Abstract
Background/Aim: The clinical importance of fracture prevention in patients with end-stage renal disease is well-established. We investigated the roles of bone metabolism-related serum biomarkers and nutritional markers for fractures in Japanese living-donor kidney transplant recipients.
Patients and Methods: We included 204 consecutive patients who underwent kidney transplantation at Nara Medical University between 2003 and 2022 and retrospectively reviewed their medical charts. The cumulative incidence of fractures was investigated by focusing on bone metabolism-related serum biomarkers and nutritional markers, and related markers were explored.
Results: The age at surgery in the fracture group was significantly higher than that in the no-fracture group (p=0.018). Patients with fractures had a significantly higher risk of mortality than those without fractures (p=0.0018); cardiovascular mortality was higher in the fracture group than in the non-fracture group (p=0.052). The cumulative incidence of fractures (median follow-up period, 98 months) was 4.6% at 1 year, 8.6% at 2 years, 12.3% at 3 years, and 15.5% at 5 years after transplant. Particularly, patients with a survival index <26.1 had a significantly higher risk of fracture (p=0.014). Serum intact parathyroid hormone level (a bone metabolism-related biomarker) and survival index (a nutritional marker) were independently related to fractures (p=0.046 and p=0.022, respectively).
Conclusion: Serum intact parathyroid hormone level and the survival index may play important roles in determining the incidence of fractures in living donor kidney transplant recipients. Identifying patients at high risk of fractures and providing optimal intervention and education may contribute to improved and personalized management strategies.
Introduction
Generally, patients with chronic kidney disease (CKD), especially end-stage renal disease (ESRD), have combined alterations in mineral metabolism due to a decline in renal function, which contributes to an increased risk of fractures (1). Kidney transplantation (KT) is considered the most successful renal replacement therapy for patients with ESRD, and particularly, living-donor KT (LDKT) is associated with better graft and patient outcomes than deceased-donor KT (2). However, previous studies reported that kidney transplant recipients (KTRs) had a higher risk of fractures than not only the general population but also patients on dialysis (3, 4). In 2002, Ball et al. reported that the risk of hip fracture 3 years after KT increased by 34% compared with that in patients undergoing dialysis (5). Furthermore, mineral and bone disorders (MBDs), including fractures, are strongly correlated with a high mortality risk in KTRs (6). Therefore, fractures remain a paramount issue in improving outcomes in KTRs.
Several potential risk factors for fractures in KTRs have been reported. These include carryover factors from advanced CKD and/or dialysis periods, such as pretransplant uremia, chronic acidosis, secondary hyperparathyroidism, hypovitaminosis D, abnormal calcium metabolism, diabetes mellitus, and prolonged dialysis exposure, as well as post-transplant factors, such as corticosteroids, other immunosuppressants, tertiary hyperparathyroidism, and age (7, 8). A previous systematic review showed that the incidence of fractures in KTRs ranged from 3.3 to 99.6 fractures per 1,000 patient-years, and differences in incidence rates among the studies were owed to differences in patient characteristics, definition of fracture, and duration of follow-up (9). These studies suggest that KTRs have various risk factors for fractures, and the incidence rate of fractures is not low; thus, management of CKD-MBD before and after KT is important for improving patient outcomes.
Easy and rapid screening and monitoring are important for preventing fractures in KTRs. The 2017 Kidney Disease: Improving Global Outcomes guidelines suggest that dual-energy X-ray absorptiometry (DXA) may be useful for evaluating the bone health of patients with CKD3-5D (10). However, the indications for and/or intensities of DXA remain controversial. Bone metabolism-related serum markers are considered tools to predict bone mineral density. Routinely measured serum biomarkers such as calcium (Ca), alkaline phosphatase (ALP), and parathyroid hormone have been reported as predictors of bone mineral density (11). Nutritional markers may also play an important role in predicting fractures in KTRs. The Malnutrition-Inflammation Score, which was established to evaluate the nutritional status of patients on dialysis, has been reported to be a predictor of new clinically detected fractures in KTRs (12). Therefore, knowledge of the associations of bone metabolism-related serum biomarkers and nutritional markers, which can be measured easily and quickly, with fractures can lead to improved screening and monitoring to prevent fractures in KTRs.
The present study aimed to evaluate the associations of bone metabolism-related serum biomarkers and nutritional markers with fractures in KTRs. Understanding the roles of these markers and the advantages of assessing them can lead to the prevention of fractures, resulting in improved patient outcomes.
