This thesis has shed light on RPL practice and the management of RPL couples in need of counselling towards future pregnancies. Both clinical practice research and prediction research indicate that... Show moreThis thesis has shed light on RPL practice and the management of RPL couples in need of counselling towards future pregnancies. Both clinical practice research and prediction research indicate that there is room for improvements in RPL practice and RPL counselling. We studied quality of care by diving into clinical practice variation and quality of counselling by diving into prediction research.In the absence of effective treatment options that increase live birth rates in RPL couples, counselling towards future pregnancies plays a key role and enables couples to make an informed decision regarding further pregnancy attempts. This will still be present when future treatment options are investigated or discovered, as these models could then evaluate the effects of these treatments on performance of the model. It is therefore of utmost importance that prediction models are well developed and validated for use in clinical practice.In an era of technological advancement bringing societies, researchers and clinicians from all over the world more closely together, it is time to step up and work together, to unify RPL care and to create collaborations that hugely impact RPL research which can lead to high impact publications that can unravel the mysteries of RPL. Show less
OBJECTIVES The aim of this study was to investigate the performance of the EuroSCORE II over time and dynamics in values of predictors included in the model.METHODS A cohort study was performed... Show moreOBJECTIVES The aim of this study was to investigate the performance of the EuroSCORE II over time and dynamics in values of predictors included in the model.METHODS A cohort study was performed using data from the Netherlands Heart Registration. All cardiothoracic surgical procedures performed between 1 January 2013 and 31 December 2019 were included for analysis. Performance of the EuroSCORE II was assessed across 3-month intervals in terms of calibration and discrimination. For subgroups of major surgical procedures, performance of the EuroSCORE II was assessed across 12-month time intervals. Changes in values of individual EuroSCORE II predictors over time were assessed graphically.RESULTS A total of 103 404 cardiothoracic surgical procedures were included. Observed mortality risk ranged between 1.9% [95% confidence interval (CI) 1.6-2.4] and 3.6% (95% CI 2.6-4.4) across 3-month intervals, while the mean predicted mortality risk ranged between 3.4% (95% CI 3.3-3.6) and 4.2% (95% CI 3.9-4.6). The corresponding observed:expected ratios ranged from 0.50 (95% CI 0.46-0.61) to 0.95 (95% CI 0.74-1.16). Discriminative performance in terms of the c-statistic ranged between 0.82 (95% CI 0.78-0.89) and 0.89 (95% CI 0.87-0.93). The EuroSCORE II consistently overestimated mortality compared to observed mortality. This finding was consistent across all major cardiothoracic surgical procedures. Distributions of values of individual predictors varied broadly across predictors over time. Most notable trends were a decrease in elective surgery from 75% to 54% and a rise in patients with no or New York Heart Association I class heart failure from 27% to 33%.CONCLUSIONS The EuroSCORE II shows good discriminative performance, but consistently overestimates mortality risks of all types of major cardiothoracic surgical procedures in the Netherlands.The EuroSCORE II model aims to support clinicians and their patients to determine whether benefits of cardiac surgery outweigh mortality risks associated with these procedures [1]. Show less
Rekkas, A.; Rijnbeek, P.R.; Kent, D.M.; Steyerberg, E.W.; Klaveren, D. van 2023
Background Baseline outcome risk can be an important determinant of absolute treatment benefit and has been used in guidelines for "personalizing" medical decisions. We compared easily applicable... Show moreBackground Baseline outcome risk can be an important determinant of absolute treatment benefit and has been used in guidelines for "personalizing" medical decisions. We compared easily applicable risk-based methods for optimal prediction of individualized treatment effects.Methods We simulated RCT data using diverse assumptions for the average treatment effect, a baseline prognostic index of risk, the shape of its interaction with treatment (none, linear, quadratic or non-monotonic), and the magnitude of treatment-related harms (none or constant independent of the prognostic index). We predicted absolute benefit using: models with a constant relative treatment effect; stratification in quarters of the prognostic index; models including a linear interaction of treatment with the prognostic index; models including an interaction of treatment with a restricted cubic spline transformation of the prognostic index; an adaptive approach using