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Prognostic models that aim to improve the prediction of clinical events, individualized treatment and decision-making are increasingly being developed and published. However, relatively few models are externally validated and validation by independent researchers is rare. External validation is necessary to determine a prediction model’s reproducibility and generalizability to new and different patients. Various methodological considerations are important when assessing or designing an external validation study. In this article, an overview is provided of these considerations, starting with what external validation is, what types of external validation can be distinguished and why such studies are a crucial step towards the clinical implementation of accurate prediction models. Statistical analyses and interpretation of external validation results are reviewed in an intuitive manner and considerations for selecting an appropriate existing prediction model and external validation population are discussed. This study enables clinicians and researchers to gain a deeper understanding of how to interpret model validation results and how to translate these results to their own patient population.

ABSTRACT In this article we introduce the concept of inverse probability of treatment weighting (IPTW) and describe how this method can be applied to adjust for measured confounding in observational research, illustrated by a clinical example from nephrology. IPTW involves two main steps. First, the probability—or propensity—of being exposed to the risk factor or intervention of interest is calculated, given an individual’s characteristics (i.e. propensity score). Second, weights are calculated as the inverse of the propensity score. The application of these weights to the study population creates a pseudopopulation in which confounders are equally distributed across exposed and unexposed groups. We also elaborate on how weighting can be applied in longitudinal studies to deal with informative censoring and time-dependent confounding in the setting of treatment-confounder feedback.

More than 2 million people worldwide are being treated for end-stage kidney disease (ESKD). This Series paper provides an overview of incidence, modality use (in-centre haemodialysis, home dialysis, or transplantation), and mortality for patients with ESKD based on national registry data. We also present data from an international cohort study to highlight differences in haemodialysis practices that affect survival and the experience of patients who rely on this therapy, which is both life-sustaining and profoundly disruptive to their quality of life. Data illustrate disparities in access to renal replacement therapy of any kind and in the use of transplantation or home dialysis, both of which are widely considered preferable to in-centre haemodialysis for many patients with ESKD in settings where infrastructure permits. For most patients with ESKD worldwide who are treated with in-centre haemodialysis, overall survival is poor, but longer in some Asian countries than elsewhere in the world, and longer in Europe than in the USA, although this gap has reduced. Commendable haemodialysis practice includes exceptionally high use of surgical vascular access in Japan and in some European countries, and the use of longer or more frequent dialysis sessions in some countries, allowing for more effective volume management. Mortality is especially high soon after ESKD onset, and improved preparation for ESKD is needed including alignment of decision making with the wishes of patients and families.

To reduce adverse drug events (ADEs), hospitals need a system to support them in monitoring ADE occurrence routinely, rapidly, and at scale. Natural language processing (NLP), a computerized approach to analyze text data, has shown promising results for the purpose of ADE detection in the context of pharmacovigilance. However, a detailed qualitative assessment and critical appraisal of NLP methods for ADE detection in the context of ADE monitoring in hospitals is lacking. Therefore, we have conducted a scoping review to close this knowledge gap, and to provide directions for future research and practice. We included articles where NLP was applied to detect ADEs in clinical narratives within electronic health records of inpatients. Quantitative and qualitative data items relating to NLP methods were extracted and critically appraised. Out of 1,065 articles screened for eligibility, 29 articles met the inclusion criteria. Most frequent tasks included named entity recognition (n = 17; 58.6%) and relation extraction/classification (n = 15; 51.7%). Clinical involvement was reported in nine studies (31%). Multiple NLP modelling approaches seem suitable, with Long Short Term Memory and Conditional Random Field methods most commonly used. Although reported overall performance of the systems was high, it provides an inflated impression given a steep drop in performance when predicting the ADE entity or ADE relation class. When annotating corpora, treating an ADE as a relation between a drug and non-drug entity seems the best practice. Future research should focus on semi-automated methods to reduce the manual annotation effort, and examine implementation of the NLP methods in practice.

AbstractObjectiveTo identify the optimal estimated glomerular filtration rate (eGFR) at which to initiate dialysis in people with advanced chronic kidney disease.DesignNationwide observational cohort study.SettingNational Swedish Renal Registry of patients referred to nephrologists.ParticipantsPatients had a baseline eGFR between 10 and 20 mL/min/1.73 m2 and were included between 1 January 2007 and 31 December 2016, with follow-up until 1 June 2017.Main outcome measuresThe strict design criteria of a clinical trial were mimicked by using the cloning, censoring, and weighting method to eliminate immortal time bias, lead time bias, and survivor bias. A dynamic marginal structural model was used to estimate adjusted hazard ratios and absolute risks for five year all cause mortality and major adverse cardiovascular events (composite of cardiovascular death, non-fatal myocardial infarction, or non-fatal stroke) for 15 dialysis initiation strategies with eGFR values between 4 and 19 mL/min/1.73 m2 in increments of 1 mL/min/1.73 m2. An eGFR between 6 and 7 mL/min/1.73 m2 (eGFR6-7) was taken as the reference.ResultsAmong 10 290 incident patients with advanced chronic kidney disease (median age 73 years; 3739 (36%) women; median eGFR 16.8 mL/min/1.73 m2), 3822 started dialysis, 4160 died, and 2446 had a major adverse cardiovascular event. A parabolic relation was observed for mortality, with the lowest risk for eGFR15-16. Compared with dialysis initiation at eGFR6-7, initiation at eGFR15-16 was associated with a 5.1% (95% confidence interval 2.5% to 6.9%) lower absolute five year mortality risk and 2.9% (0.2% to 5.5%) lower risk of a major adverse cardiovascular event, corresponding to hazard ratios of 0.89 (95% confidence interval 0.87 to 0.92) and 0.94 (0.91 to 0.98), respectively. This 5.1% absolute risk difference corresponded to a mean postponement of death of 1.6 months over five years of follow-up. However, dialysis would need to be started four years earlier. When emulating the intended strategies of the Initiating Dialysis Early and Late (IDEAL) trial (eGFR10-14v eGFR5-7) and the achieved eGFRs in IDEAL (eGFR7-10v eGFR5-7), hazard ratios for all cause mortality were 0.96 (0.94 to 0.99) and 0.97 (0.94 to 1.00), respectively, which are congruent with the findings of the randomised IDEAL trial.ConclusionsVery early initiation of dialysis was associated with a modest reduction in mortality and cardiovascular events. For most patients, such a reduction may not outweigh the burden of a substantially longer period spent on dialysis.

