The Impact of Palliative Care Team Consultation on Quality of Life of Patients with Advanced Cancer in Dutch Hospitals: An Observational Study.

INTRODUCTION: Experimental studies have shown that palliative care team (PCT) involvement can improve quality of life (QoL) and symptom burden of patients with advanced cancer. It is unclear to what extent this effect is sustained in daily practice of hospital care. OBJECTIVE: This observational study aims to investigate the effect of PCT consultation on QoL and symptom burden of hospitalized patients with advanced cancer in daily practice. METHODS: After admission to 1 of 9 participating hospitals, patients with advanced cancer for whom the attending physician answered "no" to the Surprise Question were invited to complete a questionnaire, including the EORTC QLQ-C15-PAL, at 6 points in time, until 3 months after admission. Outcomes were compared between patients who received PCT consultation and patients who did not, taking into account differences in baseline characteristics. RESULTS: A total of 164 patients consented to participate, of whom 32 received PCT consultation. Of these patients, 108 were able to complete a questionnaire at day 14, of whom 19 after receiving PCT consultation. After adjusting for baseline differences, EORTC QLQ-C15-PAL scores for pain, appetite, and emotional functioning at day 14 were more favorable for patients who received a PCT consultation. CONCLUSION: PCT consultation decreased patients' symptom burden and tends to have a positive effect on QoL of hospitalized patients with advanced cancer, even if the PCT is consulted late in the patient's disease trajectory.

Development of a prediction model to target screening for high blood pressure in children.

Targeted screening for childhood high blood pressure may be more feasible than routine blood pressure measurement in all children to avoid unnecessary harms, overdiagnosis or costs. Targeting maybe based e.g. on being overweight, but information on other predictors may also be useful. Therefore, we aimed to develop a multivariable diagnostic prediction model to select children aged 9-10 years for blood pressure measurement. Data from 5359 children in a population-based prospective cohort study were used. High blood pressure was defined as systolic or diastolic blood pressure ≥ 95th percentile for gender, age, and height. Logistic regression with backward selection was used to identify the strongest predictors related to pregnancy, child, and parent characteristics. Internal validation was performed using bootstrapping. 227 children (4.2%) had high blood pressure. The diagnostic model included maternal hypertensive disease during pregnancy, maternal BMI, maternal educational level, parental hypertension, parental smoking, child birth weight standard deviation score (SDS), child BMI SDS, and child ethnicity. The area under the ROC curve was 0.73, compared to 0.65 when using only child overweight. Using the model and a cut-off of 5% for predicted risk, sensitivity and specificity were 59% and 76%; using child overweight only, sensitivity and specificity were 47% and 84%. In conclusion, our diagnostic prediction model uses easily obtainable information to identify children at increased risk of high blood pressure, offering an opportunity for targeted screening. This model enables to detect a higher proportion of children with high blood pressure than a strategy based on child overweight only.

The association between palliative care team consultation and hospital costs for patients with advanced cancer: An observational study in 12 Dutch hospitals.

BACKGROUND: Early palliative care team consultation has been shown to reduce costs of hospital care. The objective of this study was to investigate the association between palliative care team (PCT) consultation and the content and costs of hospital care in patients with advanced cancer. MATERIAL AND METHODS: A prospective, observational study was conducted in 12 Dutch hospitals. Patients with advanced cancer and an estimated life expectancy of less than 1 year were included. We compared hospital care during 3 months of follow-up for patients with and without PCT involvement. Propensity score matching was used to estimate the effect of PCTs on costs of hospital care. Additionally, gamma regression models were estimated to assess predictors of hospital costs. RESULTS: We included 535 patients of whom 126 received PCT consultation. Patients with PCT had a worse life expectancy (life expectancy <3 months: 62% vs. 31%, p < .01) and performance status (p < .01, e.g., WHO status higher than 2:54% vs. 28%) and more often had no more options for anti-tumour therapy (57% vs. 30%, p < .01). Hospital length of stay, use of most diagnostic procedures, medication and other therapeutic interventions were similar. The total mean hospital costs were €8,393 for patients with and €8,631 for patients without PCT consultation. Analyses using propensity scores to control for observed confounding showed no significant difference in hospital costs. CONCLUSIONS: PCT consultation for patients with cancer in Dutch hospitals often occurs late in the patients' disease trajectories, which might explain why we found no effect of PCT consultation on costs of hospital care. Earlier consultation could be beneficial to patients and reduce costs of care.

