Реальный риск перелома, состояние остеопороза и смертность японских пациентов с хроническими почечными заболеваниями G3-5.

Introduction

Globally, over 800 million people are affected by chronic kidney disease (CKD), with end-stage kidney disease having increased mortality rates [ 1 , 2 ]. In Japan, the prevalence of CKD was estimated at about 13% of the adult population (13.3 million people) in 2005 [ 3 ], with a more recent study reporting that CKD prevalence was significantly higher in 2017 [ 4 ].

CKD is a lifestyle-related disease [ 5 ] and is considered a risk factor for stroke, cardiovascular disease, and hospitalization [ 2 , 6 , 7 ]. CKD also increases risk of fracture by four to six times that of age- and sex-matched controls without CKD [ 8 – 10 ]. Furthermore, patients with previous fractures have double the incidence of subsequent fractures, hampering the quality of life of patients and increasing mortality [ 11 ].

The effects of some pharmacotherapies on fractures in Japanese patients with CKD have been reported [ 12 , 13 ], and several cross-sectional studies have reported a 1.3–7.1-fold increased risk of femoral and vertebral fractures in non-Japanese patients with renal impairment with an estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m 2 [ 14 – 18 ]. However, only one Japanese study has investigated the risk of new fracture onset in patients with CKD stages G3–5 (eGFR < 60 mL/min/1.73 m 2 ), and this only included patients undergoing hemodialysis [ 12 ]. This has resulted in an evidence gap for Japanese patients with broader ranges of renal function (i.e., CKD stages G3–5). Therefore, it is important to assess epidemiological information on fracture risk and to detail the evidence of fractures occurring in CKD to understand the current status of medical care in Japanese patients with CKD.

The present study aimed to evaluate the risk of fracture and mortality, and the frequencies of osteoporosis treatments, in Japanese patients with CKD stages G3–5 in a real-world setting using a large-scale clinical database.

Materials and methods

Study design

This retrospective cohort study used data from anonymized electronic health insurance claims and diagnostic procedure combinations, linking routinely collected information for each patient, covering age, sex, height, weight, diagnosis based on International Classification of Diseases 10th Revision (ICD-10 codes), medical procedures, prescription medications, and survival status, spanning both outpatient and inpatient medical care held by Medical Data Vision (MDV; Tokyo, Japan) from 1 April 2008 to 30 April 2023. The MDV database comprises data from over 400 acute care hospitals, registering information for approximately 46 million patients, representing approximately 23% of all insurance claims in Japan [ 19 ]. So far, the MDV database has been used for several studies of CKD [ 20 – 22 ].

This study was conducted per the principles of the Declaration of Helsinki (as revised in 2013). The study was approved by Medical Corporation TOUKEIKAI Kitamachi Clinic Ethical Review Board (24 May 2023) and was registered (15 July 2023) in the University Hospital Medical Information Network (UMIN) Clinical Trials Registry under the identifier UMIN000051620. Informed consent was not obtained because the patient data are anonymized.

Definition of CKD

CKD was defined according to the following: the patient (1) had at least two eGFR assessments < 60 mL/min/1.73 m 2 at least 3 months apart; (2) had a diagnosis of CKD-related medical conditions (ICD-10 codes: N01–06, 11, 18, 26–28, Q60, 61) before the index date; and (3) aged ≥ 18 years at the time of the first eGFR measurement where the eGFR was < 60 mL/min/1.73 m 2 . The index date was defined as the time of the second eGFR measurement.

Patients with CKD who met any of the following criteria before the index date were excluded from this study: (1) received a definite diagnosis of cancer; (2) received a kidney transplant or renal dialysis; (3) had a diseases related to decreased bone density or was prescribed osteoporosis medication; (4) had a definite diagnosis of a fracture; and (5) had blood drawn in a specific department (such as an Emergency Room or Intensive Care Unit) on the index date.

Selection of matched controls

For each patient with CKD, one control patient without CKD was selected when he/she met the following criteria as assessed at the index date of the intended CKD patient to be matched: (1) had at least one eGFR measurement ≥ 60 mL/min/1.73 m 2 (the first measurement); (2) had at least one eGFR measurement ≥ 60 mL/min/1.73 m 2 during a period from 3 months to 1 year after the first measurement of eGFR [ 23 ]; (3) was not identified as having CKD related diseases before the date of first measurement; (4) did not meet the above mentioned set of exclusion criteria as the CKD group; and (5) had the same age and sex as the CKD patient to be matched.

If the candidate control met the exclusion criteria, then matching was ceased, and a search was performed for a new candidate control for the CKD patient.

Follow-up

Patients were censored at the earliest time when any of the following events whichever came first after the index date: (1) reached at the last observed day before no visit for > 3 years, or (2) reached at the final month of data provision to the MDV.

