The natural history and predictive factors of voided volume in older men: the Krimpen Study.

PURPOSE: Although functional bladder capacity, as expressed by maximum voided volume and other frequency-volume chart parameters, are important determinants of lower urinary tract symptoms, to our knowledge no population based data are available on changes in voided volume. We determined changes in and determinants of voided volume and voiding frequency with advancing age and with time, as measured by frequency-volume charts. MATERIALS AND METHODS: We performed a longitudinal, population based study in 1,688 men 50 to 78 years old with followup at 2.1, 4.2 and 6.5 years. Data were obtained using frequency-volume charts for maximum, 24-hour and average voided volume, and 24-hour voiding frequency as well as physical and urological measurements, and self-administered questionnaires. We used a linear mixed effect model to determine factors predicting volume changes. RESULTS: Median maximum and average voided volume decreased with time from 400 to 380 and 245 to 240 ml, respectively, and were smaller in older age groups while 24-hour voided volume showed no change. The 24-hour voiding frequency increased with time and with advancing age. Maximum, 24-hour and average voided volumes were positively related to alcohol intake. Maximum and average voided volumes were negatively related to higher age at baseline and the passage of time. Hypertension, diuretics and post-void residual volume were related to higher 24-hour voided volume. CONCLUSIONS: In older men maximum and average voided volume show a small but statistically significant decrease with time and with advancing age while 24-hour voided volume does not. Factors predicting the change in maximum or average voided volume are alcohol intake and higher age.

Measuring balance and model selection in propensity score methods.

PURPOSE: Propensity score (PS) methods focus on balancing confounders between groups to estimate an unbiased treatment or exposure effect. However, there is lack of attention in actually measuring, reporting and using the information on balance, for instance for model selection. We propose to use a measure for balance in PS methods and describe several of such measures: the overlapping coefficient, the Kolmogorov-Smirnov distance, and the Lévy distance. METHODS: We performed simulation studies to estimate the association between these three and several mean based measures for balance and bias (i.e., discrepancy between the true and the estimated treatment effect). RESULTS: For large sample sizes (n = 2000) the average Pearson's correlation coefficients between bias and Kolmogorov-Smirnov distance (r = 0.89), the Lévy distance (r = 0.89) and the absolute standardized mean difference (r = 0.90) were similar, whereas this was lower for the overlapping coefficient (r = -0.42). When sample size decreased to 400, mean based measures of balance had stronger correlations with bias. Models including all confounding variables, their squares and interaction terms resulted in smaller bias than models that included only main terms for confounding variables. CONCLUSIONS: We conclude that measures for balance are useful for reporting the amount of balance reached in propensity score analysis and can be helpful in selecting the final PS model.

Echocardiographic tissue deformation imaging of right ventricular systolic function in endurance athletes.

AIMS: To investigate the physiological adaptation of the right ventricle (RV) in response to endurance training and to define reference values for regional deformation in the RV in endurance athletes. METHODS AND RESULTS: Healthy controls (n = 61), athletes (n = 58), and elite athletes (n = 63) were prospectively enrolled with a training intensity of 2.2 +/- 1.6, 12.5 +/- 2.3 and 24.2 +/- 5.7 h/week, respectively (P < 0.001). Conventional echocardiographic parameters, tissue Doppler imaging (TDI), and 2D strain echo (2DSE)-derived velocity, strain, and strain rate (SR) were calculated in three RV segments. Left ventricular and RV dimensions were significantly increased (P < 0.001) in both groups of athletes compared with controls. Right ventricular systolic velocities and displacement were not different between the groups. Right ventricular strain and SR values were reduced in the RV basal and mid-segment in athletes. Athletes with marked RV dilatation showed lower strain and SR values in the basal (-20.9 +/- 4.7 vs. -24.5 +/- 4.9%, P < 0.001 and -1.23 +/- 0.31 vs. -1.50 +/- 0.33 s(-1), P < 0.001) and mid (-29.3 +/- 5.4 vs. -32.1 +/- 5.3%, P = 0.017 and -1.58 +/- 0.41 vs. -1.82 +/- 0.42 s(-1), P = 0.009) segment, whereas athletes without RV dilatation showed no significant difference compared with the controls. CONCLUSION: Regional deformation and deformation rates (TDI and 2DSE) are reduced in the basal RV segment in athletes. This phenomenon is most pronounced in athletes with RV dilatation and should be interpreted as normal when evaluating athletes suspected for RV pathology.

Rituximab treatment before reduced-intensity conditioning transplantation associates with a decreased incidence of extensive chronic GVHD.