Autonomy Challenges in Epigenetic Risk-Stratified Cancer Screening: How Can Patient Decision Aids Support Informed Consent?

Information of an individual's epigenome can be useful in cancer screening to enable personalised decision making on participation, treatment options and further screening strategies. However, adding this information might result in complex risk predictions on multiple diseases, unsolicited findings and information on (past) environmental exposure and behaviour. This complicates informed consent procedures and may impede autonomous decision-making. In this article we investigate and identify the specific features of epigenetic risk-stratified cancer screening that challenge the current informed consent doctrine. Subsequently we describe current and new informed consent models and the principle of respect for autonomy and argue for a specific informed consent model for epigenetic risk-stratified screening programmes. Next, we propose a framework that guides the development of Patient Decision Aids (PDAs) to support informed consent and promote autonomous choices in the specific context of epigenetic cancer screening programmes.

Prediction models for endometrial cancer for the general population or symptomatic women: A systematic review.

OBJECTIVE: To provide an overview of prediction models for the risk of developing endometrial cancer in women of the general population or for the presence of endometrial cancer in symptomatic women. METHODS: We systematically searched the Embase and Pubmed database until September 2017 for relevant publications. We included studies describing the development, the external validation, or the updating of a multivariable model for predicting endometrial cancer in the general population or symptomatic women. RESULTS: Out of 2756 references screened, 14 studies were included. We found two prediction models for developing endometrial cancer in the general population (risk models) and one extension. Eight studies described the development of models for symptomatic women (diagnostic models), one comparison of the performance of two diagnostic models and two external validation. Sample size varied from 60 (10 with cancer) to 201,811 (855 with cancer) women. The age of the women was included as a predictor in almost all models. The risk models included epidemiological variables related to the reproductive history of women, hormone use, BMI, and smoking history. The diagnostic models also included clinical predictors, such as endometrial thickness and recurrent bleeding. The concordance statistic (c), assessing the discriminative ability, varied from 0.68 to 0.77 in the risk models and from 0.73 to 0.957 in the diagnostic models. Methodological information was often limited, especially on the handling of missing data, and the selection of predictors. One risk model and four diagnostic models were externally validated. CONCLUSIONS: Only a few models have been developed to predict endometrial cancer in asymptomatic or symptomatic women. The usefulness of most models is unclear considering methodological shortcomings and lack of external validation. Future research should focus on external validation and extension with new predictors or biomarkers, such as genetic and epigenetic markers.

Epigenome-based cancer risk prediction: rationale, opportunities and challenges.

The incidence of cancer is continuing to rise and risk-tailored early diagnostic and/or primary prevention strategies are urgently required. The ideal risk-predictive test should: integrate the effects of both genetic and nongenetic factors and aim to capture these effects using an approach that is both biologically stable and technically reproducible; derive a score from easily accessible biological samples that acts as a surrogate for the organ in question; and enable the effectiveness of risk-reducing measures to be monitored. Substantial evidence has accumulated suggesting that the epigenome and, in particular, DNA methylation-based tests meet all of these requirements. However, the development and implementation of DNA methylation-based risk-prediction tests poses considerable challenges. In particular, the cell type specificity of DNA methylation and the extensive cellular heterogeneity of the easily accessible surrogate cells that might contain information relevant to less accessible tissues necessitates the use of novel methods in order to account for these confounding issues. Furthermore, the engagement of the scientific community with health-care professionals, policymakers and the public is required in order to identify and address the organizational, ethical, legal, social and economic challenges associated with the routine use of epigenetic testing.

Validation of the Feverkidstool and procalcitonin for detecting serious bacterial infections in febrile children.

