Max Plischke

Renal Elimination of Sclerostin Increases With Declining Kidney Function

CONTEXT Sclerostin serum levels are increased in patients with chronic kidney disease (CKD). Osteoporosis and CKD often occur simultaneously. Currently antisclerostin antibodies are in clinical development for the treatment of osteoporosis. OBJECTIVE The objective of this study was to study the renal handling of sclerostin. DESIGN This was a cross-sectional study. SETTING The study was conducted at a university hospital and outpatient renal clinic. PATIENTS One hundred twenty men and women with CKD stage 1-5 participated in the study. INTERVENTION Measurements of sclerostin in urine and serum (ELISA), renal function [estimated glomerular filtration rate (eGFR)], electrolytes, α1-microglobulin, PTH, vitamin D, and markers of bone turnover were conducted. Eight human kidney biopsies were stained for sclerostin using immunohistochemistry. MAIN OUTCOME MEASURE Urinary excretion of sclerostin was measured. RESULTS Urinary sclerostin excretion increased with declining eGFR (R=-0.75, P<.001), from 10.4 (±12.7) pmol/L in patients with eGFR greater than 90 mL/min per 1.73 m2 (CKD stage 1) to 117.9 (±65.4) pmol/L in patients with eGFR less than 15 mL/min per 1.73 m2 (CKD stage 5, P<.001). Fractional excretion of sclerostin increased with declining eGFR (R=-0.83, P<.001) from 0.45% (±0.6%) in CKD 1 to 26.3% (±17.6%) in CKD 5 (P<.001). Fractional excretion of sclerostin correlated with fractional excretion of α1-microglobulin (R=0.82, P<.001). No association between serum sclerostin and fractional excretion of phosphorus was found in a multivariate analysis. Sclerostin was detected in proximal tubular cells, showing a diffuse cytoplasmic staining pattern. CONCLUSION Increased sclerostin serum levels in CKD patients are not due to decreased renal elimination. On the contrary, renal elimination increases with declining kidney function. Whether this has consequences on antisclerostin antibody dosing, efficacy, or safety in patients with CKD remains to be determined.

PSHREG: a SAS macro for proportional and nonproportional subdistribution hazards regression.

Highlights • The %pshreg SAS macro fits Fine-Gray models for competing risks.• The macro first modifies a given data set and then uses PROC PHREG for analysis.• Many useful features of PROC PHREG can now be applied to a Fine-Gray model.• Time-dependent effects can be accommodated by time-by-covariate interactions.• For small data sets, the Firth correction is available.

Inorganic phosphate and FGF-23 predict outcome in stable systolic heart failure.

Eur J Clin Invest 2012; 42 (6): 649–656

Routinely available biomarkers improve prediction of long-term mortality in stable coronary artery disease: the Vienna and Ludwigshafen Coronary Artery Disease (VILCAD) risk score.

AIMS Previous risk assessment scores for patients with coronary artery disease (CAD) have focused on primary prevention and patients with acute coronary syndrome. However, especially in stable CAD patients improved long-term risk prediction is crucial to efficiently apply measures of secondary prevention. We aimed to create a clinically applicable mortality prediction score for stable CAD patients based on routinely determined laboratory biomarkers and clinical determinants of secondary prevention. METHODS AND RESULTS We prospectively included 547 patients with stable CAD and a median follow-up of 11.3 years. Independent risk factors were selected using bootstrapping based on Cox regression analysis. Age, left ventricular function, serum cholinesterase, creatinine, heart rate, and HbA1c were selected as significant mortality predictors for the final multivariable model. The Vienna and Ludwigshafen Coronary Artery Disease (VILCAD) risk score based on the aforementioned variables demonstrated an excellent discriminatory power for 10-year survival with a C-statistic of 0.77 (P < 0.001), which was significantly better than an established risk score based on conventional cardiovascular risk factors (C-statistic = 0.61, P < 0.001). Net reclassification confirmed a significant improvement in individual risk prediction by 34.8% (95% confidence interval: 21.7-48.0%) compared with the conventional risk score (P < 0.001). External validation of the risk score in 1275 participants of the Ludwigshafen Risk and Cardiovascular Health study (median follow-up of 9.8 years) achieved similar results (C-statistic = 0.73, P < 0.001). CONCLUSION The VILCAD score based on a routinely available set of risk factors, measures of cardiac function, and comorbidities outperforms established risk prediction algorithms and might improve the identification of high-risk patients for a more intensive treatment.