Study outcomes

The primary endpoint was the incidence of fractures after the index date. The ICD-10 codes used as diagnosis of fractures are provided in Supplementary Table 1 . The secondary endpoints included bone mineral density (BMD) measurements after the index date; osteoporosis and bone metabolism-related drug prescriptions after the index date; the incidence of all-cause mortality after the index date. Table 1 Patient characteristics CKD ( n = 38,299) Control ( n = 38,299) SMD Missing n (%) Sex Male 25,671 (67.0) 25,671 (67.0) < 0.001 0 (0.0) Age (years) Mean ± SD 72.3 ± 12.7 72.3 ± 12.7 < 0.001 0 (0.0) Median (Q1–Q3) 74 (65–82) 74 (65–82) < 65 8,998 (23.5) 8,998 (23.5) < 0.001 ≥ 65 29,301 (76.5) 29,301 (76.5) Age group (years) 10 s 12 (0.0) 12 (0.0) < 0.001 0 (0.0) 20 s 104 (0.3) 104 (0.3) 30 s 517 (1.3) 517 (1.3) 40 s 1,777 (4.6) 1,777 (4.6) 50 s 3,557 (9.3) 3,557 (9.3) 60 s 7,464 (19.5) 7,464 (19.5) 70 s 12,435 (32.5) 12,435 (32.5) 80 s 10,651 (27.8) 10,651 (27.8) 90 s 1,757 (4.6) 1,757 (4.6) ≥ 100 25 (0.1) 25 (0.1) eGFR(mL/min/1.73 m 2 ) Mean ± SD 33.8 ± 14.4 80.1 ± 19.4 2.708 0 (0.0) Median (Q1–Q3) 34.4 (22.4–45.7) 75.4 (68.0–86.1) HbA1c (%) Mean ± SD 6.3 ± 1.0 6.4 ± 1.1 0.164 22,258 (29.1) Median (Q1–Q3) 6.0 (5.6–6.6) 6.2 (5.7–6.9) Alkaline phosphatase (U/L) Mean ± SD 89.3 ± 41.8 88.8 ± 45.0 0.012 12,596 (16.4) Median (Q1–Q3) 82 (66–102) 81 (66–100) Hospital scale (number of beds) ≤ 199 3,695 (9.6) 4,693 (12.3) 0.140 0 (0.0) 200 to < 499 21,583 (56.4) 22,871 (59.7) ≥ 500 13,021 (34.0) 10,735 (28.0) Complications Hypertension 26,973 (70.4) 19,061 (49.8) 0.432 0 (0.0) Dyslipidemia 16,919 (44.2) 14,705 (38.4) 0.118 0 (0.0) Hyperuricemia 13,356 (34.9) 2,886 (7.5) 0.710 0 (0.0) Diabetes 16,739 (43.7) 15,975 (41.7) 0.040 0 (0.0) Alcoholism 61 (0.2) 129 (0.3) 0.036 0 (0.0) Rheumatoid arthritis 875 (2.3) 1,721 (4.5) 0.122 0 (0.0) Dementia 1,565 (4.1) 2,525 (6.6) 0.112 0 (0.0) Sleeping disorder 6,365 (16.6) 6,418 (16.8) 0.004 0 (0.0) COPD 1,236 (3.2) 1,710 (4.5) 0.064 0 (0.0) Drugs Glucocorticoid 1,567 (4.1) 2,106 (5.5) 0.066 0 (0.0) Proton pump inhibitor 12,815 (33.5) 12,361 (32.3) 0.025 0 (0.0) Hormonal therapy 67 (0.2) 65 (0.2) 0.001 0 (0.0) Thiazoline 611 (1.6) 1,054 (2.8) 0.079 0 (0.0) Beta-blocker 9,408 (24.6) 5,429 (14.2) 0.265 0 (0.0) Loop diuretics 11,207 (29.3) 3,555 (9.3) 0.524 0 (0.0) Heparin 5,634 (14.7) 4,273 (11.2) 0.106 0 (0.0) Warfarin 2,884 (7.5) 1,605 (4.2) 0.143 0 (0.0) Anti-anxiety drugs 7,683 (20.1) 7,780 (20.3) 0.006 0 (0.0) Anticonvulsants 881 (2.3) 1,587 (4.1) 0.105 0 (0.0) SSRI 257 (0.7) 317 (0.8) 0.018 0 (0.0) Methotrexate 100 (0.3) 876 (2.3) 0.181 0 (0.0) Calcimimetics 13 (0.0) 0 (0.0) 0.026 0 (0.0) Phosphate binder 294 (0.8) 4 (0.0) 0.122 0 (0.0) Data are n (%), mean ± SD or median (Q1–Q3) CKD Chronic kidney disease, COPD Chronic obstructive pulmonary disease, eGFR estimated glomerular filtration rate, HbA1c glycosylated Hemoglobin, Q Quartile, SD Standard deviation, SMD Standardized mean difference, SSRI Selective serotonin reuptake inhibitor

Statistical analysis

Because the study used an existing database, the sample size was not pre-specified. To describe patients’ characteristics at index date, frequencies and proportions were used for categorical variables; and mean and standard deviation (SD) and median and interquartile range were used for continuous variables. Standardized mean differences were used to assess differences between the CKD and the control groups.

