http://repub.eur.nl/res/aut/26961/ List of Publications en http://repub.eur.nl/static-eur/img/logo.png http://repub.eur.nl http://repub.eur.nl/res/pub/40024/ 2013-07-01T00:00:00Z Women from high-risk families consider preventive measures for breast cancer including screening. Guidelines on screening differ considerably regarding starting age. We investigated whether age at diagnosis in affected relatives is predictive for age at diagnosis. We analyzed the age of breast cancer detection of 1,304 first- and second-degree relatives of 314 BRCA1, 164 BRCA2 and 244 high-risk participants of the Dutch MRI-SCreening study. The within- and between-family variance in the relative's age at diagnosis was analyzed with a random effect linear regression model. We compared the starting age of screening based on risk-group (25 years for BRCA1, 30 years for BRCA2 and 35 years for familial risk), on family history, and on the model, which combines both. The findings were validated in 63 families from the UK-MARIBS study. Mean age at diagnosis in the relatives varied between families; 95% range of mean family ages was 35-55 in BRCA1-, 41-57 in BRCA2- and 44-60 in high-risk families. In all, 14% of the variance in age at diagnosis, in BRCA1 even 23%, was explained by family history, 7% by risk group. Determining start of screening based on the model and on risk-group gave similar results in terms of cancers missed and years of screening. The approach based on familial history only, missed more cancers and required more screening years in both the Dutch and the United Kingdom data sets. Age at breast cancer diagnosis is partly dependent on family history which may assist planning starting age for preventive measures. What's new? Our study shows, that beside risk group also age at diagnosis in family members is predictive for age at onset in BRCA1 and 2 mutation carriers and women with familial risk. 14% of the variance in age at diagnosis, and in BRCA1 even 23%, was explained by family history versus 7% by risk group. This may be taken into account when determining the starting age for screening or other preventive measures. Copyright http://repub.eur.nl/res/pub/37748/ 2012-11-15T00:00:00Z Randomized controlled trials in traumatic brain injury (TBI) are challenging due to the inherent heterogeneity of the patient population, the lack of early mechanistic end points, and relative insensitivity of outcome measures. Approaches to deal with the heterogeneity of the patient population are presented in this thesis. The use of strict enrollment criteria is not recommended, as this is inefficient. Rather, broad enrollment criteria may be preferred combined with covariate adjustment in the analysis phase. Dichotomization of the Glasgow Outcome Scale as the primary outcome measure in most trials is not recommended. Ordinal approaches to analysis of treatment effects offer greater statistical power and better sensitivity. To this purpose the use of proportional odds methodology or the sliding dichotomy may be considered. To practically apply these analysis techniques, well-validated prognostic models for TBI are currently available. Combining an ordinal approach to the analysis of treatment effects with covariate adjustment can increase statistical power by 40 – 50%. These recommendations are expected to enhance chances for detecting clinically relevant treatment effects for the benefit of future TBI patients. http://repub.eur.nl/res/pub/38568/ 2012-11-01T00:00:00Z Abstract In randomized clinical trials of aphasia treatment, a functional outcome measure like the Amsterdam-Nijmegen Everyday Language Test (ANELT), administered by speech-language therapists, is often used. However, the agreement between this expert rating and the judgment of the proxy about the quality of the daily life communication of the person with aphasia is largely unknown. We examined the association between ANELT scores by speech-language therapists and proxy judgments on the Partner Communication Questionnaire both at 3 and 6 months in 39 people with aphasia after stroke. We also determined which factors affected the level of agreement between expert and proxy judgment of the communicative ability at 6 months in 53 people with aphasia. We found moderate agreement (at 3 months r =.662; p = <.0001 and at 6 months r =.565; p =.0001), with proxies rating slightly higher than experts. Less severe aphasia, measured with the Aphasia Severity Rating Scale, was associated with better agreement. In conclusion, although proxies were slightly more positive than experts, we found moderate agreement between expert and proxy rating of verbal communicative ability of people with aphasia after stroke, especially in milder cases. (JINS, 2012, 18, 1064-1070) Copyright http://repub.eur.nl/res/pub/38871/ 2012-10-31T00:00:00Z Background: The long-term functional outcome of aphasia after stroke is uncertain, even though this information is needed as early as possible for adequate patient care and support. This observational prospective study was aimed at predicting functional outcome at 1 year after stroke. Methods: We examined linguistic components (ScreeLing) and functional verbal communication (Aphasia Severity Rating Scale, ASRS) in 147 aphasic patients. The ScreeLing was administered at 1, 2 and 6 weeks after stroke; the ASRS at 1 week and 1 year. The relationships between linguistic, demographic and stroke characteristics, and good functional outcome at 1 year (ASRS 4 or 5) were examined with logistic regression analyses. Results: The baseline linguistic components (ie, semantics, phonology and syntax) were significant predictors (p<0.001) for 1-year outcome in univariable analyses. In multivariable analysis, these variables explained 46.5% of the variance, with phonology being the only significant predictor (p=0.003). Age, Barthel Index score, educational level and haemorrhagic stroke were identified as other significant predictors of outcome. A prognostic model of these five baseline predictors explained 55.7% of the variance. The internally validated area under the receiver operating characteristic curve (AUC) was 0.89, indicating good predictive performance. Adding the degree of phonological recovery between 1 and 6 weeks after stroke to this model increased the explained variance to 65% and the AUC to 0.91. Conclusions: The outcome of aphasia at 1 year after stroke can be predicted in the first week by the phonology score, the Barthel Index score, age, educational level and stroke subtype, with phonology being the strongest predictor. Copyright Article author (or their employer) 2012. http://repub.eur.nl/res/pub/34738/ 2012-01-01T00:00:00Z During the National Neurotrauma Symposium 2010, the DG Research of the European Commission and the National Institutes of Health/National Institute of Neurological Disorders and Stroke (NIH/NINDS) organized a workshop on comparative effectiveness research (CER) in traumatic brain injury (TBI). This workshop reviewed existing approaches to improve outcomes of TBI patients. It had two main outcomes: First, it initiated a process of re-orientation of clinical research in TBI. Second, it provided ideas for a potential collaboration between the European Commission and the NIH/NINDS to stimulate research in TBI. Advances in provision of care for TBI patients have resulted from observational studies, guideline development, and meta-analyses of individual patient data. In contrast, randomized controlled trials have not led to any identifiable major advances. Rigorous protocols and tightly selected