Clinical and Patient-reported Outcomes in Patients with Psoriatic Arthritis (PsA) by Body Surface Area Affected by Psoriasis: Results from the Corrona PsA/Spondyloarthritis Registry.

OBJECTIVE: Psoriatic arthritis (PsA) is commonly comorbid with psoriasis; the extent of skin lesions is a major contributor to psoriatic disease severity/burden. We evaluated whether extent of skin involvement with psoriasis [body surface area (BSA) > 3% vs ≤ 3%] affects overall clinical and patient-reported outcomes (PRO) in patients with PsA. METHODS: Using the Corrona PsA/Spondyloarthritis Registry, patient characteristics, disease activity, and PRO at registry enrollment were assessed for patients with PsA aged ≥ 18 years with BSA > 3% versus ≤ 3%. Regression models were used to evaluate associations of BSA level with outcome [modified minimal disease activity (MDA), Health Assessment Questionnaire (HAQ) score, patient-reported pain and fatigue, and the Work Productivity and Activity Impairment questionnaire score]. Adjustments were made for age, sex, race, body mass index, disease duration, and history of biologics, disease-modifying antirheumatic drug, and prednisone use. RESULTS: This analysis included 1240 patients with PsA with known BSA level (n = 451, BSA > 3%; n = 789, BSA ≤ 3%). After adjusting for potential confounding variables, patients with BSA > 3% versus ≤ 3% had greater patient-reported pain and fatigue and higher HAQ scores (p = 2.33 × 10-8, p = 0.002, and p = 1.21 × 10-7, respectively), were 1.7× more likely not to be in modified MDA (95% CI 1.21-2.41, p = 0.002), and were 2.1× more likely to have overall work impairment (1.37-3.21, p = 0.0001). CONCLUSION: These Corrona Registry data show that substantial skin involvement (BSA > 3%) is associated with greater PsA disease burden, underscoring the importance of assessing and effectively managing psoriasis in patients with PsA because this may be a contributing factor in PsA severity.

Development of a flattening filter free multiple source model for use as an independent, Monte Carlo, dose calculation, quality assurance tool for clinical trials.

PURPOSE: The Imaging and Radiation Oncology Core-Houston (IROC-H) Quality Assurance Center (formerly the Radiological Physics Center) has reported varying levels of compliance from their anthropomorphic phantom auditing program. IROC-H studies have suggested that one source of disagreement between institution submitted calculated doses and measurement is the accuracy of the institution's treatment planning system dose calculations and heterogeneity corrections used. In order to audit this step of the radiation therapy treatment process, an independent dose calculation tool is needed. METHODS: Monte Carlo multiple source models for Varian flattening filter free (FFF) 6 MV and FFF 10 MV therapeutic x-ray beams were commissioned based on central axis depth dose data from a 10 × 10 cm2 field size and dose profiles for a 40 × 40 cm2 field size. The models were validated against open-field measurements in a water tank for field sizes ranging from 3 × 3 cm2 to 40 × 40 cm2 . The models were then benchmarked against IROC-H's anthropomorphic head and neck phantom and lung phantom measurements. RESULTS: Validation results, assessed with a ±2%/2 mm gamma criterion, showed average agreement of 99.9% and 99.0% for central axis depth dose data for FFF 6 MV and FFF 10 MV models, respectively. Dose profile agreement using the same evaluation technique averaged 97.8% and 97.9% for the respective models. Phantom benchmarking comparisons were evaluated with a ±3%/2 mm gamma criterion, and agreement averaged 90.1% and 90.8% for the respective models. CONCLUSIONS: Multiple source models for Varian FFF 6 MV and FFF 10 MV beams have been developed, validated, and benchmarked for inclusion in an independent dose calculation quality assurance tool for use in clinical trial audits.

Development of a Monte Carlo multiple source model for inclusion in a dose calculation auditing tool.

PURPOSE: The Imaging and Radiation Oncology Core Houston (IROC-H) (formerly the Radiological Physics Center) has reported varying levels of agreement in their anthropomorphic phantom audits. There is reason to believe one source of error in this observed disagreement is the accuracy of the dose calculation algorithms and heterogeneity corrections used. To audit this component of the radiotherapy treatment process, an independent dose calculation tool is needed. METHODS: Monte Carlo multiple source models for Elekta 6 MV and 10 MV therapeutic x-ray beams were commissioned based on measurement of central axis depth dose data for a 10 × 10 cm2 field size and dose profiles for a 40 × 40 cm2 field size. The models were validated against open field measurements consisting of depth dose data and dose profiles for field sizes ranging from 3 × 3 cm2 to 30 × 30 cm2 . The models were then benchmarked against measurements in IROC-H's anthropomorphic head and neck and lung phantoms. RESULTS: Validation results showed 97.9% and 96.8% of depth dose data passed a ±2% Van Dyk criterion for 6 MV and 10 MV models respectively. Dose profile comparisons showed an average agreement using a ±2%/2 mm criterion of 98.0% and 99.0% for 6 MV and 10 MV models respectively. Phantom plan comparisons were evaluated using ±3%/2 mm gamma criterion, and averaged passing rates between Monte Carlo and measurements were 87.4% and 89.9% for 6 MV and 10 MV models respectively. CONCLUSIONS: Accurate multiple source models for Elekta 6 MV and 10 MV x-ray beams have been developed for inclusion in an independent dose calculation tool for use in clinical trial audits.

