PurposeGastric cancer is a leading cause of death, particularly in the developing world. The literature reports individual socioeconomic status (SES) or neighborhood SES as related to survival, but the effect of both has not been studied. This study investigated the effect of individual and neighborhood SES simultaneously on mortality in gastric cancer patients in Taiwan.Materials and MethodsA study was conducted of 3,396 patients diagnosed with gastric cancer between 2002 and 2006. Each patient was followed for five years or until death. Individual SES was defined by income-related insurance premium (low, moderate, and high). Neighborhood SES was based on household income dichotomized into advantaged and disadvantaged areas. Multilevel logistic regression model was used to compare survival rates by SES group after adjusting for possible confounding factors.ResultsIn patients younger than 65 years, 5-year overall survival rates were lowest for those with low individual SES. After adjusting for patient characteristics (age, gender, Charlson Comorbidity Index Score), gastric cancer patients with high individual SES had 68% risk reduction of mortality (adjusted odds ratio [OR] of mortality, 0.32; 95% confidence interval [CI], 0.17–0.61). Patients aged 65 and above had no statistically significant difference in mortality rates by individual SES group. Different neighborhood SES did not statistically differ in the survival rates.ConclusionGastric cancer patients aged less than 65 years old with low individual SES have higher risk of mortality, even under an universal healthcare system. Public health strategies, education and welfare policies should seek to correct the inequality in gastric cancer survival, especially in those with lower individual SES.

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A recently developed diagnostic tool, trabecular bone score (TBS), can provide quality of trabecular microarchitecture based on images obtained from dual-energy X-ray absorptiometry (DXA). Since patients receiving glucocorticoid are at a higher risk of developing secondary osteoporosis, assessment of bone microarchitecture may be used to evaluate risk of fragility fractures of osteoporosis. In this pre-post study of female patients, TBS and fracture risk assessment tool (FRAX) adjusted with TBS (T-FRAX) were evaluated along with bone mineral density (BMD) and FRAX. Medical records of patients with (n = 30) and without (n = 16) glucocorticoid treatment were retrospectively reviewed. All patients had undergone DXA twice within a 12- to 24-month interval. Analysis of covariance was conducted to compare the outcomes between the two groups of patients, adjusting for age and baseline values. Results showed that a significant lower adjusted mean of TBS (p = 0.035) and a significant higher adjusted mean of T-FRAX for major osteoporotic fracture (p = 0.006) were observed in the glucocorticoid group. Conversely, no significant differences were observed in the adjusted means for BMD and FRAX. These findings suggested that TBS and T-FRAX could be used as an adjunct in the evaluation of risk of fragility fractures in patients receiving glucocorticoid therapy.

• 40 million Americans cannot read general consumer health information, and 90 million have difficulty understanding and acting upon this information.• Patients with poor literacy skills are often older adults, people with limited education, and those with limited native language proficiency.• Low-literacy patients are often embarrassed to ask health care professionals for help with understanding instructions, and without help they are likely to misunderstand written medication use instructions, contributing to medical errors and noncompliance.• Early work with pictographs found that patients recalled about 14% of verbal medical instructions, but correct recall improved to 85% when verbal instructions were enhanced with pictographs. What is already known about this subject Development of Pictographs Depicting Medication Use Instructions for Low-Literacy Medical Clinic Ambulatory PatientsMei-Hua Chuang, PharmD; Chin-Lon Lin, MD; Yuh-Feng Wang, MD, MS; and Thau-Ming Cham, PhD ABSTRACT BACKGROUND: One approach to help elderly and low-literacy patients understand instructions for medication use is to use pictographs or pictorial diagrams. However, most of these pictographs are designed by medical professionals and may not be optimal for such patients.

The application of an artificial neural network (ANN) in prediction of outcomes using clinical data is being increasingly used. The aim of this study was to assess whether an ANN model is a useful tool for predicting skeletal metastasis in patients with prostate cancer. Consecutive patients with prostate cancer who underwent the technetium-99m methylene diphosphate (Tc-99m MDP) whole body bone scintigraphies were retrospectively analyzed between 2001 and 2005. The predictors were the patient's age and radioimmunometric serum PSA concentration. The outcome variable was dichotomous, either skeletal metastasis or non-skeletal metastasis, based on the results of Tc-99m MDP whole body bone scintigraphy. To assess the performance for classification model in clinical study, the discrimination and calibration of an ANN model was calculated. The enrolled subjects consisted of 111 consecutive male patients aged 72.41 +/- 7.69 years with prostate cancer. Sixty-seven patients (60.4%) had skeletal metastasis based on the scintigraphic diagnosis. The final best architecture of neural network model was four-layered perceptrons. The area under the receiver-operating characteristics curve (0.88 +/- 0.07) revealed excellent discriminatory power (p < 0.001) with the best simultaneous sensitivity (87.5%) and specificity (83.3%). The Hosmer-Lemeshow statistic was 6.74 (p = 0.08 > 0.05), which represented a good-fit calibration. These results suggest that an ANN, which is based on limited clinical parameters, appears to be a promising method in forecasting of the skeletal metastasis in patients with prostate cancer.