In their study based on data from the Dialysis Outcomes and Practice Patterns Study (DOPPS) census database, including 86,886 hemodialysis patients from 11 countries, Robinson and colleagues show that in all countries studied, mortality is higher in the first 120 days after the start of dialysis than after this period. We discuss factors that may affect international differences in early mortality, including current dialysis initiation practices and withdrawal from dialysis.

The aim of this study is to present average annual healthcare costs for Dutch renal replacement therapy (RRT) patients for 7 treatment modalities. Health insurance claims data from 2012-2014 were used. All patients with a 2014 claim for dialysis or kidney transplantation were selected. The RRT related and RRT unrelated average annual healthcare costs were analysed for 5 dialysis modalities (in-centre haemodialysis (CHD), home haemodialysis (HHD), continuous ambulatory peritoneal dialysis (CAPD), automated peritoneal dialysis (APD) and multiple dialysis modalities in a year (Mix group)) and 2 transplant modalities (kidney from living and deceased donor, respectively). The total average annual healthcare costs in 2014 ranged from €77,566 (SD = €27,237) for CAPD patients to €105,833 (SD = €30,239) for patients in the Mix group. For all dialysis modalities, the vast majority (72-84%) of costs was RRT related. Patients on haemodialysis ≥4x/week had significantly higher average annual costs compared to those dialyzing 3x/week (Δ€19,122). Costs for kidney transplant recipients were €85,127 (SD = €39,679) in the year of transplantation and rapidly declined in the first and second year after successful transplantation (resp. €29,612 (SD = €34,099) and €15,018 (SD = €16,186)). Transplantation with a deceased donor kidney resulted in higher costs (€99,450, SD = €36,036)) in the year of transplantation compared to a living donor kidney transplantation (€73,376, SD = €38,666). CAPD patients have the lowest costs compared to other dialysis modalities. Costs in the year of transplantation are 25% lower for patients with kidneys from living vs. deceased donor. After successful transplantation, annual costs decline substantially to a level that is approximately 14-19% of annual dialysis costs.

The internal validity of an epidemiological study can be affected by random error and systematic error. Random error reflects a problem of precision in assessing a given exposure-disease relationship and can be reduced by increasing the sample size. On the other hand, systematic error or bias reflects a problem of validity of the study and arises because of any error resulting from methods used by the investigator when recruiting individuals for the study, from factors affecting the study participation (selection bias) or from systematic distortions when collecting information about exposures and outcomes (information bias). Another important factor which may affect the internal validity of a clinical study is confounding. In this article, we focus on two categories of bias: selection bias and information bias. Confounding will be described in a future article of this series. Copyright © 2010 S. Karger AG, Basel [PUBLICATION ABSTRACT]

Resistant hypertension is defined as blood pressure above goal despite adherence to a combination of at least three optimally dosed antihypertensive medications, one of which is a diuretic. Chronic kidney disease is the most frequent of several patient factors or comorbidities associated with resistant hypertension. The prevalence of resistant hypertension is increased in patients with chronic kidney disease, while chronic kidney disease is associated with an impaired prognosis in patients with resistant hypertension. Recommended low-salt diet and triple antihypertensive drug regimens that include a diuretic, should be complemented by the sequential addition of other antihypertensive drugs. New therapeutic innovations for resistant hypertension, such as renal denervation and carotid barostimulation, are under investigation especially in patients with advanced chronic kidney disease. We discuss resistant hypertension in chronic kidney disease stages 3–5 (ie, patients with an estimated glomerular filtration rate below 60 mL/min per 1·73 m2 and not on dialysis), in terms of worldwide epidemiology, outcomes, causes and pathophysiology, evidence-based treatment, and a call for action.

End-stage renal disease requiring renal replacement therapy (RRT) during the neonatal period is a very rare condition, and little information is available regarding long-term RRT and outcomes. To gain more information, we performed a collaborative study on patient characteristics and treatment outcomes in children who started RRT as neonates during their first month of life between 2000 and 2011 who were prospectively registered in the ESPN/ERA-EDTA, the IPPN (since 2007), the Japanese registry, or the Australian and New Zealand Dialysis and Transplant (ANZDATA) registry. During the first month of life, 264 patients from 32 countries started RRT and were followed for a median of 29 months (interquartile range 11–60 months). Most neonates (242) started on peritoneal dialysis, 21 started on hemodialysis, and 1 patient with a transplant. The most important causes of renal failure were congenital anomalies of the kidney and urinary tract in 141, cystic kidneys in 35, and cortical necrosis in 30. Within 2 years after the start of RRT, 69 children changed dialysis modality and 53 received a renal transplant. After a median of 7 months, 45 children had died, mainly because of infection, resulting in an estimated 2-year survival of 81%, and 5-year survival of 76%. Growth retardation (63%), anemia (55%), and hypertension (57%) were still major problems after 2 years. Thus, relatively good medium-term patient survival may be achieved with RRT started during the neonatal period, but specific therapeutic challenges continue to exist in this age group.