José Cortiñas Abrahantes

Reintroduction of Oxaliplatin Is Associated With Improved Survival in Advanced Colorectal Cancer

PURPOSE In the OPTIMOX1 trial, previously untreated patients with advanced colorectal cancer were randomly assigned to two different schedules of leucovorin, fluorouracil, and oxaliplatin that were administered until progression in the control arm or in a stop-and-go fashion in the experimental arm. The randomly assigned treatment groups did not differ significantly in terms of response rate, progression-free survival, and overall survival (OS). However, the impact of oxaliplatin reintroduction on OS was potentially masked by the fact that a large number of patients did not receive the planned oxaliplatin reintroduction or received oxaliplatin after second-line therapy in both treatment groups. PATIENTS AND METHODS A Cox model was fitted with all significant baseline factors plus time-dependent variables reflecting tumor progression, reintroduction of oxaliplatin, and use of second-line irinotecan. A shared frailty model was fitted with all significant baseline factors plus the number of lines of chemotherapy received by the patient and the percentage of patients with oxaliplatin reintroduction in the center. An adjusted hazard ratio (HR) was calculated for three reintroduction classes (1% to 20%, 21% to 40%, and > 40%), using centers with no reintroduction (0%) as the reference group. RESULTS Oxaliplatin reintroduction had an independent and significant impact on OS (HR = 0.56, P = .009). The percentage of patients with oxaliplatin reintroductions also had a significant impact on OS. Centers in which more than 40% of the patients were reintroduced had an adjusted HR for OS of 0.59 compared with centers in which no patient was reintroduced. CONCLUSION Oxaliplatin reintroduction is associated with improved survival in patients with advanced colorectal cancer.

Evaluation of Chromogenic Media for Detection of Methicillin-Resistant Staphylococcus aureus

ABSTRACT Rapid laboratory diagnosis is critical for treating, managing, and preventing methicillin-resistant Staphylococcus aureus (MRSA) infections. We evaluated and compared the potential for MRSA detection of five chromogenic media, Brilliance MRSA agar (Oxoid), ChromID (bioMérieux), MRSASelect (Bio-Rad), CHROMagar (CHROMagar Microbiology), and BBL-CHROMagar (BD Diagnostics). Media were tested with log serial dilutions (100 to 106 CFU) of pure isolates of MRSA (n = 60), non-MRSA (n = 27), and defined mixtures thereof simulating clinical samples (n = 84). Further evaluations were done on pre-enriched nasal and groin screening swabs (n = 213) from 165 hospitalized patients. Randomized samples were spiral plated on each medium and independently scored by five investigators for characteristic colonies at 24 and 48 h of incubation. Confirmatory testing of up to five putative MRSA colonies recovered from each medium was done. The cumulative average sensitivity with isolates, mixtures, and clinical samples was the highest for Brilliance MRSA agar (97%) and similar for the other four media (≥92%). The cumulative average specificity was the highest for BBL-CHROMagar (99%), followed by MRSASelect (98%), CHROMagar (97%), ChromID (89%), and Brilliance MRSA agar (86%). All of the media detected MRSA at 10 and 1 CFU, although at these low loads, few MRSA samples harboring SCCmec type III or IV were misinterpreted as non-MRSA by investigators. False-positive results were mainly due to methicillin-resistant S. epidermidis. For an arbitrary MRSA prevalence of 5% and based on patient sample evaluations, the positive predictive values for BBL-CHROMagar and CHROMagar (∼84%) were the highest. The negative predictive values of all of the media were ≥92% for MRSA prevalences ranging from 5% to 30%. In conclusion, BBL-CHROMagar and CHROMagar gave the best overall results for detection of MRSA, irrespective of the sample concentration, investigator, or incubation period.

The Schmallenberg virus epidemic in Europe—2011–2013

During the Schmallenberg virus (SBV) epidemic, the European Food Safety Authority (EFSA) collected data on SBV occurrence across Europe in order to provide an assessment of spread and impact. By May 2013, twenty-nine countries were reporting to EFSA and twenty-two countries had reported cases of SBV. The total number of SBV herds reported was 13,846 and the number of SBV laboratory confirmed herds was 8730. The surveillance activities were based on the detection of SBV clinical cases (either adults or newborns). Malformation in newborns was the most commonly reported clinical sign of SBV-infection. All countries were able to provide the date when the first suspicion of SBV in the herd was reported and nineteen could report the location of the herd at a regional level. This allowed the spread of SBV in Europe to be measured both temporally and spatially. The number of SBV confirmed herds started to increase in December 2011 and two peaks were observed in 2012 (February and May). Confirmed herds continued to be reported in 2012 and into 2013. An increase during winter 2012 and spring 2013 was again observed, but the number of confirmed herds was lower than in the previous year. SBV spread rapidly throughout Europe from the initial area of detection. SBV was detected above the latitude of 60° North, which exceeds the northern expansion observed during the bluetongue virus serotype 8 epidemic in 2006-2009. The impact of SBV was calculated as ratio of the number of herds with at least one malformed SBV positive foetus and the total number of herds in this region. The 75th percentile of the malformations ratio in the various affected countries for the whole reporting period was below 1% and 3% for cattle and sheep herds, respectively. International data collection on emerging diseases represents a challenge as the nature of available data, data quality and the proportion of reported cases may vary widely between affected countries. Surveillance activities on emerging animal diseases are often structured only for case detection making the estimation of infection/diseases prevalence and the investigation of risk factors difficult. The impact of the disease must be determined to allow risk managers to take appropriate decisions. Simple within-herd impact indicators suitable for emerging disease outbreaks should be defined that could be measured as part of routine animal health surveillance programmes and allow for rapid and reliable impact assessment of emerging animal health diseases.