Augmented Backward Elimination: A Pragmatic and Purposeful Way to Develop Statistical Models

Statistical models are simple mathematical rules derived from empirical data describing the association between an outcome and several explanatory variables. In a typical modeling situation statistical analysis often involves a large number of potential explanatory variables and frequently only partial subject-matter knowledge is available. Therefore, selecting the most suitable variables for a model in an objective and practical manner is usually a non-trivial task. We briefly revisit the purposeful variable selection procedure suggested by Hosmer and Lemeshow which combines significance and change-in-estimate criteria for variable selection and critically discuss the change-in-estimate criterion. We show that using a significance-based threshold for the change-in-estimate criterion reduces to a simple significance-based selection of variables, as if the change-in-estimate criterion is not considered at all. Various extensions to the purposeful variable selection procedure are suggested. We propose to use backward elimination augmented with a standardized change-in-estimate criterion on the quantity of interest usually reported and interpreted in a model for variable selection. Augmented backward elimination has been implemented in a SAS macro for linear, logistic and Cox proportional hazards regression. The algorithm and its implementation were evaluated by means of a simulation study. Augmented backward elimination tends to select larger models than backward elimination and approximates the unselected model up to negligible differences in point estimates of the regression coefficients. On average, regression coefficients obtained after applying augmented backward elimination were less biased relative to the coefficients of correctly specified models than after backward elimination. In summary, we propose augmented backward elimination as a reproducible variable selection algorithm that gives the analyst more flexibility in adopting model selection to a specific statistical modeling situation.

Urine Osmolarity and Risk of Dialysis Initiation in a Chronic Kidney Disease Cohort – a Possible Titration Target?

Background Increasing evidence is linking fluid intake, vasopressin suppression and osmotic control with chronic kidney disease progression. Interestingly, the association between urine volume, urine osmolarity and risk of dialysis initiation has not been studied in chronic kidney disease patients before. Objective To study the relationship between urine volume, urine osmolarity and the risk of initiating dialysis in chronic kidney disease. Design In a retrospective cohort analysis of 273 patients with chronic kidney disease stage 1–4 we assessed the association between urine volume, urine osmolarity and the risk of dialysis by a multivariate proportional sub-distribution hazards model for competing risk data according to Fine and Gray. Co-variables were selected via the purposeful selection algorithm. Results Dialysis was reached in 105 patients over a median follow-up period of 92 months. After adjustment for age, baseline creatinine clearance, other risk factors and diuretics, a higher risk for initiation of dialysis was found in patients with higher urine osmolarity. The adjusted sub-distribution hazard ratio for initiation of dialysis was 2.04 (95% confidence interval, 1.06 to 3.92) for each doubling of urine osmolarity. After 72 months, the estimated adjusted cumulative incidence probabilities of dialysis were 15%, 24%, and 34% in patients with a baseline urine osmolarity of 315, 510, and 775 mosm/L, respectively. Conclusions We conclude that higher urine osmolarity is associated with a higher risk of initiating dialysis. As urine osmolarity is a potentially modifiable risk factor, it thus deserves further, prospective research as a potential target in chronic kidney disease progression.

Renal function in heart failure: a disparity between estimating function and predicting mortality risk

To compare the predictive value of estimated renal function calculated by the Chronic Kidney Disease Epidemiology Collaboration (eGFRCKD‐EPI), four‐variable Modification of Diet in Renal Disease (eGFRMDRD‐4), and Cockcroft–Gault [estimated creatinine clearance (eCcr)] equation in terms of all‐cause mortality in heart failure. Renal function is an important prognostic factor in heart failure. Established methods of estimating renal function are known to under‐/overestimate true function in certain settings.

Clinical evaluation of two novel biointact PTH(1-84) assays in hemodialysis patients.

OBJECTIVES In chronic kidney disease-mineral and bone disorder (CKD-MBD), most treatment decisions are guided by parathyroid hormone (PTH) levels. Here, we aimed at assessing the technical and clinical performance of two novel automated biointact PTH(1-84) assays, from Roche Diagnostics (Ro) and DiaSorin (DS), in hemodialysis patients. DESIGN AND METHODS We recorded demographics, dialysis treatment characteristics, pharmacotherapy for CKD-MBD and laboratory work-up. Statistical methods included Passing-Bablok, and multiple linear regression. RESULTS 121 patients, dialyzing on average for 3.5 years (range: 0.1-22.5), with serum phosphate 1.9±0.6 mmol/L (mean±SD), participated in the study. Median serum concentration for intact PTH was 223 ng/L (range: 5-2844), and for biointact PTH(1-84) was 136 ng/L (Ro; range: 1-1644), respectively 138 ng/L (DS; range: 4-1580). Both biointact assays were significantly correlated (r=0.98; Ro=0.87×DS+19.60). Bland-Altmann plots revealed an average bias ±2 SD of 10±27 ng/L below 200 ng/L, and -32±157 ng/L above 200 ng/L (Ro minus DS). The variably adjusted association between PTH and serum phosphate was very similar, regardless of the PTH assay, but this was not the case for PTH-derived measures (ratios biointact/intact; differences intact minus biointact). (Log)PTH concentrations as well as serum phosphate were significantly associated with serum creatinine, but only in patients with >0 mL urine per day. CONCLUSIONS Results from Roche and DiaSorin biointact PTH(1-84) assays were well correlated, but showed increased deviations at higher concentrations. Biointact PTH(1-84) levels are roughly two third of intact PTH. The association between PTH and serum creatinine may depend on residual renal clearance of PTH and/or serum phosphate.

