Stratification of high-risk prostate cancer into prognostic categories: a European multi-institutional study

BACKGROUND High-risk prostate cancer (PCa) is an extremely heterogeneous disease. A clear definition of prognostic subgroups is mandatory. OBJECTIVE To develop a pretreatment prognostic model for PCa-specific survival (PCSS) in high-risk PCa based on combinations of unfavorable risk factors. DESIGN, SETTING, AND PARTICIPANTS We conducted a retrospective multicenter cohort study including 1360 consecutive patients with high-risk PCa treated at eight European high-volume centers. INTERVENTION Retropubic radical prostatectomy with pelvic lymphadenectomy. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS Two Cox multivariable regression models were constructed to predict PCSS as a function of dichotomization of clinical stage (< cT3 vs cT3-4), Gleason score (GS) (2-7 vs 8-10), and prostate-specific antigen (PSA; ≤ 20 ng/ml vs > 20 ng/ml). The first "extended" model includes all seven possible combinations; the second "simplified" model includes three subgroups: a good prognosis subgroup (one single high-risk factor); an intermediate prognosis subgroup (PSA >20 ng/ml and stage cT3-4); and a poor prognosis subgroup (GS 8-10 in combination with at least one other high-risk factor). The predictive accuracy of the models was summarized and compared. Survival estimates and clinical and pathologic outcomes were compared between the three subgroups. RESULTS AND LIMITATIONS The simplified model yielded an R(2) of 33% with a 5-yr area under the curve (AUC) of 0.70 with no significant loss of predictive accuracy compared with the extended model (R(2): 34%; AUC: 0.71). The 5- and 10-yr PCSS rates were 98.7% and 95.4%, 96.5% and 88.3%, 88.8% and 79.7%, for the good, intermediate, and poor prognosis subgroups, respectively (p = 0.0003). Overall survival, clinical progression-free survival, and histopathologic outcomes significantly worsened in a stepwise fashion from the good to the poor prognosis subgroups. Limitations of the study are the retrospective design and the long study period. CONCLUSIONS This study presents an intuitive and easy-to-use stratification of high-risk PCa into three prognostic subgroups. The model is useful for counseling and decision making in the pretreatment setting.

Contraceptive use in women by body mass index categories

The prevalence of obesity has increased sharply in the United States since the mid 1970's. Obese women who become pregnant are at increased risk of pregnancy complications for both mother and fetus. This study assessed whether women in higher body mass index (BMI) categories engage in the preventive behaviors of contraception more frequently than normal weight women. It also evaluated the type of contraception used by both obese and normal weight women. The study used cross-sectional data from 7 states participating in the Family Planning Module of the 2006 Behavioral Risk Factor Surveillance System (BRFSS). The Behavioral Risk Factor Surveillance System survey is an annual random digit dialed telephone survey of the non-institutionalized civilian population aged 18 years and older. The Family Planning Module was administered by Arizona, Kentucky, Minnesota, Missouri, Montana, Oregon, and Wisconsin. Of the 4,757 women who participated in the Family Planning Module, 2,244 (53.2%) were normal weight, 1,202 (25.6%) were overweight, and 1,072 (21.2%) were obese. The majority of these women 4,115 (86.2%) reported using some type of contraception to prevent pregnancy. Six hundred forty two women (13.8%) stated they did not use any type of contraception to prevent pregnancy. Within body mass index categories, 14% of normal weight women, 13% of overweight women, and 13.4% of obese women did not use any type of contraception. Neither the bivariate analysis nor the logistic regressions found body mass index categories to be statistically associated with contraceptive use. The relationship between body mass index categories and contraceptive method was found to be statistically significant. The predictive probability graph found that women at all levels of BMI have a lower probability of using barrier contraception methods as compared to procedural and hormonal methods. Hormonal contraception methods have the highest probability of use for women with a BMI of 15 to 25. In contrast, the probability of using procedural contraception methods is relatively flat and less than hormonal methods for BMI between 15 and 25. However, the probability of using procedural contraception increases dramatically with a BMI greater than 25. At a BMI greater than 42, women have a greater than 50% probability of using procedural contraception. Although a relationship between body mass index and contraception use was not found, contraception method was found to be associated with body mass index. The reasons why normal weight women prefer hormonal contraception while overweight/obese women are more likely to use procedural methods needs to be explored. By understanding the relationship between obesity and contraception, we can hopefully decrease unintended pregnancies and overall improve pregnancy related health outcomes. To determine if relationships between contraception use/type and body mass index exist, further research needs to be conducted on a national level. ^

Differences in performance for quality of care indicators for acute myocardial infarction (AMI) across various hospital categories in Texas

The study analyzed Hospital Compare data for Medicare Fee-for-service patients at least 65 years of age to determine whether hospital performance for AMI outcome and processes of care measures differ amongst Texas hospitals with respect to ownership status (for profit vs. not-for-profit), academic status (teaching vs. non-teaching) and geographical setting (rural vs. urban). ^ The study found a statistically significant difference between for-profit and not-for-profit hospitals in four process-of-care measures (aspirin at discharge, P=0.028; ACE or ARB inhibitor for LSVD, P=0.048; Smoking cessation advice: P=0.034; outpatients who got aspirin with 24 hours of arrival in the ED, P=0.044). No significant difference in performance was found between COTH-member teaching and non-teaching hospitals for any of the eight process-of-care measures or the two outcome measures for AMI. The study was unable to compare performance based on geographic setting of hospitals due to lack of sufficient data for rural hospitals. ^ The results of the study suggest that for-profit Texas hospitals might be slightly better than not-for –profit hospitals at providing possible heart attack patients with certain processes of care.^

Macroinvertebrate abundance and proportion of trait categories in river biotopes across England and Wales

There is a long tradition of river monitoring using macroinvertebrate communities to assess environmental quality in Europe. A promising alternative is the use of species life-history traits. Both methods, however, have relied on the time-consuming identification of taxa. River biotopes, 1-100 m**2 'habitats' with associated species assemblages, have long been seen as a useful and meaningful way of linking the ecology of macroinvertebrates and river hydro-morphology and can be used to assess hydro-morphological degradation in rivers. Taxonomic differences, however, between different rivers had prevented a general test of this concept until now. The species trait approach may overcome this obstacle across broad geographical areas, using biotopes as the hydro-morphological units which have characteristic species trait assemblages. We collected macroinvertebrate data from 512 discrete patches, comprising 13 river biotopes, from seven rivers in England and Wales. The aim was to test whether river biotopes were better predictors of macroinvertebrate trait profiles than taxonomic composition (genera, families, orders) in rivers, independently of the phylogenetic effects and catchment scale characteristics (i.e. hydrology, geography and land cover). We also tested whether species richness and diversity were better related to biotopes than to rivers. River biotopes explained 40% of the variance in macroinvertebrate trait profiles across the rivers, largely independently of catchment characteristics. There was a strong phylogenetic signature, however. River biotopes were about 50% better at predicting macroinvertebrate trait profiles than taxonomic composition across rivers, no matter which taxonomic resolution was used. River biotopes were better than river identity at explaining the variability in taxonomic richness and diversity (40% and <=10%, respectively). Detailed trait-biotope associations agreed with independent a priori predictions relating trait categories to near river bed flows. Hence, species traits provided a much needed mechanistic understanding and predictive ability across a broad geographical area. We show that integration of the multiple biological trait approach with river biotopes at the interface between ecology and hydro-morphology provides a wealth of new information and potential applications for river science and management.