populations constrain generalizability. The workshop addressed additional research approaches, summarized the greatest unmet needs, and highlighted priorities for future research. The collection of high-quality clinical databases, associated with systems biology and CER, offers substantial opportunities. Systems biology aims to identify multiple factors contributing to a disease and addresses complex interactions. Effectiveness research aims to measure benefits and risks of systems of care and interventions in ordinary settings and broader populations. These approaches have great potential for TBI research. Although not new, they still need to be introduced to and accepted by TBI researchers as instruments for clinical research. As with therapeutic targets in individual patient management, so it is with research tools: one size does not fit all. http://repub.eur.nl/res/pub/37209/ 2012-01-01T00:00:00Z Objective: The ability to predict the time of death after withdrawal of life support is of specific interest for organ donation after cardiac death. We aimed to externally validate a previously developed model to predict the probability of death within the time constraint of 60 mins after withdrawal of life-sustaining measures. Design: The probability to die within 60 mins for each patient in this validation sample was calculated based on the model developed by Yee et al, which includes four variables (absent corneal reflex, absent cough reflex, extensor or absent motor response, and an oxygenation index >4.2). Analyses included logistic regression modeling with bootstrapping to adjust for overoptimism. Performance was assessed by calibration (agreement between observed and predicted outcomes) and discrimination (distinction of those Patients who die within 60 mins from those who do not, expressed by the area under the receiver operating characteristic curve). Setting: Mixed intensive care unit in The Netherlands. Patients: We analyzed data from 152 Patients who died as a result of a neurologic condition between 2007 and 2009. Interventions: None. Measurements and Main Results: A total of 82 Patients had sufficient data. Fifty (61%) died within 60 mins. Univariable and multivariable odds ratios of the predictors were very similar between the development and validation sample. The prediction model showed good discrimination with an area under the receiver operating characteristic curve of 0.75 (95% confidence interval [CI] 0.63-0.87) but calibration was modest. The mean predicted probability was 80%, overestimating the 61% overall observed risk of death within 60 mins. Modeling oxygenation index as a linear term led to an improved version of the Mayo NICU model. (area under the receiver operating characteristic curve [95% CI] = 0.774 [0.69-0.90], bootstrap-validated area under the receiver operating characteristic curve [95% CI] = 0.74 [0.66-0.87]). Conclusions: The model discriminated well between Patients who died within 60 mins after withdrawal of life support and those who did not. Further prospective validation is needed. http://repub.eur.nl/res/pub/34338/ 2011-12-01T00:00:00Z Background: Pathological waves of spreading mass neuronal depolarisation arise repeatedly in injured, but potentially salvageable, grey matter in 50-60% of patients after traumatic brain injury (TBI). We aimed to ascertain whether spreading depolarisations are independently associated with unfavourable neurological outcome. Methods: We did a prospective, observational, multicentre study at seven neurological centres. We enrolled 109 adults who needed neurosurgery for acute TBI. Spreading depolarisations were monitored by electrocorticography during intensive care and were classified as cortical spreading depression (CSD) if they took place in spontaneously active cortex or as isoelectric spreading depolarisation (ISD) if they took place in isoelectric cortex. Investigators who treated patients and assessed outcome were masked to electrocorticographic results. Scores on the extended Glasgow outcome scale at 6 months were fitted to a multivariate model by ordinal regression. Prognostic score (based on variables at admission, as validated by the IMPACT studies) and spreading depolarisation category (none, CSD only, or at least one ISD) were assessed as outcome predictors. Findings: Six individuals were excluded because of poor-quality electrocorticography. A total of 1328 spreading depolarisations arose in 58 (56%) patients. In 38 participants, all spreading depolarisations were classified as CSD; 20 patients had at least one ISD. By multivariate analysis, both prognostic score (p=0·0009) and spreading depolarisation category (p=0·0008) were significant predictors of neurological outcome. CSD and ISD were associated with an increased risk of unfavourable outcome (common odds ratios 1·56 [95% CI 0·72-3·37] and 7·58 [2·64-21·8], respectively). Addition of depolarisation category to the regression model increased the proportion of variance in outcome that could be attributed to predictors from 9% to 22%, compared with the prognostic score alone. Interpretation: Spreading depolarisations were associated with unfavourable outcome, after controlling for conventional prognostic variables. The possibility that spreading depolarisations have adverse effects on the traumatically injured brain, and therefore might be a target in the treatment of TBI, deserves further research. Funding: US Army CDMRP PH/TBI research programme. http://repub.eur.nl/res/pub/34612/ 2011-10-20T00:00:00Z http://repub.eur.nl/res/pub/34286/ 2011-10-07T00:00:00Z Introduction: We studied whether the choice of timing of discussing organ donation for the first time with the relatives of a patient with catastrophic brain injury in The Netherlands has changed over time and explored its possible consequences. Second, we investigated how thorough the process of brain death determination was over time by studying the number of medical specialists involved. And we studied the possible influence of the Donor Register on the consent rate.Methods: We performed a retrospective chart review of all effectuated brain dead organ donors between 1987 and 2009 in one Dutch university hospital with a large neurosurgical serving area.Results: A total of 271 medical charts were collected, of which 228 brain dead patients were included. In the first period, organ donation was discussed for the first time after brain death determination (87%). In 13% of the cases, the issue of organ donation was raised before the first EEG. After 1998, we observed a shift in this practice. Discussing organ donation for the first time after brain death determination occurred in only 18% of the cases. In 58% of the cases, the issue of organ donation was discussed before the first EEG but after confirming the absence of all brain stem reflexes, and in 24% of the cases, the issue of organ donation was discussed after the prognosis was deemed catastrophic but before a neurologist or neurosurgeon assessed and determined the absence of all brain stem reflexes as required by the Dutch brain death determination protocol.Conclusions: The phases in the process of brain death determination and the time at which organ donation is first discussed with relatives have changed over time. Possible causes of this change are the introduction of the Donor Register, the reintroduction of donation after circulatory death and other logistical factors. It is unclear whether the observed shift contributed to the high refusal rate in The Netherlands and the increase in family refusal in our hospital