Gender associated risk factors of aortic aneurysms and dissections

Objectives. Predict who will develop a dissection. To create male and female prediction models using the risk factors: age, ethnicity, hypertension, high cholesterol, smoking, alcohol use, diabetes, heart attack, congestive heart failure, congenital and non-congenital heart disease, Marfan syndrome, and bicuspid aortic valve. ^ Methods. Using 572 patients diagnosed with aortic aneurysms, a model was developed for each of males and females using 80% of the data and then verified using the remaining 20% of the data. ^ Results. The male model predicted the probability of a male in having a dissection (p=0.076) and the female model predicted the probability of a female in having a dissection (p=0.054). The validation models did not support the choice of the developmental models. ^ Conclusions. The best models obtained suggested that those who are at a greater risk of having a dissection are males with non-congenital heart disease and who drink alcohol, and females with non-congenital heart disease and bicuspid aortic valve.^

Identification of diabetic retinopathy genes through a genome-wide association study among Mexican-Americans from Starr County, Texas

To identify genetic susceptibility loci for severe diabetic retinopathy, 286 Mexican-Americans with type 2 diabetes from Starr County, Texas completed detailed physical and ophthalmologic examinations including fundus photography for diabetic retinopathy grading. 103 individuals with moderate-to-severe non-proliferative diabetic retinopathy or proliferative diabetic retinopathy were defined as cases for this study. DNA samples extracted from study subjects were genotyped using the Affymetrix GeneChip® Human Mapping 100K Set, which includes 116,204 single nucleotide polymorphisms (SNPs) across the whole genome. Single-marker allelic tests and 2- to 8-SNP sliding-window Haplotype Trend Regression implemented in HelixTreeTM were first performed with these direct genotypes to identify genes/regions contributing to the risk of severe diabetic retinopathy. An additional 1,885,781 HapMap Phase II SNPs were imputed from the direct genotypes to expand the genomic coverage for a more detailed exploration of genetic susceptibility to diabetic retinopathy. The average estimated allelic dosage and imputed genotypes with the highest posterior probabilities were subsequently analyzed for associations using logistic regression and Fisher's Exact allelic tests, respectively. To move beyond these SNP-based approaches, 104,572 directly genotyped and 333,375 well-imputed SNPs were used to construct genetic distance matrices based on 262 retinopathy candidate genes and their 112 related biological pathways. Multivariate distance matrix regression was then used to test hypotheses with genes and pathways as the units of inference in the context of susceptibility to diabetic retinopathy. This study provides a framework for genome-wide association analyses, and implicated several genes involved in the regulation of oxidative stress, inflammatory processes, histidine metabolism, and pancreatic cancer pathways associated with severe diabetic retinopathy. Many of these loci have not previously been implicated in either diabetic retinopathy or diabetes. In summary, CDC73, IL12RB2, and SULF1 had the best evidence as candidates to influence diabetic retinopathy, possibly through novel biological mechanisms related to VEGF-mediated signaling pathway or inflammatory processes. While this study uncovered some genes for diabetic retinopathy, a comprehensive picture of the genetic architecture of diabetic retinopathy has not yet been achieved. Once fully understood, the genetics and biology of diabetic retinopathy will contribute to better strategies for diagnosis, treatment and prevention of this disease.^

Outcomes associated with chemotherapy in elderly patients with early stage operable breast cancer

Background. Various clinical trials have proved the efficacy of adjuvant chemotherapy in women with breast cancer. Chemotherapy efficacy and guidelines for its use differ by stage of tumor and age of the patient with no clear recommendations for patients aged 70 and above. Objective. To examine the clinical and economic outcomes associated with chemotherapy use in and to examine the disparities in treatment and survival in elderly patients with early stage operable breast cancer by age and axillary node status. Methods. We studied a cohort of 23,110 node positive and 31,572 node negative women aged 65 and over diagnosed with incident American Joint Committee on Cancer (AJCC) stage I, II or IIIa breast cancer between January 1, 1991 and December 31, 2002 using SEER-Medicare data. Total patient costs were estimated using the phase of care approach and adjusted cost estimates were obtained from regression analysis using a 3% discount rate. Cox proportional hazard ratio of mortality was used to determine the effectiveness of chemotherapy. Propensity score approach was also used to minimize the bias associated with receipt of chemotherapy. To assess disparity in treatment, multivariate logistic regression analyses were performed to assess the relative odds of receiving surgery, chemotherapy and radiation after BCS for African Americans compared to Whites. Results. Regression adjusted cost estimates for all node positive patients receiving chemotherapy was approximately $2,300 and was significantly higher (p<0.05) than for patients not receiving chemotherapy. Mortality was significantly lower in node positive and node negative women aged 65-74 years receiving chemotherapy. There was a significant difference between African American and White women in receiving BCS and radiation after BCS; however this difference was explained by patient demographics, tumor characteristics and socioeconomic status (SES). African American node positive women were 21% less likely to receive chemotherapy than White women (OR, 0.79; CI, 0.68-0.92) in multivariate analysis. Conclusion. Chemotherapy is associated with increased survival in patients aged 65-74 and total costs attributable to chemotherapy differ by phase and age of the patient. Underutilization of systemic adjuvant chemotherapy in African American women requires attention and may serve as potential areas for appropriate intervention.^