BackgroundTo validate the Feverkidstool, a prediction model consisting of clinical signs and symptoms and C-reactive protein (CRP) to identify serious bacterial infections (SBIs) in febrile children, and to determine the incremental diagnostic value of procalcitonin.MethodsThis prospective observational study that was carried out at two Dutch emergency departments included children with fever, aged 1 month to 16 years. The prediction models were developed with polytomous logistic regression differentiating "pneumonia" and "other SBIs" from "non-SBIs" using standardized, routinely collected data on clinical signs and symptoms, CRP, and procalcitonin.ResultsA total of 1,085 children were included with a median age of 1.6 years (interquartile range 0.8-3.4); 73 children (7%) had pneumonia and 98 children (9%) had other SBIs. The Feverkidstool showed good discriminative ability in this new population. After adding procalcitonin to the Feverkidstool, c-statistic for "pneumonia" increased from 0.85 (95% confidence interval (CI) 0.76-0.94) to 0.86 (0.77-0.94) and for "other SBI" from 0.81 (0.73-0.90) to 0.83 (0.75- 0.91). A model with clinical features and procalcitonin performed similar to the Feverkidstool.ConclusionThis study confirms the external validity of the Feverkidstool, with CRP and procalcitonin being equally valuable for predicting SBI in our population of febrile children. Our findings do not support routine dual use of CRP and procalcitonin.

Angiogenic Markers Predict Pregnancy Complications and Prolongation in Preeclampsia: Continuous Versus Cutoff Values.

To assess the incremental value of a single determination of the serum levels of sFlt-1 (soluble Fms-like tyrosine kinase 1) and PlGF (placental growth factor) or their ratio, without using cutoff values, for the prediction of maternal and fetal/neonatal complications and pregnancy prolongation, 620 women with suspected/confirmed preeclampsia, aged 18 to 48 years, were included in a prospective, multicenter, observational cohort study. Women had singleton pregnancies and a median pregnancy duration of 34 (range, 20-41) weeks. Complications occurred in 118 women and 248 fetuses. The median duration between admission and delivery was 12 days. To predict prolongation, PlGF showed the highest incremental value (R2=0.72) on top of traditional predictors (gestational age at inclusion, diastolic blood pressure, proteinuria, creatinine, uric acid, alanine transaminase, lactate dehydrogenase, and platelets) compared with R2=0.53 for the traditional predictors only. sFlt-1 showed the highest value to discriminate women with and without maternal complications (C-index=0.83 versus 0.72 for the traditional predictors only), and the sFlt-1/PlGF ratio showed the highest value to discriminate fetal/neonatal complications (C-index=0.86 versus 0.78 for the traditional predictors only). Applying previously suggested cutoff values for the sFlt-1/PlGF ratio yielded lower incremental values than applying continuous values. In conclusion, sFlt-1 and PlGF are strong and independent predictors for days until delivery along with maternal and fetal/neonatal complications on top of the traditional criteria. Their use as continuous variables (instead of applying cutoff values for different gestational ages) should now be tested in a prospective manner, making use of an algorithm calculating the risk of an individual woman with suspected/confirmed preeclampsia to develop complications.

Prediction of Multiple Recurrent Events: A Comparison of Extended Cox Models in Bladder Cancer.

Recurrence of bladder cancer can occur repeatedly in the same patient after treatment of the primary tumor. Models predicting the risk of a next recurrence may inform individualized decision-making on surveillance frequency. We aimed to assess the usefulness of extensions of the Cox proportional hazards model for repeated events in this context. We analyzed 531 Dutch patients with bladder cancer (1990-2012) with information on 7 prespecified predictors at the time of diagnosis of the primary and recurrent tumors. We considered 3 aspects of model variants: how to model time to the repeated events (calendar time, gap time, elapsed time); the number of preceding events (predictor, stratum variable); and the within-subject correlation (ignored in a simple Cox model, robust standard errors in a variance-correction model, random effect in a frailty model). First to fourth recurrences of bladder cancer occurred in 313, 174, 103, and 66 patients, respectively, with median calendar follow-up times of 1.1, 2.5, 3.8, and 4.5 years, respectively. We focused on gap time in the detailed analyses, allowing for clinically meaningful predictions. Variance-correction models may be useful if predictor selection is part of the model development. Frailty models may be useful when within-subject correlation is strong.

FGFR3, TERT and OTX1 as a Urinary Biomarker Combination for Surveillance of Patients with Bladder Cancer in a Large Prospective Multicenter Study.

