Serum iPTH, calcium and phosphate, and the risk of mortality in a European haemodialysis population

Abstract

Background: A number of US observational studies reported an increased mortality risk with higher intact parathyroid hormone (iPTH), calcium and/or phosphate. The existence of such a link in a European haemodialysis population was explored as part of the Analysing Data, Recognising Excellence and Optimising Outcomes (ARO) Chronic Kidney Disease (CKD) Research Initiative.

Methods: The association between the markers of mineral and bone disease and clinical outcomes was examined in 7970 patients treated in European Fresenius Medical Care facilities over a median of 21 months. Baseline and time-dependent (TD) Cox regression were performed using Kidney Disease Outcomes Quality Initiative (KDOQI) target ranges as reference categories, adjusting for demographics, medical history, dialysis parameters, inflammation, medications and laboratory parameters. Fractional polynomial (FP) models were also used.

Results: Hazard ratio (HR) estimates from baseline analysis for iPTH were U-shaped [>600 pg/mL, HR = 2.10, 95% confidence interval (CI) 1.62-2.73; <75 pg/mL, HR = 1.46, 95% CI 1.17-1.83]. TD analysis confirmed the results for iPTH. Baseline analysis showed that calcium >2.75 mmol/L increased risk of death (HR = 1.70, 95% CI 1.19-2.42). TD analysis showed that both low (HR = 1.19, 95% CI 1.04-1.37) and high calcium (HR = 1.74, 95% CI 1.30-2.34) increased risk of death. Baseline analysis for phosphate showed a U-shaped pattern (<1.13 mmol/L, HR = 1.18, 95% CI 1.01-1.37; >1.78 mmol/L, HR = 1.32, 95% CI 1.13-1.55). TD analysis confirmed the results for phosphate <1.13 mmol/L. HR estimates were higher in patients with diabetes versus those without diabetes for baseline analysis only (P-value = 0.014). FP analysis confirmed the results of baseline and TD analyses.

Conclusion: Patients with iPTH, calcium and phosphate levels within the KDOQI target ranges have the lowest risk of mortality compared with those outside the target ranges.

Fig. 1

(a) Relative risk of all-cause mortality for iPTH comparing baseline versus time-dependent Cox regression using fractional polynomials. Values <0.5% percentile and >99.5% percentile were removed from both models (baseline model = 29 observations removed and time-dependent model = 838 observations removed). iPTH values >1000 pg/mL not shown. Baseline model: log (HR) = −0.28iPTH^0.5 + 0.04iPTH^0.5 log iPTH + β_k×_k (P = 0.001); time-dependent model: log (HR) = −0.38 log iPTH + 0.05iPTH^0.5 + β_k×_k (P < 0.001). (b) Relative risk of all-cause mortality for total serum calcium comparing baseline versus time-dependent Cox regression using fractional polynomials. Calcium values <1.15 mmol/L and >3.74 mmol/L not shown. Baseline model: log (HR) = −0.23 calcium² + 0.19 calcium² log calcium + β_k×_k (P = 0.82); time-dependent model: log (HR) = −4.10 calcium¹ + 2.26 calcium¹ log calcium + β_k×_k (P = 0.015). (c) Relative risk of all-cause mortality for serum phosphate comparing baseline versus time-dependent Cox regression using fractional polynomials. Baseline model: log (HR) = −6.48 phosphate^0.5 + 2.78 phosphate^0.5 log phosphate + β_k×_k (P = 0.027); time-dependent model: log (HR) = 5.18 phosphate^−0.5 + 1.98 log phosphate + β_k×_k (P < 0.001). (a–c) Adjusted for demographics (age, gender, country, body mass index, smoking status), medical history (chronic kidney disease aetiology, history of diabetes, history of CVD and history of cancer), dialysis parameters [dialysis vintage, vascular access type, dialysis adequacy (Kt/V) and blood flow], markers of inflammation (serum albumin and CRP), CVD medications (antihypertensives, angiotensin-converting enzyme inhibitors, oral anticoagulants and anti-aggregants), mineral and bone disorder medications (oral vitamin D and phosphate binders), calcium, phosphate, iPTH, haemoglobin, ferritin, cholesterol, blood leucocytes, hospitalization, and change in vascular access type. In the time-dependent model, serum albumin, CRP, vitamin D, phosphate binders, hospitalization and change in vascular access were treated as time-dependent covariates.

Fig. 2

Relative risk of all-cause mortality for iPTH baseline Cox regression using fractional polynomials in patients with diabetes and without diabetes. Values <0.5% percentile and >99.5% percentile were removed from both models (no history of diabetes model = 22 observations removed; history of diabetes model = 7 observations removed). Number of observations used: no history of diabetes model = 2906; history of diabetes model = 1011. iPTH values >1000 pg/mL not shown. No history of diabetes: log (HR) = −0.23 log iPTH + 0.001iPTH¹ + β_k×_k (P = 0.03); history of diabetes model: log (HR) = −0.70 log iPTH + 0.11 iPTH^0.5 + β_k×_k (P = 0.03). Adjusted for demographics (age, gender, country, body mass index, smoking status), medical history (chronic kidney disease aetiology, history of diabetes, history of CVD and history of cancer), dialysis parameters [dialysis vintage, vascular access type, dialysis adequacy (Kt/V) and blood flow], markers of inflammation (serum albumin and C-reactive protein), CVD medications (antihypertensives, angiotensin-converting enzyme inhibitors, oral anticoagulants and anti-aggregants), mineral and bone disorder medications (oral vitamin D and phosphate binders), calcium, phosphate, haemoglobin, ferritin, cholesterol, blood leucocytes, hospitalization, and change in vascular access type.