Selection and Misclassification Biases in Longitudinal Studies.

Using imperfect tests may lead to biased estimates of disease frequency and measures of association. Many studies have looked into the effect of misclassification on statistical inferences. These evaluations were either within a cross-sectional study framework, assessing biased prevalence, or for cohort study designs, evaluating biased incidence rate or risk ratio estimates based on misclassification at one of the two time-points (initial assessment or follow-up). However, both observations at risk and incident cases can be wrongly identified in longitudinal studies, leading to selection and misclassification biases, respectively. The objective of this paper was to evaluate the relative impact of selection and misclassification biases resulting from misclassification, together, on measures of incidence and risk ratio. To investigate impact on measure of disease frequency, data sets from a hypothetical cohort study with two samples collected one month apart were simulated and analyzed based on specific test and disease characteristics, with no elimination of disease during the sampling interval or clustering of observations. Direction and magnitude of bias due to selection, misclassification, and total bias was assessed for diagnostic test sensitivity and specificity ranging from 0.7 to 1.0 and 0.8 to 1.0, respectively, and for specific disease contexts, i.e., disease prevalences of 5 and 20%, and disease incidences of 0.01, 0.05, and 0.1 cases/animal-month. A hypothetical exposure with known strength of association was also generated. A total of 1,000 cohort studies of 1,000 observations each were simulated for these six disease contexts where the same diagnostic test was used to identify observations at risk at beginning of the cohort and incident cases at its end. Our results indicated that the departure of the estimates of disease incidence and risk ratio from their true value were mainly a function of test specificity, and disease prevalence and incidence. The combination of the two biases, at baseline and follow-up, revealed the importance of a good to excellent specificity relative to sensitivity for the diagnostic test. Small divergence from perfect specificity extended quickly to disease incidence over-estimation as true prevalence increased and true incidence decreased. A highly sensitive test to exclude diseased subjects at baseline was of less importance to minimize bias than using a highly specific one at baseline. Near perfect diagnostic test attributes were even more important to obtain a measure of association close to the true risk ratio, according to specific disease characteristics, especially its prevalence. Low prevalent and high incident disease lead to minimal bias if disease is diagnosed with high sensitivity and close to perfect specificity at baseline and follow-up. For more prevalent diseases we observed large risk ratio biases towards the null value, even with near perfect diagnosis.

Herd-Level Mastitis-Associated Costs on Canadian Dairy Farms.

Mastitis imposes considerable and recurring economic losses on the dairy industry worldwide. The main objective of this study was to estimate herd-level costs incurred by expenditures and production losses associated with mastitis on Canadian dairy farms in 2015, based on producer reports. Previously, published mastitis economic frameworks were used to develop an economic model with the most important cost components. Components investigated were divided between clinical mastitis (CM), subclinical mastitis (SCM), and other costs components (i.e., preventive measures and product quality). A questionnaire was mailed to 374 dairy producers randomly selected from the (Canadian National Dairy Study 2015) to collect data on these costs components, and 145 dairy producers returned a completed questionnaire. For each herd, costs due to the different mastitis-related components were computed by applying the values reported by the dairy producer to the developed economic model. Then, for each herd, a proportion of the costs attributable to a specific component was computed by dividing absolute costs for this component by total herd mastitis-related costs. Median self-reported CM incidence was 19 cases/100 cow-year and mean self-reported bulk milk somatic cell count was 184,000 cells/mL. Most producers reported using post-milking teat disinfection (97%) and dry cow therapy (93%), and a substantial proportion of producers reported using pre-milking teat disinfection (79%) and wearing gloves during milking (77%). Mastitis costs were substantial (662 CAD per milking cow per year for a typical Canadian dairy farm), with a large portion of the costs (48%) being attributed to SCM, and 34 and 15% due to CM and implementation of preventive measures, respectively. For SCM, the two most important cost components were the subsequent milk yield reduction and culling (72 and 25% of SCM costs, respectively). For CM, first, second, and third most important cost components were culling (48% of CM costs), milk yield reduction following the CM events (34%), and discarded milk (11%), respectively. This study is the first since 1990 to investigate costs of mastitis in Canada. The model developed in the current study can be used to compute mastitis costs at the herd and national level in Canada.

Diagnosing intramammary infection: Controlling misclassification bias in longitudinal udder health studies.