PURPOSE: Patients with nonmuscle invasive bladder cancer are followed with frequent cystoscopies. In this study FGFR3, TERT and OTX1 were investigated as a diagnostic urinary marker combination during followup of patients with primary nonmuscle invasive bladder cancer. MATERIALS AND METHODS: In this international, multicenter, prospective study 977 patients with nonmuscle invasive bladder cancer were included. A total of 2,496 urine samples were collected prior to cystoscopy during regular visits. Sensitivity was estimated to detect concomitant recurrences. Kaplan-Meier curves were used to estimate the development of future recurrences after urinalysis and a negative cystoscopy. RESULTS: Sensitivity of the assay combination for recurrence detection was 57% in patients with primary low grade, nonmuscle invasive bladder cancer. However, sensitivity was 83% for recurrences that were pT1 or muscle invasive bladder cancer. Of the cases 2% progressed to muscle invasive bladder cancer. Sensitivity for recurrence detection in patients with primary high grade disease was 72% and 7% of them had progression to muscle invasive bladder cancer. When no concomitant tumor was found by cystoscopy, positive urine samples were more frequently followed by a recurrence over time compared to a negative urine sample (58% vs 36%, p <0.001). High stage recurrences were identified within 1 year after a positive urine test and a negative cystoscopy. CONCLUSIONS: Recurrences in patients with primary nonmuscle invasive bladder cancer can be detected by a combination of urine assays. This study supports the value of urinalysis as an alternative diagnostic tool in patients presenting with low grade tumors and as a means to identify high stage tumors earlier.

A closed testing procedure to select an appropriate method for updating prediction models.

Prediction models fitted with logistic regression often show poor performance when applied in populations other than the development population. Model updating may improve predictions. Previously suggested methods vary in their extensiveness of updating the model. We aim to define a strategy in selecting an appropriate update method that considers the balance between the amount of evidence for updating in the new patient sample and the danger of overfitting. We consider recalibration in the large (re-estimation of model intercept); recalibration (re-estimation of intercept and slope) and model revision (re-estimation of all coefficients) as update methods. We propose a closed testing procedure that allows the extensiveness of the updating to increase progressively from a minimum (the original model) to a maximum (a completely revised model). The procedure involves multiple testing with maintaining approximately the chosen type I error rate. We illustrate this approach with three clinical examples: patients with prostate cancer, traumatic brain injury and children presenting with fever. The need for updating the prostate cancer model was completely driven by a different model intercept in the update sample (adjustment: 2.58). Separate testing of model revision against the original model showed statistically significant results, but led to overfitting (calibration slope at internal validation = 0.86). The closed testing procedure selected recalibration in the large as update method, without overfitting. The advantage of the closed testing procedure was confirmed by the other two examples. We conclude that the proposed closed testing procedure may be useful in selecting appropriate update methods for previously developed prediction models. Copyright © 2016 John Wiley & Sons, Ltd.

Prediction of Preadolescent Overweight and Poor Cardiometabolic Outcome in Children up to 6 Years of Age: Research Protocol.

BACKGROUND: Dynamic risk estimations may enable targeting primary prevention of overweight and overweight-related adverse cardiometabolic outcome in later life, potentially serving as a valuable addition to universal primary prevention. This approach seems particularly promising in young children, as body mass index (BMI) changes at a young age are highly predictive of these outcomes, and parental lifestyle interventions at a young age are associated with improved long-term outcome. OBJECTIVE: This paper describes the design of our study, which aims to develop digitized tools that can be implemented in the Dutch Child Health Care (CHC) system or by pediatricians for children up to 6 years of age. These tools will enable (1) dynamically predicting the development of overweight, hypertension or prehypertension, low high-density lipoprotein cholesterol (HDL-C) values, and high total cholesterol to HDL-C ratio by early adolescence and (2) identifying children who are likely to have poor cardiometabolic outcome by the age of 5-6 years and by the age of 10 years. METHODS: Data will be obtained from the Generation R (n=7893) and Prevention and Incidence of Asthma and Mite Allergy (PIAMA; n=3963) cohorts, two Dutch prenatally recruited cohorts. We will select candidate predictors that can be assessed during the first visit and/or during subsequent visits to the CHC center or pediatrician, including sex; parental age, education level, and BMI; smoking exposure; ethnicity; birth weight; gestational age; breastfeeding versus formula feeding; and growth data through the age of 6 years. We will design dynamic prediction models that can be updated with new information obtained during subsequent CHC visits, allowing each measurement to be added to the model. Performance of the model will be assessed in terms of discrimination and calibration. Finally, the model will be validated both internally and externally using the combined cohort data and then converted into a computer-assisted tool called ProCOR (Prediction Of Child CardiOmetabolic Risk). RESULTS: This is an ongoing research project financed by the Dutch government. The first results are expected in 2016. CONCLUSIONS: This study may contribute to the national implementation of digitized tools for assessing the risk of overweight and related cardiometabolic outcome in young children, enabling targeted primary prevention, ultimately yielding relevant health gains and improved resource allocation.