in the second studied period. Taking published literature on this subject into account, it is possible that this may have a counterproductive effect. http://repub.eur.nl/res/pub/34578/ 2011-08-25T00:00:00Z Background: In Traumatic Brain Injury (TBI), large between-centre differences in outcome exist and many clinicians believe that such differences influence estimation of the treatment effect in randomized controlled trial (RCTs). The aim of this study was to assess the influence of between-centre differences in outcome on the estimated treatment effect in a large RCT in TBI.Methods: We used data from the MRC CRASH trial on the efficacy of corticosteroid infusion in patients with TBI. We analyzed the effect of the treatment on 14 day mortality with fixed effect logistic regression. Next we used random effects logistic regression with a random intercept to estimate the treatment effect taking into account between-centre differences in outcome. Between-centre differences in outcome were expressed with a 95% range of odds ratios (OR) for centres compared to the average, based on the variance of the random effects (tau2). A random effects logistic regression model with random slopes was used to allow the treatment effect to vary by centre. The variation in treatment effect between the centres was expressed in a 95% range of the estimated treatment ORs.Results: In 9978 patients from 237 centres, 14-day mortality was 19.5%. Mortality was higher in the treatment group (OR = 1.22, p = 0.00010). Using a random effects model showed large between-centre differences in outcome (95% range of centre effects: 0.27- 3.71), but did not substantially change the estimated treatment effect (OR = 1.24, p = 0.00003). There was limited, although statistically significant, between-centre variation in the treatment effect (OR = 1.22, 95% treatment OR range: 1.17-1.26).Conclusion: Large between-centre differences in outcome do not necessarily affect the estimated treatment effect in RCTs, in contrast to current beliefs in the clinical area of TBI. andcopy; 2011 Lingsma et al; licensee BioMed Central Ltd. http://repub.eur.nl/res/pub/26119/ 2011-06-03T00:00:00Z Objective: There is a growing focus on quality and safety in healthcare. Outcome indicators are increasingly used to compare hospital performance and to rank hospitals, but the reliability of ranking (rankability) is under debate. This study aims to quantify the rankability of several outcome indicators of hospital performance currently used by the Dutch government. Methods: From 52 indicators used by the Netherlands Inspectorate, the authors selected nine outcome indicators presenting a fraction and absolute numbers. Of these indicators, four were combined into two, resulting in seven indicators for analysis. The official data of 97 Dutch hospitals for the year 2007 were used. Uncertainty in the observed outcomes within the hospitals (within hospital variance, σ2) was estimated using fixed effect logistic regression models. Heterogeneity (between hospital variance, τ2) was measured with random effect logistic regression models. Subsequently, the rankability was calculated by relating heterogeneity to uncertainty within and between hospitals (τ2/(τ2+median σ2)). Results: Sample sizes varied but were typically around 200 per hospital (range of median 90-277) with a median of 2-21 cases, causing a substantial uncertainty in outcomes per hospital. Although fourfold to eightfold differences between hospitals were noted, the uncertainty within hospitals caused a poor (<50%) rankability in three indicators and moderate rankability (50-75%) in the other four indicators. Conclusion: The currently used Dutch outcome indicators are not suitable for ranking hospitals. When judging hospital quality the influence of random variation must be accounted for to avoid overinterpretation of the numbers in the quest for more transparency in healthcare. Adequate sample size is a prerequisite in attempting reliable ranking. Copyright Article author (or their employer) 2011. http://repub.eur.nl/res/pub/25183/ 2011-05-25T00:00:00Z Background: Logistic random effects models are a popular tool to analyze multilevel also called hierarchical data with a binary or ordinal outcome. Here, we aim to compare different statistical software implementations of these models. Methods. We used individual patient data from 8509 patients in 231 centers with moderate and severe Traumatic Brain Injury (TBI) enrolled in eight Randomized Controlled Trials (RCTs) and three observational studies. We fitted logistic random effects regression models with the 5-point Glasgow Outcome Scale (GOS) as outcome, both dichotomized as well as ordinal, with center and/or trial as random effects, and as covariates age, motor score, pupil reactivity or trial. We then compared the implementations of frequentist and Bayesian methods to estimate the fixed and random effects. Frequentist approaches included R (lme4), Stata (GLLAMM), SAS (GLIMMIX and NLMIXED), MLwiN ([R]IGLS) and MIXOR, Bayesian approaches included WinBUGS, MLwiN (MCMC), R package MCMCglmm and SAS experimental procedure MCMC. Three data sets (the full data set and two sub-datasets) were analysed using basically two logistic random effects models with either one random effect for the center or two random effects for center and trial. For the ordinal outcome in the full data set also a proportional odds model with a random center effect was fitted. Results: The packages gave similar parameter estimates for both the fixed and random effects and for the binary (and ordinal) models for the main study and when based on a relatively large number of level-1 (patient level) data compared to the number of level-2 (hospital level) data. However, when based on relatively sparse data set, i.e. when the numbers of level-1 and level-2 data units were about the same, the frequentist and Bayesian approaches showed somewhat different results. The software implementations differ considerably in flexibility, computation time, and usability. There are also differences in the availability of additional tools for model evaluation, such as diagnostic plots. The experimental SAS (version 9.2) procedure MCMC appeared to be inefficient. Conclusions: On relatively large data sets, the different software implementations of logistic random effects regression models produced similar results. Thus, for a large data set there seems to be no explicit preference (of course if there is no preference from a philosophical point of view) for either a frequentist or Bayesian approach (if based on vague priors). The choice for a particular implementation may largely depend on the desired flexibility, and the usability of the package. For small data sets the random effects variances are difficult to estimate. In the frequentist approaches the MLE of this variance was often estimated zero with a standard error that is either zero or could not be determined, while for Bayesian methods the estimates could depend on the chosen "non-informative" prior of the variance parameter. The starting value for the variance parameter may be also critical for the convergence of the Markov chain. http://repub.eur.nl/res/pub/34307/ 2011-05-17T00:00:00Z Introduction: In clinical trials, ordinal outcome measures are often dichotomized into two categories. In traumatic brain injury (TBI) the 5-point Glasgow outcome scale (GOS) is collapsed into unfavourable versus favourable outcome. Simulation studies have shown that exploiting the ordinal nature of the GOS increases chances of detecting