Using imperfect tests may lead to biased estimates of disease frequency and of associations between risk factors and disease. For instance in longitudinal udder health studies, both quarters at risk and incident intramammary infections (IMI) can be wrongly identified, resulting in selection and misclassification bias, respectively. Diagnostic accuracy can possibly be improved by using duplicate or triplicate samples for identifying quarters at risk and, subsequently, incident IMI. The objectives of this study were to evaluate the relative impact of selection and misclassification biases resulting from IMI misclassification on measures of disease frequency (incidence) and of association with hypothetical exposures. The effect of improving the sampling strategy by collecting duplicate or triplicate samples at first or second sampling was also assessed. Data sets from a hypothetical cohort study were simulated and analyzed based on a separate scenario for two common mastitis pathogens representing two distinct prevailing patterns. Staphylococcus aureus, a relatively uncommon pathogen with a low incidence, is identified with excellent sensitivity and almost perfect specificity. Coagulase negative staphylococci (CNS) are more prevalent, with a high incidence, and with milk bacteriological culture having fair Se but excellent Sp. The generated data sets for each scenario were emulating a longitudinal cohort study with two milk samples collected one month apart from each quarter of a random sample of 30 cows/herd, from 100 herds, with a herd-level exposure having a known strength of association. Incidence of IMI and measure of association with exposure (odds ratio; OR) were estimated using Markov Chain Monte Carlo (MCMC) for each data set and using different sampling strategies (single, duplicate, triplicate samples with series or parallel interpretation) for identifying quarters at risk and incident IMI. For S. aureus biases were small with an observed incidence of 0.29 versus a true incidence of 0.25IMI/100 quarter-month. In the CNS scenario, diagnostic errors in the two samples led to important selection (40IMI/100 quarter-month) and misclassification (23IMI/100 quarter-month) biases for estimation of IMI incidence, respectively. These biases were in opposite direction and therefore the incidence measure obtained using single sampling on both the first and second test (29IMI/100 quarter-month) was exactly the true value. In the S. aureus scenario the OR for association with exposure showed little bias (observed OR of 3.1 versus true OR of 3.2). The CNS scenario revealed the presence of a large misclassification bias moving the association towards the null value (OR of 1.7 versus true OR of 2.6). Little improvement could be brought using different sampling strategies aiming at improving Se and/or Sp on first and/or second sampling or using a two out of three interpretation for IMI definition. Increasing number of samples or tests can prevent bias in some situations but efforts can be spared by holding to a single sampling approach in others. When designing longitudinal studies, evaluating potential biases and best sampling strategy is as critical as the choice of test.

Marginal structural Cox model to estimate the causal effect of clinical mastitis on Québec dairy cow culling risk.

Health disorders, such as milk fever, displaced abomasum, or retained placenta, as well as poor reproductive performance, are known risk factors for culling in dairy cows. Clinical mastitis (CM) is one of the most influential culling risk factors. However the culling decision could be based either on the disease status or on the current milk yield, milk production being a significant confounder when modelling dairy cow culling risk. But milk yield (and somatic cell count) are time-varying confounders, which are also affected by prior CM and therefore lie on the causal pathway between the exposure of interest, CM, and the outcome, culling. Including these time-varying confounders could result in biased estimates. A marginal structural model (MSM) is a statistical technique allowing estimation of the causal effect of a time-varying exposure in the presence of time-varying covariates without conditioning on these covariates. The objective of this paper is to estimate the causal effect on culling of CM occurring between calving and 120 days in milk, using MSM to control for such time-varying confounders affected by previous exposure. A retrospective longitudinal study was conducted on data from dairy herds in the Province of Québec, Canada, by extracting health information events from the dairy herd health management software used by most Québec dairy producers and their veterinarians. The data were extracted for all lactations starting between January 1st and December 31st, 2010. A total of 3952 heifers and 8724 cows from 261 herds met the inclusion criteria and were used in the analysis. The estimated CM causal hazard ratios were 1.96 [1.57-2.44] and 1.47 [1.28-1.69] for heifers and cows, respectively, and as long as causal assumptions hold. Our findings confirm that CM was a risk factor for culling, but with a reduced effect compared to previous studies, which did not properly control for the presence of time-dependent confounders such as milk yield and somatic cell count. Cows experienced a lower risk for CM, with milk production having more influence on culling risk in cows than heifers.