Akaike's Information Criterion. We evaluated predictive performance using root mean squared error and measures of discrimination and calibration for benefit.Results The linear-interaction model displayed optimal or close-to-optimal performance across many simulation scenarios with moderate sample size (N = 4,250; similar to 785 events). The restricted cubic splines model was optimal for strong non-linear deviations from a constant treatment effect, particularly when sample size was larger (N = 17,000). The adaptive approach also required larger sample sizes. These findings were illustrated in the GUSTO-I trial.Conclusions An interaction between baseline risk and treatment assignment should be considered to improve treatment effect predictions. Show less
Horst, D.E.M. van der; Engels, N.; Hendrikx, J.; Dorpel, M.A. van den; Pieterse, A.H.; Stiggelbout, A.M.; ... ; Bos, W.J.W. 2023
IntroductionGuidelines on chronic kidney disease (CKD) recommend that nephrologists use clinical prediction models (CPMs). However, the actual use of CPMs seems limited in clinical practice. We... Show moreIntroductionGuidelines on chronic kidney disease (CKD) recommend that nephrologists use clinical prediction models (CPMs). However, the actual use of CPMs seems limited in clinical practice. We conducted a national survey study to evaluate: 1) to what extent CPMs are used in Dutch CKD practice, 2) patients' and nephrologists' needs and preferences regarding predictions in CKD, and 3) determinants that may affect the adoption of CPMs in clinical practice.MethodsWe conducted semi-structured interviews with CKD patients to inform the development of two online surveys; one for CKD patients and one for nephrologists. Survey participants were recruited through the Dutch Kidney Patient Association and the Dutch Federation of Nephrology.ResultsA total of 126 patients and 50 nephrologists responded to the surveys. Most patients (89%) reported they had discussed predictions with their nephrologists. They most frequently discussed predictions regarded CKD progression: when they were expected to need kidney replacement therapy (KRT) (n = 81), and how rapidly their kidney function was expected to decline (n = 68). Half of the nephrologists (52%) reported to use CPMs in clinical practice, in particular CPMs predicting the risk of cardiovascular disease. Almost all nephrologists (98%) reported discussing expected CKD trajectories with their patients; even those that did not use CPMs (42%). The majority of patients (61%) and nephrologists (84%) chose a CPM predicting when patients would need KRT in the future as the most important prediction. However, a small portion of patients indicated they did not want to be informed on predictions regarding CKD progression at all (10-15%). Nephrologists not using CPMs (42%) reported they did not know CPMs they could use or felt that they had insufficient knowledge regarding CPMs. According to the nephrologists, the most important determinants for the adoption of CPMs in clinical practice were: 1) understandability for patients, 2) integration as standard of care, 3) the clinical relevance.ConclusionEven though the majority of patients in Dutch CKD practice reported discussing predictions with their nephrologists, CPMs are infrequently used for this purpose. Both patients and nephrologists considered a CPM predicting CKD progression most important to discuss. Increasing awareness about existing CPMs that predict CKD progression may result in increased adoption in clinical practice. When using CPMs regarding CKD progression, nephrologists should ask whether patients want to hear predictions beforehand, since individual patients' preferences vary. Show less
Dijkstra, H.; Oosterhoff, J.H.F.; Kuit, A. van de; Ijpma, F.F.A.; Schwab, J.H.; Poolman, R.W.; ... ; Hendrickx, L.A.M. 2023
Aims To develop prediction models using machine-learning (ML) algorithms for 90 -day and oneyear mortality prediction in femoral neck fracture (FNF) patients aged 50 years or older based on the Hip... Show moreAims To develop prediction models using machine-learning (ML) algorithms for 90 -day and oneyear mortality prediction in femoral neck fracture (FNF) patients aged 50 years or older based on the Hip fracture Evaluation with Alternatives of Total Hip arthroplasty versus Hemiarthroplasty (HEALTH) and Fixation using Alternative Implants for the Treatment of Hip fractures (FAITH) trials.Methods This study included 2,388 patients from the HEALTH and FAITH trials, with 90 -day and oneyear mortality proportions of 3.0% (71/2,388) and 6.4% (153/2,388), respectively. The mean age was 75.9 years (SD 10.8) and 65.9% of patients (1,574/2,388) were female. The algorithms included patient and injury characteristics. Six algorithms were developed, internally validated and evaluated across discrimination (c-statistic; discriminative ability between those with risk of mortality and those without), calibration (observed outcome compared