Reminders at the point of care, computerized or not, have been demonstrated to be effective in changing physicians prescription behavior.The quality control of oral anticoagulant therapy (OAT) during the initiation and maintenance treatment is generally poor. Physicians' ordering of OAT (especially However, few studies have addressed the benefit of personalized reminders versus non personalized reminders, whereas the personalized reminders require more development to access patient record data and integrate with the computerized physician order entry system.The Hospital Information System of George Pompidou European Hospital integrates an electronic medical record, lab test and drugs order entry system. This system allows to evaluate such reminders and to consider their implementation for routine use as well as the continuous evaluation of their impact on medical practice quality indicators.The objective of this study is to evaluate the impact of two types of reminders on overtreatment by oral anticoagulant: a simple reminder of text formatted dose adjustment table and a personalized recommendation for oral anticoagulant dose and next date of INR control, adapted to patient data. Both types of reminders appear to the physician at the moment of drug ordering.fluindione or warfarin, will be included in the study between November 2004 and May 2006.The study is an alternating time series experiment with three 6 months periods, each one including every 2 months according to a Latin square scheme: a control period without any reminder, a period with the simple non personalized reminder, a period with personalized reminder. All patients hospitalized in departments using the computerized physician order entry system and ordered Main outcome will be the proportion of overcoagulation, as expressed by the proportion of observation time with INR over 4.5, assuming INR change linearly. Secondary outcome is the incidence of major haemorrhagic events. Data will be collected thanks to Hospital Information Systems databases.Data will be analyzed taking into account patient and physician clustering effect. According to a study carried out by French pharmacovigilance centres, haemorrhage subsequent to oral anticoagulant treatment (OAT) is the most common drug-related side effect resulting in hospitalisation in public hospitals in France . On the basis of these findings, the AFSSAPS  has made the prevention of iatrogenic effects related to OAT one of its priorities. Many of these events are consequences of interactions between different drugs, resulting in inappropriate doses [Implementation of a system of support when prescriptions are made out is likely to improve prescription practices and to decrease the frequency of side effects. It should be possible to integrate a support tool into the drug prescription system, by using nomograms to adjust OAT doses.et al. [The efficiency of reminders issued at the time of prescription has been demonstrated by a various studies -8. Theseet al.  reviewedet al. . We haveet al.  and in tet al. . ComputeSeveral types of reminders can be issued at the time of prescription :• simple, general information concerning the recommendations that should be taken into account ,• "check list": includes questions or a precise list of practices that the doctor must tick to show that it has been done,• reminders including clinical data concerning a specific patient that must be taken into account for a given procedure .The advantage of personalised reminders over non-personalised reminders has not been demonstrated in the literature. However, the production of personalised reminders necessitates better integration of existing information and is thus more expensive to develop. It is important to determine whether this personalised tool results in a better quality of care than non-personalised tools.Several randomised clinical trials have tried to evaluate decision support systems for the prescription of OAT, but failed to draw any conclusions about their efficiency for several reasons: heterogeneity and complexity of the systems evaluated, experimental designs difficult to apply and not necessarily adapted, and too few patients included -17.Reminders issued at the time of prescription have been shown to be effective by experimental studies, but the difficulties of maintaining the effectiveness of interventions designed to improve clinical practices remains a major problem. We evaluated the effect of an active decision support system for the prescription of low molecular weight heparin as prophylaxis for venal thrombosis in an orthopaedic surgery department. In this study, the system was and was not used during alternate periods. It showed that such programs affect practices without affecting learning . Other aThe hospital information system currently collates prescriptions and results of biological tests and imaging procedures. Eight hundred computers, both laptops and fixed posts, are used to in care procedures .® program is at the centre of care delivery. It is used by doctors and nurses:The Dx-Care• to prescribe laboratory examinations and imaging tests for a patient,• to visualise the results of laboratory tests,• to establish and to consult nursing schedules,• to archive a structured observation,• to prescribe drugs.® is integrated with other applications to allow circulation of information between departments, laboratories and the pharmacy. Prescriptions for laboratory tests are transmitted to the Netlab® program which manages such tests  The laboratories return the results using this same program, which retransmits them to Dx-Care®. Furthermore, prescriptions of drugs are transmitted to the Phedra program, which is used by the pharmacy to manage prescriptions. The prescription is validated by the pharmacy and this validation is then transferred to Dx-Care®. The lab test prescription facility has been available in the hospital information system since 2000 and is used by all departments of the hospital. The drug prescription facility has been implemented later on, since January 2003, and its use is still increasing .Dx-CareThe hospital information system thus allows to install decision support systems that are activated whenever a prescription is issued and routinely to collect evaluation criteria of prescription practices. If possible and validated, the use of the hospital information system to evaluate care procedures will make it possible to collect data regularly, and routinely to assess methods for the improvement of care practices.With the aim of quality of care and preventing risks, the hospital is developing a system, based on the Intranet network, of declaration of undesirable events. This system must be able to record all undesirable events and incidents linked to the use of health products  and care  as well as those due to the patient environment  and the job of health care professionals .When a health care professional decides to report an undesirable event, he or she must complete a dedicated form available on the Intranet with all relevant information. This incident form includes an item entitled "complications associated with anti-coagulants". When the doctor clicks on this item, a form specific to haemorrhagic accidents following anti-coagulant treatment appears (see form in appendix).Among departments which already started to use the computerised drug order entry system, several (cardiology and vascular medicine departments) are heavy "consumers" of anti-thrombosis drugs  in arterial thrombosis and venous thrombosis, and the way in which patients receiving anticoagulants are monitored and handled in cases of overdose. The procedure concerning curative OAT included a nomogram for adjusting doses of 1. To evaluate the effect on the frequency of overanticoagulation of the implementation in the computerised physician order entry system of two types of tool to adjust OAT doses .2. To assess any advantages of using the personalised tool rather than the non-personalised tool.1. To evaluate the frequency of haemorrhagic accidents in the context of the study.2. To evaluate the feasibility of long-term implementation of the intervention.The study is an alternate time series experiment which consists of three successive six-month periods . Each phase will consist of:• a two-month period without active support during which evaluation criteria will be collected (period A),• a two-month period with non-personalised active support (period B),• a two-month period with personalised active support (period C).To limit the impact of a learning effect on appropriate OAT management practice within the department over time , the order of these three periods was determined by using a Latin square plan . This experimental design can be considered valid for an impact study in this context whereas a randomised controlled design is difficult to apply with just one hospital .This study will include all the patients who are prescribed OAT for any indication and are hospitalised in clinical care departments where physicians are using the hospital information system to prescribe drugs.The following table shows the number of INR examinations prescribed by these departments in a three-month period. It provides an estimation of the approximate proportion of overdoses among the INR that exceeded 2, which is supposed to be found in patients treated with OAT in these units.All doctors authorised to prescribe drugs in the participating departments will be included in the study: residents and fellows, registered and non registered university hospital doctors. Each six-month period will coincide with an internship semester.