted in 2001 (mean age, 67.4 years; N = 12,631). CKD was defined by hospital discharge diagnosis and/or estimated glomerular filtration rate less than 45 mL/min/1.73 m(2) (<0.75 mL/s/1.73 m(2)). Social class was categorized as working class or non-working class at ages 30, 40, or 50 years. Area-level socioeconomic status was based on a composite of census scores during the same period. Adjusted odds ratios were obtained within strata of white and African-American race.

RESULTS

The adjusted odds ratio of CKD for persons belonging to the working class versus non-working class at age 30 was 1.4 (95% confidence interval, 1.0 to 2.0) in whites and 1.9 (95% confidence interval, 1.1 to 3.0) in African Americans. Working class membership was associated with CKD, even at earlier stages of adult life, and class was associated more strongly with CKD than was education. Working class membership also suggested a stronger association with CKD among African Americans than whites, independent of diabetes and hypertension status. At later periods in the life course, area socioeconomic status was associated with CKD.

CONCLUSION

Socioeconomic factors, including area socioeconomic status and social class, are associated with CKD and may account for some of the racial disparity in kidney disease.

Early-life and adult socioeconomic status and inflammatory risk markers in adulthood

BACKGROUND

Associations between childhood and adult socioeconomic status (SES) and adult levels of inflammatory markers (C-reactive protein [CRP], fibrinogen, white blood cell count [WBC], and von Willebrand factor [vWF]) were examined in the Atherosclerosis Risk in Communities (ARIC) Study cohort.

METHODS

A total of 12,681 white and African-American participants provided information on SES (via education and social class) and place of residence in childhood and adulthood. Residences were linked to census data for neighborhood SES information. Multiple imputation was used to impute missing data. Hierarchical and linear regression were used to estimate the effects of SES and possible mediation by adult cardiovascular disease (CVD) risk factors.

FINDINGS

Low childhood social class and education were associated with elevated levels of CRP, fibrinogen, WBC, and vWF (increments of 17%, 2%, 4% and 3% for lowest versus highest education in childhood, respectively) among whites. Findings were less consistent among African-Americans. Adult SES was more strongly associated with inflammation than childhood SES. Individual-level SES measures were more consistently associated with inflammation than neighborhood-level measures. Fibrinogen and WBC showed the most consistent associations with SES; the largest changes in inflammation by SES were observed for CRP. Covariate adjustment strongly attenuated these associations. Mediation of the SES-inflammation associations by BMI, smoking and HDL cholesterol (HDL-C) are suggested by these data.

CONCLUSION

Low individual- and neighborhood-level SES in childhood and adulthood are associated with modest increments in adult inflammatory burden. These associations may operate through the influence of low SES on traditional CVD risk factors, especially BMI, smoking and HDL-C.

Association of polymorphisms in the CRP gene with circulating C-reactive protein levels and cardiovascular events

CONTEXT

C-reactive protein (CRP) is an inflammation protein that may play a role in the pathogenesis of cardiovascular disease (CVD).

OBJECTIVE

To assess whether polymorphisms in the CRP gene are associated with plasma CRP, carotid intima-media thickness (CIMT), and CVD events.

DESIGN, SETTING, AND PARTICIPANTS

In the prospective, population-based Cardiovascular Health Study, 4 tag single-nucleotide polymorphisms (SNPs) (1919A/T, 2667G/C, 3872G/A, 5237A/G) were genotyped in 3941 white (European American) participants and 5 tag SNPs (addition of 790A/T) were genotyped in 700 black (African American) participants, aged 65 years or older, all of whom were without myocardial infarction (MI) or stroke before study entry. Median follow-up was 13 years (1989-2003).

MAIN OUTCOME MEASURES

Baseline CIMT; occurrence of MI, stroke, and CVD mortality during follow-up.

RESULTS

In white participants, 461 incident MIs, 491 incident strokes, and 490 CVD-related deaths occurred; in black participants, 67 incident MIs, 78 incident strokes, and 75 CVD-related deaths occurred. The 1919T and 790T alleles were associated with higher CRP levels in white and black participants, respectively. The 3872A allele was associated with lower CRP levels in both populations, and the 2667C allele was associated with lower CRP levels in white participants only. There was no association between CIMT and any CRP gene polymorphism in either population. In white participants, the 1919T allele was associated with increased risk of stroke for TT vs AA (hazard ratio [HR], 1.40; 95% confidence interval [CI], 1.06-1.87) and for CVD mortality (HR, 1.40; 95% CI, 1.10-1.90). In black participants, homozygosity for the 790T allele was associated with a 4-fold increased risk of MI compared with homozygosity for the 790A allele (95% CI, 1.58-10.53). The minor alleles of the 2 SNPs associated with lower plasma CRP concentration in white participants (2667C and 3872A) were associated with decreased risk of CVD mortality.