Patients and Methods
Patient selection and data collection. The study protocol was approved by the Institutional Review Board for Clinical Studies at Nara Medical University (Medical Ethics Committee ID: 2014). The requirement for informed patient consent was waived owing to the retrospective nature of the analysis. The study was conducted in compliance with the study protocol and provisions of the Declaration of Helsinki (2013). This retrospective study included consecutive patients who underwent KT at our institution between April 2003 and March 2022. We retrospectively reviewed the medical charts of the patients and obtained their clinical information.
Bone metabolism-related serum biomarkers and nutritional markers. Bone metabolism-related serum biomarkers, including phosphorus (P), Ca, calcium-phosphate product (Ca×P), intact parathyroid hormone (iPTH), ALP, hydroxyproline, 1,25-dihydroxyvitamin D, and osteocalcin, were evaluated. These markers are routinely measured immediately before LDKT at our institution. In addition, the following nutritional markers were assessed: body mass index (BMI), geriatric nutritional risk index (GNRI) [14.89 × albumin (g/dl) + 41.7 × current body weight (kg)/ideal body weight (kg)] (13), prognostic nutritional index (PNI) [10 × albumin (g/dl) + 0.0005 × total lymphocyte count (/mm3)] (14), controlling nutritional status (CONUT) (15), nutritional risk index for Japanese hemodialysis patients (NRI-JH) (16), and survival index (SI) [10 –(0.4 × age) + (0.3 × BMI) + (0.7 × serum creatinine level) + (6 × serum albumin level) + (0.03 × serum total cholesterol) − (serum P level) − (2 × cardiovascular diseases) + (2 × arteriovenous fistula)] (17). Assessments of these markers have been implemented in Japanese patients with CKD or devised by Japanese researchers, especially for patients with CKD.
Definition of fracture. Fracture was defined as a clinically significant fracture that was symptomatic and required treatment. In contrast, patients with compression fractures of vertebrae that were incidentally detected during routine radiographic examinations were excluded from the analysis.
Outcomes. The primary outcome was the incidence of fractures after LDKT. As a secondary outcome, related factors for the incidence of fractures among bone metabolism and nutritional markers were evaluated.
Statistical analysis. Continuous variables are reported as median and interquartile range (IQR) values. Categorical variables are reported as numbers and percentages. The Mann–Whitney U-test, Fisher’s exact test, or chi-squared test was used for comparisons between groups, as appropriate. Statistical analyses were performed, and figures were plotted using GraphPad Prism 9.0 (GraphPad Software, San Diego, CA, USA). A survival curve was obtained using the Kaplan–Meier method and compared using the log-rank test for each variable. Multivariable Cox regression analysis was performed using SPSS Statistics version 19 (IBM Corp., Armonk, NY, USA). In the multivariable analysis, bone metabolism and nutritional markers, which significantly associated with fractures in the univariable analysis, were evaluated. Death was censored for the graft survival analysis. The cutoff value of iPTH was identified by receiver operating characteristic curve analysis, and that of SI was determined according to the original report (17). Two-sided tests were used in all cases, and a p-value of <0.05 was considered statistically significant in all analyses.
Results
Comparison of clinical information between patients with and without fractures. Of the 204 consecutive patients, 13, 8, 25, and 2 patients were excluded from the analysis because of a lack of data, second KT, deceased donor KT, and age <18 years, respectively. Of the remaining 156 patients, three were excluded from the analysis because of clinically insignificant compression fractures of vertebrae. Eventually, fractures were found in 27 patients, and the regions of fractures included the hip (n=8, 29.6%), leg (n=8, 29.6%), arm (n=6, 22.2%), rib (n=4, 14.8%), and vertebrae (n=1, 3.8%) (Figure 1). Table I shows a comparison of the clinical characteristics between patients with and without fractures (n=153). The age at LDKT in the fracture group was significantly higher than that in the no-fracture group [p= 0.018; median (IQR): 57 (44-64) vs. 48 (37-56) years]. The median (IQR) BMI and follow-up period were 22.0 (19.0-25.5) kg/m2 and 97 (54-147) months, respectively, in the no-fracture group and 22.7 (20.4-24.5) kg/m2 and 98 (67-120) months, respectively, in the fracture group. The no-fracture group consisted of 39.7% women (n=50) and included 30 patients with ESRD secondary to diabetic nephropathy (23.8%), whereas the fracture group included 12 women (44.4%) and 9 patients with diabetic nephropathy (33.3%). No significant difference existed in the proportion of preemptive KTRs between the two groups (p= 0.26), and the dialysis duration before LDKT also did not differ between the two groups (p=0.57). Furthermore, the use of immunosuppressants, including steroids, was not significantly different between the two groups.