®, the doctor selects the required drug from an exhaustive list. This opens up a dialogue box in which the doctor types the dose, the frequency of intake and the mode of administration. From this window, it is possible to add a text comment or to consult particular protocols that have been defined by the departments.To prescribe a drug using Dx-CareIt is planned to integrate two types of decision support systems into the computerised prescription program:1) non-personalised active system: when the drug is selected a window automatically opens giving the prescribing the nomogram for the adjustment of OAT doses in the form of a table (see Tables 2) personalised active system: when the drug is selected a window automatically opens suggesting a dose recommended according to the nomogram (taking into account the doses previously received by the patient and the patient's INR), together with a date for next INR control and an explication.Proportion of patient observation time with INR results > 4.5, assuming linear change of INRs.Intra-cranial haemorrhage or spontaneous haemorrhage necessitating surgery or a transfusion or decreasing haemoglobin concentration by more than 2 g/dl.® application allows biological laboratories to receive prescriptions and to return results. All of the INR results can be extracted from the Netlab® database accompanied by information making it possible to identify the patient, the treatment and dose received, the prescribing doctor, the hospitalisation unit, the date the test was prescribed. Data about overdoses can therefore be collected systematically by regular database searches.The NetlabFurthermore, the storage of the information in a computerised tool will make it possible to determine previous doses and INR results each time a drug is prescribed.When a health care professional decides to declare an undesirable event, he or she fills in a specific, pre-formatted form available on the Intranet. This form includes a list of events that must be declared at the GPEH.The declaration form includes an item entitled "complication of haemorrhagic accidents". When the doctor clicks on this item, a specific form for the declaration of a haemorrhagic accident associated with anti-coagulant treatment appears (see form in appendix).The determination of the number of participants necessary requires the definition of the statistical unit of interest, information about the incidence of the evaluation criteria in the study population and a hypothesis about the efficiency of the intervention.In this study, the main aims are to guide each prescription and to reduce the number of anti-coagulant overdoses: the simplest statistical unit to study is therefore the INR result. This unit will be used to calculate the sample size.This choice is not, however, perfect and the efficacy results will be presented using other indicators of the quality control of anti-coagulant treatments:Given the low incidence of major haemorrhagic accidents (not currently measured at the GPEH but probably below 1%), it is not possible in this study to estimate the number of subjects necessary to demonstrate an effect of intervention on the "haemorrhagic accident" endpoint. Recording haemorrhagic accidents will give the frequency of such accidents, which will then be used for realistic estimates of power and sample size if further studies are carried out.In previous studies evaluating the efficacy of tools to aid the prescription of OAT, the unit considered was not always the same, taking into account the number of INR per patient and the time between INR measurements to greater or lesser extents. The most recent studies considered the number of patient-days according to the method described by Rosendaal ,16,21. Ta priori lower than inter-physician variability.We may also carry out an analysis for each prescribing doctor given that the intervention targets doctors directly. This will involve adjusting the effect of the intervention to the fact that intra-physician variability is During a six-month period (January to June 2004), 4 920 INRs were requested by the six departments which already routinely use the computerized physician order entry system. The frequency of overtreatment can approximately be estimated from the percentage of INR > 4.5 among INR >2. Among the 2620 INR > 2, 330 (12%) were higher than 4.5 , for a basal incidence of the judgement criterion of 12% are and for the following hypotheses on relative reduction of the risk (RRR) of overdose, are:• RRR 30%: 2500• RRR 40%: 1300• RRR 50%: 800• RRR 60%: 500Carrying out approximately 5000 tests over six months will make it possible to detect an intervention effect of less than 30% in this period. The experimental design includes three six-month periods and should thus ensure adequate power.Statistical analyses will be performed with the STATA statistical software (release 8, STATA corp, College station, Tex, USA)Standard statistical tests will be used to compare the baseline characteristics of the departments and patients.The main analysis concerns the effect of the intervention on the number of dangerously high INRs. The analysis will be carried out using a mixed effect analysis of variance model, in which the effect linked to the period will be considered fixed and that linked to the prescription tool will be considered random .Rosendaal's method will be used to analyse the number of patient-days with INR over the target .According to French policy, this study was exempt from medical ethics committee approval. The anti-coagulants being evaluated are prescribed as recommended by clinical studies validated within the GPEH. These recommendations are available on the hospital's Intranet and are thus accessible to all doctors. They conform to standard practices. Neither the patients nor the doctors will be randomised. The interventions are simply different means of giving valid information to physicians. Using funding from the PHRC , we carried out two research studies related to this project. In the first (PHRC 95), an intervention aimed at modifying the way in which emergency department doctors handle ankle injuries, the study design was a randomised controlled study and the randomisation unit was the hospital . In the OAT: Oral Anticoagulant TherapyINR: International Normalized RatioGPEH: Georges Pompidou European HospitalPHRC: Hospital Clinical Research ProgramIC and PD, conceived, wrote the protocol and prepared the manuscript.GC is the statistical expert and performed the power calculationsGC and ABR revised the protocol and the manuscript.The pre-publication history for this paper can be accessed here:


Over 750 million children have iron-deficiency anemia. A simple powdered sachet may be the key to addressing this global problem A simple powdered sachet may be the key to addressing a global problem Recent World Health Organization (WHO)/United Nations Children's Fund estimates suggest that the number of children with iron-deficiency anaemia (IDA) is greater than 750 million In the developing world, there are three major approaches available to address iron deficiency: dietary diversification so as to include foods rich in absorbable iron, fortification of staple food items (such as wheat flour), and the provision of iron supplements. When dietary or fortification strategies are not logistically or economically feasible, supplementation of individuals and groups at risk is an alternative strategy. For the past 150 years or more, oral ferrous sulphate syrups have been the primary strategy to control IDA in infants and young children Our research group at the Hospital for Sick Children in Toronto conceived the strategy of “home fortification” with “Sprinkles”—single-dose sachets containing micronutrients in a powdered form, which are easily sprinkled onto any foods prepared in the household. We hypothesized that this would be a successful method to deliver iron and other micronutrients to children at risk In Sprinkles, the iron (ferrous fumarate) is encapsulated within a thin lipid layer to prevent the iron from interacting with food. This means that there are minimal changes to the taste, color, or texture of the food upon adding Sprinkles. Other micronutrients including zinc, iodine, vitamins C, D, and A, and folic acid may be added to Sprinkles sachets. Any homemade food can be fortified with the single-dose sachets, hence the term “home fortification”. Two formulations have been developed, a nutritional anaemia formulation  and a coTo investigate the bioavailability of the iron in Sprinkles, we used a dual stable isotope method and showed that anaemic infants absorbed iron from Sprinkles about twice as efficiently as nonanaemic infants when delivered in a maize-based diet in West Africa. The study was conducted in collaboration with the Kintampo Health Research Centre of the Ministry of Health in Accra, Ghana. The geometric mean iron absorption from two doses of iron  was 8.3% range, 2.9%–17.8%) in infants with anaemia and 4.5% (range, 1.1%–10.6%) in infants without anaemia %–17.8% iIt has been suggested that zinc may compete with iron for the same receptor sites on intestinal mucosal cells in the proximal duodenum, thereby compromising the absorption of both minerals Over the past five years, we have completed seven community-based trials in four different countries ,17,18,19We further examined this through quantile-quantile plots of haemoglobin concentrations at the end of the studies for Sprinkles and ferrous sulphate drops . The oveDuring our studies we also asked about the caregivers' perception of their infants' responses to Sprinkles as compared to drops, the Sprinkles' impact on the food to which they were added (change in taste, color, or consistency), the use of sachets as a delivery vehicle, and the perceived side effects of Sprinkles ,18,19. IAs the results of the first studies showing the efficacy of Sprinkles became available, the need for a reliable high-quality supply became apparent. In 2000, the H. J. Heinz Company of Pittsburgh, Pennsylvania, United States, expressed an interest in the Sprinkles program as a component of their corporate social responsibility program. Since 2001, the H. J. Heinz Company has provided support and expertise in the evaluation of consumer needs and a supply of Sprinkles for research, while the H. J. Heinz Company Foundation has provided financial support for research activities. Through a formal process of technology transfer, local overseas Sprinkles production has been encouraged. Currently, an independently licensed copacker is supporting local production for a national program in