Culling from the herd's perspective-Exploring herd-level management factors and culling rates in Québec dairy herds.

The relationship between cows' health, reproductive performance or disorders and their longevity is well demonstrated in the literature. However these associations at the cow level might not hold true at the herd level, and herd-level variables can modify cow-level outcomes independently of the cows' characteristics. The interaction between cow-level and herd-level variables is a relevant issue for understanding the culling of dairy cows. However it requires the appropriate group-level variables to assess any contextual effect. Based on 10 years of health and production data, the objectives of this paper are:(a) to quantify the culling rates of dairy herds in Québec; (b) to determine the profiles of the herds based on herd-level factors, such as demographics, reproduction, production and health indicators, and whether these profiles can be related to herd culling rates for use as potential contextual variables in multilevel modelling of culling risk. A retrospective longitudinal study was conducted on data from dairy herds in Québec, Canada, by extracting health information events from the dairy herd health management software used by most Québec producers and their veterinarians. Data were extracted for all lactations taking place between January 1st, 2001 and December 31st, 2010. A total of 432,733 lactations from 156,409 cows out of 763 herds were available for analysis. Thirty cow-level variables were aggregated for each herd and years of follow-up, and their relationship was investigated by Multiple Factor Analysis (MFA). The overall annual culling rate was 32%, with a 95% confidence interval (CI) of [31.6%,32.5%]. The dairy sale rate by 60 days in milk (DIM) was 3.2% [2.8%,3.6%]. The annual culling rate within 60 DIM was 8.2% [7.9%,8.4%]. The explained variance for each axis from the MFA was very low: 14.8% for the first axis and 13.1% for the second. From the MFA results, we conclude there is no relationship between the groups of herd-level indicators, demonstrating the heterogeneity among herds for their demographics, reproduction and production performance, and health status. However, based on Principal Component Analysis (PCA), the profiles of herds could be determined according to specific, single, herd-level indicators independently. The relationships between culling rates and specific herd-level variables within factors were limited to livestock sales, proportion of first lactation cows, herd size, proportion of calvings occurring in the fall, longer calving intervals and reduced 21-day pregnancy rates, increased days to first service, average age at first calving, and reduced milk fever incidence. The indicators found could be considered as contextual variables in multilevel model-building strategies to investigate cow culling risk.

Culling from the actors' perspectives-Decision-making criteria for culling in Québec dairy herds enrolled in a veterinary preventive medicine program.

The series of events leading to the decision to cull a cow is complex, involving both individual-level and herd-level factors. While the decision is guided by financial returns, it is also influenced by social and psychological factors. Research studies on the motivational and behavioural aspects of farmers' decision utility are sparse, and nonexistent regarding culling expectations and its decision process. Our goal was to identify shared criteria on culling decisions held by dairy producers and farm advisers, with the help of the Q-methodology. Forty-one dairy producers and 42 advisers (17 veterinarians, 13 feed mill advisers, and 12 dairy herd improvement (DHI) advisers) undertook a Q-sort with 40 statements that represented a range of views about cow and herd health, production performance, management issues, and material factors that might impact their culling decision-making process. The sorts were analysed by-person using factor analysis and oblimin rotation. A single view on culling could be identified among dairy producers that can be extended to dairy farm advisers, who showed two variations of the same well-structured, uni-dimensional decision-making process. Udder health, milk production performance, and milk quota management were the key criteria for the culling decision. Farm management parameters (debts, amortization, employees, milking parlour capacity, herd size) did not play any role in the decision process. Three key differences were, however, identified between producers and the two types of advisers. One group of advisers followed the recommendations from mathematical models, where pregnancy is a major determinant of a cow's value. They assessed the cow in a more abstract way than did the other participants, still taking into account udder health and milk production, but adding economic considerations, like the availability of financial incentives and an evaluation of the post-partum health of the cow. Dairy producers were also more concerned about producing healthy and safe milk, which might reflect a different value given to dairy farming than by advisers. Very different degrees of importance were given to animal welfare by the three groups, which could represent different views on the attributed relationships between dairy farmers and their animals. Our findings suggest that dairy producers and their advisers hold a general common view regarding culling decision-making. However there are significant differences between producers and advisers, and among advisers. Understanding and managing these differences is important for assisting the change management processes required to increase farm profitability, and call for further investigation.