Study workflow of the 204 consecutive patients who underwent kidney transplantation as a primary renal replacement therapy, 126 patients without fractures were compared with 27 patients with fractures. KT, Kidney transplantation; LDKT, living donor kidney transplantation.
Clinical characteristics of the kidney transplant recipients with and without fracture.
Patient survival and graft survival according to fractures. Patients with fractures had a significantly higher risk of mortality compared with those without fractures (p= 0.0018; Figure 2A), and patients with fractures tended to have a higher risk of cardiovascular mortality compared with those without fractures (p=0.052; Figure 2B). No significant difference in graft survival existed between patients with and without fractures (p=0.95; Figure 2C).
Patient survival, death-censored graft survival, and incidence of fractures. Compared to patients without fractures, patients with fractures had a significantly higher risk of mortality (A), had a higher risk of cardiovascular mortality (B), but no significant difference in death-censored graft survival was observed (C). Incidence probabilities of fractures were 4.6%, 8.6%, 12.3%, and 15.5% within 1, 2, 3 and 5 years, respectively (D). CVD, Cardiovascular disease; LDKT, living donor kidney transplantation.
Incidence of fractures. The incidence probabilities of fractures were 4.6% at 1 year, 8.6% at 2 years, 12.3% at 3 years, 13.8% at 4 years, and 15.5% at 5 years after LDKT (Figure 2D). The fracture risk increased almost linearly for 3 years after LDKT.
Association between bone metabolism-related serum biomarkers and fractures. The serum levels of several bone metabolism-related biomarkers were compared between patients with and without fractures. The levels of P, Ca, and ALP, which are generally measured as markers of CKD-MBD, did not differ between the two groups (Figure 3A-C). The serum level of iPTH, the upper center hormone regulating P and Ca levels, was significantly higher in the fracture group than in the no-fracture group (p<0.0001; Figure 3D). Serum Ca×P level was not significantly different between the two groups (Figure 3E). Similarly, serum levels of hydroxyproline, 1,25-dihydroxyvitamin D, and osteocalcin were not significantly different between the two groups (Figure 3F-H).
Comparison of bone metabolism-related serum biomarkers between patients with and without fractures. No significant differences in serum levels of phosphorus (A), calcium (B), and alkaline phosphatase (C) were observed between the two patient groups. The serum level of intact parathyroid hormone was significantly higher in patients with fractures than in those without fractures (D). No significant differences were observed between the two groups in the serum levels of calcium-phosphorus product (E), hydroxyproline (F), 1,25-dihydroxyvitamin D (G), and osteocalcin (H).
Association between nutritional markers and fractures. Figure 4 shows a comparison of the cumulative incidence of fracture between patients with good nutrition and those with malnutrition according to each nutritional marker. No significant difference in the cumulative incidence of fracture existed between patients with a BMI <25 kg/m2 and those with a BMI ≥25 kg/m2 (Figure 4A). Similarly, patients with malnutrition, assessed using the GNRI, PNI, CONUT, and NRI-JH, were not at a significantly higher risk of fracture compared with those with good nutrition (Figure 4B-E). In contrast, patients with malnutrition, assessed using the SI (SI <26.1), were at a significantly higher risk of fracture within 3 years after LDKT, than those with good nutrition (SI ≥26.1) (p=0.014; Figure 4F). In addition, assessments of inflammatory markers (C-reactive protein and neutrophil-lymphocyte ratio) revealed no significant differences in the incidence of fracture (Figure 5).
Comparison of the cumulative incidence of fracture according to each nutritional marker. No significant differences in the cumulative incidence of fracture in terms of body mass index (A), geriatric nutritional risk index (B), prognostic nutritional index (C), controlling nutritional status (D), and nutritional risk index for Japanese hemodialysis patients (E) were observed. A significant difference in the cumulative incidence of fracture existed between patients with a survival index <26.1 and those with a survival index ≥26.1 (F). BMI, Body mass index; CONUT, controlling nutritional status; GNRI, geriatric nutritional risk index; LDKT, living donor kidney transplantation; NRI-JH, nutritional risk index for Japanese hemodialysis patients; PNI, prognostic nutritional index; SI, survival index.
Comparison of the cumulative incidence of fracture according to each inflammatory marker. No significant differences were observed in the cumulative incidence of fracture based on serum C-reactive protein level (A) and neutrophil-lymphocyte ratio (B). CRP, C-reactive protein; LDKT, living donor kidney transplantation; NLR: neutrophil-lymphocyte ratio.