to the predicted probability), and the Brier score (composite of discrimination and calibration).Results The developed algorithms distinguished between patients at high and low risk for 90 -day and one -year mortality. The penalized logistic regression algorithm had the best performance metrics for both 90 -day (c-statistic 0.80, calibration slope 0.95, calibration intercept-0.06, and Brier score 0.039) and one -year (c-statistic 0.76, calibration slope 0.86, calibration intercept-0.20, and Brier score 0.074) mortality prediction in the hold -out set.Conclusion Using high-quality data, the ML -based prediction models accurately predicted 90 -day and one -year mortality in patients aged 50 years or older with a FNF. The final models must be externally validated to assess generalizability to other populations, and prospectively evaluated in the process of shared decision-making. Show less
The focus of this thesis is the improvement of diagnosis, early detection and treatment of CD in children. Increased knowledge, available guidelines and reliable diagnostics allow for timely... Show moreThe focus of this thesis is the improvement of diagnosis, early detection and treatment of CD in children. Increased knowledge, available guidelines and reliable diagnostics allow for timely diagnosis which can prevent complications and improve QoL, but the current healthcare approach is often unable to make the diagnosis in a timely manner. Moreover, despite timely diagnosis and effective therapy, there is a need to improve the follow up. Show less
Due to a shorter remaining life expectancy, the risk of recurrence in older patients with low risk breast cancer is often reduced and the benefit of treatments may be very limited, especially with... Show moreDue to a shorter remaining life expectancy, the risk of recurrence in older patients with low risk breast cancer is often reduced and the benefit of treatments may be very limited, especially with adjuvant treatments. In the first part of this thesis, we studied the interplay between breast cancer mortality and other-cause mortality. In the second part of this thesis, we investigated the effect of surgery and radiotherapy in subsets of the older population of patients with breast cancer in which the actual treatment effect is questionable. Show less
In part 1 of the thesis Predicting Outcomes in Patients with Kidney Disease, key differences between etiological and prediction research are explored and it is shown that observational research... Show moreIn part 1 of the thesis Predicting Outcomes in Patients with Kidney Disease, key differences between etiological and prediction research are explored and it is shown that observational research often conflates etiology and prediction which leads to incorrect causal conclusions. A framework for the external validation of prognostic models is provided and it is shown how competing events can be dealt with when externally validating a time-to-event prognostic model. These results are applicable to many clinical research fields, including nephrology as exemplified in part 2. Within the six applied chapters in part 2, prediction models for various adverse outcomes in patients with advanced kidney disease are identified, validated and developed. The thesis provides a broad overview of prognostic model applications in patients with chronic kidney disease, including comprehensive external validation studies for kidney failure prediction models, mortality prediction models and graft failure prediction models. Models to predict mortality on conservative care and dialysis and models to predict adverse outcomes after kidney transplantation were developed and validated. These results may improve shared decision-making processes and individualized medicine for patients with kidney disease. Show less
Spreafico, M.; Ieva, F.; Arlati, F.; Capello, F.; Fatone, F.; Fedeli, F.; ... ; Fiocco, M. 2021
Objectives This study aims at exploring and quantifying multiple types of adverse events (AEs) experienced by patients during cancer treatment. A novel longitudinal score to evaluate the Multiple... Show moreObjectives This study aims at exploring and quantifying multiple types of adverse events (AEs) experienced by patients during cancer treatment. A novel longitudinal score to evaluate the Multiple Overall Toxicity (MOTox) burden is proposed. The MOTox approach investigates the personalised evolution of high overall toxicity (high-MOTox) during the treatment.Design Retrospective analysis of the MRC-BO06/EORTC-80931 randomised controlled trial for osteosarcoma.Setting International multicentre population-based study.Participants A total of 377 patients with resectable high-grade osteosarcoma, who completed treatment within 180 days after randomisation without abnormal dosages (+25% higher than planned).Interventions Patients were randomised to six cycles of conventional versus dose-intense regimens of doxorubicin and cisplatin. Non-haematological