treatment effects. The objective of this study is to quantify the benefits of ordinal analysis in the real-life situation of a large TBI trial.Methods: We used data from the CRASH trial that investigated the efficacy of corticosteroids in TBI patients (n = 9,554). We applied two techniques for ordinal analysis: proportional odds analysis and the sliding dichotomy approach, where the GOS is dichotomized at different cut-offs according to baseline prognostic risk. These approaches were compared to dichotomous analysis. The information density in each analysis was indicated by a Wald statistic. All analyses were adjusted for baseline characteristics.Results: Dichotomous analysis of the six-month GOS showed a non-significant treatment effect (OR = 1.09, 95% CI 0.98 to 1.21, P = 0.096). Ordinal analysis with proportional odds regression or sliding dichotomy showed highly statistically significant treatment effects (OR 1.15, 95% CI 1.06 to 1.25, P = 0.0007 and 1.19, 95% CI 1.08 to 1.30, P = 0.0002), with 2.05-fold and 2.56-fold higher information density compared to the dichotomous approach respectively.Conclusions: Analysis of the CRASH trial data confirmed that ordinal analysis of outcome substantially increases statistical power. We expect these results to hold for other fields of critical care medicine that use ordinal outcome measures and recommend that future trials adopt ordinal analyses. This will permit detection of smaller treatment effects. http://repub.eur.nl/res/pub/25811/ 2011-05-01T00:00:00Z BACKGROUND AND PURPOSE-Thrombolysis with intravenous recombinant tissue plasminogen activator is an effective treatment for acute ischemic stroke, but the number of treatable patients is limited. The PRomoting ACute Thrombolysis in Ischemic StrokE (PRACTISE) trial evaluated the effectiveness of a multidimensional implementation strategy for thrombolysis with intravenous recombinant tissue plasminogen activator in acute ischemic stroke. METHODS-The PRACTISE trial was a national multicenter cluster-randomized controlled trial with randomization after pairwise matching. Twelve hospitals, both urban and community, academic and nonacademic, in the Netherlands participated. All patients admitted with stroke within 24 hours from onset of symptoms were registered. The intervention included 5 implementation meetings based on the Breakthrough Series model. The primary outcome was treatment with thrombolysis. Secondary outcomes were admission within 4 hours after onset of symptoms, death or disability at 3 months, and quality of life. RESULTS-Overall 5515 patients were included in the study' 308 patients (12.2%) in the control centers and 393 patients (13.1%) in the intervention centers were treated with thrombolysis (adjusted OR, 1.25; 95% CI, 0.93 to 1.68). Among the 1657 patients with ischemic stroke admitted within 4 hours from onset, 391 (44.5%) of 880 in the intervention centers were treated with thrombolysis and 305 (39.3%) of 777 in the control centers; the adjusted OR for treatment with thrombolysis was 1.58 (95% CI, 1.11 to 2.27). CONCLUSIONS-An intensive implementation strategy increases the proportion of patients with acute stroke treated with thrombolysis in real-life settings. An apparently pivotal factor in the improvement of the treatment rate is better application of contraindications for thrombolysis. http://repub.eur.nl/res/pub/33967/ 2011-05-01T00:00:00Z Objective: Encapsulating peritoneal sclerosis (EPS) is a serious complication of peritoneal dialysis (PD) with a multifactorial pathophysiology and possible increasing incidence. The aim of the present study was to evaluate the independent associations of PD duration, age, dialysis fluids, and kidney transplantation with EPS. Methods: A multicenter case-control study was performed in the Netherlands from 1 January 1996 until 1 July 2007. The population comprised 63 patients with EPS and 126 control patients. Control patients were selected from the national registry and were matched for date of PD start. Associations were analyzed using a log linear regression model. Primary outcome was appearance of EPS. Results: Compared with control patients, patients with EPS were younger at the start of PD (34.7 ±15.4 years vs. 51.5± 14.7 years, p < 0.0001). The cumulative period on PD was longer in EPS patients than in control patients (78.7 ± 37.8 months vs. 32.8 ±24 months, p < 0.0001), and the cumulative period on icodextrin was also longer in EPS patients (32.7 ±23.3 months vs. 18.1 ±15.7 months, p = 0.006). Compared with control patients, more EPS patients underwent kidney transplantation (47 vs. 59, p< 0.0001). With regard to the period after transplantation, the yearly probability of EPS increased in the year after transplantation to 7.5% from 1.75%. In multivariate regression analysis, cumulative PD duration, age at PD start, transplantation, time from last transplantation to EPS, calendar time, time on icodextrin, and ultrafiltration failure were independently associated with EPS. Transfer from PD to hemodialysis for reasons other than suspected EPS could not be identified as a risk factor for EPS. Conclusions: Duration of PD, age at PD start, kidney transplantation, time since last transplantation, ultrafiltration failure, and time on icodextrin were associated with a higher risk of EPS. http://repub.eur.nl/res/pub/26016/ 2011-04-01T00:00:00Z Purpose: It is desirable to identify a potential organ donor (POD) as early as possible to achieve a donor conversion rate (DCR) as high as possible which is defined as the actual number of organ donors divided by the number of patients who are regarded as a potential organ donor. The DCR is calculated with different assessment tools to identify a POD. Obviously, with different assessment tools, one may calculate different DCRs, which make comparison difficult. Our aim was to determine which assessment tool can be used for a realistic estimation of a POD pool and how they compare to each other with regard to DCR. Methods: Retrospective chart review of patients diagnosed with a subarachnoid haemorrhage, traumatic brain injury or intracerebral haemorrhage. We applied three different assessment tools on this cohort of patients. Results: We identified a cohort of 564 patients diagnosed with a subarachnoid haemorrhage, traumatic brain injury or intracerebral haemorrhage of whom 179/564 (31.7%) died. After applying the three different assessment tools the number of patients, before exclusion of medical reasons or age, was 76 for the IBD-FOUR definition, 104 patients for the IBD-GCS definition and 107 patients based on the OPTN definition of imminent neurological death. We noted the highest DCR (36.5%) in the IBD-FOUR definition. Conclusion: The definition of imminent brain death based on the FOUR-score is the most practical tool to identify patients with a realistic chance to become brain dead and therefore to identify the patients most likely to become POD. http://repub.eur.nl/res/pub/25602/ 2011-03-15T00:00:00Z Background: Guillain-Barré syndrome (GBS) has a highly diverse clinical course and outcome, yet patients are treated with a standard therapy. Patients with poor prognosis may benefit from additional treatment, provided they can be identified early, when nerve degeneration is potentially reversible and treatment is most effective. We developed a clinical prognostic model for early prediction of outcome in GBS, applicable for clinical practice and future therapeutic trials. Methods: Data collected prospectively from a derivation cohort of 397 patients with GBS were used