Contextual herd factors associated with cow culling risk in Québec dairy herds: A multilevel analysis.

Several health disorders, such as milk fever, displaced abomasum, and mastitis, as well as impaired reproductive performance, are known risk factors for the removal of affected cows from a dairy herd. While cow-level risk factors are well documented in the literature, herd-level associations have been less frequently investigated. The objective of this study was to investigate the effect of cow- and herd-level determinants on variations in culling risk in Québec dairy herds: whether herd influences a cow's culling risk. For this, we assessed the influence of herd membership on cow culling risk according to displaced abomasum, milk fever, and retained placenta. A retrospective longitudinal study was conducted on data from dairy herds in the Province of Québec, Canada, by extracting health information events from the dairy herd health management software used by most Québec dairy producers and their veterinarians. Data were extracted for all lactations starting between January 1st and December 31st, 2010. Using multilevel logistic regression, we analysed a total of 10,529 cows from 201 herds that met the inclusion criteria. Milk fever and displaced abomasum were demonstrated to increase the cow culling risk. A minor general herd effect was found for the culling risk (i.e. an intra-class correlation of 1.0% and median odds ratio [MOR] of 1.20). The proportion of first lactation cows was responsible for this significant, but weak herd effect on individual cow culling risk, after taking into account the cow-level factors. On the other hand, the herd's average milk production was a protective factor. The planning and management of forthcoming replacement animals has to be taken into consideration when assessing cow culling risks and herd culling rates.

Characterization of the ability of coagulase-negative staphylococci isolated from the milk of Canadian farms to form biofilms.

Mastitis is the most common and detrimental infection of the mammary gland in dairy cows and has a major economic impact on the production of milk and dairy products. Bacterial mastitis is caused by several pathogens, and the most frequently isolated bacterial species are coagulase-negative staphylocci (CNS). Although CNS are considered minor mastitis pathogens, the importance of CNS has increased over the years. However, the mechanism and factors involved in CNS intramammary infection are poorly studied and defined. Biofilms have been proposed as an important component in the persistence of CNS intramammary infection. Biofilms are defined as a cluster of bacteria enclosed in a self-produced matrix. The objectives of this study were to investigate the ability of CNS to form biofilms. A total of 255 mastitis-associated CNS isolates were investigated using a standard microtiter plate biofilm assay. The biofilms of some isolates were also observed by using confocal microscopy. The presence of biofilm-associated genes icaA, bap, aap, embP, fbe, and atlE was determined by PCR in the 255 isolates. The 5 dominant species assayed were Staphylococcus chromogenes (n=111), Staphylococcus simulans (n=53), Staphylococcus xylosus (n=25), Staphylococcus haemolyticus (n=15), and Staphylococcus epidermidis (n=13), and these represented 85% of the isolates. The data gathered were analyzed to identify significant links with the data deposited in the Canadian Bovine Mastitis Research Network database. Overall, Staph. xylosus is the species with the strongest ability to form biofilm, and Staph. epidermidis is the species with the lowest ability to form biofilm. Regardless of the species, the presence of icaA, bap, or the combination of multiple genes was associated with a greater ability to form biofilm. A strong relationship between the strength of a biofilm and days in milk was also noted, and CNS isolated later in the lactation cycle appeared to have a greater ability to form biofilm than those isolated earlier in the lactation cycle. In conclusion, Staph. xylosus is the species with the strongest biofilm formation ability. Furthermore, days in milk and gene combinations are predicted to be the variables with the strongest effect on biofilm formation by CNS.

Tramiprosate in mild-to-moderate Alzheimer's disease - a randomized, double-blind, placebo-controlled, multi-centre study (the Alphase Study).