Improved Prediction by Dynamic Modeling: An Exploratory Study in the Adult Cardiac Surgery Database of the Netherlands Association for Cardio-Thoracic Surgery.

BACKGROUND: The predictive performance of static risk prediction models such as EuroSCORE deteriorates over time. We aimed to explore different methods for continuous updating of EuroSCORE (dynamic modeling) to improve risk prediction. METHODS AND RESULTS: Data on adult cardiac surgery from 2007 to 2012 (n=95 240) were extracted from the Netherlands Association for Cardio-Thoracic Surgery database. The logistic EuroSCORE predicting in-hospital death was updated using 6 methods: recalibrating the intercept of the logistic regression model; recalibrating the intercept and joint effects of the prognostic factors; re-estimating all prognostic factor effects, re-estimating all prognostic factor effects, and applying shrinkage of the estimates; applying a test procedure to select either of these; and a Bayesian learning strategy. Models were updated with 1 or 3 years of data, in all cardiac surgery or within operation subgroups. Performance was tested in the subsequent year according to discrimination (area under the receiver operating curve, area under the curve) and calibration (calibration slope and calibration-in-the-large). Compared with the original EuroSCORE, all updating methods resulted in improved calibration-in-the-large (range -0.17 to 0.04 versus -1.13 to -0.97, ideally 0.0). Calibration slope (range 0.92-1.15) and discrimination (area under the curve range 0.83-0.87) were similar across methods. In small subgroups, such as aortic valve replacement and aortic valve replacement+coronary artery bypass grafting, extensive updating using 1 year of data led to poorer performance than using the original EuroSCORE. The choice of updating method had little effect on benchmarking results of all cardiac surgery. CONCLUSIONS: Several methods for dynamic modeling may result in good discrimination and superior calibration compared with the original EuroSCORE. For large populations, all methods are appropriate. For smaller subgroups, it is recommended to use data from multiple years or a Bayesian approach.

Prediction of Chlamydia trachomatis infection to facilitate selective screening on population and individual level: a cross-sectional study of a population-based screening programme.

OBJECTIVES: To develop prediction models for Chlamydia trachomatis (Ct) infection with different levels of detail in information, that is, from readily available data in registries and from additional questionnaires. METHODS: All inhabitants of Rotterdam and Amsterdam aged 16-29 were invited yearly from 2008 until 2011 for home-based testing. Their registry data included gender, age, ethnicity and neighbourhood-level socioeconomic status (SES). Participants were asked to fill in a questionnaire on education, sexually transmitted infection history, symptoms, partner information and sexual behaviour. We developed prediction models for Ct infection using first-time participant data-including registry variables only and with additional questionnaire variables-by multilevel logistic regression analysis to account for clustering within neighbourhoods. We assessed the discriminative ability by the area under the receiver operating characteristic curve (AUC). RESULTS: Four per cent (3540/80 385) of the participants was infected. The strongest registry predictors for Ct infection were young age (especially for women) and Surinamese, Antillean or sub-Saharan African ethnicity. Neighbourhood-level SES was of minor importance. Strong questionnaire predictors were low to intermediate education level, ethnicity of the partner (non-Dutch) and having sex with casual partners. When using a prediction model including questionnaire risk factors (AUC 0.74, 95% CI 0.736 to 0.752) for selective screening, 48% of the participating population needed to be screened to find 80% (95% CI 78.4% to 81.0%) of Ct infections. The model with registry risk factors only (AUC 0.67, 95% CI 0.656 to 0.675) required 60% to be screened to find 78% (95% CI 76.6% to 79.4%) of Ct infections. CONCLUSIONS: A registry-based prediction model can facilitate selective Ct screening at population level, with further refinement at the individual level by including questionnaire risk factors.