Exploration of related factors of fractures. A multivariable analysis was performed to explore factors related to fractures. As candidates, age, iPTH, and SI were selected due to their strong association with fractures in the univariable analysis. Cox regression logistic analysis revealed that serum iPTH level ≥180 pg/ml [hazard ratio (HR)=2.31; 95% confidence interval (CI)=1.01-5.32; p=0.047] and SI <26.1 (HR=2.45; 95% CI=1.15-5.206; p=0.025) were independent predictors for fracture (Table II).
Multivariable analysis for clinically significant fractures.
Discussion
The present study showed that bone metabolism-related serum biomarkers and nutritional markers were closely related to fractures after LDKT. A high preoperative serum level of iPTH was a representative bone metabolism-related serum marker; although there were only 10 patients who underwent previous parathyroidectomy, none of them had fractures after LDKT. These results might be because of the poor control or resistance to treatment of secondary hyperparathyroidism that caused disharmony of bone metabolism and resulted in fractures (18), and parathyroidectomy may be negatively correlated with the incidence of fractures. Furthermore, preoperative SI was a representative nutritional marker, and patients with an SI <26.1 had higher risk of clinically significant fractures within 3 years after LDKT, than patients with SI ≥26.1. Figure 6 presents a summary of this study. Screening and monitoring of CKD-MBD using serum iPTH level and SI and identifying KTRs at high risk of fracture are important to provide optimal interventions, such as treatment using bone-protective agents, parathyroidectomy, and nutritional education. Not only transplant doctors but also all medical personnel involved in transplantation, including nephrologists and dialysis practitioners, need to reaffirm the importance of preoperative management.
Summary of the present study. This study showed that bone metabolism-related serum biomarkers (especially intact parathyroid hormone) and nutritional markers (especially survival index) were closely related to fractures after LDKT. Kidney transplant recipients have various risk factors for fractures; therefore, screening and monitoring these risk factors are important, and identifying patients with a high risk of fracture leads to better management and improved patient outcomes after LDKT. Screening and monitoring should be initiated before LDKT in patients with advanced chronic kidney disease regardless of dialysis. Optimal interventions such as treatment using bone-protective agents, parathyroidectomy, and nutritional education should be provided to patients with a high risk of fracture after LDKT. CKD, Chronic kidney disease; iPTH, intact parathyroid hormone; LDKT, living donor kidney transplantation; MBD, mineral and bone disorder; SI, survival index; Vit D, vitamin D.
Bone metabolism gradually changes with CKD progression and dramatically changes after KT, owing to the rapid improvement in renal function. The changes in bone metabolism are induced by several bone metabolism-related biomarkers, such as P, Ca, iPTH, fibroblast growth factor 23, klotho a, and 1,25-dihydroxyvitamin D (19). Among the bone metabolism-related markers, serum iPTH level was an independent predictor for fractures. High serum levels of iPTH cause a decrease in cortical bone density, which increases the risk of fracture, and bone metabolism is accelerated after KT because of improved iPTH resistance. Resistance to inhibitory calcium-iPTH feedback occurs in 20%-30% of KTRs, leading to persistently high serum iPTH levels and an increased risk of fractures (known as tertiary hyperparathyroidism) (20-22). Therefore, the association between high serum iPTH levels and the risk of fracture is understandable. The optimal intervention before and after KT is important; however, whether oral cinacalcet or parathyroidectomy should be the first-line therapy remains unclear. A recent meta-analysis revealed that the effect of vitamin D treatment on fractures in KTRs remained uncertain and, on the contrary, vitamin D treatment did not reduce the risk of all-cause mortality (23). Further research is warranted to establish optimal interventions to prevent fractures in KTRs.
The mechanism of malnutrition in patients with ESRD correlates closely with proinflammatory cytokines such as interleukin-6 and tumor necrosis factor-α (24). Similarly, various pathophysiological mechanisms of cytokine-induced bone loss that can directly stimulate bone resorption and reduce bone formation, leading to bone loss and fractures, have been proposed (25). Although inflammatory markers such as C-reactive protein were not correlated with the incidence of fractures in this study, fracture risks may be predicted by investigating inflammatory cytokines upstream of C-reactive protein production. The detailed mechanisms are unclear; however, malnutrition, which is concomitant with microinflammation in most cases, causes bone fragility and sometimes results in fractures. A previous report from Japan suggested that the CONUT score was a significantly greater predictor of acute osteoporotic vertebral fractures in hospitalized elderly patients than the GNRI and PNI (26). In the present study, SI, which is composed of multiple elements, including age, BMI, serum P level, and cardiovascular events, was strongly correlated with the risk of fracture. Specifically, a SI <26.1 was an independent risk factor for fractures. Regardless of the reasons, attention should be paid to patients with a low SI to prevent fractures during the follow-up period, especially in the first 3 years after LDKT.