Guyana, and plans are in place for technology transfer to Bangladesh and Pakistan.The final stage, the scale-up process, is by far the most challenging. First, this process involves dialogue with the Ministries of Health, scientific community, civil society, and other private partners. Second, it is important to identify sustainable methods of distribution that are able to reach and provide Sprinkles to the most vulnerable populations in the developing world. From our experience in Mongolia, we have determined that it is feasible to distribute Sprinkles in partnership with a non-governmental organization called World Vision. Sprinkles sachets distributed in Mongolia over a two-year period included both iron and vitamin D. Sprinkles have been successfully distributed by World Vision field staff to over 15,000 children in seven districts. Coverage has been over 80%, at a cost of about US$0.03 per sachet. In the project area, the prevalence of anaemia (haemoglobin < 115 g/l) and rickets decreased from 42% to 24% and 48% to 33%, respectively Notwithstanding these positive results on anaemia control, without committed, long-term financial input from national governments, international agencies, or nongovernmental organizations, sustainability is not guaranteed. Clearly, sustainability over the long term can most likely be achieved if a program becomes self-financing. This may be achieved through public- and private-sector partnerships that use effective social marketing models or possibly through programs which include microcredit in order to reach poorer population groups.When strategizing how to scale up Sprinkles from small-scale research projects to large-scale programs, we quickly realized that our research group did not have the necessary funding, experience, or personnel needed to influence health policy, develop a social marketing strategy, or maintain a distribution network at a countrywide level. We have thus partnered with organizations that specialize in each of these areas to help achieve our goal of sustainable distribution.Shastha Shebika). In both of these countries, Sprinkles would be produced locally through public–private partnerships via a technology transfer agreement. The cost per sachet of locally produced Sprinkles should range from US$0.010 to US$0.015, depending on the volume of production, as compared to US$0.020 to US$0.025 if imported.For example, the government of Pakistan is planning to distribute Sprinkles through their ongoing Lady Health Worker Program, which is the largest public-sector primary health-care program implemented by the Federal Ministry of Health. In Bangladesh, BRAC , the largest national non-governmental organization in the country, is planning to distribute Sprinkles through their ongoing Female Community Health Worker program (popularly known as Each stage in the evolution of the Sprinkles intervention has been evaluated in a controlled manner. We determined that the use of encapsulated iron did not appreciably change the taste or color of the food to which it was added, we showed that the haemoglobin response in anaemic infants was equivalent to the current standard of practice, and we documented the acceptability of Sprinkles among caregivers who used Sprinkles in their homes. Finally, through various partnerships, we have developed a successful model to scale up the intervention for countrywide use. Our challenge for the future is to demonstrate the cost-effectiveness of this new intervention and to advocate for the adoption of Sprinkles in the nutrition policy of developing countries.


Allelic-loss studies record data on the loss of genetic material in tumor tissue relative to normal tissue at various loci along the genome. As the deletion of a tumor suppressor gene can lead to tumor development, one objective of these studies is to determine which, if any, chromosome arms harbor tumor suppressor genes.n0 versus n1. In these cases, frequentist test statistics based on the likelihood ratio statistic have unknown distributions and are therefore not applicable. Our simulation study shows that Bayes factors favor the right model most of the time when tumor suppressor genes are present. When no tumor suppressor genes are present and background allelic-loss varies, the Bayes factors are often inconclusive, although this results in a markedly reduced false-positive rate compared to that of standard frequentist approaches. Application of our methods to three data sets of esophageal adenocarcinomas yields interesting differences from those results previously published.We propose a large class of mixture models for describing the data, and we suggest using Bayes factors to select a reasonable model from the class in order to classify the chromosome arms. Bayes factors are especially useful in the case of testing that the number of components in a mixture model is Our results indicate that Bayes factors are useful for analyzing allelic-loss data. The goal of studies of allelic loss is to determine those loci in tumor tissue where genetic material has been lost. A tumor suppressor gene (TSG) is much more likely to lie on a chromosome arm where there has been significant allelic loss than elsewhere ,2. The sEsophageal adenocarcinoma is a form of cancer involving the cells along the lining of the esophagus. The cause of esophageal adenocarcinoma is not well understood. The incidence of this cancer has been increasing rapidly. In fact, it is one of the fastest growing cancers in the United States over the past 20 years ,3,4. A sWe examine three data sets of allelic-loss on esophageal adenocarcinomas that attempt to identify the tumor suppressor genes (TSGs) involved in the development of this disease. These data sets have been previously analyzed and published. We refer to each data set by the last name of the first author of the publication. Some of the data sets record allelic loss on multiple loci per chromosome arm for some of the arms. However, because the number of loci evaluated per chromosome arm is not random (i.e., chromosome arms suspected of harboring a TSG will be assessed at more loci than others), we consider only one locus per chromosome arm. In these cases, we choose data from the most informative locus for that chromosome arm.Our general approach to analyzing allelic-loss data can be described in two main steps. The first step is to choose an appropriate model for the data using Bayes factors. The second step is to classify the chromosome arms as harboring TSGs or not according to the selected model. The details involved in these two steps are described below.A natural way to model allelic-loss data is in terms of a mixture of two distributions: one distribution corresponds to chromosome arms that harbor TSGs and the other corresponds to arms that do not. It is reasonable to expect considerable variability in the loss rates of arms that harbor TSGs due to the existence of multiple pathways leading to the same tumor type . For exaXi be the number of tumors with allelic-loss for the ith chromosome arm, and let ni be the number of informative tumors for the ith chromosome arm, for i = 1, 2,...,N, where N is the number of chromosome arms in the study. The density function for Xi is written as follows:We propose a class of mixture models that account for the variation inherent in this type of data. Specifically, the class of models we propose is a mixture of two beta-binomial distributions. Let θ ≡ (η, π1, ω1, π0, ω0) is a vector of unknown parameters, η is the mixing probability, πj is the average loss rate, and ωj is the dispersion parameter for j = 0,1.where ω0 → 0 and ω1 → 0). If only one of the dispersion parameters goes to 0 (ω0 → 0 or ω1 → 0), the distribution reduces to a mixture of a beta-binomial and a binomial distribution. Note that the model has only one component when the mixing parameter is zero (η = 0).The distribution converges to a mixture of two binomial distributions as both dispersion parameters go to 0 /Pr(X|H0). Thus, as Bayes factors are proportional to the posterior odds of one model to another, they are desirable measures to use for model selection. Note that if the prior odds are assumed to be 1, then the Bayes factor is equivalent to the posterior odds.Equation (1) shows that the posterior odds is calculated as the product of a term known as the Bayes factor and the prior odds. The Bayes factor is the marginal likelihood of the data under One can think of the Bayes factor as a Bayesian likelihood ratio statistic. Like the likelihood ratio statistic, the Bayes factor is a ratio of likelihoods under two models being considered. However, while the likelihood ratio statistic is the ratio of two maximized likelihoods for two competing, nested models, the Bayes factor is the ratio of two likelihoods integrated or averaged over the entire parameter space and the models need not be nested. An important consideration with a Bayesian approach is that a prior distribution is assumed for all of the parameters in the model. The advantage to this is that one can incorporate prior information into determining which model is more appropriate. This is a disadvantage, however, if the Bayes factor is sensitive to the prior and if the prior has been chosen incorrectly.lnB10 > 2 implies positive evidence in favor of the alternative model.Large Bayes factors are evidence in favor of the alternative hypothesis. Kass and Raftery (1995) discuss guidelines for interpreting the measure . FollowiComparing a uni-component model to a two-component model would address the question of whether there is one versus two groups of chromosome arms. Further, comparing a two-component beta-binomial model to a two-component binomial model would address whether there is overdispersion in either group. The advantage of this is that it provides insight into the number of chromosome arm groups, whereas standard applicable frequentist tests will only indicate whether there is one or more groups ,9.Xi ~ ηf1(xi, ni, θ1) + (1 - η)f0(xi, ni, θ0), then it can be shown using Bayes' rule thatProvided there is sufficient evidence to indicate that there are two groups of