CONCLUSIONS

Genetic variation in the CRP gene is associated with plasma CRP levels and CVD risk in older adults.

A semiparametric additive rates model for recurrent event data

Recurrent event data often arise in biomedical studies, with examples including hospitalizations, infections, and treatment failures. In observational studies, it is often of interest to estimate the effects of covariates on the marginal recurrent event rate. The majority of existing rate regression methods assume multiplicative covariate effects. We propose a semiparametric model for the marginal recurrent event rate, wherein the covariates are assumed to add to the unspecified baseline rate. Covariate effects are summarized by rate differences, meaning that the absolute effect on the rate function can be determined from the regression coefficient alone. We describe modifications of the proposed method to accommodate a terminating event (e.g., death). Proposed estimators of the regression parameters and baseline rate are shown to be consistent and asymptotically Gaussian. Simulation studies demonstrate that the asymptotic approximations are accurate in finite samples. The proposed methods are applied to a state-wide kidney transplant data set.

Structural inference in transition measurement error models for longitudinal data

We propose a new class of models, transition measurement error models, to study the effects of covariates and the past responses on the current response in longitudinal studies when one of the covariates is measured with error. We show that the response variable conditional on the error-prone covariate follows a complex transition mixed effects model. The naive model obtained by ignoring the measurement error correctly specifies the transition part of the model, but misspecifies the covariate effect structure and ignores the random effects. We next study the asymptotic bias in naive estimator obtained by ignoring the measurement error for both continuous and discrete outcomes. We show that the naive estimator of the regression coefficient of the error-prone covariate is attenuated, while the naive estimators of the regression coefficients of the past responses are generally inflated. We then develop a structural modeling approach for parameter estimation using the maximum likelihood estimation method. In view of the multidimensional integration required by full maximum likelihood estimation, an EM algorithm is developed to calculate maximum likelihood estimators, in which Monte Carlo simulations are used to evaluate the conditional expectations in the E-step. We evaluate the performance of the proposed method through a simulation study and apply it to a longitudinal social support study for elderly women with heart disease. An additional simulation study shows that the Bayesian information criterion (BIC) performs well in choosing the correct transition orders of the models.

Consensus review: A method of assessment of calcifications that appropriately undergo a six-month follow-up

RATIONALE AND OBJECTIVES

Breast calcifications seen on mammography may be associated with benign conditions or malignancies. Accurate characterization of these calcifications is crucial to providing optimal care that may spare women unnecessary biopsies and appropriately allow interval mammography. The purpose of this study is to determine if consensus characterization of calcifications by two breast imaging experts using standardized criteria can establish that follow-up is a safe option.

MATERIALS AND METHODS

For this retrospective study, our breast imaging database was reviewed and the cases imaged between the years 1999 and 2001 were used to identify patients with calcifications who were recommended for a six-month follow-up or biopsy. All cases had been prospectively assessed by at least two expert breast imagers using standardized features to assess the findings before a recommendation for follow-up or a biopsy was made. A retrospective chart review examining the radiology reports was done to determine the percentage of women from each of the two groups who developed malignancies.

RESULTS

Of 744 patients who had mammographically identified clusters of calcifications, 490 clusters (409 single and 81 multiple) were diagnosed as probably-benign, and a short-interval 6-month follow-up was recommended. Of these calcifications followed for three years, only two (0.5%) of the single clusters proved to be malignant, and malignancy was diagnosed at the 12-month follow-up examination. In both cases, the women were diagnosed with ductal carcinoma in situ (DCIS). Of 254 clusters recommended for biopsy, 242 (215 single and 27 multiple) underwent biopsy. A total of 70 cancers were diagnosed: 54 (77.1%) were DCIS and 16 (22.9%) were primary invasive mammary carcinoma (10 cases of invasive ductal carcinoma, 3 cases of invasive lobular carcinoma, 2 cases of invasive ductal carcinoma with DCIS, and one case of invasive mucinous carcinoma with DCIS). Twenty-nine percent of women who had a biopsy performed had calcifications associated with malignancy. In contrast, in the women whose calcifications were followed by mammography, only 0.5% went on to develop malignancies.