Reportedly, KTRs have a higher risk of fracture within 3 years after KT than the general population, and fractures are associated with a five-fold higher incidence rate of hospitalization, a 60% higher risk of mortality, and reduced quality of life (27, 28). Salter et al. also reported that hip, vertebral, and extremity fractures had 2.31-fold (95% CI=2.11-2.52), 2.8-fold (95% CI=2.44-3.21), and 1.85-fold (95% CI=1.64-2.10) higher risks of mortality, respectively. Similarly for graft survival, hip and extremity fractures were associated with 1.34-fold (95% CI=1.12-1.60) and 1.30-fold (95% CI=1.08-1.57) higher risks of graft loss, respectively, whereas vertebral fracture was not independently correlated with graft loss (29). In the present study, patients with fractures had a higher mortality risk than those without, whereas graft survival did not differ between patients with and without fractures. Considering the close relationship between declining renal function and increased fracture risk (6, 29), graft survival may be important in preventing fractures in KTRs, although the result of this study was different. Previous reports and the present study suggest that fractures resulted in decreased patient survival. Therefore, establishing easy and rapid strategies for screening and monitoring the risk of fracture and interventions, such as treatment using bone-protective agents and parathyroidectomy, seem essential in busy clinical practice.
Fracture prevention in KTRs is a major concern. Although various treatments have been considered, optimal and effective treatment strategies, including minimization of corticosteroid treatment and parathyroidectomy, are still debated (23, 30, 31). To improve patient outcomes after LDKT, various challenges should be addressed, and optimal medication, education, and rehabilitation may contribute to improved and personalized management that is different from immunological management.
Study limitations. First, the data were retrospectively obtained from a single institution, and the sample size was relatively small. Furthermore, the follow-up period was too short to adequately evaluate the prognosis. Parameters measured using DXA were not evaluated, and the associations between these parameters and bone metabolism-related serum biomarkers and nutritional markers were not clear. This was because the timing and intensity of the DXA were not constant. In addition, interventions such as treatment using calcimimetics and bisphosphonates were not evaluated because of the lack of data. Therefore, careful interpretation of the results is necessary. Evidence-based recommendations for appropriate decision-making and personalized management are essential to improve outcomes in KTRs, who have undergone LDKT.
Conclusion
The incidence probabilities of fractures were 4.6% at 1 year, 12.3% at 3 years, and 15.5% at 5 years after LDKT. Furthermore, bone metabolism- and nutritional- related serum biomarkers, especially iPTH, and SI, may predict clinically significant fractures in KTRs and should be considered before and during follow-up after LDKT. Optimal management may be possible in clinical practice by stratifying the risk of fracture according to these markers. Further investigations are needed to establish the optimal criteria for LDKT screening and monitoring. Knowledge of the potential benefits of assessing bone metabolism-related serum biomarkers and nutritional markers can improve patient outcomes after LDKT.
Acknowledgements
The Authors would like to thank all patients who participated in this study for their important contributions. We also would like to thank Editage (www.editage.com) for English language editing.
Footnotes
Authors’ Contributions
S.H, T.Y, and K.F contributed to the conception and design. S.H, M.T, K.I, K.O, Y.M, D.G, Y.N, M.M, and K.T contributed to the acquisition of patients’ data, analysis of data, and interpretation of data. S.H, M.T, N.T, and T.Y performed the treatment. All authors were involved in drafting the manuscript and revising it critically for important intellectual content and approved the version to be published. All Authors have participated sufficiently in this work to take public responsibility for appropriate portions of the content.
Conflicts of Interest
The Authors have declared that no conflicts of interest exist.
Funding
No funding was obtained for the present study.
Availability of Data and Material
The datasets generated and/or analyzed during the current study are not publicly available due to our hospital policy but are available from the corresponding author upon reasonable request.
- Received December 11, 2024.
- Revision received March 5, 2025.
- Accepted March 11, 2025.
- Copyright © 2025 The Author(s). Published by the International Institute of Anticancer Research.
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY-NC-ND) 4.0 international license (https://creativecommons.org/licenses/by-nc-nd/4.0).
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