The incidences of a fracture in the CKD and control groups were compared using Fine–Gray method where death was handled as a competing risk [ 24 ]. The covariates were added to each multivariable regression model to control for potential confounders. The covariates include age at the index date, sex, number of creatinine measurements in the year before the index date, comorbidities and prescribed medications. The list of comorbidities is provided in the Supplementary Text.

For assessing the effect of CKD over a wide age range, we test the hypothesis that the effect of CKD was null at any given level of age, the multivariable regression models included a cross-product term between CKD and age variables. Wald tests were conducted assessing difference between the full model including the cross-product terms and all covariates and the model excluding CKD main effect and the cross-product terms from the full model. In the multivariable analyses, non-linear effect of covariates of continuous variables were assessed using the cubic-spline method.

For the outcome of death, the Cox proportional hazards model adjusting for the above-described covariates was used to calculate the hazard ratio (HR) for death in the CKD group vs the control group. Effect modification (i.e., whether the effect of CKD on the risk of hip fracture was modified by levels of a covariate) was assessed using an interaction analysis where a cross-product term between the CKD group and a binary variable indicating a sub-group of patients was added to the above multivariable regression analyses. Forest plots were used to graphically depict the effect modifications.

The two-sided 5% significance level was used for all statistical inferences. No adjustment was made for multiple comparisons of P -values. All statistical analyses were conducted using R version 4.3.1 (The R Foundation for Statistical Computing, Vienna, Austria).

Results

Study population

For each of the CKD and control groups, 38,299 individuals were identified and used in the analysis.

Patient characteristics at the index date are shown in Table 1 . In common with both groups, a mean ± SD age was 72.3 ± 12.7 years, 76.5% of patients were aged ≥ 65 years, and 67.0% of patients were male. The most common complications were hypertension, diabetes, and dyslipidemia, and the common concomitant medications were proton pump inhibitors, anti-anxiety drugs, beta-blockers, and loop diuretics.

The mean ± SD eGFR was 33.8 ± 14.4 mL/min/1.73 m 2 in the CKD group and 80.1 ± 19.4 mL/min/1.73 m 2 in the control group. The CKD group had a higher complication rate than the control group in hypertension (70.4% and 49.8%) and hyperuricemia (34.9% and 7.5%), and more received beta-blockers (24.6% and 14.2%) and loop diuretics (29.3% and 9.3%).

Incidence of fractures

The incidence of all fractures in the CKD and control groups was not significantly different (5.7% vs 5.8%; HR 1.022 [95% CI 0.952–1.098], P = 0.542; Table 2 , Fig. 1 a). Table 2 Incidence of fracture n Overall Hip Overall 76,598 4,402 (5.7) 1,132 (1.5) Group Control 38,299 2,206 (5.8) 480 (1.3) CKD 38,299 2,196 (5.7) 652 (1.7) CKD stage G3a 10,111 386 (3.8) 77 (0.8) G3b 12,763 688 (5.4) 183 (1.4) G4–5 15,425 1,122 (7.3) 392 (2.5) Age group (years) 10 s 24 0 (0.0) 0 (0.0) 20 s 208 1 (0.5) 0 (0.0) 30 s 1,034 17 (1.6) 0 (0.0) 40 s 3,554 91 (2.6) 8 (0.2) 50 s 7,114 207 (2.9) 26 (0.4) 60 s 14,928 617 (4.1) 131 (0.9) 70 s 24,870 1,469 (5.9) 322 (1.3) 80 s 21,302 1,723 (8.1) 533 (2.5) 90 s 3,514 275 (7.8) 112 (3.2) ≥ 100 50 2 (4.0) 0 (0.0) Sex Male 51,342 2,251 (4.4) 509 (1.0) Female 25,256 2,251 (8.5) 623 (2.5) Complications Hypertension 46,034 2,842 (6.2) 742 (1.6) Dyslipidemia 31,624 1,788 (5.7) 425 (1.3) Hyperuricemia 16,242 852 (5.2) 223 (1.4) Diabetes 32,714 1,899 (5.8) 488 (1.5) Alcoholism 190 10 (5.3) 1 (0.5) Rheumatoid arthritis 2,596 190 (7.3) 41 (1.6) Dementia 4,090 342 (8.4) 130 (3.2) Sleeping disorder 12,783 1,006 (7.9) 255 (2.0) COPD 2,946 194 (6.6) 41 (1.4) Drugs Glucocorticoid 3,673 275 (7.5) 58 (1.6) Proton pump inhibitor 25,176 1,633 (6.5) 437 (1.7) Hormonal therapy 132 8 (6.1) 5 (3.8) Thiazoline 1,665 138 (8.3) 26 (1.6) Beta-blocker 14,837 785 (5.3) 227 (1.5) Loop diuretics 14,762 1,149 (7.8) 361 (2.4) Heparin 9,907 517 (5.2) 138 (1.4) Warfarin 4,489 391 (8.7) 112 (2.5) Anti-anxiety drugs 15,463 1,268 (8.2) 344 (2.2) Anticonvulsants 2,468 189 (7.7) 63 (2.6) SSRI 574 48 (8.4) 15 (2.6) Methotrexate 976 60 (6.1) 9 (0.9) Calcimimetics 13 0 (0.0) 0 (0.0) Phosphate binder 298 18 (6.0) 2 (0.7) Data are n (%) CKD chronic kidney disease, COPD chronic obstructive pulmonary disease, SSRI selective serotonin reuptake inhibitor Fig. 1 Incidences of a all fracture and b hip fracture after the index date. CI Confidence interval, CKD Chronic kidney disease, HR Hazard ratio calculated using the Fine–Gray model