chromosome arms, it is desirable to identify which chromosome arms belong in which group. Classification of the chromosome arms can be done by calculating the conditional probability of group membership of each arm under a given model. If  is the maximum likelihood estimate (MLE) of θ, Zi is the group membership of the ith chromosome arm and Zi = 1 implies that the ith chromosome arm is in the TSG group. For the analyses here, chromosome arms with conditional probabilities exceeding 0.5 are classified in the TSG group. Also note that MLEs are computed using the nlminb function in S-Plus.where Table ln(Bayes factor) for data generated under each of the scenarios described in Table H1 (models appearing in the numerator of the Bayes factor). The columns of the matrix correspond to models considered under H0 (models appearing in the denominator of the Bayes factor).Table For data generated from a two-component binomial model (Scenario 1), the true model is mostly favored over the uni-component models. In fact, when comparing the true model to a uni-component beta-binomial model, the latter model is only favored 5% of the time. This can be viewed as a false-negative rate. Note that the Bayes factors never provide evidence in favor of a uni-component model in comparisons with either of the other two-component models for data from this scenario. Furthermore, the true model is selected 75% of the time over the two-component beta-binomial model. The Bayes factors are ambiguous, however, when comparing the true model to a two-component beta-binomial/binomial model, where neither is favored 69% of the time.For data that follow a uni-component beta-binomial distribution (Scenario 2), the results are inconclusive 62% of the time when comparing the true model to the two-component binomial model. For twenty-two percent of the data sets the right model is favored, but 16% of the time, the two-component model is selected. Thus, this comparison results in a 16% false-positive rate. Similar results are found when comparing the true model to a two-component beta-binomial/binomial model. The Bayes factors favor the correct model over the two-component beta-binomial model roughly half the time and favor neither model the other half. Comparisons between the two-component models and the one-component binomial model not surprisingly show a strong preference for the two-component models, as they better accommodate the variability of the data.The third quarter of Table For data generated under Scenario 4, we expect the two-component beta-binomial model to be chosen over the other models in the class as this model is closest to the truth. The results show that when this model is compared to the two-component binomial or the one-component beta-binomial, it is mostly favored, and these models are never selected. As the two-component beta-binomial model is fairly similar to the two-component beta-binomial/binomial model, however, most of the time neither model is chosen over the other. The two-component beta-binomial is favored only 35% of the time, while the two-component beta-binomial/binomial is favored 9% of the time. Interestingly, when comparing the one-component beta-binomial to the two-component binomial, the one-component model is chosen 72% of the time and the two-component binomial model is chosen only 5% of the time. This suggests that the measure is fairly sensitive to the overdispersion in the two groups. Another example of this is a comparison between the two-component beta-binomial/binomial model and the one-component beta-binomial model. In this case, the two-component model is only favored 54% of the time, where the uni-component model is a better fit to 5% of the data sets, and both models are equally good fits to the data 41% of the time.This simulation study demonstrates that the Bayes factors are an appropriate method of model selection. They perform particularly well for data generated from the two-component models. In particular, most of the time, the correct model is chosen, and furthermore, reasonable false-negative rates are observed for comparisons made on data generated from the two-component binomial model as well as the two-component beta-binomial/binomial model. Data generated from a one-component beta-binomial model produces interesting results. Although the false-positive rates are reasonable when comparing the one-component beta-binomial model to the other two-component models , there is a large percentage of time, when neither model is favored (62%, 69% and 50%). Since both models are often good fits to the data, it would be difficult to decide with confidence whether or not there is a second group of arms in these cases.In this section, we apply the methods discussed to three allelic-loss data sets. Specifically, we use Bayes factors to choose a reasonable model or set of models for the data in order to address whether TSGs exist on any of the chromosome arms, and we classify the chromosome arms as harboring TSGs or not based on the selected model(s).ln(Bayes factors) exceeding 2 when compared to models outside the set and with 2ln(Bayes factors) less than 2 when compared to models within the set. Details of the analysis for each data set are described below, with slightly more emphasis placed on the first data set.Table The Barrett data set records allelic loss on 20 esophageal adenocarcinomas and two high-grade dysplasias. Figure ln(Bayes factors) for the pairwise comparisons of the models for each of the three data sets. In addition, the posterior probability of each model is presented assuming a prior probability for the models such thatTable P(2 Component Model) = P(1 Component Model) = 1/2This givesP(2 bb) = P(2 bb/bin) = P(2 bin) = 1/6P(1 bb) = P(1 bin) = 1/4.For the Barrett data set, the two-component models are strongly favored over the one-component models, clearly indicating a group of arms that exhibit higher than background loss rates. In particular, the Bayes factors demonstrate that the two-component beta-binomial/binomial model provides the best fit. Note that the posterior probability of this model is considerably higher than that of the others, providing further evidence of its superiority. = 0, reducing the two-component beta-binomial model to a two-component beta-binomial/binomial model. The parameter estimates for these two models are identical and imply that the beta-binomial distribution corresponds to the TSG loss and the binomial distribution corresponds to the background loss. The estimate of the probability that a chromosome arm is in the TSG group is 0.097. The estimated background loss rate is 0.228, and the expected background loss rate for arms with TSGs is estimated at 0.708 with a loss rate variance of 0.07. The fit from the two-component binomial model gives a slightly lower mixing parameter estimate and a slightly higher estimate of the TSG loss rate.Table The conditional probabilities of group membership based on the two-component beta-binomial/binomial model yield the same classification rule as that based on the other two-component models. Chromosome arms 5q, 9p, and 17p are classified in the TSG group. The conditional probabilities of group membership for these chromosome arms are quite similar across the three models.The Gleeson data set consists of 38 esophageal adenocarcinomas. Allelic-loss data were recorded on 39 chromosome arms (as in the Barrett data set, the short arms of chromosomes 13, 14, 15, 21, and 22 were not included in the study). A histogram of the proportion of tumors with allelic loss is presented in Figure For the Gleeson data set, the two-component beta-binomial/binomial model, the two-component binomial model and the uni-component beta-binomial model are all favored over the two-component beta-binomial model and the uni-component binomial model  exhibit lower than the average background loss rate in the Barrett data set. However, 9p and 17p are categorized along with 5q in the TSG group. Furthermore, although not classified in the TSG group, chromosome arm 18q exhibits the fourth highest allelic-loss rate in the Barrett data set.The Hammoud data set consists of 30 esophageal adenocarcinomas on 39 chromosome arms (the same arms included in the Gleeson data set). A histogram of the Hammoud data set is presented in Figure The pairwise comparisons using the Bayes factors for the Hammoud data set , the authors consider a uni-component binomial distribution for the background loss [996, the The analytic approach employed by Gleeson et al. 1997) is to select a chromosome arm with a corresponding allelic-loss rate above an arbitrarily chosen cut-off of 50% as criterion for potentially harboring a TSG . With th997 is toResults from the Bayes factors for the Gleeson data set are not completely clear. They cast doubt on whether the true underlying distribution really has two components or whether the two-component models chosen also provide a reasonable fit  to overdispersed data exhibiting only background loss. Recall the simulation study where we demonstrate that for data arising from a uni-component beta-binomial model, the Bayes factors indicate that both the true model and the two-component binomial model are often both reasonable fits to the data. This motivates incorporating Bayesian model averaging (BMA) into the inference process . An alteP(Hj|X). For example, suppose chromosome arm 13q is suspected of harboring a TSG from past experiments and we desire a probability that Zq 13= 1 based on these data. Because of model uncertainty we may be hesitant to compute the probability based solely on one model. Instead, we could estimate this probability as:Furthermore, one could use Bayesian model averaging when estimating the conditional probability of group membership for each of the chromosome arms. Maximum likelihood estimates from different high probability models could lead to different inferences about parameters. Thus, this approach of averaging the conditional probability over the various models to classify the arms or weighting the parameter estimates by the posterior probability of a given model may be more desirable than