to identify risk factors of being unable to walk at 4 weeks, 3 months, and 6 months. Potential predictors of poor outcome (unable to walk unaided) were considered in univariable and multivariable logistic regression models. The clinical model was based on the multivariable logistic regression coefficients of selected predictors and externally validated in an independent cohort of 158 patients with GBS. Results: High age, preceding diarrhea, and low Medical Research Council sumscore at hospital admission and at 1 week were independently associated with being unable to walk at 4 weeks, 3 months, and 6 months (all p 0.05-0.001). The model can be used at hospital admission and at day 7 of admission, the latter having a better predictive ability for the 3 endpoints; the area under the receiver operating characteristic curve (AUC) is 0.84-0.87 and at admission the AUC is 0.73-0.77. The model proved to be valid in the validation cohort. Conclusions: A clinical prediction model applicable early in the course of disease accurately predicts the first 6 months outcome in GBS. http://repub.eur.nl/res/pub/23057/ 2011-03-01T00:00:00Z Background: Differences between centers in patient outcome after traumatic brain injury are of importance for multicenter studies and have seldom been studied. Objective: To quantify the differences in centers enrolling patients in randomized clinical trials (RCTs) and surveys. Methods: We analyzed individual patient data from 9578 patients with moderate and severe traumatic brain injury enrolled in 10 RCTs and 3 observational studies. We used random-effects logistic regression models to estimate the between-center differences in unfavorable outcome (dead, vegetative state, or severe disability measured with the Glasgow Outcome Scale) at 6 months adjusted for differences in patient characteristics. We calculated the difference in odds of unfavorable outcome between the centers at the higher end vs those at the lower end of the outcome distribution. We analyzed the total database, Europe and the United States separately, and 4 larger RCTs. Results: The 9578 patients were enrolled at 265 centers, and 4629 (48%) had an unfavorable outcome. After adjustment for patient characteristics, there was a 3.3-fold difference in the odds of unfavorable outcome between the centers at the lower end of the outcome distribution (2.5th percentile) vs those at the higher end of the outcome distribution (97.5th percentile; P < .001). In the 4 larger RCTs, the differences between centers were similar. However, differences were smaller between centers in the United States (2.4-fold) than between centers in Europe (3.8-fold). Conclusion: Outcome after traumatic brain injury differs substantially between centers, particularly in Europe. Further research is needed to study explanations for these differences to suggest where quality of care might be improved. http://repub.eur.nl/res/pub/31587/ 2011-02-01T00:00:00Z Background. Encapsulating peritoneal sclerosis (EPS) is a serious complication of peritoneal dialysis (PD) with an increasing incidence. There is no clear consensus on the treatment of EPS, but anecdotal reports indicate improvement in EPS patients treated with tamoxifen. At present, there is no evidence for the effect of tamoxifen treatment in EPS patients. This study investigates the effect of treatment with tamoxifen on survival in EPS patients.Methods. This study is a retrospective analysis of survival in EPS patients as part of the Dutch multicentre EPS study in the period January 1996 to July 2007. Sixty-three patients with severe EPS were followed up until August 2008. Demographic, patient and PD-related variables of EPS patients were investigated. Patients treated with tamoxifen were compared to patients not treated with tamoxifen. Survival was analysed with multivariate Cox regression analysis.Results. Twenty-four patients were treated with tamoxifen, and 39 were not treated with tamoxifen. The clinical and demographic characteristics were similar for the tamoxifen-treated and non-treated groups. The mortality rate was significantly lower in tamoxifen-treated patients compared to EPS patients not treated with tamoxifen (45.8% vs 74.4%, P = 0.03). Survival in tamoxifen-treated patients, adjusted for calendar time, age, use of corticosteroids, presence of functioning transplantation, use of parental nutrition and centre influences was longer in comparison to not-treated patients (HR 0.39, P = 0.056).Conclusions. Tamoxifen treatment in EPS patients is associated with lower mortality and shows a trend to an increased multivariate-adjusted survival. This supports additional use of tamoxifen to treat patients with severe EPS. http://repub.eur.nl/res/pub/21732/ 2010-12-01T00:00:00Z http://repub.eur.nl/res/pub/28488/ 2010-10-01T00:00:00Z Background. Aneurysmal subarachnoid haemorrhage (aSAH) is a devastating event with a frequently disabling outcome. Our aim was to develop a prognostic model to predict an ordinal clinical outcome at two months in patients with aSAH. Methods. We studied patients enrolled in the International Subarachnoid Aneurysm Trial (ISAT), a randomized multicentre trial to compare coiling and clipping in aSAH patients. Several models were explored to estimate a patient's outcome according to the modified Rankin Scale (mRS) at two months after aSAH. Our final model was validated internally with bootstrapping techniques. Results. The study population comprised of 2,128 patients of whom 159 patients died within 2 months (8%). Multivariable proportional odds analysis identified World Federation of Neurosurgical Societies (WFNS) grade as the most important predictor, followed by age, sex, lumen size of the aneurysm, Fisher grade, vasospasm on angiography, and treatment modality. The model discriminated moderately between those with poor and good mRS scores (c statistic = 0.65), with minor optimism according to bootstrap re-sampling (optimism corrected c statistic = 0.64). Conclusion. We presented a calibrated and internally validated ordinal prognostic model to predict two month mRS in aSAH patients who survived the early stage up till a treatment decision. Although generalizability of the model is limited due to the selected population in which it was developed, this model could eventually be used to support clinical decision making after external validation. Trial Registration. International Standard Randomised Controlled Trial, Number ISRCTN49866681. http://repub.eur.nl/res/pub/27561/ 2010-07-01T00:00:00Z Aim and background - The benefit of statin treatment in patients with a previous ischemic stroke or transient ischemic attack (TIA) has been demonstrated in randomized clinical trials (RCT). However, the effectiveness in everyday clinical practice may be decreased because of a different patient population and less controlled setting. We aim to describe statin use in an unselected cohort of patients, identify factors related to statin use and test whether the effect of statins on recurrent vascular events and mortality observed in RCTs is also observed in everyday clinical practice. Methods - In 10 centers in the Netherlands, patients admitted to the hospital or visiting the outpatient clinic with a recent TIA or ischemic stroke were prospectively and consecutively enrolled between October 2002 and May 2003. Statin use was determined at discharge and during follow-up. We used logistic regression models to estimate the effect of statins on the occurrence of vascular events (stroke or myocardial infarction) and mortality within 3 years. We adjusted