INTRODUCTION: The aim of the study was to assess the clinical efficacy, safety, and disease-modification effects of tramiprosate (homotaurine, ALZHEMED(TM)) in mild-to-moderate Alzheimer's disease (AD). MATERIAL AND METHODS: Double-blind, placebo-controlled, randomized trial in 67 clinical centres across North America. Patients aged ≥ 50 years, with mild-to-moderate AD (Mini-Mental State Examination score between 16 and 26) and on stable doses of cholinesterase inhibitors, alone or with memantine. INTERVENTION: 78-week treatment with placebo, tramiprosate 100 mg or tramiprosate 150 mg BID. MEASUREMENTS: Alzheimer Disease Assessment Scale - cognitive subscale (ADAS-cog) and Clinical Dementia Rating - Sum of Boxes (CDR-SB) assessments were performed at baseline and every 13 weeks. Baseline and 78-week magnetic resonance imaging (MRI) hippocampus volume (HV) measurements were conducted in a subgroup of patients. RESULTS: A total of 1,052 patients were enrolled and 790 (75.1%) completed the 78-week trial. Patient discontinuation and reasons for withdrawal were similar across groups. Planned analyses did not reveal statistically significant between-group differences. Lack of adequate statistical validity of the planned analysis models led to the development of revised predictive models. These adjusted models showed a trend toward a treatment effect for ADAS-cog (P = 0.098) and indicated significantly less HV loss for tramiprosate 100 mg (P = 0.035) and 150 mg (P = 0.009) compared to placebo. The incidence of adverse events was similar across treatment groups. CONCLUSIONS: The primary planned analyses did not show a significant treatment effect, but were confounded by unexplained variance. Post-hoc analyses showed a significant treatment-related reduction in HV loss. However, there was only a trend towards slowing of decline on the ADAS-cog and no slowing of decline on the CDR-SB. These results must be interpreted in consideration of the limitations of clinical and disease-modification outcome measures and their relationship, the heterogeneity of the disease and the impact of confounding demographic and clinical variables.

Tolerability and effectiveness of preservative-free dorzolamide-timolol (preservative-free COSOPT) in patients with open-angle glaucoma or ocular hypertension.

PURPOSE: To assess the effect of preservative-free dorzolamide-timolol on nonvisual symptoms and intraocular pressure (IOP) in newly diagnosed and untreated patients with open-angle glaucoma or ocular hypertension. METHODS: This was a prospective, 8-week, open-label, Canadian multicenter study. All patients were treated with preservative-free dorzolamide-timolol formulation. The primary outcome was the change in the nonvisual symptom score of the Glaucoma Symptom Scale (GSS-SYMP-6) from baseline to 8 weeks. Secondary effectiveness outcome measures were absolute and percent changes in IOP from baseline to 4 and 8 weeks. RESULTS: One hundred and seventy-eight patients were enrolled. Mean (SD) age was 65.6 (12.1) years and 90 (50.6%) were females. There were 92 patients diagnosed with open-angle glaucoma, 62 with ocular hypertension, and 23 with both diseases (diagnosis was missing for one patient). The mean (SD) GSS-SYMP-6 score increased from 73.6 (21.8) at baseline to 76.1 (20.7) at 8 weeks (P = 0.097). Mean (SD) IOP significantly decreased by 11.7 (5.1) mmHg at 4 weeks (P < 0.001) and by 11.5 (5.3) mmHg at 8 weeks (P < 0.001), representing reductions of -38.5% (P < 0.001) and -38.0% (P < 0.001), respectively. CONCLUSION: Preservative-free dorzolamide-timolol does not increase eye discomfort while significantly reducing IOP in patients with open-angle glaucoma or ocular-hypertension.

Montelukast as add-on therapy to inhaled corticosteroids in the management of asthma (the SAS trial).

AIM: To evaluate the effectiveness of montelukast as add-on therapy for asthmatic patients who remain uncontrolled with low, moderate or high doses of inhaled corticosteroid monotherapy. DESIGN: An eight-week, multicentre, open-label, observational study. RESULTS: Of 320 patients enrolled, 288 (90.0%) completed the study. Of patients who had uncontrolled asthma symptoms (Canadian Asthma Consensus Guidelines Update, 2003) but were controlled according to the Asthma Control Questionnaire (ACQ score of less than 1.5), 93.9% maintained asthma control at week 8. Of patients with uncontrolled asthma at baseline for both definitions, 63.5% achieved asthma control by week 8. The mean +/- SD ACQ score decreased from 1.13+/-0.28 to 0.57+/-0.50 (P<0.001) for controlled patients at baseline and from 2.38+/-0.73 to 1.03+/-0.80 (P<0.001) for patients who were uncontrolled at baseline, each representing a clinically significant improvement. CONCLUSION: Montelukast add-on therapy is an effective alternative to inhaled corticosteroid monotherapy.