choosing a single best model from which to make inference. Specifically, one could weight estimates by j indexes over all of the models considered. This is a potential alternative to classifying the chromosome arms using the classical maximum likelihood approach that needs to be further explored. It is interesting to note that the two-component beta-binomial mixture model was never chosen for any of the data sets. Although it was certainly favored over the one-component binomial model in all data sets and over the uni-component beta-binomial model in the Barrett data set, it was never chosen to be in the set of candidate models. The class of models considered here is based on our beliefs of the biology of the data. However, the ability to screen the tumor cell genome for chromosome arms which harbor TSGs lies in a better understanding of the background distribution. Characterizing the background distribution would allow a more definitive identification of arms exhibiting abnormal loss.where The three data sets to which we apply our methods were previously published and analyzed using other techniques ,4,11.Computing Bayes factors can be challenging as non-trivial integration is often required to estimate the marginal probabilities under each model considered. Specifically, calculating Bayes factors involves integrating the likelihood over the entire parameter space for each model considered. Thus, the integrals tend to be high-dimensional. In general, we need to computeI = ∫ Pr(X|λ, H)π(λ|H)dλ.This can be quite computationally intensive. When the integral is of high dimension (> 6), quadrature methods can be unreliable . In addiπ(λ). The simple Monte Carlo estimate of the integral is the averaged likelihood at the sampled parameter values orAnother method of estimating integrals is simple Monte Carlo, that involves sampling from the prior distribution, π*(λ), the importance sampling function [This has been shown to be a good estimate for likelihoods that are relatively flat. However, if the posterior is concentrated relative to the prior, the variance of the estimate will be large, and convergence to a Gaussian will be slow . Thus, sfunction ,14. The  is known as the importance sampling ratio. The simple Monte Carlo estimate is a special case of importance sampling where π*(·) is chosen to be the prior distribution. However, the importance sampling estimate can be an improvement over the simple Monte Carlo estimate if π*(·) is chosen such that the sampling is more efficient, e.g., if π*(·) is centered around the mass. There has been some success with importance sampling in a non-mixture model setting [where  setting .Our solution is to first write the likelihood in its complete-data form. The likelihood for the mixture of two beta-binomial distributions is written as follows:z = (z1, z2,...,zN)T and the zis are unobserved group membership indicators such that zi = 0 if xi is from the background component and zi = 1 if xi is from the TSG component. Then the marginal probability of X becomeswhere I denotes the marginal probability of the data (or integrated likelihood) and where g is the prior distribution of θ.where Z. The idea behind the method is to use P(Z|θ = , x) where  is the MLE of θ to provide information on the important groupings, i.e., which chromosome arms are likely to be clustered together. While the membership vectors are sampled independently, the membership values within a group are sampled dependently, making these groupings more likely to be maintained than if the values were sampled independently.We then estimate this integral using a method we developed called the Uniform Distance Method (UDM). This method is a variant on importance sampling and involves a combination of either quadrature or exact integration and sampling of the membership vectors, The development and assessment of UDM is discussed in detail in Desai (2000) and demonstrates solid performance in estimating these integrals . SoftwarTSG, tumor suppressor gene; MLE, maximum likelihood estimate; 2 bb, two-component beta-binomial model; 2 bb/bin, two-component beta-binomial/binomial model; 2 bin, two-component binomial model; 1 bb, uni-coniponent beta-binomial model; 1 bin, uni-component binomial model; BMA, Bayesian model averaging; UDM, uniform distance methodBoth MD and MJE contributed substantially to the development of the models and the methodology. MD performed the simulation study and analysis of the three data sets. Both authors have read and approved the final version of the manuscript.


Adhesive capsulitis or frozen shoulder is a common condition characterized by shoulder pain and stiffness. In patients in whom conservative measures have failed, more invasive interventions such as arthrographic or arthroscopic distension can be very effective in relieving symptoms and improving range of movement. However, absolute contraindications to these procedures include the presence of neoplasia around the shoulder girdle. We present five cases referred to our institution where the diagnosis of shoulder joint malignancy was delayed, following prolonged, ineffective treatment for frozen shoulder. These cases highlight the importance of careful review of the radiology and the need for reconsideration of the diagnosis in refractory "frozen shoulder". Frozen shoulder was first described by Codman in 1934, as an idiopathic painful restriction in the range of shoulder joint movement, in the presence of normal plain radiographs . It is uTumours around the shoulder girdle are uncommon causes of shoulder pain and stiffness, but often present with symptoms and a clinical history identical to that of a frozen shoulder. A strict contraindication to arthrographic or arthroscopic distension of the shoulder is the presence of a local oncological process. Such procedures may change the surgical management from being a limb-preserving resection to a forequarter amputation. In the past month, five patients have been referred to us with malignant tumours around the shoulder joint, all previously diagnosed as having a frozen shoulder. All patients had undergone prolonged conservative management and hydrodilatation, with persistence of symptoms. Two of the patients had also undergone arthroscopic surgery. The following cases illustrate the importance of reconsidering the diagnosis in refractory frozen shoulder and the value of a detailed clinical history and examination and careful consideration of radiologic imaging in assessing recalcitrant "frozen shoulder".A 60 year old woman presented to her local medical officer with an eighteen month history of worsening right shoulder pain and stiffness. She was initially treated with oral analgesia followed by a cortisone injection without improvement. Two months later she had a hydrodilatation of the shoulder but her symptoms persisted. MRI was then performed, which demonstrated a large permeative tumour arising from the scapula Figure . She wasA 42 year old man was referred to an orthopaedic specialist with a history of sudden onset left shoulder pain following a work related activity. He was initially diagnosed with rotator cuff tendinopathy and subacromial impingement, and had a course of intensive physiotherapy followed by arthroscopic shoulder surgery, without improvement in symptoms. Two months later a minor incident involving his left shoulder led to an increase in pain and swelling and reduction in movement. Hydrodilatation was then performed but pain and function of the shoulder continued to worsen. On retrospective review of plain x-rays of the shoulder, a destructive lesion at the metaphysis with a cortical breach medially in the region of the surgical neck of the humerus was realized (Figure A 50 year old women was referred to an orthopaedic specialist with a 6 month history of episodic pain in the right shoulder, with associated decreased range of movement. Initial plain x-rays were unremarkable. She then underwent a variety of procedures, which included repeated subacromial corticosteroid injections, arthrographic distension, manipulation under anaesthetic, and arthroscopic debridement and acromioplasty. On arthroscopy, a marked synovitis was observed, to which her ongoing symptoms and the development of a palpable mass on the anterior aspect of the shoulder was initially attributed. Repeat plain radiographs two years after the onset of her symptoms demonstrated a large lesion extending from the glenoid cartilage into the base of the coracoid process Figure . She wasA 68 year old man had previously had a squamous cell carcinoma of the upper back excised, after which he had a three year history of shoulder pain and stiffness. He was treated for a frozen shoulder and received intensive physiotherapy and multiple subacromial corticosteroid injections, followed by hydrodilatation. Initially this seemed to settle his symptoms, although a month later pain and stiffness recurred, with marked reduction in shoulder function, and he was referred to us. An MRI was performed, which showed lesions in the supraspinatus and trapezius muscles, which were consistent with metastatic deposits Figure . The patA 55 year old female with a past history of malignant fibrous histiocytoma of the left thigh resected five years previously, presented to her local medical officer with right shoulder pain. Plain films were performed at the time which appeared normal (Figure et al. [Adhesive capsulitis or frozen shoulder is a common condition that may affect up to 5% of the general population in their lifetime. Although the aetiology of frozen shoulder is unknown, it has been associated with diabetes mellitus, thyroid disease, ischaemic heart disease and various autoimmune conditions . Other cet al.  demonstret al. [Tumours of the shoulder girdle are uncommon causes of shoulder pain and restricted movement. In most cases, they are diagnosed based on the presence of a soft tissue mass on clinical examination, as well as characteristic radiographic changes. Robinson et al.  suggesteet al. . MisdiagMRI: magnetic resonance imaging, CT: computed tomography, TSE: turbo spin echo, STIR: short tau inversion recovery.