A Dutch Prediction Tool to Assess the Risk of Additional Axillary Non-Sentinel Lymph Node Involvement in Sentinel Node-Positive Breast Cancer Patients.

BACKGROUND: Multiple predictive systems have previously been developed to identify the sentinel lymph node (SLN)-positive patients at low risk of additional axillary non-SLN involvement and for whom completion axillary lymph node dissection (ALND) could be avoided. However, previous studies showed that these tools had poor performance in Dutch patients with breast cancer, probably owing to variations in pathology settings and differences in population characteristics. The aim of the present study was to develop a predictive tool for the risk of non-SLN involvement in a Dutch population with SLN-positive breast cancer. MATERIALS AND METHODS: The data from 513 patients with SLN-positive breast cancer at 10 participating hospitals, who had undergone ALND from January 2007 to December 2008 were studied. The uni- and multivariable associations of predictors for non-SLN metastases were analyzed, and a predictive model was developed. The discriminatory ability of the model was measured by the area under the receiver operating characteristic curve (AUC) and the agreement between predicted probabilities and observed frequencies was visualized by a calibration plot. RESULTS: A predictive model was developed that included the 2 strongest predictors: the size of the SLN metastases in millimeters and the presence of a negative sentinel lymph node. The model showed good discriminative ability (AUC, 0.75) and good calibration over the complete range of predicted probabilities. CONCLUSION: We have developed a tool to predict additional non-SLN metastases in Dutch patients with SLN-positive breast cancer that is easy to use in daily clinical breast cancer practice.

Palliative care consultation services in hospitals in the Netherlands: the design of the COMPASS study.

BACKGROUND: Patients with an advanced incurable disease are often hospitalised for some time during the last phase of life. Care in hospitals is generally focussed at curing disease and prolonging life and may therefore not in all cases adequately address the needs of such patients. We present the COMPASS study, a study on the effects and costs of consultation teams for palliative care in hospitals. This observational study aims to investigate the use, effects and costs of PCT consultation services for hospitalized patients with incurable cancer in the Netherlands. METHODS/DESIGN: The study consists of 3 parts: 1. A questionnaire, interviews and a focus group discussion to investigate the characteristics of PCT consultation in 12 hospitals. PCTs will register their activities to calculate the costs of PCT consultation. 2. Cancer patients for whom the attending physician would not be surprised that they would die within 12 month will be included in a medical file search in three hospitals. Medical records will be investigated to compare care, treatment and hospital costs between patients with and patients without PCT consultation. 3. In the other nine hospitals, we will perform a longitudinal study, and compare quality of life between 100 patients for whom a PCT was consulted with 200 patients without PCT consultation. Propensity score matching will be used to adjust for differences between both patient groups. Patients will be followed for three months after inclusion. Quality of life will be assessed with the Palliative Outcome Scale, the EuroQol-5d and the EORTC-QLQ-C15 PAL. Satisfaction with care in the hospital is measured with the IN-PATSAT32. The cost impact of PCT consultation will also be explored. DISCUSSION: This is the first multicenter study on PCT consultation in the Netherlands. The study will give valuable insight in the process, effects and costs of PCT consultation in hospitals. It is anticipated that PCT consultation has a positive effect on patients' quality of life and satisfaction with care and will lead to less hospital care costs.

A head to head comparison of nine tools predicting non-sentinel lymph node status in sentinel node positive breast cancer women.