Simplified hierarchical linear models for the evaluation of surrogate endpoints

The linear mixed-effects model (Verbeke and Molenberghs, 2000) has become a standard tool for the analysis of continuous hierarchical data such as, for example, repeated measures or data from meta-analyses. However, in certain situations the model does pose insurmountable computational problems. Precisely this has been the experience of Buyse et al. (2000a) who proposed an estimation- and prediction-based approach for evaluating surrogate endpoints. Their approach requires fitting linear mixed models to data from several clinical trials. In doing so, these authors built on the earlier, single-trial based, work by Prentice (1989), Freedman et al. (1992), and Buyse and Molenberghs (1998). While Buyse et al. (2000a) claim their approach has a number of advantages over the classical single-trial methods, a solution needs to be found for the computational complexity of the corresponding linear mixed model. In this paper, we propose and study a number of possible simplifications. This is done by means of a simulation study and by applying the various strategies to data from three clinical studies: Pharmacological Therapy for Macular Degeneration Study Group (1977), Ovarian Cancer Meta-analysis Project (1991) and Corfu-A Study Group (1995).

Update: use of the benchmark dose approach in risk assessment

Abstract The Scientific Committee (SC) reconfirms that the benchmark dose (BMD) approach is a scientifically more advanced method compared to the NOAEL approach for deriving a Reference Point (RP). Most of the modifications made to the SC guidance of 2009 concern the section providing guidance on how to apply the BMD approach. Model averaging is recommended as the preferred method for calculating the BMD confidence interval, while acknowledging that the respective tools are still under development and may not be easily accessible to all. Therefore, selecting or rejecting models is still considered as a suboptimal alternative. The set of default models to be used for BMD analysis has been reviewed, and the Akaike information criterion (AIC) has been introduced instead of the log‐likelihood to characterise the goodness of fit of different mathematical models to a dose–response data set. A flowchart has also been inserted in this update to guide the reader step‐by‐step when performing a BMD analysis, as well as a chapter on the distributional part of dose–response models and a template for reporting a BMD analysis in a complete and transparent manner. Finally, it is recommended to always report the BMD confidence interval rather than the value of the BMD. The lower bound (BMDL) is needed as a potential RP, and the upper bound (BMDU) is needed for establishing the BMDU/BMDL per ratio reflecting the uncertainty in the BMD estimate. This updated guidance does not call for a general re‐evaluation of previous assessments where the NOAEL approach or the BMD approach as described in the 2009 SC guidance was used, in particular when the exposure is clearly smaller (e.g. more than one order of magnitude) than the health‐based guidance value. Finally, the SC firmly reiterates to reconsider test guidelines given the expected wide application of the BMD approach.

Evaluation of Molecular Assays for Rapid Detection of Methicillin-Resistant Staphylococcus aureus

ABSTRACT The diagnostic sensitivities of the BD GeneOhm and Cepheid Xpert assays were compared using culture on log-serial dilutions of well-characterized methicillin-resistant Staphylococcus aureus (MRSA) and non-MRSA strains and on nasal and groin swabs from patients with histories of MRSA carriage. The sensitivities of GeneOhm and Xpert were high at 103-CFU/ml MRSA concentrations (92.3% and 96.3%, respectively) although decreased considerably (<35%) at a 1-log-lower concentration. Unexpectedly, both assays also detected select coagulase-negative staphylococci, which requires further evaluation.