The Menopause Rating Scale is a health-related Quality of Life scale developed in the early 1990s and step-by-step validated since then. No methodologically detailed work on the utility of the scale to assess health-related changes after treatment was published before.We analysed an open, uncontrolled post-marketing study with over 9000 women with pre- and post-treatment data of the MRS scale to critically evaluate the capacity of the scale to measure the health-related effects of hormone treatment independent from the severity of complaints at baseline.The improvement of complaints during treatment relative to the baseline score was 36% in average. Patients with little/no complaints before therapy improved by 11%, those with mild complaints at entry by 32%, with moderate by 44%, and with severe symptoms by 55% – compared with the baseline score. We showed that the distribution of complaints in women before therapy returned to norm values after 6 months of hormone treatment. We also provided weak evidence that the MRS results may well predict the assessment of the treating physician. Limitations of the study, however, may have lead to overestimating the utility of the MRS scale as outcome measure.The MRS scale showed some evidence for its ability to measure treatment effects on quality of life across the full range of severity of complaints in aging women. This however needs confirmation in other and better-designed clinical/outcome studies. The Menopause Rating Scale (MRS) was initially developed in the early 1990s  to measuThe validation of the MRS began some years ago -6 with t.Development and standardization of the scale were published elsewhere . In brieThe scale was defined as a menopause-specifc, health-related quality of life scale (HRQoL), because the profil of complaints in this scale importantly determines the HRQoL of women in this age span. Moreover, a good correlation between the results obtained with the MRS scale and the generic QoL scale was observed .).The MRS scale became internationally well accepted as far as the usage many countries is concerned. The first translation was into English . Other tLike in other health-related QoL scales, it is a challenge to satisfy the demands of a clinical utility and outcomes sensitivity. A comprehensive overview regarding conventional psychometric requirements of test reliability and validity were recently published elsewhere . It is t® = 2 mg estradiol valerate/2 mg estradiol valerate + 1 mg cyproterone acetate) using the MRS scale as outcome measure under routine conditions of office-based gynaecologists. The study was described in detail elsewhere [A multicenter, open post-marketing study was conducted with a product for hormone therapy .The statistical analyses were performed with the commercial statistical package SAS 8.2.Altogether, data of 9311 women were available for most of our analysis. However, the sample size varied slightly depending on the variables used because we had also missing information in a few variables.The mean age was 49.8 years (SD 6.4). About half of the participating women were still perimenopausal (51.9%) or were already in the postmenopausal phase (48.1%). The mean body mass index was not eye-catching with 24.7 (SD 3.7).The improvement of the health-related quality of life (HRQoL) – measured with the MRS scale – is described in Table Apart from the comparison of means, we calculated the relative improvement compared with the situation before therapy (baseline) to better understand the magnitude of change after therapy Table , i.e. inThe scale is able to measure an improvement in patients starting with "no/little complaints" , "mild" (5–8), "moderate"(9–15), and "severe" (16 + points) before therapy (= baseline). This is presented in Table It is interesting to compare the HRQoL before and after hormone treatment with the norm values of MRS obtained in an average population of aging women, i.e. not patients as in our post-marketing study. To this end, we compared only the MRS total scores in patients with the average female population Table . It becasuccessful (very effective and effective) and not successful (little, no, or negative effects). This alternative variable was then used for the comparison with the alternative "success-variable" based on MRS : "successful" (5 and more points reduction after therapy compared with baseline test) and "not successful" (less than 5 scoring points reduction after therapy compared with baseline test).The treating gynaecologist  assessed individually the efficiency of the hormone treatment in the above mentioned intervention study. The gynaecologist's expert opinion regarding treatment efficiency was categorized into two categories for the purpose of this analysis: The prediction of the expert opinion of the treating gynaecologist with the MRS data seems to be good: sensitivity (correct prediction of a positive assessment by the physician) 70.8% and specificity (correct prediction of a negative assessment by the physician) 73.5% Table .The MRS scale was developed (a) to assess symptoms of aging/menopause (independent from those that are disease-related) or HRQoL between groups of women under different conditions, (b) to evaluate the severity of symptoms over time, and (c) to measure changes pre- and post hormone replacement therapy. The aim of this paper was to empirically demonstrate that the latter claim is evident.Reliability measures  were found to be good across countries [validity it was shown that the internal structure of the MRS across countries was sufficiently similar to conclude that the scale really measures the same phenomenon [Reliability and validity are important to show the usefulness of the scale as a clinical utility in monitoring treatment effects – once all other methodological requirements are successfully demonstrated before. ountries . Regardienomenon .The comparison with another scale for aging women – although not a validated HRQoL scale (Kupperman) – showed sufficiently good correlations of the total score, which is compatible with the notion of a good criterion-oriented validity. The same is true for the comparison with the generic quality-of-life scale SF36 where also high correlation coefficients have been shown . AnotherHaving the above-mentioned psychometric data available, a point was reached to critically evaluate the capacity of the scale to reliably measure health-related effects of hormone treatment independent from the severity of complaints and – in addition – to the comparison of treatment effects measured by the MRS scale and the subjective assessment by the treating physician. To this end, many clinicians use the term "validity" and mean high utility for clinical work or research.The only hormone treatment study with the MRS scale as outcome measure in women during menopausal transition we could get data for methodological analysis was the above described postmarketing study. We hope to repeat/confirm this analysis with data of a more stringently designed clinical trial. But even on the basis of a methodologically weak dataset, in absence of other data, we got re-assuring methodological information about the MRS scale.It is a well-established experience that women with menopausal complaints respond to hormone therapy with a marked improvement of the HRQoL. This is what the MRS scale should be able to detect.We saw that the increased mean MRS total score at baseline (before treatment) markedly decreased after 6 months under treatment indicating a significant improvement of complaints & HRQoL. This was also the case for the mean scores of the three subscales. These data cannot disentangle the effect of treatment and "natural variation" of complaints over time. This however was not the point: It was not the intention of this paper to evaluate effectiveness of hormone therapy in an uncontrolled post-marketing study.The absolute improvement of symptoms during treatment was 9.3 points of the MRS total score on average. This is equivalent to 36% of the baseline score, and similar also for all three subscales. In other words, the MRS scale was shown to be successful in detecting treatment effects. The impressive magnitude of the therapy-related improvement of HRQoL should be obviously discussed in the context of selection of women with complaints susceptible for this kind of treatment by the participating gynaecologists. Another critical remark is that we cannot comment as to what extend the MRS scale is able to measure true or placebo treatment effects. But this is more a question concerning efficacy and the study draw any conclusions in this regard by definition of the study design.To answer the question whether the