toxicity data were collected prospectively and graded according to the Common Terminology Criteria for Adverse Events (CTCAE).Main outcome measures The MOTox score described the overall toxicity burden in terms of multiple toxic AEs, maximum-severity episode and cycle time-dimension. Evolution of high-MOTox was assessed through multivariable models, that investigated the impact of personalised characteristics (eg, achieved chemotherapy dose, previous AEs or biochemical factors) cycle-by-cycle.Results A cycle-by-cycle analysis identifies different evolutions of MOTox levels during treatment, detecting differences in patients' health. Mean MOTox values and percentages of patients with high-MOTox decreased cycle-by-cycle from 2.626 to 1.953 and from 57.8% to 36.6%, respectively. High-MOTox conditions during previous cycles were prognostic risk factors for a new occurrence (ORs range from 1.522 to 4.439), showing that patient's history of toxicities played an important role in the evolution of overall toxicity burden during therapy. Conventional regimen may be preferred to dose-intense in terms of AEs at cycles 2-3 (p<0.05).Conclusions The novel longitudinal method developed can be applied to any cancer studies with CTCAE-graded toxicity data. After validation in other studies, the MOTox approach may lead to improvements in healthcare assessment and treatment planning. Show less
Aims This study was performed to develop and externally validate prediction models for appropriate implantable cardioverter-defibrillator (ICD) shock and mortality to identify subgroups with... Show moreAims This study was performed to develop and externally validate prediction models for appropriate implantable cardioverter-defibrillator (ICD) shock and mortality to identify subgroups with insufficient benefit from ICD implantation.Methods and results We recruited patients scheduled for primary prevention ICD implantation and reduced left ventricular function. Bootstrapping-based Cox proportional hazards and Fine and Gray competing risk models with likely candidate predictors were developed for all-cause mortality and appropriate ICD shock, respectively. Between 2014 and 2018, we included 1441 consecutive patients in the development and 1450 patients in the validation cohort. During a median follow-up of 2.4 (IQR 2.1-2.8) years, 109 (7.6%) patients received appropriate ICD shock and 193 (13.4%) died in the development cohort. During a median follow-up of 2.7 (IQR 2.0-3.4) years, 105 (7.2%) received appropriate ICD shock and 223 (15.4%) died in the validation cohort. Selected predictors of appropriate ICD shock were gender, NSVT, ACE/ARB use, atrial fibrillation history, Aldosterone-antagonist use, Digoxin use, eGFR, (N)OAC use, and peripheral vascular disease. Selected predictors of all-cause mortality were age, diuretic use, sodium, NT-pro-BNP, and ACE/ARB use. C-statistic was 0.61 and 0.60 at respectively internal and external validation for appropriate ICD shock and 0.74 at both internal and external validation for mortality.Conclusion Although this cohort study was specifically designed to develop prediction models, risk stratification still remains challenging and no large group with insufficient benefit of ICD implantation was found. However, the prediction models have some clinical utility as we present several scenarios where ICD implantation might be postponed. Show less
Patients with lower leg cast immobilization or who had knee arthroscopy have an increased risk of venous thrombosis. Because of this increased risk, thromboprophylaxis was given to the majority of... Show morePatients with lower leg cast immobilization or who had knee arthroscopy have an increased risk of venous thrombosis. Because of this increased risk, thromboprophylaxis was given to the majority of these patients in the Netherlands, despite insufficient evidence for its effect. In this thesis, two large randomized controlled trials (including 1500 patients each, in which half of patients were randomized to prophylaxis with Low Molecular Weight Heparin (LMWH) and half of patients to no treatment) are described. Despite having an increased VTE risk, routine thromboprophylaxis with low dose LMWH did not decrease VTE risk in these patients. Therefore, we recommend no routine thromboprophylaxis with anticoagulants to these patients. Identification of high-risk patients and selective treatment of patients can be beneficial. Therefore, prediction models for the development of VTE in these patients were developed. The prediction models had good predictive value and were validated in two other studies. Hence, identification of high-risk patient can help to optimize prophylactic treatment: providing a higher dose or longer duration of anticoagulant treatment to patients with an additionally increased risk, whilst patients with a low risk will not be needlessly exposed to the burden and risk of anticoagulants. Show less