Inferences about the transmission of Schmallenberg virus within and between farms

In the summer of 2011 Schmallenberg virus (SBV), a Culicoides-borne orthobunyavirus, emerged in Germany and The Netherlands and subsequently spread across much of Europe. To draw inferences about the transmission of SBV we have developed two models to describe its spread within and between farms. The within-farm model was fitted to seroprevalence data for cattle and sheep farms in Belgium and The Netherlands, with parameters estimated using approximate Bayesian computation. Despite the short duration of viraemia in cattle and sheep (mean of 3–4 days) the within-farm seroprevalence can reach high levels (mean within-herd seroprevalence >80%), largely because the probability of transmission from host to vector is high (14%) and SBV is able to replicate quickly (0.03 per day-degree) and at relatively low temperatures (threshold for replication: 12.3 °C). Parameter estimates from the within-farm model were then used in a separate between-farm model to simulate the regional spread of SBV. This showed that the rapid spread of SBV at a regional level is primarily a consequence of the high probability of transmission from host to vector and the temperature requirements for virus replication. Our results, obtained for a region of the UK in a typical year with regard to animal movements, indicate that there is no need to invoke additional transmission mechanisms to explain the observed patterns of rapid spread of SBV in Europe. Moreover, the imposition of movement restrictions, even a total movement ban, has little effect on the spread of SBV at this scale.

Choice of units of analysis and modeling strategies in multilevel hierarchical models

Hierarchical models are common in complex surveys, psychometric applications, as well as agricultural and biomedical applications, to name but a few. The context of interest here is meta-analysis, with emphasis on the use of such an approach in the evaluation of surrogate endpoints in randomized clinical trials. The methodology rests on the ability to replicate the effect of treatment on both the true endpoint, as well as the candidate surrogate endpoint, across a number of trials. However, while a meta-analysis of clinical trials in the same indication seems the natural hierarchical structure, some authors have considered center or country as the unit, either because no meta-analytic data were available or because, even when available, they might not allow for a sufficient level of replication. This leaves us with two important, related questions. First, how sensible is it to replace one level of replication by another one? Second, what are the consequences when a truly three- or higher-level model (e.g., trial, center, patient) is replaced by a coarser two-level structure (either trial and patient or center and patient). The same or similar questions may occur in a number of different settings, as soon as interest is placed on the validity of a conclusion at a certain level of the hierarchy, such as in sociological or genetic studies. Using the framework of normally distributed endpoints, these questions will be studied, using both analytic calculation as well as Monte Carlo simulation.

Identification of risk factors for the prevalence and persistence of Salmonella in Belgian broiler chicken flocks

According to the European Food Safety Authority, salmonellosis is still one of the main causes of infectious foodborne gastroenteritis in humans. Broilers are an important source of salmonellosis after eggs and pork. Between 1987 and 1999 the trend of human salmonellosis incidence in Belgium increased constantly. However, from 2000 until 2005 a decrease in human cases was observed, probably following the sanitary measures implemented in the poultry breeder and laying sector. In order to decrease human infections it is essential to tackle the problem at the farm level to minimize cross-contamination from farm to fork. This paper seeks to answer two questions: (i) given the Salmonella status of the farm at a certain occasion (equal to the sampling time of the flock), what are the risk factors that the farm will be Salmonella positive at a following occasion? And (ii) what are the risk factors for a farm to be persistently positive for two consecutive flocks? We used surveillance data on 6824 broiler flocks studied for Salmonella infectivity from 2005 to 2006 in Belgium. The farms were tested regularly (3 weeks before slaughter of each broiler flock) for the presence of Salmonella based on multiple faecal samples per flock on a farm yielding clustered data. Generalized estimating equations, alternating logistic regression models, and random-intercept logistic regression models were employed to analyse these correlated binary data. Our results indicated that there are many factors that influence Salmonella risk in broiler flocks, and that they interact. Accounting for interactions between risk factors leads to an improved determination of those risk factors that increase infection with Salmonella. For the conditional analysis, the risk factors found to increase the risk of Salmonella infection on a farm at a current occasion given the previous Salmonella status included: Salmonella infection of day-old chicks (of the current flock); a previously infected flock even though the farm was equipped with a hygiene place to change clothes prior to entering the broiler house; having temporary workmen when there was a separation between birds of different species; and separating birds of different species in the Walloon region relative to the Flanders region. Sanitary measures such as a cleaning and disinfecting procedure conducted by an external cleaning firm, applying the all-in all-out procedure, and hand washing decreased the risk despite their interaction with other factors. From the joint analysis, the most important factors identified for increased risk for persistent Salmonella on a farm involved the interaction between having temporary workmen when there were poultry or farmers in contact with foreign poultry or persons, and the interaction between having temporary workmen when there were poultry or farmers in contact with external poultry or persons.

Comparison of different estimation procedures for proportional hazards model with random effects

Proportional hazards models with multivariate random effects (frailties) acting multiplicatively on the baseline hazard are a topic of intensive research. Several estimation procedures have been proposed to deal with this type of models. Four procedures used to fit these models are compared in two real-life datasets and in a simulation study. The performance of the four methods is investigated in terms of the bias of point estimates, their empirical variability and the bias of the estimation of the variability.