Chronic graft-versus-host-disease (cGVHD) is the major cause of late morbidity and mortality after allogeneic stem cell transplantation. B cells have been reported to be involved in mediating cGVHD. To assess whether preemptive host B cell depletion prevents extensive cGVHD after allogeneic reduced-intensity conditioning transplantation (RICT), 173 patients treated with RICT for various hematologic diseases, who had or had not received Rituximab (Rtx) within 6 month prior to RICT, were analyzed retrospectively. Rtx treatment within 6 months prior to RICT reduced extensive cGVHD significantly from 45.8% to 20.1%. We hypothesize that most likely host B cells initiate cGVHD, and thus, host B cell depletion prior to RICT by Rtx might be a valuable strategy to reduce extensive cGVHD after RICT.

Thiazolidinediones and blood lipids in type 2 diabetes.

We evaluated study population characteristics and treatment effects on blood lipids between studies in which either rosiglitazone (RSG) or pioglitazone (PIO) was investigated in patients with type 2 diabetes. We performed a summary analysis of all published double-blind, placebo-controlled studies with RSG (4 and 8 mg/d) and PIO (15, 30, and 45 mg/d). Data were analyzed by the random-effects model. Nineteen trials met our inclusion criteria, yielding 5304 patients, 3236 in studies with RSG and 2068 in studies with PIO. Subjects treated with PIO were more obese and showed more pronounced hyperglycemia and dyslipidemia (increased triglycerides and decreased HDL cholesterol) at baseline than did subjects treated with RSG. By weighted linear-regression analysis, studies with PIO showed greater beneficial effects on triglycerides, total cholesterol, and LDL cholesterol, after adjustment for the respective lipid levels at baseline. RSG 8 mg/d showed greater increases in total cholesterol and LDL cholesterol than did RSG 4 mg/d. PIO 30 mg/d showed greater reductions in triglycerides than did PIO 15 mg/d. Studies conducted with PIO showed more beneficial effects on blood lipids, but also different study population characteristics in comparison with studies conducted with RSG. Differences in both pharmacologic properties between agents and study population characteristics are likely to have influenced the results.

Methods to assess intended effects of drug treatment in observational studies are reviewed.

BACKGROUND AND OBJECTIVE: To review methods that seek to adjust for confounding in observational studies when assessing intended drug effects. METHODS: We reviewed the statistical, economical and medical literature on the development, comparison and use of methods adjusting for confounding. RESULTS: In addition to standard statistical techniques of (logistic) regression and Cox proportional hazards regression, alternative methods have been proposed to adjust for confounding in observational studies. A first group of methods focus on the main problem of nonrandomization by balancing treatment groups on observed covariates: selection, matching, stratification, multivariate confounder score, and propensity score methods, of which the latter can be combined with stratification or various matching methods. Another group of methods look for variables to be used like randomization in order to adjust also for unobserved covariates: instrumental variable methods, two-stage least squares, and grouped-treatment approach. Identifying these variables is difficult, however, and assumptions are strong. Sensitivity analyses are useful tools in assessing the robustness and plausibility of the estimated treatment effects to variations in assumptions about unmeasured confounders. CONCLUSION: In most studies regression-like techniques are routinely used for adjustment for confounding, although alternative methods are available. More complete empirical evaluations comparing these methods in different situations are needed.

Systematic differences in treatment effect estimates between propensity score methods and logistic regression.

BACKGROUND: In medical research both propensity score methods and logistic regression analysis are used to estimate treatment effects in observational studies. From literature reviews it has been concluded that treatment effect estimates from both methods are quite similar. With this study we will show that there are systematic differences which can be substantial. METHODS: We used a simulated population with a known marginal treatment effect and applied a propensity score method and logistic regression analysis to adjust for confounding. RESULTS: The adjusted treatment effect in logistic regression is in general further away from the true marginal treatment effect than the adjusted effect in propensity score methods. The difference is systematic and dependent on the incidence proportion, the number of prognostic factors and the magnitude of the treatment effect. For instance, a substantial difference of 20% is found when the treatment effect is 2.0, the incidence proportion is 0.20 and there are more than 11 prognostic factors. CONCLUSIONS: Propensity score methods give in general treatment effect estimates that are closer to the true marginal treatment effect than a logistic regression model in which all confounders are modelled.

Comparing treatment effects after adjustment with multivariable Cox proportional hazards regression and propensity score methods.