sensitivity of the MRS scale is good enough to detect even treatment-related changes in women with only little or mild symptoms as compared with severe ones, the analysis was stratified. An improvement of complaints/QoL was seen in an increasing degree in patients with little, mild, moderate and severe symptoms at baseline. The relative improvement increased with the degree of severity of symptoms at baseline, which is consistent with the general expectation. It seems to be important to underscore: The MRS scale seems to detect also a positive treatment effect in women with little complaints – although to a lesser degree.Moreover, we showed the capacity of the MRS scale to determine therapeutic efficiency with another approach: a face-value-comparison with norm values of the population ,3. The lsuccessful" and "not successful" for both the subjective opinion of the physician and the result of the MRS scale: The sensitivity (correct prediction of a positive assessment by the physician) was 70.8% and specificity (correct prediction of a negative assessment by the physician) 73.5%. In other words, the MRS scale fits well with the subjective assessment of the treatment effect estimated by the physician. However, conclusions have to be drawn very carefully because of a possibly inherent bias that may have inflated the positive result: The subjective assessment of "success" by the treating physician was obviously not as independent from the assessment by the MRS scale as desirable because the physician applied the scale to the patient. Even without being able to recall the result of the MRS six month ago or to calculate and compare the total score of both administrations, the interaction with the patients is likely to have introduced this bias in the direction of a higher compatibility between both assessments.The MRS scale was also tested whether it predicts the therapeutic assessment of the treating physician. At face value, the individually assessed efficiency of hormone treatment by the treating gynaecologists was comparable with the assessment by the MRS scale, i.e. using a simple dichotomization of the treatment effect in "Although the result may too positive compared with a blinded, really independent assessment, it permits to generate the working hypothesis of a sufficiently good prediction of the therapeutic effect by means of the MRS scale. This needs to be confirmed with better data, i.e. data from a blinded, independent comparison, i.e. with the currently used, self-administered MRS scale.The aim of this exercise was only to demonstrate that the MRS scale may well predict the clinical opinion about efficiency of hormone therapy, what was not empirically shown before. We recommend the MRS as standardized/validated "objective" scale for use in clinical studies, although some aspects discussed above need confirmation in a new study. Moreover, since the scale is already broadly used at the international level, it is important to sensitise users about some lacking information or weak evidence.The limitations of this study should be shortly summarized. First of all, this study was performed in a dataset where an earlier version of the MRS scale was used, i.e. the scale was not self-administered but completed in an interview of the physician with the patient. This could have influenced the magnitude of the absolute scores of the total and sub-scales. As far as pre-/post-treatment changes are concerned, the magnitude of the absolute changes may have been more influenced than the relative changes of the HRQoL assessment of the patients as discussed in this paper. Another problem along the same line is that we had to transform the old coding system into the new one. This was done with a simple linear transformation and is not likely to have introduced any bias. Another limitation is that this is the first study we are aware of for this kind of assessment of the validity to measure therapeutic intervention.It is not likely that the main conclusions of the study are materially biased. However, the results should be cautiously used  as long as not confirmed with data obtained with the currently used self-administered MRS scale without potential influence of the physician. It can be assumed that a new study with the currently recommended MRS scale – in the sense of "patient-reported-outcome" – would demonstrate positive results but to a lesser degree.The MRS scale showed some evidence for its ability to measure treatment effects on quality of life across the full range of severity of complaints in aging women. This however needs confirmation in other and better-designed clinical studies.The authors FS and SG are employees of the company that produces HRT products.We cannot however see any conflict of interest as far as the methodological aspects of the validation of the MRS scale are concerned.LAJH: responsible for the collection and evaluation of the data, and involved in writing of the paper. DMT: responsible for building the database of this publication, responsible for the statistical evaluation, and contributed to writing of the paper. FS: responsible for the post-marketing study and designing this paper, contributed to the manuscript. SG: responsible for designing and overseeing the post-marketing study of Climen, contributed to writing and revising of the paper JS: responsible for the field work of the post-marketing study, setting up the initial database, and for the preparation of the subset of data used for this publication. HPGS: Major responsibility in developing the MRS scale, contributed to writing/revision of the manuscript.


Mental fatigue, with decreased concentration capacity, is common in neuroinflammatory and neurodegenerative diseases, often appearing prior to other major mental or physical neurological symptoms. Mental fatigue also makes rehabilitation more difficult after a stroke, brain trauma, meningitis or encephalitis. As increased levels of proinflammatory cytokines are reported in these disorders, we wanted to explore whether or not proinflammatory cytokines could induce mental fatigue, and if so, by what mechanisms.+) in humans suffering from mental fatigue. At present, this is not possible for technical reasons. Therefore, more knowledge of neuronal-glial signaling in in vitro systems and animal experiments is important.It is well known that proinflammatory cytokines are increased in major depression, "sickness behavior" and sleep deprivation, which are all disorders associated with mental fatigue. Furthermore, an influence by specific proinflammatory cytokines, such as interleukin (IL)-1, on learning and memory capacities has been observed in several experimental systems. As glutamate signaling is crucial for information intake and processing within the brain, and due to the pivotal role for glutamate in brain metabolism, dynamic alterations in glutamate transmission could be of pathophysiological importance in mental fatigue. Based on this literature and observations from our own laboratory and others on the role of astroglial cells in the fine-tuning of glutamate neurotransmission we present the hypothesis that the proinflammatory cytokines tumor necrosis factor-α, IL-1β and IL-6 could be involved in the pathophysiology of mental fatigue through their ability to attenuate the astroglial clearance of extracellular glutamate, their disintegration of the blood brain barrier, and effects on astroglial metabolism and metabolic supply for the neurons, thereby attenuating glutamate transmission. To test whether our hypothesis is valid or not, brain imaging techniques should be applied with the ability to register, over time and with increasing cognitive loading, the extracellular concentrations of glutamate and potassium (KIn summary, we provide a hypothetic explanation for a general neurobiological mechanism, at the cellular level, behind one of our most common symptoms during neuroinflammation and other long-term disorders of brain function. Understanding pathophysiological mechanisms of mental fatigue could result in better treatment. Diagnostic and Statistical Manual of Mental Disorders, 4th edition [Mental fatigue with reduced capacity for attention, concentration, and learning, as well as subsequent disturbance of short-term memory, is a common symptom in diseases with general or patchy neuroinflammation, such as multiple sclerosis (MS) and neurodegenerative diseases, such as Ahlzheimer's and Parkinson's diseases -6. The m edition , mental  edition , mental Although mental fatigue is not exactly the same as depression, where the patient has a feeling of not being able to do anything, there are overlaps and both disorders have behavioral manifestations such as