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Objective. To investigate the status of pharmacoeconomics education in Egyptian schools of pharmacy and compile and construct recommendations on how Egypt and similar countries could improve their educational infrastructure in pharmacoeconomics. Methods. A modified version of a published survey instrument was sent to all schools of pharmacy in Egypt (n5 24). The data were assessed to identify associations between offering pharmacoeconomics education and school characteristics. Results. Usable responses were obtained from 20 schools (response rate: 83%). Only 7 schools offered pharmacoeconomics education, with a median of 20 teaching hours per semester. Among respondents, 4 schools had instructors with some training in pharmacoeconomics and only 1 school had a faculty member with PhD-level training. Only 4 schools offered graduate-level courses in pharmacoeconomics. Eight additional schools expressed interest in teaching pharmacoeconomics in the near future. Having 1 or more faculty members with training in pharmacoeconomics was significantly associated with offering pharmacoeconomics education (p 5 0.03). Conclusions. Pharmacoeconomics education in Egypt is still in its infancy and there exists a unique opportunity for well-trained instructors and researchers to fill this gap. Providing structured pharmacoeconomics education to student pharmacists, researchers, and stakeholders can help countries establish an integrated scientific community that can start applying pharmacoeconomic evidence to healthcare decision-making.

2+, 3+. States: A feature selection is executed by a modeler who decides which set of features describes a disease state or patient cohort best. For identifying the most relevant attribute combinations a cluster analysis is applied beforehand. Transitions: Patients remain in one particular state as long as they match the predetermined features and attributes. Otherwise, a change to another state occurs. Thereby, a sequence of states for each patient is defined. As a final step, these sequences are used for deriving a model structure. ExpEctEd REsults: Markov models backed up by real-life patient records. As a result of the automatic generation process models can be used for validating hypotheses or comparing outcomes for different patient cohorts. Therefore, the usage of such models is not strictly limited to health economic analysis. A first validation indicates the feasibility of the outlined methods. It was possible to reconstruct a published disease model. conclusions: Ongoing research is conducted with focus on data quality, i.e., accuracy, completeness and timeliness, at the regional cancer registry.

postmenopausal women attending a clinic in Western New York, to undergo mammographic assessment. Eligible participants included women without cancer, no recent use of hormone-replacement therapy, and no history of breast augmentation or breast reduction surgery. A self-administered questionnaire was used to obtain information on demographics, anthropometry, and breast cancer risk factors. Percent density (PD) was measured using computer-assisted assessment of mammographic films. General linear models were used to test for differences in PD by smoking variables while adjusting for selected covariates (age, body mass index, age at first live birth, age at menopause, use of hormone therapy, level of education, and family history of breast cancer). Results: Study participants (n= 229) included 125 never-smokers, 87 former smokers, and 17 current smokers. Current smokers had a lower mean percent density (SE) compared to non-current smokers and former smokers (29.6 (5.1) vs. 34.8 (3.9) and 37.5 (4.1) p= 0.09). Among ever smokers, age at smoking initiation was inversely associated with percent density (P= 0.002). No significant associations were observed for the other smoking variables. ConClusions: Younger age at smoking initiation is associated with higher PD while current smoking is associated with lower PD. These findings suggest that smoking may have differential effects on risk of postmenopausal breast cancer depending on the timing of exposure.objeCtives: Tobacco contains numerous carcinogens, including several known to cause mammary tumors in animal models. Our study aimed to investigate whether mammographic density (MD), a recognized risk factor associated with breast cancer, is influenced by smoking history. Methods: This was a cross-sectional study of

143 Background: Fractures (fx) are common in men with stage 4 prostate cancer (S4PC), resulting in significant clinical consequences, such as increased pain and decreased quality of life. The aim of this study was to estimate the prevalence of fx among men diagnosed with non-metastatic (M0) or metastatic (M1) S4PC and evaluate risk factors associated with fx. Methods: We estimated the prevalence of fx among men age 66 or older diagnosed with M0 or M1 S4PC using data from the U.S. SEER-Medicare datasets between 2000 to 2007. Men were followed through December 2009 or until they were lost to follow up. Codes indicating “pathologic fracture” or “fracture,” excluding codes suggesting accidents/falls in the 14 days prior to the fx, were used to identify fx. Results: Among 9,826 men with S4PC (M1 = 7301; M0 = 2525), 12.9% experienced a post-diagnosis fx based on the codes used. The prevalence of fx was nearly twice as high in men with M1 versus M0 S4PC (M1 = 14.7%; M0 = 7.5%). The median time from diagnosis of S4PC to first fx was five months for men with M1 S4PC versus 34 months for men with M0 S4PC. Compared to men with no fx, men who experienced fx were more likely to be older (20.3% vs. 17.8%), of white/non-Hispanic race (81.1% vs. 75.3%), have well (cancer grade 1) or moderately (cancer grade 2) differentiated tumors (48.7% vs. 41.7%), have a claim of osteoporosis (2.4% vs. 0.6%) or osteoarthritis (9.3% vs. 6.5%) in the year prior to S4PC diagnosis, and to have taken a bone mineral density (BMD) test (13.5% vs. 8.1%). All differences were significant at p<0.05 level. Overall, 92% of men did not receive BMD testing at any time post diagnosis despite the fact that 67% of the men received ADT. Conclusions: In men with M1 S4PC at diagnosis, the prevalence of fx is higher and the time to fx is substantially shorter than in men with M0 S4PC at diagnosis. Furthermore, most men with S4PC do not receive BMD testing. A significant need remains to monitor bone health and treat fx, particularly among M1 S4PC patients.

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60 hours per year. The median number of PE hours for required courses was 16 and the mean number of students enrolled annually was 117. Learning objectives and covered topics obtained from syllabi and surveys varied among colleges/schools. CONCLUSIONS: More US Colleges/Schools of Pharmacy required PE education compared to the 2007 survey, and the number of hours and students in these courses increased. Although the extent of PE education has increased, a large variation in the number of teaching hours and list of covered topics among the colleges and schools demonstrates a lack of uniformity or standardization for this area.