PURPOSE: To compare adjusted effects of drug treatment for hypertension on the risk of stroke from propensity score (PS) methods with a multivariable Cox proportional hazards (Cox PH) regression in an observational study with censored data. METHODS: From two prospective population-based cohort studies in The Netherlands a selection of subjects was used who either received drug treatment for hypertension (n = 1293) or were untreated 'candidates' for treatment (n = 954). A multivariable Cox PH was performed on the risk of stroke using eight covariates along with three PS methods. RESULTS: In multivariable Cox PH regression the adjusted hazard ratio (HR) for treatment was 0.64 (CI(95%): 0.42, 0.98). After stratification on the PS the HR was 0.58 (CI(95%): 0.38, 0.89). Matching on the PS yielded a HR of 0.49 (CI(95%): 0.27, 0.88), whereas adjustment with a continuous PS gave similar results as Cox regression. When more covariates were added (not possible in multivariable Cox model) a similar reduction in HR was reached by all PS methods. The inclusion of a simulated balanced covariate gave largest changes in HR using the multivariable Cox model and matching on the PS. CONCLUSIONS: In PS methods in general a larger number of confounders can be used. In this data set matching on the PS is sensitive to small changes in the model, probably because of the small number of events. Stratification, and covariate adjustment, were less sensitive to the inclusion of a non-confounder than multivariable Cox PH regression. Attention should be paid to PS model building and balance checking.

The impact of environmental temperature on lithium serum levels.

OBJECTIVES: Three studies have reported a seasonal variation in lithium serum levels, with higher levels during summer. Our objective was to investigate the impact of actual environmental temperature on lithium serum levels. METHODS: A retrospective study was conducted using available records of lithium serum levels for the period between January 1995 and July 2004, obtained from three large teaching hospitals in The Netherlands. Lithium serum levels were linked to season and average daily temperature data obtained from the Royal Netherlands Meteorological Institute. An analysis was performed on all lithium serum levels not accounting for the intra-individual dependency of lithium serum levels. The association between season, temperature and both absolute lithium serum level and the frequency of potentially toxic serum levels was investigated. A mixed model analysis, accounting for intra-individual dependency of lithium serum levels, was performed. RESULTS: A total of 41,102 lithium serum levels (3,054 patients) were included. A significant difference in mean lithium serum levels across seasons (p < 0.001) and temperature categories (p = 0.001) was found, peaking in summer [0.761 mmol/L, +/- standard error of the mean (SEM) 0.002] and at temperatures of 15-20 degrees C [0.762 mmol/L (+/- SEM 0.005)], and at a minimum in winter [0.748 mmol/L (+/- SEM 0.002)] and at <0 degrees C [0.741 mmol/L (+/- SEM 0.005)]. The relative frequency of potentially toxic serum levels significantly differed between seasons (p = 0.023, highest in winter), but not between temperature categories (p = 0.481). A significant positive association for intra-individual lithium serum level and season (p < 0.001) and temperature (p < 0.001) was established. CONCLUSIONS: Season and environmental temperature have a statistically significant but therapeutically irrelevant effect on lithium serum levels.

Instrumental variables: application and limitations.

To correct for confounding, the method of instrumental variables (IV) has been proposed. Its use in medical literature is still rather limited because of unfamiliarity or inapplicability. By introducing the method in a nontechnical way, we show that IV in a linear model is quite easy to understand and easy to apply once an appropriate instrumental variable has been identified. We also point out some limitations of the IV estimator when the instrumental variable is only weakly correlated with the exposure. The IV estimator will be imprecise (large standard error), biased when sample size is small, and biased in large samples when one of the assumptions is only slightly violated. For these reasons, it is advised to use an IV that is strongly correlated with exposure. However, we further show that under the assumptions required for the validity of the method, this correlation between IV and exposure is limited. Its maximum is low when confounding is strong, such as in case of confounding by indication. Finally, we show that in a study in which strong confounding is to be expected and an IV has been used that is moderately or strongly related to exposure, it is likely that the assumptions of IV are violated, resulting in a biased effect estimate. We conclude that instrumental variables can be useful in case of moderate confounding but are less useful when strong confounding exists, because strong instruments cannot be found and assumptions will be easily violated.

Hyphal differentiation in the exploring mycelium of Aspergillus niger.

Mycelial fungi play a central role in element cycling in nature by degrading dead organic material such as wood. Fungal colonization of a substrate starts with the invasion of exploring hyphae. These hyphae secrete enzymes that convert the organic material into small molecules that can be taken up by the fungus to serve as nutrients. Using green fluorescent protein (GFP) as a reporter, we show for the first time that exploring hyphae of Aspergillus niger differentiate with respect to enzyme secretion; some strongly express the glucoamylase gene glaA, while others hardly express it at all. When a cytoplasmic GFP was used, 27% of the exploring hyphae of a 5-day-old colony belonged to the low expressing hyphae. By fusing GFP to glucoamylase and by introducing an ER retention signal, this number increased to 50%. This difference is due to cytoplasmic streaming of the reporter in the former case, as was shown by using a photo-activatable GFP. Our findings indicate that a fungal mycelium is highly differentiated, especially when taking into account that hyphae in the exploration zone were exposed to the same nutritional conditions.