Correlations and time course of FGF23 and markers of bone metabolism in maintenance hemodialysis patients

OBJECTIVE Parathyroid hormone (iPTH) and fibroblast growth factor 23 (FGF23) are elevated in secondary hyperparathyroidism. In hemodialysis, higher dialysate calcium (1.5 mmol/L) induces intradialytic suppression of iPTH, whereas its impact on FGF23 and markers of bone metabolism is unknown. We assessed the time course of FGF23 and markers of bone metabolism in relationship to dialysate calcium. DESIGN AND METHODS In this prospective cohort study of 19 patients on maintenance hemodialysis, we measured serum calcium (sCa), inorganic phosphate (iP), blood urea nitrogen (BUN), β2-microglobulin (ßMG), iPTH, FGF23, aminoterminal propeptide type 1 procollagen (P1NP), C-telopeptide of type I collagen for bone degradation (CTX-I), osteocalcin (OC), bone specific alkaline phosphatase (BALP), and tartrate-resistant acid phosphatase (TRAP5b) during a single hemodialysis session at baseline, 1, 2, and 3h of dialysis. The time course of measured parameters was compared according to groups of prescribed dialysate calcium of 1.25 mmol/L and 1.5 mmol/L. RESULTS iPTH declined in the 1.5 mmol/L dialysis group as serum calcium increased whereas it tended to increase in the 1.25 mmol/L group without significant changes in serum calcium. Patients on long-term dialysate calcium of 1.5 mmol/L had significantly lower CTX-I levels and tended to lower levels of iPTH, FGF23, OC, P1NP and TRAP5b at the start of dialysis compared to those on 1.25 mmol/L. CTX-I, FGF23 and OC but not BALP, P1NP and TRAP5b decreased during dialysis independent of dialysate calcium. CONCLUSIONS In spite of immediate effects on iPTH, dialysate calcium does not acutely affect other parameters of bone and mineral metabolism. SHORT SUMMARY Dialysate calcium concentration is known to have both immediate and longer-term impact on parathyroid hormone levels in hemodialysis patients. Little is known about the acute impact of dialysate calcium on bone metabolism. In this cross-sectional study of prevalent hemodialysis patients, we found no evidence of immediate short-term dialysate calcium-induced changes of fibroblast growth factor 23 or anabolic and catabolic markers of bone turnover during hemodialysis. However, differences in CTX-I and to a lesser extent other parameters between groups of higher and lower dialysate calcium suggest a longer-term effect that remains to be validated.

Effect of conversion from ciclosporin to tacrolimus on endothelial progenitor cells in stable long-term kidney transplant recipients.

Background Endothelial progenitor cell (EPC) counts are proposed surrogate markers for vascular function and cardiovascular risk. The effect of tacrolimus (TAC) on EPC is unknown. Methods In this randomized controlled trial, we assigned 148 stable long-term kidney transplant recipients (KTR) to maintaining ciclosporin (CSA) or to commencing TAC-based immunosuppression at a 2:1 ratio. EPC counts (CD34+/KDR+) after 24 months were defined as primary endpoint. Results The intent-to-treat analysis included 141 KTR (estimated glomerular filtration rate, 46.7 [40.1–61.8] mL/min per 1.73 m2). Median (interquartile range [IQR]) EPC counts at baseline and month 24 were 6 (2–9) and 3 (1–9) cells and 4 (2–8) and 2 (0–5) cells per 5×104 mononuclear cells in CSA and TAC, respectively. Median (IQR) circulating angiogenic cells at baseline and month 24 were 28 (10.7–57) and 44.33 (14.6–59.8) cells and 22 (10.8–41) and 21 (9.7–49.5) cells per high-power field in CSA and TAC, respectively. Median (IQR) endothelial cell colony-forming units count per well at baseline and month 24 were 10.5 (3.3–34.3) and 4.38 (1.7–26.5) in CSA and significantly declined from 9.31 (1.8–29.3) to 4.13 (1.1–9.5) in TAC (P=0.003). There were no cardiovascular events in either group. Conclusion Although late conversion from CSA to TAC appears safe in KTR, conversion to TAC has no favorable effect on EPC. Low EPC levels are associated with a higher risk of subsequent cardiovascular events and are therefore of prognostic value. Their trend to decline over time deserves further examination.