for confounders with a propensity score that relates patient characteristics to the probability of using statins. Results - Of the 751 patients in the study, 252 (34%) experienced a vascular event within 3 years. Age, elevated cholesterol levels and other cardiovascular risk factors were associated with statin use at discharge. After 3 years, 109 of 280 (39%) of the users at discharge had stopped using statins. Propensity score adjusted analyses showed a beneficial effect of statins on the occurrence of the primary outcome (odds ratio 0.8, 95% CI: 0.6-1.2). Conclusion - In our study, we found poor treatment adherence to statins. Nevertheless, after adjustment for the differences between statin users and non-statin users, the observed beneficial effect of statins on the occurrence of vascular events within 3 years, although not statistically significant, is compatible with the effect observed in clinical trials. Copyright http://repub.eur.nl/res/pub/33155/ 2010-06-08T00:00:00Z http://repub.eur.nl/res/pub/27900/ 2010-06-01T00:00:00Z Objective: Respiratory insufficiency is a frequent and serious complication of the Guillain-Barré syndrome (GBS). We aimed to develop a simple but accurate model to predict the chance of respiratory insufficiency in the acute stage of the disease based on clinical characteristics available at hospital admission. Methods: Mechanical ventilation (MV) in the first week of admission was used as an indicator of acute stage respiratory insufficiency. Prospectively collected data from a derivation cohort of 397 GBS patients were used to identify predictors of MV. A multivariate logistic regression model was validated in a separate cohort of 191 GBS patients. Model performance criteria comprised discrimination (area under receiver operating curve [AUC]) and calibration (graphically). A scoring system for clinical practice was constructed from the regression coefficients of the model in the combined cohorts. Results: In the derivation cohort, 22% needed MV in the first week of admission. Days between onset of weakness and admission, Medical Research Council sum score, and presence of facial and/or bulbar weakness were the main predictors of MV. The prognostic model had a good discriminative ability (AUC, 0.84). In the validation cohort, 14% needed MV in the first week of admission, and both calibration and discriminative ability of the model were good (AUC, 0.82). The scoring system ranged from 0 to 7, with corresponding chances of respiratory insufficiency from 1 to 91%. Interpretation: This model accurately predicts development of respiratory insufficiency within 1 week in patients with GBS, using clinical characteristics available at admission. After further validation, the model may assist in clinical decision making, for example, on patient transfer to an intensive care unit. http://repub.eur.nl/res/pub/28372/ 2010-06-01T00:00:00Z Purpose: Mutations in the fibroblast growth factor receptor 3 (FGFR3) have been found in 70% of the low-grade non-muscle-invasive bladder cancer (NMI-BC) tumors. We aim to determine the potential of FGFR3 mutation analysis on voided urine to detect recurrences during surveillance of patients with low-grade NMI-BC. Experimental Design: FGFR3 mutation status of the study inclusion tumor was determined from 200 low-grade NMI-BC patients. Patients with an FGFR3-mutant inclusion tumor were selected for analysis and monitored by cystoscopy, and voided urine samples were collected. FGFR3 mutation analysis was done on 463 prospectively collected urines. Sensitivity and predictive value of the assay were determined for detection of concomitant recurrences. Longitudinal and Cox time-to-event analyses were done to determine the predictive value for detection of future recurrences. Results: Median follow-up was 3.5 years. The sensitivity of the assay for detection of concomitant recurrences was 26 of 45 (58%). Of the 105 positive urine samples, 85 (81%) were associated with a concomitant or a future recurrence. An FGFR3-positive urine was associated with a 3.8-fold (P < 0.0001) higher risk of having a recurrence in the Cox analysis. In contrast, only 41 of 358 (11%) FGFR3-negative urine samples were associated with a recurrence. Positive predictive value increased from 25% to 90% in patients having consecutive FGFR3-positive urine tests. Conclusions: FGFR3 mutation analysis on voided urine is a simple and noninvasive diagnostic method for detection of recurrences during surveillance of patients presenting with a low-grade FGFR3-mutant NMI-BC tumor. http://repub.eur.nl/res/pub/28450/ 2010-05-01T00:00:00Z Traumatic brain injury (TBI) is a heterogeneous condition that encompasses a broad spectrum of disorders. Outcome can be highly variable, particularly in more severely injured patients. Despite the association of many variables with outcome, prognostic predictions are notoriously difficult to make. Multivariable analysis has identified age, clinical severity, CT abnormalities, systemic insults (hypoxia and hypotension), and laboratory variables as relevant factors to include in models to predict outcome in individual patients. Advances in statistical modelling and the availability of large datasets have facilitated the development of prognostic models that have greater performance and generalisability. Two prediction models are currently available, both of which have been developed on large datasets with state-of-the-art methods, and offer new opportunities. We see great potential for their use in clinical practice, research, and policy making, as well as for assessment of the quality of health-care delivery. Continued development, refinement, and validation is advocated, together with assessment of the clinical impact of prediction models, including treatment response. http://repub.eur.nl/res/pub/27268/ 2010-02-01T00:00:00Z Background & Aims: Although gastric cancer forms part of the Lynch syndrome tumor spectrum, the risk of developing gastric cancer in Lynch syndrome families is unknown, resulting in a lack of clear guidelines for surveillance. The aim of this study was to evaluate incidence trends and risk of developing gastric cancer among Lynch syndrome mutation carriers in a Western population. Methods: Lynch syndrome mutation carriers were selected from the Dutch Hereditary Cancer Registry. The gastric cancer incidence in Lynch syndrome mutation carriers was compared to the gastric cancer incidence in the Dutch population between 1970 and 2003. Standardized incidence ratios were calculated by a Poisson model. Cumulative risks were calculated by Kaplan-Meier analysis. Results: Overall, 2014 Lynch syndrome mutation carriers were identified. Gastric cancer was diagnosed in 32 (1.6%) subjects (male/female: 21/11), 22 (69%) of them had a negative family history of gastric cancer. The standardized incidence ratios of gastric cancer was 3.4 (95% confidence interval, 2.1-5.2) and showed a nonsignificant decline between 1970 and 2003 (P = .30). Absolute risk of developing gastric cancer also showed no significant change over time (P = .51). Lifetime risk of developing gastric cancer was 8.0% in males vs 5.3% in females (P = .02), and 4.8% and 9% for MLH1 and MSH2 carriers, respectively. None of the 378 MSH6 carriers developed gastric cancer (P = .002 vs MLH1 and MSH2 combined lifetime risk). Conclusions: Lynch syndrome mutation carriers have a substantial risk for gastric cancer, in particular patients with an MLH1 or MSH2 mutation. Family history for gastric cancer is a poor indicator for individual risk. Surveillance