CONCLUSION

Consensus review of calcifications by two breast imagers using standardized criteria is a safe follow-up option.

Malignancy-associated vessel tortuosity: a computer-assisted, MR angiographic study of choroid plexus carcinoma in genetically engineered mice

BACKGROUND AND PURPOSE

The ability to assess tumor malignancy and monitor treatment response noninvasively would be of value to both clinicians and animal investigators. This report describes the MR imaging characteristics of a genetically engineered mouse model of choroid plexus carcinoma (CPC) during tumor growth and progression to malignancy. We assess the ability of vessel tortuosity measurements, as calculated from high-resolution MR angiographic (MRA) images, to detect emerging CPC cancers.

METHODS

MR images of 9 healthy mice and of 20 CPC mice with precancerous choroid dysplasia or with cancer over a wide range of sizes were analyzed. Two vessel tortuosity measures and a measure of vessel attenuation (vessel count) were calculated from MRA images. Malignancy assessment was based upon a statistical analysis of vessel tortuosity, by using an equation derived from an earlier study of human brain tumor patients.

RESULTS

Choroid dysplasia was correctly judged nonmalignant. On the basis of vessel count, neoangiogenesis could not be detected until cancers were full-blown and had reached a volume of approximately 80 mm3. Vessel tortuosity measurements, however, correctly identified emerging malignancy in lesions larger than 0.3 mm3.

CONCLUSION

To the best of our knowledge, this report provides the first description of in vivo, MR imaging characteristics of genetically engineered CPC mice during the progression from dysplasia to cancer. Vessel tortuosity measurements offer promise of correctly defining even tiny tumors as malignant.

Efficient semiparametric estimation of haplotype-disease associations in case-cohort and nested case-control studies

Estimating the effects of haplotypes on the age of onset of a disease is an important step toward the discovery of genes that influence complex human diseases. A haplotype is a specific sequence of nucleotides on the same chromosome of an individual and can only be measured indirectly through the genotype. We consider cohort studies which collect genotype data on a subset of cohort members through case-cohort or nested case-control sampling. We formulate the effects of haplotypes and possibly time-varying environmental variables on the age of onset through a broad class of semiparametric regression models. We construct appropriate nonparametric likelihoods, which involve both finite- and infinite-dimensional parameters. The corresponding nonparametric maximum likelihood estimators are shown to be consistent, asymptotically normal, and asymptotically efficient. Consistent variance-covariance estimators are provided, and efficient and reliable numerical algorithms are developed. Simulation studies demonstrate that the asymptotic approximations are accurate in practical settings and that case-cohort and nested case-control designs are highly cost-effective. An application to a major cardiovascular study is provided.

Maximum likelihood estimation of haplotype effects and haplotype-environment interactions in association studies

The associations between haplotypes and disease phenotypes offer valuable clues about the genetic determinants of complex diseases. It is highly challenging to make statistical inferences about these associations because of the unknown gametic phase in genotype data. We describe a general likelihood-based approach to inferring haplotype-disease associations in studies of unrelated individuals. We consider all possible phenotypes (including disease indicator, quantitative trait, and potentially censored age at onset of disease) and all commonly used study designs (including cross-sectional, case-control, cohort, nested case-control, and case-cohort). The effects of haplotypes on phenotype are characterized by appropriate regression models, which allow various genetic mechanisms and gene-environment interactions. We present the likelihood functions for all study designs and disease phenotypes under Hardy-Weinberg disequilibrium. The corresponding maximum likelihood estimators are approximately unbiased, normally distributed, and statistically efficient. We provide simple and efficient numerical algorithms to calculate the maximum likelihood estimators and their variances, and implement these algorithms in a freely available computer program. Extensive simulation studies demonstrate that the proposed methods perform well in realistic situations. An application to the Carolina Breast Cancer Study reveals significant haplotype effects and haplotype-smoking interactions in the development of breast cancer.

