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This note outlines the estimation methodology of the degree of over- or under-pricing for a given housing market relative to its long-term pricing trend. The purpose of this effort is to provide buyers, sellers, real estate professionals, and policy makers a tool that estimates the premium (over-pricing) or discount (under-pricing) a local market is experiencing at a given moment. In general, this model is designed more for greater public rather than academic consumption. [ABSTRACT FROM AUTHOR]

Background: Although physical activity (PA) has been recognized as a favourable factor in the prevention of various diseases, including certain forms of cancer, the relationship between PA and gastric cancer (GC) is not yet fully understood. This study aims to provide data from a pooled analysis of case-control studies within the Stomach cancer Pooling (StoP) Project to estimate the association between leisure-time PA and the occurrence of GC. Methods: Six case-control studies from StoP project collected data on leisure-time PA, for a total of 2,343 cases and 8,614 controls. Subjects were classified into three leisure-time PA categories, either none/low, intermediate or high, based on study-specific tertiles. We used a two-stage approach. Firstly, we applied multivariable logistic regression models to obtain study-specific odds ratios (ORs) and corresponding 95% confidence intervals (CIs) then, we used a random-effect models to obtain pooled effect estimates. We performed stratified analyses according to demographic, lifestyle and clinical covariates. Results: The meta-analysis showed ORs of GC with no significant differences between intermediate vs low and high vs low PA level (OR 1.05 [95%CI 0.76–1.45]; OR 1.23 [95%CI 0.78–1.94], respectively). GC risk estimates did not strongly differ across strata of selected covariates except for age ≤ 55 years old (high vs low level: OR 0.72 [95%CI 0.55–0.94]) and for control population-based studies (high vs low level: OR 0.79 [95%CI 0.68–0.93]). Conclusions: No association was found between leisure time PA and GC, apart from a slight suggestion of decreased risk below age 55 and in control population-based studies. These results may reflect specific characteristics of GC at a younger age, or the presence of a cohort effect mediating and interacting with socioeconomic determinants of GC The different distribution of PA levels among hospitalized controls could have led to an underestimated effect of PA on GC risk. [ABSTRACT FROM AUTHOR]

Background: There is insufficient prospective evidence regarding the relationship between surgical experience and prolonged opioid use and pain. The authors investigated the association of patient characteristics, surgical procedure, and perioperative anesthetic course with postoperative opioid consumption and pain 3 months postsurgery. The authors hypothesized that patient characteristics and intraoperative factors predict opioid consumption and pain 3 months postsurgery. Methods: Eleven U.S. and one European institution enrolled patients scheduled for spine, open thoracic, knee, hip, or abdominal surgery, or mastectomy, in this multicenter, prospective observational study. Preoperative and postoperative data were collected using patient surveys and electronic medical records. Intraoperative data were collected from the Multicenter Perioperative Outcomes Group database. The association between postoperative opioid consumption and surgical site pain at 3 months, elicited from a telephone survey conducted at 3 months postoperatively, and demographics, psychosocial scores, pain scores, pain management, and case characteristics, was analyzed. Results: Between September and October 2017, 3,505 surgical procedures met inclusion criteria. A total of 1,093 cases were included; 413 patients were lost to follow-up, leaving 680 (64%) for outcome analysis. Preoperatively, 135 (20%) patients were taking opioids. Three months postsurgery, 96 (14%) patients were taking opioids, including 23 patients (4%) who had not taken opioids preoperatively. A total of 177 patients (27%) reported surgical site pain, including 45 (13%) patients who had not reported pain preoperatively. The adjusted odds ratio for 3-month opioid use was 18.6 (credible interval, 10.3 to 34.5) for patients who had taken opioids preoperatively. The adjusted odds ratio for 3-month surgical site pain was 2.58 (1.45 to 4.4), 4.1 (1.73 to 8.9), and 2.75 (1.39 to 5.0) for patients who had site pain preoperatively, knee replacement, or spine surgery, respectively. Conclusions: Preoperative opioid use was the strongest predictor of opioid use 3 months postsurgery. None of the other variables showed clinically significant association with opioid use at 3 months after surgery. In these prospectively collected cohort data, preoperative opioid use was identified as the strongest risk factor for opioid use at 3 months postoperatively. No correlation was found between persistent opioid use at 3 months and surgical site pain at 3 months. No association was identified between preoperative anxiety, preoperative depression, or surgery type and opioid use at 3 months in multivariable models, although credible intervals were large for some variables. [ABSTRACT FROM AUTHOR]

A letter to the editor is presented in response to the article about Partnership for Prescription Assistance (PPA) in the May and June 2009 issue.