gastroscopy for Lynch syndrome patients carrying an MLH1 or MSH2 mutation should therefore be considered. http://repub.eur.nl/res/pub/28661/ 2010-02-01T00:00:00Z Background Clinical trials in traumatic brain injury have a disappointing track record, with a long history of ĝ€negative' Phase III trials. One contributor to this lack of success is almost certainly the low efficiency of the conventional approach to the analysis, which discards information by dichotomizing an ordinal outcome scale. Purpose Our goal was to evaluate the potential efficiency gains, which can be achieved by using techniques, which extract additional information from ordinal outcome data - the proportional odds model and the sliding dichotomy. In addition, we evaluated the additional efficiency gains, which can be achieved through covariate adjustment. Methods The study was based on simulations, which were built around a database of patient-level data extracted from eight Phase III trials and three observational studies in traumatic brain injury. Two different putative treatment effects were explored, one which followed the proportional odds model, and the other which assumed that the effect of the intervention was to reduce the risk of death without changing the distribution of outcomes within survivors. The results are expressed as efficiency gains, reported as the percentage reduction in sample size that can be used with the ordinal analyses without loss of statistical power relative to the conventional binary analysis. Results The simulation results show substantial efficiency gains. Use of the sliding dichotomy allows sample sizes to be reduced by up to 40% without loss of statistical power. The proportional odds model gives modest additional gains over and above the gains achieved by use of the sliding dichotomy. Limitations As with any simulation study, it is difficult to know how far the findings may be extrapolated beyond the actual situations that were modeled. Conclusions Both ordinal techniques offer substantial efficiency gains relative to the conventional binary analysis. The choice between the two techniques involves subtle value judgments. In the situations examined, the proportional odds model gave efficiency gains over and above the sliding dichotomy, but arguably, the sliding dichotomy is more intuitive and clinically appealing. http://repub.eur.nl/res/pub/28694/ 2010-01-01T00:00:00Z In this article, we review past and current experience in clinical trials of traumatic brain injuries (TBIs), we discuss limitations and challenges, and we summarize current directions. The focus is on severe and moderate TBIs. A systematic literature search of the years from 1980 to 2009 revealed 27 large phase III trials in TBI; we were aware of a further 6 unpublished trials. Analysis of these 33 trials yielded interesting observations:•There was a peak incidence of trial initiations that occurred in the mid-1990s with a sharp decline during the period from 2000 to 2004.•Most trials that reported a significant treatment effect were studies on a therapeutic strategy (e.g., decompressive craniectomy, hypothermia), and these were single-center studies.•Increasingly, studies have been shifting toward the Far East. The currently existing trial registries permit insight into ongoing or recently conducted trials. Compared with the past decade, the number of studies on neuroprotective agents taken forward into efficacy-oriented studies is low. In contrast, the number of studies on therapeutic strategies appears to be increasing again. The disappointing results in trials on neuroprotective agents in TBI have led to a critical reappraisal of clinical trial methodology. This has resulted in recommendations for preclinical workup and has triggered extensive analysis on approaches to improve the design and analysis of clinical trials in TBI. An interagency initiative toward standardization on selection and coding of data elements across the broad spectrum of TBI is ongoing, and will facilitate comparison of research findings across studies and encourage high-quality meta-analysis of individual patient data in the future. http://repub.eur.nl/res/pub/28726/ 2010-01-01T00:00:00Z Clinical trials in traumatic brain injury (TBI) pose complex methodological challenges, largely related to the heterogeneity of the population. The International Mission on Prognosis and Clinical Trial Design in TBI study group has explored approaches for dealing with this heterogeneity with the aim to optimize clinical trials in TBI. Extensive prognostic analyses and simulation studies were conducted on individual patient data from eight trials and three observational studies. Here, we integrate the results of these studies into the International Mission on Prognosis and Clinical Trial Design in TBI recommendations for design and analysis of trials in TBI:•Details of the major baseline prognostic characteristics should be provided in every report on a TBI study; in trials they should be differentiated per treatment group. We also advocate the reporting of the baseline prognostic risk as determined by validated prognostic models.•Inclusion criteria should be as broad as is compatible with the current understanding of the mechanisms of action of the intervention being evaluated. This will maximize recruitment rates and enhance the generalizability of the results.•The statistical analysis should incorporate prespecified covariate adjustment to mitigate the effects of the heterogeneity.•The statistical analysis should use an ordinal approach, based on either sliding dichotomy or proportional odds methodology. Broad inclusion criteria, prespecified covariate adjustment, and an ordinal analysis will promote an efficient trial, yielding gains in statistical efficiency of more than 40%. This corresponds to being able to detect a 7% treatment effect with the same number of patients needed to demonstrate a 10% difference with an unadjusted analysis based on the dichotomized Glasgow outcome scale. http://repub.eur.nl/res/pub/24703/ 2009-12-11T00:00:00Z Background: Measuring quality of care and ranking hospitals with outcome measures poses two major methodological challenges: case-mix adjustment and variation that exists by chance. Aim: To compare methods for comparing and ranking hospitals that considers these. Methods: The Netherlands Stroke Survey was conducted in 10 hospitals in the Netherlands, between October 2002 and May 2003, with prospective and consecutive enrolment of patients with acute brain ischaemia. Poor outcome was defined as death or disability after 1 year (modified Rankin scale of >3). We calculated fixed and random hospital effects on poor outcome, unadjusted and adjusted for patient characteristics. We compared the hospitals using the expected rank, a novel statistical measure incorporating the magnitude and the uncertainty of differences in outcome. Results: At 1 year after stroke, 268 of the total 505 patients (53%) had a poor outcome. There were substantial differences in outcome between hospitals in unadjusted analysis (X2= 48, 9 df, P<0.0001). Adjustment for 12 confounders led to halving of the X2(X2= 24). The same pattern was observed in random effects analysis. Estimated performance of individual hospitals changed considerably between unadjusted and adjusted analysis. Further changes were seen with random effect estimation, especially for smaller hospitals. Ordering by expected rank led to shrinkage of the original ranks of 1-10 towards the median rank of 5.5 and to a different order of the hospitals, compared to