Comparison of attitudes regarding preimplantation genetic diagnosis among patients with hereditary cancer syndromes.

Preimplantation genetic diagnosis (PGD) allows couples to avoid having a child with an inherited condition, potentially reducing cancer burden in families with a hereditary cancer predisposition. This study investigated and compared awareness and acceptance of PGD among patients with different hereditary cancer syndromes. Questionnaires were mailed to 984 adults with hereditary breast and ovarian cancer, Lynch syndrome, familial adenomatous polyposis, or multiple endocrine neoplasia type 1 or 2. Associations between clinical, demographic, and psychosocial factors and awareness and acceptance of PGD were examined. Of 370 respondents (38 % return rate), 28 % felt their syndrome impacted family planning, 24 % were aware of PGD, 72 % felt that PGD should be offered, 43 % would consider using PGD, and 29 % were uncertain. Family experience and syndrome-specific characteristics, such as disease severity, quality of life and availability of medical interventions as well as gender, family planning stage, and religiosity impact perceptions of the acceptability of PGD, though a high level of uncertainty exists. Hereditary cancer patients lack awareness of PGD despite feeling that PGD should be offered, highlighting the need for education on this topic. While we found attitudes about the acceptability of PGD to be generally similar to those reported in the literature and of genetics and ethics experts, we observed similarities and differences between syndromes that provide insight into why some hereditary cancer patients may find PGD more acceptable than others.

Risk of radiogenic second cancers following volumetric modulated arc therapy and proton arc therapy for prostate cancer.

Prostate cancer patients who undergo radiotherapy are at an increased risk to develop a radiogenic second cancer. Proton therapy has been shown to reduce the predicted risk of second cancer when compared to intensity modulated radiotherapy. However, it is unknown if this is also true for the rotational therapies proton arc therapy and volumetric modulated arc therapy (VMAT). The objective of this study was to compare the predicted risk of cancer following proton arc therapy and VMAT for prostate cancer. Proton arc therapy and VMAT plans were created for three patients. Various risk models were combined with the dosimetric data (therapeutic and stray dose) to predict the excess relative risk (ERR) of cancer in the bladder and rectum. Ratios of ERR values (RRR) from proton arc therapy and VMAT were calculated. RRR values ranged from 0.74 to 0.99, and all RRR values were shown to be statistically less than 1, except for the value calculated with the linear-non-threshold risk model. We conclude that the predicted risk of cancer in the bladder or rectum following proton arc therapy for prostate cancer is either less than or approximately equal to the risk following VMAT, depending on which risk model is applied.

Gender differences in sociodemographic and behavioral influences of physical activity in Mexican-origin adolescents.

BACKGROUND: Understanding the factors that contribute to physical activity (PA) in Mexican-origin adolescents is essential to the design of effective efforts to enhance PA participation in this population. METHODS: Multivariable logistic regression was used to identify sociodemographic and behavioral correlates of self-reported PA in school and community settings in 1154 Mexican-origin adolescents aged 12-17 years in Houston, TX. RESULTS: The majority of adolescents were born in the US (74%), approximately half (51%) were overweight or obese, and nearly three-quarters (73%) watched more than 2 hours of weekday television. Similarities and differences by setting and gender were observed in the relationships between sociodemographic and behavioral characteristics and PA. In boys, parental education and attending physical education (PE) were positively associated with PA across multiple PA outcomes. Adolescent linguistic acculturation was inversely associated with participation in community sports, whereas parental linguistic acculturation was positively associated with PA at school. In girls, PA in school and community settings was inversely associated with TV viewing and positively associated with PE participation. CONCLUSIONS: These findings highlight similarities and differences in correlates of PA among boys and girls, and point toward potential sources of opportunities as well as disparities for PA behaviors in Mexican-origin adolescents.

Policy implications of early onset breast cancer among Mexican-origin women.

BACKGROUND: Overall, Latinas are more likely to be diagnosed with a more advanced stage of breast cancer and are 20% more likely to die of breast cancer than non-Hispanic white women. It is estimated that from 2003 to 2006, $82.0 billion in direct medical care expenditures, in addition to 100,000 lives annually, could be saved by eliminating health disparities experienced by Latinos and increasing the use of up to 5 preventive services in the United States. An additional 3700 lives could be saved if 90% of women aged ≥40 years were recently screened for breast cancer. METHODS: The authors examined the risk for breast cancer in a case-control, population-based sample of Mexican-origin women in Harris County, Texas (n=714), where the rates of breast cancer mortality for Latina women have doubled since 1990. RESULTS: Half of breast cancer cases (n=119) were diagnosed in women aged <50 years. In a multivariate model, women who had a family history of breast cancer (odds ratio [OR], 4.3), who were born in Mexico and had high levels of language acculturation (OR, 2.5), and who did not have health insurance (OR, 1.6) had the highest risk for breast cancer. CONCLUSIONS: Because the current results indicated that Mexican-origin women are at high-risk for early onset, premenopausal breast cancer, the authors recommended policies that target screening, education, and treatment to prevent increased disparities in mortality. The authors concluded that the inclusion of community members and policymakers as partners in these endeavors would further safeguard against an increase in cancer health disparities and aid in formulating a policy agenda congruent with scientifically based, community-driven policy efforts that address breast cancer screening, education, and treatment in this vulnerable population.