BACKGROUND AND OBJECTIVES: This study was conducted to evaluate the performance of available tools predicting non-sentinel lymph node (non-SLN) status in women with SLN positive breast cancer and to see if they can be safely used in everyday clinical practice. METHODS: Data of 220 women with breast cancer who underwent a SLN biopsy at the Máxima Medical Centre between 2000-2008 were analysed. Tools evaluated were: the models from Memorial Sloan Kettering Cancer Centre, Stanford, Mayo, Cambridge, Gur, and MOU, and the scores from Saidi, Tenon, and MDA. Model performance was assessed using calibration, discrimination and Nagelkerke's explained variation. RESULTS: The MSKCC nomogram showed best overall performance with best discrimination (AUC 0.69), second best calibration, and highest explained variation (31%). The 10% low risk threshold led to defining only 22% (38/176) of the women as being low risk while in fact 66% (116/176) were non-SLN negative. The false negative rate was 13% (5/38). CONCLUSIONS: Current models for predicting non-SLN metastases in SLN positive breast cancer are not yet ready for implementation in general practice. Further research efforts should improve model performance in selecting patients or perhaps find a role in support in the paradigm shift to a "treat none unless" approach.

Epilepsy in children with tuberous sclerosis complex: Chance of remission and response to antiepileptic drugs.

OBJECTIVE: To describe treatment and outcome of epilepsy in children with tuberous sclerosis complex (TSC). METHODS: Seventy-one children with TSC and epilepsy treated at the ENCORE TSC Expertise Center between 1988 and 2014 were included. Patient characteristics and duration and effectiveness of antiepileptic treatments were extracted from our clinical database. Correlations were made between recurrence of seizures after response to treatment, and several patient characteristics. RESULTS: Median age at time of inclusion was 9.4 years (range 0.9-18.0). Seizure history showed that 55 children (77%) of 71 became seizure-free for longer than 1 month, and 21 (30%) of 71 for longer than 24 months. Remission of seizures was associated with higher IQ, and a trend was observed between seizure remission and age at onset of seizures. A total of 19 antiepileptic drugs (AEDs) were used. Valproic acid, vigabatrin, levetiracetam, and carbamazepine were used most frequently. Nonpharmacologic therapies (ketogenic diet, epilepsy surgery, and vagus nerve stimulation) were used 13 times. Epilepsy surgery was most effective, with four of five children becoming seizure-free. AEDs prescribed as first and second treatment were most effective. Valproic acid was prescribed most frequently as first and second treatment, followed by vigabatrin. Thirty-one children had infantile spasms, preceded by focal seizures in 18 children (58%). Vigabatrin was used by 29 children (94%), and was first treatment in 15 (48%). Vigabatrin was more effective than other AEDs when prescribed as first treatment. SIGNIFICANCE: We showed that, although 77% of children with epilepsy due to TSC reached seizure remission, usually after their first or second AED, this was sustained for at least 24 months in only 38%. Almost half of those with 24 months of remission later had relapse of seizures. Our results support vigabatrin as first choice drug, and show the need for better treatment options for these children.

Estimates of absolute treatment benefit for individual patients required careful modeling of statistical interactions.

OBJECTIVES: We aimed to compare modeling approaches to estimate the individual survival benefit of treatment with either coronary artery bypass graft surgery (CABG) or percutaneous coronary intervention (PCI) for patients with complex coronary artery disease. STUDY DESIGN AND SETTING: We estimated survival with Cox regression models that included the treatment variable (CABG/PCI) interacting with either an internally developed overall prognostic index (PI) or with individual prognostic factors. We analyzed data of patients who were randomized in the Synergy between Percutaneous Coronary Intervention with Taxus and Cardiac Surgery trial (1,800 patients, 178 deaths). RESULTS: A negligible interaction with the PI (P = 0.51) led to 4-year survival estimates in favor of CABG for all patients. In contrast, individual interactions indicated substantial relative treatment effect heterogeneity (overall interaction P = 0.004), and estimates of 4-year survival were numerically in favor of CABG for 1,275 of 1,800 patients (71%; 519 with 95% confidence). To test the more complex model with individual interactions, we first used penalized regression, resulting in smaller but largely consistent individual estimates of the survival difference between CABG and PCI. Second, strong treatment interactions were confirmed at external validation in 2,891 patients from a multinational registry. CONCLUSION: Modeling strategies that omit interactions may result in misleading estimates of absolute treatment benefit for individual patients with the potential hazard of suboptimal decision making.