Effect of salbutamol on nasal symptoms and mast cell degranulation induced by adenosine 5' monophosphate nasal challenge

BACKGROUND

In addition to its well-known functional agonism at the level of beta(2) adrenergic receptors on airways smooth muscle cells, salbutamol appears to have additional protective effects, possibly through an inhibition of mast cell activation.

OBJECTIVE

The aim of this study is to provide the first evidence in vivo of inhibition of human mast cell activation by salbutamol.

METHODS

Nine atopic subjects received placebo and salbutamol (5 mg/mL) 15 min before an adenosine 5' monophosphate (AMP) nasal provocation in a double-blind crossover study design. The nasal lavage was collected from these subjects prior to or 3, 5, 15 or 30 min after the AMP nasal challenge, and concentrations of histamine and tryptase in the nasal lavage were measured.

RESULTS

AMP nasal provocation produced considerable sneezing and induced a transient increase in histamine and tryptase release with peak values achieved at 3 min after the challenge in all the subjects studied. Compared with placebo, salbutamol significantly attenuated the release of histamine and tryptase induced by AMP challenge (P=0.048 and 0.020, respectively). Moreover, the AMP-induced sneezing was also inhibited by pre-treatment with salbutamol (P=0.004).

CONCLUSIONS

Intranasal salbutamol attenuates nasal symptoms and inhibits histamine and tryptase release caused by AMP nasal provocation thus supporting the hypothesis that salbutamol may play an additional protective role in the airways by inhibiting mast cell activation.

A comparative study of mobile electronic data entry systems for clinical trials data collection

PURPOSE

To determine the speed, accuracy, ease of use, and user satisfaction of various electronic data entry platforms for use in the collection of mammography clinical trials data.

METHOD AND MATERIALS

Four electronic data entry platforms were tested: standalone personal digital assistant (PDA), Tablet PC, digitizer Tablet/PDA Hybrid (DTP Hybrid), and digital pen (d-pen). Standard paper data entry was used as control. Each of five radiologist readers was assigned to enter interpretations for 20 screening mammograms using three out of the five data entry methods. Assistants recorded both start and stop data entry times of the radiologists and the number of help requests made. Data were checked for handwriting recognition accuracy for the d-pen platform using handwriting verification software. A user satisfaction survey was administered at the end of each platform reading session.

RESULTS

Tablet PC and d-pen were statistically equivalent to conventional pen and paper in initial data entry speed. Average verification time for d-pen was significantly less than secondary electronic data entry of paper forms (p-value <0.001). The number of errors in handwriting recognition for d-pen was less than secondary electronic data entry of the paper forms data. Users were most satisfied with Tablet PC, d-pen, and conventional pen and paper for data entry.

CONCLUSIONS

Tablet PC and d-pen are equally fast and easy-to-use data entry methods that are well tolerated by radiologist users. Handwriting recognition review and correction for the d-pen is significantly faster and more accurate than secondary manual keyboard and mouse data entry.

Comparison of full-field digital mammography to screen-film mammography with respect to contrast and spatial resolution in tissue equivalent breast phantoms

To determine if the improved contrast resolution of full-field digital mammography (FFDM) with reduced spatial resolution allows for superior or equal phantom object detection compared with screen-film mammography (SFM). Tissue equivalent breast phantoms simulating an adipose to glandular ratio of 50/50,30/70, and 20/80 were imaged according to each manufacturers' recommendation with four full-field digital mammography units (Fuji, Sectra, Fischer, and General Electric) and a screen-film mammography unit (MammoMatII 2000, Siemens, Munich, Germany). A total of 20 images were obtained in both hard- and soft-copy formats. For the purpose of soft-copy display, the screen-film hard-copy images were digitized with a 50 microm micron scanner. Six radiologists, experts in breast imaging, and three physicists, experts in scoring mammography phantoms, participated in a reader study where each reader scored each phantom for visibility of line-pairs and for 24 objects (fibers, clusters of specks, and masses). The data were recorded, entered into a database, and analyzed by a mixed-effect model. The limiting spatial resolution in line-pairs per millimeter visible with the digital units was less, regardless of display modality used, than that provided by the screen-film unit. The difference was statistically significant for the General Electric (p < 0.01) and Fuji digital mammography units (p = 0.03). With respect to the number of visible objects, a statistically significant higher number could be detected with the screen-film unit as compared to the Fischer (p < 0.01) and Sectra (p < 0.01) digital mammography units, but there was no significant difference between the other digital units and screen film. Overall, there was significantly better performance on the 50/50 phantom than with the 30/70 and 20/80 phantoms (p = 0.01, p < 0.01) for object visibility. For the digital mammography units, soft-copy display performed better than hard-copy display for the Fischer and Sectra images, but worse for Fuji and General Electric. In addition, soft-copy display of digitized screen-film images was significantly better than hard-copy display (p =0.02) of the original screen films for object visibility, but worse for spatial resolution. The higher contrast resolution of the FFDM units tested did not result in improved detection of line-pair resolution or objects in the phantoms tested versus screen-film mammography. The phantom performance of a digital mammography unit seems to be influenced by the type of detection task (line-pair resolution versus object visibility), the display modality (soft-copy versus hard-copy) chosen to score the phantoms, and the parenchymal pattern composition of the phantom.