Cytokinesis-blocked micronucleus assay and cancer risk assessment.

Cancer risk assessment is a multidisciplinary process that goes beyond the scope of classical epidemiology to include the biological evaluation of individual differences to carcinogenic exposures. The inclusion of genetic biomarkers such as mutagen sensitivity or cytokinesis-blocked micronucleus (CBMN) assay end points into risk assessment models allows for a more comprehensive determination of cancer risk that includes known demographic (age and gender), lifestyle exposures (smoking and alcohol) and occupational or environmental exposures. The CBMN assay generates multiple correlated end points that, after applying data reduction methods, could be combined into a summary measure that incorporates information from each individual variable into a single (or possible multiple, uncorrelated) measure of risk. In this article, we highlight the use of the CBMN assay in radiosensitivity assessment. In addition, we demonstrate the potential use of the combined summary measures in cancer risk assessment as a result of chronic exposure to tobacco carcinogens. The simplicity, rapidity and sensitivity of the CBMN assay not only make it a valuable tool for screening but also the multiple end points simultaneously generated lead to a better understanding of the underlying mechanisms involved in the carcinogenic process that could in turn substantially improve risk predictions.

The advantage of imputation of missing income data to evaluate the association between income and self-reported health status (SRH) in a Mexican American cohort study.

Missing data often occur in cross-sectional surveys and longitudinal and experimental studies. The purpose of this study was to compare the prediction of self-rated health (SRH), a robust predictor of morbidity and mortality among diverse populations, before and after imputation of the missing variable "yearly household income." We reviewed data from 4,162 participants of Mexican origin recruited from July 1, 2002, through December 31, 2005, and who were enrolled in a population-based cohort study. Missing yearly income data were imputed using three different single imputation methods and one multiple imputation under a Bayesian approach. Of 4,162 participants, 3,121 were randomly assigned to a training set (to derive the yearly income imputation methods and develop the health-outcome prediction models) and 1,041 to a testing set (to compare the areas under the curve (AUC) of the receiver-operating characteristic of the resulting health-outcome prediction models). The discriminatory powers of the SRH prediction models were good (range, 69-72%) and compared to the prediction model obtained after no imputation of missing yearly income, all other imputation methods improved the prediction of SRH (P < 0.05 for all comparisons) with the AUC for the model after multiple imputation being the highest (AUC = 0.731). Furthermore, given that yearly income was imputed using multiple imputation, the odds of SRH as good or better increased by 11% for each $5,000 increment in yearly income. This study showed that although imputation of missing data for a key predictor variable can improve a risk health-outcome prediction model, further work is needed to illuminate the risk factors associated with SRH.

Self-Rated Health Among Adult Women of Mexican Origin.

Self-rated health (SRH), a consistent predictor of mortality among diverse populations, is sensitive to health indicators and social factors. American-born Hispanics report better SRH than their foreign-born counterparts but simultaneously report poorer health indicators and have shorter life expectancy. Using a matched prospective cross-sectional design, we analyzed data from 631 age-matched pairs of women, born in the United States or Mexico, enrolled in a cohort study based in Houston, Texas. Our first goal was to describe the relationships between SRH and health behaviors, physician-diagnosed chronic conditions, acculturation, and socioeconomic status (SES) by birthplace. Our second goal was to investigate the relative influence of SES, acculturation, health behaviors, and physician-diagnosed conditions in explaining expected differences in SRH between the two groups. Number of chronic conditions reported, particularly depression, more strongly influenced SRH than SES, acculturation, or reported health risk behaviors and the influence of birthplace is accounted for by these factors.

Bias in estimates of quantitative-trait-locus effect in genome scans: demonstration of the phenomenon and a method-of-moments procedure for reducing bias.

An attractive feature of variance-components methods (including the Haseman-Elston tests) for the detection of quantitative-trait loci (QTL) is that these methods provide estimates of the QTL effect. However, estimates that are obtained by commonly used methods can be biased for several reasons. Perhaps the largest source of bias is the selection process. Generally, QTL effects are reported only at locations where statistically significant results are obtained. This conditional reporting can lead to a marked upward bias. In this article, we demonstrate this bias and show that its magnitude can be large. We then present a simple method-of-moments (MOM)-based procedure to obtain more-accurate estimates, and we demonstrate its validity via Monte Carlo simulation. Finally, limitations of the MOM approach are noted, and we discuss some alternative procedures that may also reduce bias.