reduction in motivation that would appear similar in animal models, where affective state is either irrelevant or difficult to assess. Even the "sickness behavior"  containsec).Mental fatigue appears as a decreased ability to intake and process information over time. Mental exhaustion becomes pronounced when cognitive tasks have to be performed for longer time periods with no breaks (cognitive loading). Often, the symptoms are absent or mild in a relaxed and stress-free environment. To explore the possible cellular neurobiology of mental fatigue, we start by looking at some components important for information intake and processing within the central nervous system, namely glutamate neurotransmission, and focus on the clearance of extracellular glutamate  at normal glutamate neurotransmission [+)-dependent electrogenic uptake transporters. The glutamate aspartate transporter (GLAST) and glutamate transporter 1 (GLT-1) are most abundantly located on astrocytes surrounding synapses of glutamate-bearing neurons [ec low, it has been demonstrated with knockout techniques in rats that loss of GLT-1 or GLAST produces elevated [Glu]ec and neurodegeneration characteristic of excitotoxicity, while the loss of neuronal glutamate transporter does not elevate [Glu]ec [In brain, the [Glu]smission  and also neurons . In fact neurons . Even mo [Glu]ec .A large number of factors have been shown to affect the activity and expression of the glutamate transporters GLT-1 and GLAST. For example, GLT-1 is stimulated by phosphorylation by protein kinase C (PKC), while GLAST is inhibited by PKC at a non-PKC consensus site . The synProinflammatory cytokines tumor necrosis factor-α (TNF-α), interleukin (IL)-1β and IL-6 have since long been known to impair astroglial glutamate uptake even if the mechanisms are not fully understood. The inhibitory function of TNF-α was established as early as the 1990s, when TNF-α was shown to inhibit astroglial glutamate uptake  reported2+) signaling between BBB endothelial cells by reducing gap junction coupling and inhibiting triggered ATP release [Even dysregulation of the blood brain barrier (BBB) is seen early in neuroinflammation, and parallels the release of proinflammatory cytokines -28. Mech release .ec exceeds some 3–5 μM, the efficiency of the glutamate signaling is considered to be reduced [2+ oscillations, both within and between the gap junction-coupled astroglial syncytia [As stated above, already when the [Glu] reduced . There i reduced , with lesyncytia -33, and syncytia  could insyncytia ,36. Thissyncytia  and leadsyncytia .ec would also lead to astroglial cell swelling, with a resulting decrease in the extracellular space volume, and locally further increased [Glu]ec [+]ec [+]ec levels have been shown in experimental systems to inhibit glutamate release [Increased [Glu] [Glu]ec -42. The ec [+]ec ,44. Even release .Recent data indicate a dynamic and fine-tuning regulation of the glutamatergic transmission. One mechanism by which neurons regulate excitatory transmission is by altering the number and composition of glutamate receptors at the postsynaptic plasma membrane. This has been shown for the NMDA receptor in experimental systems and could have prominent importance for dynamic processes as learning and memory . Of greaFurthermore, in states of decreased astroglial glutamate uptake capacity, even astroglial glucose uptake, and consequently the supply of metabolic substrates to the neurons, has been reported to decrease -50 and tec in the basal frontal cortex could lead to a decrease in the noradrenaline and serotonin (5-HT) release in the cerebral cortex, which would also decrease glucogenolysis [Experimental investigations in the rat and monkey have demonstrated a feedback loop from the left basal frontal cortex, with an inhibitory influence on the locus coeruleus in the brain stem . If thisenolysis ,53 and, ec levels could be one factor to impair glutamate transmission.Thus, it might be that glutamate neurotransmission could be regulated by changing astroglial glutamate transporter capacity, and thus, increases in [Glu]There is an extensive literature on inflammatory response with microglial activation and the production of proinflammatory cytokines (TNF-α, IL-1β and IL-6) in neuroinflammatory/infectious and neurodegenerative diseases as well as in stroke and trauma ,54. The Several groups have also described enhanced production of proinflammatory cytokines in major depression [see ] and sicIn states of anxiety and stress, often experienced as secondary to mental fatigue, increased glucocorticoid levels have been demonstrated. Interestingly, long-term increases in glucocorticoids have been demonstrated to result in the production of both TNF-α and IL-1β .In the search for pathophysiological correlates to fatigue in MS, Roelcke and co-workers  demonstrec. The initial consequence would be slightly increased [Glu]ec, with less precision in glutamate transmission. This would disintegrate the "filter", which normally selects information and prevents it from reaching the cerebral cortex. We can take the sound from a low-frequency fan as an example. This sound is normally sorted out after hearing it for a while. If this sound is handled with less precision by auditory recognition systems, it will continually be recognized by brain centers as "new" information and be processed in the cerebral cortex as long as the sound is on. The "filter" that normally restrains already recognized information from reaching higher brain centers, has been "opened". From a physiological point of view, it seems appropriate that the individual, and not the brain at the synaptic level, should determine which information should reach, and be processed by, the cerebral cortex. The decreased attention, increased loudness and light sensitivity, and irritability could be physiological ways of avoiding overstimulation of higher cortical centers. In case the individuals cannot protect themselves from too much sensory stimulation, the filter's opening leads to overstimulation of the cerebral cortex. Here, the final shutdown of the glutamate transmission could be one mechanism underlying mental exhaustion  could be studied in animal models. Effects of astroglial dysfunction with regard to glutamate transport capacity would be of special interest. Even clinical studies with different treatment strategies could be important in casting some light on the accuracy of the hypothesis. Of utmost importance in all such studies would be test batteries making it possible to objectify and even quantify the degree of mental fatigue.It is not possible at present to ultimately prove whether or not the altered neuronal-glial interactions in glutamatergic transmission induced by proinflammatory cytokines could serve as a model to explain cellular mechanisms underlying mental fatigue. Brain imaging techniques able to determine and follow [Glu]Normally, mental fatigue and the associated symptoms disappear when the brain dysfunction is over. In some patients, the symptoms persist. We have at present no explanation for this, but if our hypothesis is correct, there could be a genetic failure preventing astroglial glutamate transporters from upregulating. Another explanation for why the symptoms persist could be that the pathological stimulation by brain plasticity creates new neuronal networks ,36.Providing information about mental fatigue, its cause and the prognosis, is of utmost importance for breaking the vicious circle, which comes with the risk for secondary anxiety and depression. Furthermore, it is important for the patient to imagine and learn how much sensory stimulation they can tolerate prior to feeling too exhausted. Due to recent results on changes in cell signaling and neuronal plasticity ,36, it mADHD attention deficit hyperactivity disorderAMPA alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionateATP adenosine triphosphateBBB blood brain barrier2+ calciumCaEc extracellularGLAST glutamate aspartate transporterGLT-1 glutamate transporter-1ec extracellular glutamate concentration[Glu]5-HT 5-hydroxytryptamineth revisionICD-10 International Classification of Diseases, 10IL-1/-6 interleukin-1/-6+ potassiumK+]ec extracellular potassium concentration[KLC locus coeruleusLTP long term potentialMS multiple sclerosis+ sodiumNaNA noradrenalineNFκB nuclear transcription factor kappaBNMDA N-methyl-D-aspartateNO nitric oxidePACAP pituitary adenylate cyclase-activating polypeptidePI3K phosphatidylinositol-3-kinasePKC protein kinase CSiv mac simian immunodeficiency virus macaquesTNF-α tumor necrosis factor alphaThe author(s) declare that they have no competing interests.Equal contributions by both authors.