Vessel tortuosity and brain tumor malignancy: a blinded study

RATIONALE AND OBJECTIVES

Malignancy provokes regional changes to vessel shape. Characteristic vessel tortuosity abnormalities appear early during tumor development, affect initially healthy vessels, spread beyond the confines of tumor margins, and do not simply mirror tissue perfusion. The ability to detect and quantify tortuosity abnormalities on high-resolution magnetic resonance angiography (MRA) images offers a new approach to the noninvasive diagnosis of malignancy. This report evaluates a computerized, statistical method of analyzing the shapes of vessels extracted from MRA in diagnosing cancer.

MATERIALS AND METHODS

The regional vasculature of 34 healthy subjects was compared with the tumor-associated vasculature of 30 brain tumors before surgical resection. The operator performing the analysis was blinded to the diagnosis. Vessels were segmented from an MRA of each subject, a region of interest was defined in each tumor patient and was mapped to all healthy controls, and a statistical analysis of vessel shape measures was then performed over the region of interest. Many difficult cases were included, such as pinpoint, hemorrhagic, and irradiated tumors, as were hypervascular benign tumors. Tumors were identified as benign or malignant on the basis of histological evaluation.

RESULTS

A discriminant analysis performed at the study's conclusion successfully classified all but one of the 30 tumors as benign or malignant on the basis of vessel tortuosity.

CONCLUSIONS

Quantitative, statistical measures of vessel shape offer a new approach to the diagnosis and staging of disease. Although the methods developed under the current report must be tested against a new series of cases, initial results are promising.

Estimating haplotype-disease associations with pooled genotype data

The genetic dissection of complex human diseases requires large-scale association studies which explore the population associations between genetic variants and disease phenotypes. DNA pooling can substantially reduce the cost of genotyping assays in these studies, and thus enables one to examine a large number of genetic variants on a large number of subjects. The availability of pooled genotype data instead of individual data poses considerable challenges in the statistical inference, especially in the haplotype-based analysis because of increased phase uncertainty. Here we present a general likelihood-based approach to making inferences about haplotype-disease associations based on possibly pooled DNA data. We consider cohort and case-control studies of unrelated subjects, and allow arbitrary and unequal pool sizes. The phenotype can be discrete or continuous, univariate or multivariate. The effects of haplotypes on disease phenotypes are formulated through flexible regression models, which allow a variety of genetic hypotheses and gene-environment interactions. We construct appropriate likelihood functions for various designs and phenotypes, accommodating Hardy-Weinberg disequilibrium. The corresponding maximum likelihood estimators are approximately unbiased, normally distributed, and statistically efficient. We develop simple and efficient numerical algorithms for calculating the maximum likelihood estimators and their variances, and implement these algorithms in a freely available computer program. We assess the performance of the proposed methods through simulation studies, and provide an application to the Finland-United States Investigation of NIDDM Genetics Study. The results show that DNA pooling is highly efficient in studying haplotype-disease associations. As a by-product, this work provides valid and efficient methods for estimating haplotype-disease associations with unpooled DNA samples.

Simultaneous modelling of survival and longitudinal data with an application to repeated quality of life measures

In biomedical studies, interest often focuses on the relationship between patient's characteristics or some risk factors and both quality of life and survival time of subjects under study. In this paper, we propose a simultaneous modelling of both quality of life and survival time using the observed covariates. Moreover, random effects are introduced into the simultaneous models to account for dependence between quality of life and survival time due to unobserved factors. EM algorithms are used to derive the point estimates for the parameters in the proposed model and profile likelihood function is used to estimate their variances. The asymptotic properties are established for our proposed estimators. Finally, simulation studies are conducted to examine the finite-sample properties of the proposed estimators and a liver transplantation data set is analyzed to illustrate our approaches.