Aims/hypothesis The aims of this study were to identify all published prognostic models predicting retinopathy risk applicable to people with type 2 diabetes, to assess their quality and accuracy,... Show moreAims/hypothesis The aims of this study were to identify all published prognostic models predicting retinopathy risk applicable to people with type 2 diabetes, to assess their quality and accuracy, and to validate their predictive accuracy in a head-to-head comparison using an independent type 2 diabetes cohort. Methods A systematic search was performed in PubMed and Embase in December 2019. Studies that met the following criteria were included: (1) the model was applicable in type 2 diabetes; (2) the outcome was retinopathy; and (3) follow-up was more than 1 year. Screening, data extraction (using the checklist for critical appraisal and data extraction for systemic reviews of prediction modelling studies [CHARMS]) and risk of bias assessment (by prediction model risk of bias assessment tool [PROBAST]) were performed independently by two reviewers. Selected models were externally validated in the large Hoorn Diabetes Care System (DCS) cohort in the Netherlands. Retinopathy risk was calculated using baseline data and compared with retinopathy incidence over 5 years. Calibration after intercept adjustment and discrimination (Harrell's C statistic) were assessed. Results Twelve studies were included in the systematic review, reporting on 16 models. Outcomes ranged from referable retinopathy to blindness. Discrimination was reported in seven studies with C statistics ranging from 0.55 (95% CI 0.54, 0.56) to 0.84 (95% CI 0.78, 0.88). Five studies reported on calibration. Eight models could be compared head-to-head in the DCS cohort (N = 10,715). Most of the models underestimated retinopathy risk. Validating the models against different severities of retinopathy, C statistics ranged from 0.51 (95% CI 0.49, 0.53) to 0.89 (95% CI 0.88, 0.91). Conclusions/interpretation Several prognostic models can accurately predict retinopathy risk in a population-based type 2 diabetes cohort. Most of the models include easy-to-measure predictors enhancing their applicability. Tailoring retinopathy screening frequency based on accurate risk predictions may increase the efficiency and cost-effectiveness of diabetic retinopathy care. Registration PROSPERO registration ID CRD42018089122 Show less
Klaveren, D. van; Balan, T.A.; Steyerberg, E.W.; Kent, D.M. 2019
The number of older people in the population is rising and so is the number of older patients in the Emergency Department (ED). Older patients often have complex problems which leads to an... Show moreThe number of older people in the population is rising and so is the number of older patients in the Emergency Department (ED). Older patients often have complex problems which leads to an increased change of repeat ED visits, longer length of stay, higher chance of hospital admission and higher chance of negative health outcomes. Cognitive impairment is a frequent problem in older ED patients but often remains unrecognized and little is known about the association between cognitive impairment and adverse outcomes in older ED patients. In this thesis we show that cognitive impairment is associated with adverse outcomes in acutely presenting older patients. Secondly, we show that routinely collected parameters in addition to cognitive impairment can be used to screen for high risk of adverse outcomes in older ED patients. We investigated two delirium screeners and showed the CAM-ICU might not be suitable for early detection of delirium in the ED. Finally, vital signs that associate with decreased brain perfusion and oxygenation, such as low systolic blood pressure, were associated with cognitive impairment in older ED patients. Next steps would be to investigate if optimal resuscitation might improve cognition and decrease risk of subsequent delirium and adverse outcomes. Show less
The objective of the work presented in this thesis is to assess information provision about adjuvant systemic therapy during consultations between early-stage breast cancer patients and medical... Show moreThe objective of the work presented in this thesis is to assess information provision about adjuvant systemic therapy during consultations between early-stage breast cancer patients and medical oncologists in general. In this era of personalized medicine, prediction tools (e.g., Adjuvant!) are becoming an integral part of information provision during patient consultations. However, evidence is lacking about a) how prevalent the use of such tools is during patient consultations, and b) whether and how the use of such tools influences information provision. Therefore, this thesis in addition to assessing the availability and the quality of prediction tools for the early-stage breast cancer setting, also zooms in on the use of such tools during patient consultations and their impact on the content of consultations. Show less