Validity of using item response theory to analyze data from the Work Limitations Questionnaire

The Work Limitations Questionnaire (WLQ) is used to determine the amount of work loss and productivity which stem from certain health conditions, including rheumatoid arthritis and cancer. The questionnaire is currently scored using methodology from Classical Test Theory. Item Response Theory, on the other hand, is a theory based on analyzing item responses. This study wanted to determine the validity of using Item Response Theory (IRT), to analyze data from the WLQ. Item responses from 572 employed adults with dysthymia, major depressive disorder (MDD), double depressive disorder (both dysthymia and MDD), rheumatoid arthritis and healthy individuals were used to determine the validity of IRT (Adler et al., 2006).^ PARSCALE, which is IRT software from Scientific Software International, Inc., was used to calculate estimates of the work limitations based on item responses from the WLQ. These estimates, also known as ability estimates, were then correlated with the raw score estimates calculated from the sum of all the items responses. Concurrent validity, which claims a measurement is valid if the correlation between the new measurement and the valid measurement is greater or equal to .90, was used to determine the validity of IRT methodology for the WLQ. Ability estimates from IRT were found to be somewhat highly correlated with the raw scores from the WLQ (above .80). However, the only subscale which had a high enough correlation for IRT to be considered valid was the time management subscale (r = .90). All other subscales, mental/interpersonal, physical, and output, did not produce valid IRT ability estimates.^ An explanation for these lower than expected correlations can be explained by the outliers found in the sample. Also, acquiescent responding (AR) bias, which is caused by the tendency for people to respond the same way to every question on a questionnaire, and the multidimensionality of the questionnaire (the WLQ is composed of four dimensions and thus four different latent variables) probably had a major impact on the IRT estimates. Furthermore, it is possible that the mental/interpersonal dimension violated the monotonocity assumption of IRT causing PARSCALE to fail to run for these estimates. The monotonicity assumption needs to be checked for the mental/interpersonal dimension. Furthermore, the use of multidimensional IRT methods would most likely remove the AR bias and increase the validity of using IRT to analyze data from the WLQ.^

Predictors of Contralateral Breast Cancer in BRCA Negative Women

Breast cancer is the most common cancer diagnosis and second leading cause of death in women. Risk factors associated with breast cancer include: increased age, alcohol consumption, cigarette smoking, white race, physical inactivity, benign breast conditions, reproductive and hormonal factors, dietary factors, and family history. Hereditary breast and ovarian cancer syndrome (HBOC) is caused by mutations in the BRCA1 and BRCA2 genes. Women carrying a mutation in these genes are at an increased risk to develop a second breast cancer. Contralateral breast cancer is the most common second primary cancer in patients treated for a first breast cancer. Other risk factors for developing contralateral breast cancer include a strong family history of breast cancer, age of onset of first primary breast cancer, and if the first primary was a lobular carcinoma, which has an increased risk of being bilateral. A retrospective chart review was performed on a select cohort of women in an IRB approved database at MD Anderson Cancer Center. The final cohort contained 572 women who tested negative for a BRCA1 or BRCA2 mutation, had their primary invasive breast cancer diagnosed under the age of 50, and had a BRCAPro risk assessment number over 10%. Of the 572 women, 97 women developed contralateral breast cancer. A number of predictors of contralateral breast cancer were looked at between the two groups. Using univariable Cox Proportional Hazard model, thirteen statistically interesting risk factors were found, defined as having a p-value under 0.2. Multivariable stepwise Cox Proportional Hazard model found four statistically significant variables out of the thirteen found in the univariable analysis. In our study population, the incidence of contralateral breast cancer was 17%. Four statistically significant variables were identified. Undergoing a prophylactic mastectomy was found to reduce the risk of developing contralateral breast cancer, while not having a prophylactic mastecomy, a young age at primary diagnosis, having a positive estrogen receptor status of the primary tumor, and having a family history of breast cancer increased a woman’s risk to develop contralateral breast cancer.