The effects of gray scale image processing on digital mammography interpretation performance

RATIONALE AND OBJECTIVES

To determine the effects of three image-processing algorithms on diagnostic accuracy of digital mammography in comparison with conventional screen-film mammography.

MATERIALS AND METHODS

A total of 201 cases consisting of nonprocessed soft copy versions of the digital mammograms acquired from GE, Fischer, and Trex digital mammography systems (1997-1999) and conventional screen-film mammograms of the same patients were interpreted by nine radiologists. The raw digital data were processed with each of three different image-processing algorithms creating three presentations-manufacturer's default (applied and laser printed to film by each of the manufacturers), MUSICA, and PLAHE-were presented in soft copy display. There were three radiologists per presentation.

RESULTS

Area under the receiver operating characteristic curve for GE digital mass cases was worse than screen-film for all digital presentations. The area under the receiver operating characteristic for Trex digital mass cases was better, but only with images processed with the manufacturer's default algorithm. Sensitivity for GE digital mass cases was worse than screen film for all digital presentations. Specificity for Fischer digital calcifications cases was worse than screen film for images processed in default and PLAHE algorithms. Specificity for Trex digital calcifications cases was worse than screen film for images processed with MUSICA.

CONCLUSION

Specific image-processing algorithms may be necessary for optimal presentation for interpretation based on machine and lesion type.

Cytomegalovirus Viremia, Mortality, and End-Organ Disease Among Patients With AIDS Receiving Potent Antiretroviral Therapies

OBJECTIVE

To determine the association of cytomegalovirus (CMV) viremia with CMV disease and death in patients with AIDS.

DESIGN AND SETTING

Prospective, observational cohort study conducted at a university hospital.

METHODS

A cohort of 190 subjects with AIDS who were CMV seropositive and had no history or evidence of CMV disease were longitudinally evaluated for signs and symptoms of CMV disease and CMV viremia with plasma CMV DNA polymerase chain reaction (PCR) and whole blood CMV hybrid capture.

RESULTS

A total of 187 subjects had at least 1 study visit following entry. At baseline, the median CD4 cell count and plasma HIV RNA level were 110/microL (range = 3-620/microL) and 47,973 copies/mL (<30- >750,000 copies/mL), respectively. Highly active antiretroviral therapy (HAART) use increased from 87.5% during the 1st study year to 98.5% by the end of the study. During a median follow-up of 334 days, 16% (30) of the subjects died and 2 (6%) developed CMV disease. No deaths were attributable to CMV disease; 4 subjects who died developed CMV prior to death. Baseline HIV viral load and final CD4 cell count were significantly and independently associated with mortality. Detectable plasma CMV DNA PCR was an independent predictor of death even after adjusting for HIV RNA level and CD4 cell count prior to death (P = 0.038). In contrast, whole blood CMV hybrid capture did not predict mortality. The CMV assays neither collectively nor individually were found to be associated with the few cases of CMV disease.

CONCLUSIONS

In patients with AIDS and seropositive for CMV, detection of CMV viremia with plasma CMV DNA PCR was predictive of death and provided additional prognostic information on the risk of all cause-mortality beyond that obtained with CD4 cell count and HIV viral load testing alone. Detection of CMV viremia by plasma with CMV DNA PCR in patients with AIDS, particularly those with low CD4 cell counts, provides additional rationale for optimization of antiretroviral therapy and consideration for preemptive anti-CMV therapy.

Pair chart test for an early survival difference

The log-rank test is commonly used in comparing survival distributions between treatment and control groups in clinical trials. However, in many studies, the treatment is only effective at the early stage of the trial. Especially when the two survival curves cross, the log-rank test has a low statistical power to show the survival difference. We propose a test statistic for detecting such an early difference between the two treatment arms. The new test has an intuitive geometric interpretation based on a pair chart and is shown to have more power than the log-rank test when the treatment effect only appears in the early phase of the study. This advantage is evaluated for finite sample sizes in simulation studies. Finally, the proposed method is illustrated with a real data example of patients with gastric cancer.