ranking based on fixed effects. Conclusion: In comparing and ranking hospitals, case-mix-adjusted random effect estimates and the expected ranks are more robust alternatives to traditional fixed effect estimates and simple rankings. http://repub.eur.nl/res/pub/24709/ 2009-10-01T00:00:00Z Objective: Heterogeneity of patients is a common problem in randomized controlled trials (RCTs) in various fields of clinical research. We aimed to investigate the potential benefits of different approaches for dealing with heterogeneity in a case study on traumatic brain injury (TBI). Design and Setting: Statistical modeling studies in three surveys and six randomized controlled trials. Patients: Individual patient data (n = 8033) from the IMPACT database. Interventions: We investigated the statistical power and efficiency of randomized controlled trials (RCTs) in relation to (1) selection according to baseline characteristics, (2) prognostic targeting (i.e., excluding those with a relatively extreme prognosis), and (3) covariate-adjusted analysis. Statistical power was expressed as the required sample size for obtaining 80% power and efficiency as the relative change in study duration, reflecting both gains in power and adverse effects on recruitment. Uniform and targeted treatment effects were simulated for 6 month unfavorable outcome. Results: For a uniform treatment effect, selection resulted in a sample size reduction of 33% in the surveys and 5% in the RCTs, but decreased recruitment by 65% and 41%, respectively. Hence, the relative study duration was prolonged (surveys: +95%; RCTs: +60%). Prognostic targeting resulted in sample size reductions of 28% and 17%, and increased relative study duration by +5% in surveys and +11% in the RCTs. Covariate adjustment reduced sample sizes by 30% and 16%, respectively, and did not affect recruitment. For a targeted treatment effect, the sample size reductions by selection (surveys: 47%; RCTs: 20%) and prognostic targeting (surveys: 49%; RCTs: 41%) were larger and adverse effects on recruitment smaller. Conclusions: The benefits of selection and prognostic targeting in terms of statistical power are reversed by adverse effects on recruitment. Covariate adjusted analysis in a broadly selected group of patients is advisable if a uniform treatment effect is assumed, since there is no decrease in recruitment. http://repub.eur.nl/res/pub/24943/ 2009-08-26T00:00:00Z Background. Rankings based on outcome are often used to present health care provider performance. These rankings do however not reflect that part of the variation in outcome between providers is caused by natural variation, and not by any differences in quality of care. The aim of this study is to compare standard methods for ranking with a novel method that takes into account natural variation. Methods. We used data on the number of treatment cycles and the number of pregnancies of 13 Dutch IVF clinics from 2004. We calculated the Expected Rank (ER), an estimate of the true rank of a provider, accounting for natural variation. We rescaled the ER to obtain the Percentile based on ER (PCER), that can be interpreted as the probability that a clinic is worse than a randomly selected other clinic. We also calculated a measure for rankability ρ, which is the part of variation between providers that is due to true differences (as opposed to natural variation). Results. The expected ranks ranged from 1.4 to 11.9 instead of the original ranks 1-13. The ER showed that some clinics performed very similar, which would be disregarded when using standard ranks. The PCER ranged from 7% to 88%. Rankability was substantial (ρ = 0.9). Conclusion. The Expected Rank provides a way to combine the attractiveness of a ranking, a single number and easy interpretation, with reliable analyses that does justice to the providers, and also allows individual comparisons. http://repub.eur.nl/res/pub/25209/ 2009-07-01T00:00:00Z Substantial heterogeneity exists among patients who suffer from traumatic brain injury (TBI). Strict enrollment criteria may diminish heterogeneity in randomized controlled trials (RCTs), but will also decrease recruitment and may affect the outcome distribution. The aim of this study was to investigate the influences of commonly used enrollment criteria for RCTs in TBI on potential recruitment and on outcome distribution. We used individual patient data from the International Mission on Prognosis and Analysis of Clinical Trials in TBI (IMPACT) database, including six therapeutic phase III RCTs (n = 5816) and three surveys (n = 2217) in TBI. The primary outcome was the Glasgow Outcome Scale (GOS) at 6 months after injury, which we dichotomized as favorable/unfavorable. We investigated the influences of commonly used enrollment criteria on recruitment and outcome distribution: time window between injury and admission to study hospital ≤ 8 h; age at injury ≤ 65 years; ≥ 1 reactive pupil; motor score > 1; Glasgow Coma Scale ≤ 8. Application of all enrollment criteria resulted in a large reduction of recruitment in both the surveys (up to 65%) and the RCTs (up to 41%). Among the remaining patients, fewer had an unfavorable outcome in both the surveys (original, 60%; remaining, 44%) and the RCTs (original, 43%; remaining, 38%). Applying these enrollment criteria to patients from the surveys resulted in an outcome distribution that approximated the outcome observed in the RCTs. The use of strict enrollment criteria leads to substantial reductions in the recruitment of RCTs in TBI. The outcome in TBI studies depends strongly on the enrollment criteria. http://repub.eur.nl/res/pub/32435/ 2008-06-01T00:00:00Z The Glasgow Outcome Scale (GOS) is the primary endpoint for efficacy analysis of clinical trials in traumatic brain injury (TBI). Accurate and consistent assessment of outcome after TBI is essential to the evaluation of treatment results, particularly in the context of multicenter studies and trials. The inconsistent measurement or interobserver variation on GOS outcome, or for that matter, on any outcome scales, may adversely affect the sensitivity to detect treatment effects in clinical trial. The objective of this study is to examine effects of nondifferential misclassification of the widely used five-category GOS outcome scale and in particular to assess the impact of this misclassification on detecting a treatment effect and statistical power. We followed two approaches. First, outcome differences were analyzed before and after correction for misclassification using a dataset of 860 patients with severe brain injury randomly sampled from two TBI trials with known differences in outcome. Second, the effects of misclassification on outcome distribution and statistical power were analyzed in simulation studies on a hypothetical 800-patient dataset. Three potential patterns of nondifferential misclassification (random, upward and downward) on the dichotomous GOS outcome were analyzed, and the power of finding treatments differences was investigated in detail. All three patterns of misclassification reduce the power of detecting the true treatment effect and therefore lead to a reduced estimation of the true efficacy. The magnitude of such influence not only depends on the size of the misclassification, but also on the magnitude of the treatment effect. In conclusion, nondifferential misclassification directly reduces the power of finding the true treatment effect. An awareness of this procedural error and methods to reduce misclassification should be incorporated in TBI clinical trials.