Development and testing of a procedure for systematically assigning gestational age for clinical and research use

A graphing method was developed and tested to estimate gestational ages pre-and postnatally in a consistent manner for epidemiological research and clinical purposes on feti/infants of women with few consistent prenatal estimators of gestational age. Each patient's available data was plotted on a single page graph to give a comprehensive overview of that patient. A hierarchical classification of gestational age determination was then applied in a systematic manner, and reasonable gestational age estimates were produced. The method was tested for validity and reliability on 50 women who had known dates for their last menstrual period or dates of conception, and multiple ultrasound examinations and other gestational age estimating measures. The feasibility of the procedure was then tested on 1223 low income women with few gestational age estimators. The graphing method proved to have high inter- and intrarater reliability. It was quick, easy to use, inexpensive, and did not require special equipment. The graphing method estimate of gestational age for each infant was tested against the last menstrual period gestational age estimate using paired t-Tests, F tests and the Kolmogorov-Smirnov test of similar populations, producing a 98 percent probability or better that the means and data populations were the same. Less than 5 percent of the infants' gestational ages were misclassified using the graphing method, much lower than the amount of misclassification produced by ultrasound or neonatal examination estimates. ^

Logistic regression models for ordinal response: A study of self-efficacy in colorectal cancer screening

The ordinal logistic regression models are used to analyze the dependant variable with multiple outcomes that can be ranked, but have been underutilized. In this study, we describe four logistic regression models for analyzing the ordinal response variable. ^ In this methodological study, the four regression models are proposed. The first model uses the multinomial logistic model. The second is adjacent-category logit model. The third is the proportional odds model and the fourth model is the continuation-ratio model. We illustrate and compare the fit of these models using data from the survey designed by the University of Texas, School of Public Health research project PCCaSO (Promoting Colon Cancer Screening in people 50 and Over), to study the patient’s confidence in the completion colorectal cancer screening (CRCS). ^ The purpose of this study is two fold: first, to provide a synthesized review of models for analyzing data with ordinal response, and second, to evaluate their usefulness in epidemiological research, with particular emphasis on model formulation, interpretation of model coefficients, and their implications. Four ordinal logistic models that are used in this study include (1) Multinomial logistic model, (2) Adjacent-category logistic model [9], (3) Continuation-ratio logistic model [10], (4) Proportional logistic model [11]. We recommend that the analyst performs (1) goodness-of-fit tests, (2) sensitivity analysis by fitting and comparing different models.^

A case-control study of tea/coffee consumption and lung cancer risk

Background. Despite the increasing attention to the effects of dietary factors on lung cancer risk, epidemiological research on the role of black/green tea and coffee intake and lung cancer risk is scarce. The purpose of this study was to explore the following three hypotheses: (1) the preventive (protective) effect from lung cancer is higher in green tea than in black tea and coffee consumption. (2) brewed tea (either black or green) daily drinkers have lower odds of lung cancer than non-drinkers of brewed tea (3) regular black and green tea have more preventive effect against lung cancer than decaffeinated teas due to the synergistic effect of caffeine and other tea components. ^ Methods. Data on 1,088 lung cancer cases and 1,127 controls from an ongoing epidemiological study of lung cancer by the Department of Epidemiology of the University of Texas M.D. Anderson Cancer were analyzed. Multiple logistic regressions were performed for testing associations between frequency of specific types of tea/coffee consumption and the risk of lung cancer. ^ Results. We observed that more than a cup a week of green tea and decaffeinated black tea were significantly associated with reduced odds of lung cancer by 64% for green tea (adjusted OR = 0.44; 95% CI = 0.31–0.64), 36% for decaffeinated black tea (OR = 0.64; 95% CI = 0.45–0.90), when compared with non-drinkers and those who drank less than a cup a week. On the other hand, increasing intake of regular coffee (more than 3 cups a day) was associated with a 30% higher odds ratio of lung cancer (OR = 1.30; 95% CI = 1.01–1.09). No association was found between regular black tea, decaffeinated coffee consumption and the odds ratio of lung cancer. However, when drinkers of other tea/coffee beverages were excluded from each model in order to explore the independent effect of each type of tea/coffee, green tea and decaffeinated black tea-lung cancer associations remained but no association was observed for drinkers of regular coffee. ^ Conclusion. We report the chemopreventive effects of more than a cup a week of green tea and decaffeinated black tea on lung cancer. ^

Clinical and epidemiological characteristics of breast cancer metastases

Introduction. Breast cancer is a highly variable disease, and long-term outcomes for individual patients are difficult to predict. We evaluated a retrospective cohort of early stage breast cancer (ESBC) patients based on a variety of clinical and epidemiological factors, specifically looking at the distribution of metastasis and associations with these clinical and epidemiological factors. ^ Methods. Patients were derived from the Early Stage Breast Cancer Repository (ESBCR) with a breast cancer diagnosed between 1985 and 2000. We conducted univariate and multivariate analysis of the data to evaluate associations between characteristics and occurrence of overall, visceral, and bone metastasis. Visceral metastasis was defined as lung, liver, peritoneal, lymph node (thoracic, abdominal, pelvis), and contralateral breast cancer. ^ Results. Overall, 394 (16%) patients developed a metastasis. Of these, 83% were visceral and 17% were bone. Multivariate analyses identified the following variables to be associated with metastasis: Any metastasis: age at diagnosis, stage, ER/PR status, hormone treatment, and type of surgery (1)Visceral metastasis: age at diagnosis, stage, hormone treatment, and type of surgery (2) Bone metastasis –Alcohol use, stage, and ER/PR status ^ Discussion/conclusion. ER-/PR- status has previously been found to be associated with bone metastasis, as we confirm in our cohort. We report an association between alcohol use and bone metastasis whereas previous studies find an association with recurrence. Distribution of metastases varies from previous studies. Typically, previous studies reported bone metastasis >30%, yet our study found 17%. Previous studies varied in design, and definition of visceral metastasis. Future research is needed to further elucidate prognostic factors associated with specific metastases A more thorough understanding of what might predict which ESBC patients will develop metastases can help direct future treatment. Future studies of this nature could include the Perou intrinsic subtypes, biomarkers like Ki-67, and genetic analyses such as Oncotype DX or MammaPrint.^