Compared with the control group, the CKD group had a higher risk of hip fracture (incidence, 1.7% vs 1.3%; HR 1.415 [95% CI 1.234–1.622], P < 0.001; Table 2 , Fig. 1 b). However, the risk of vertebral fractures and non-vertebral fractures did not significantly differ between the groups (1.9% vs 2.1%; HR 0.962 [95% CI 0.854–1.083], P = 0.520; 4.0% vs 3.9%; HR 1.057 [95% CI 0.973–1.148], P = 0.188; Supplementary Table 2 , Supplementary Figs. 1 and 2).

Modification of effect of CKD vs control in the risk of hip fracture by age, sex, and eGFR

Multivariable regression analysis for hip fracture risk showed that the CKD group had a higher risk of hip fracture at age levels ≤ 80 years (all P < 0.001); 40 years, HR 9.306 [95% CI 3.735–23.187]; 50 years, 5.655 [95% CI 2.944–10.864]; 60 years, 3.437 [95% CI 2.299–5.137]; 70 years, 2.089 [95% CI 1.712–2.548]; and 80 years, 1.330 [95% CI 1.122–1.577]. For patients aged 90 years, the effect was not statistically significant (HR 1.003 [95% CI 0.775–1.300]) (Fig. 2 a). Similar tendencies, except for in males aged 80 years, were observed in both the male and female populations (Fig. 2 b and c). Fig. 2 Multivariable regression analysis of hip fracture risk using age as covariate in a overall, b male, and c female populations. P for group < 0.05 rejects the null hypothesis indicating the HR of an event by CKD group = 1.0 for all age levels. * indicates a significant difference between the CKD and control groups. CI Confidence interval, CKD Chronic kidney disease, HR Hazard ratio calculated using the Fine–Gray model

Figure 3 shows the risk of hip fracture by CKD stages at age levels in overall, male, and female populations. The difference in hip fracture risk between CKD stage G4–5 patients and controls was notable in younger patients, with CKD stages G4–5 patients in the 40, 50, 60, 70, and 80 year groups having significantly higher risks of hip fracture than controls (Fig. 3 a). However, in the populations aged ≥ 90 years, the risk of hip fracture was similar between patients with CKD stages G4–5 and controls. Similar trends were observed irrespective of sex (Fig. 3 b and c). Fig. 3 Multivariable regression analysis of hip fracture risk using age as covariate in a overall, b male, and c female populations in controls and patients with stage G3a, G3b, and G4–5 CKD. The HR was calculated for each age with controls as reference. P for CKD stage < 0.05 rejects the null hypothesis indicating the HR of an event by CKD stage = 1.0 for all age levels. CI Confidence interval, CKD Chronic kidney disease, HR Hazard ratio calculated using the Fine–Gray model

Incidences of hip fractures in the CKD vs control groups within each subgroup of patients are shown in Supplementary Fig. 3. Statistically significantly associated effect modifiers were older age (≥ 80 years vs < 80 years), dementia, and the use of anti-anxiety drugs or phosphate binders ( P values for interaction < 0.05).

An increased risk of hip fracture with decreasing eGFR was also observed ( P < 0.001) (Supplementary Fig. 4).

Bone mineral density measurements, prescription osteoporosis medications and mortality

The BMD measurements rates after the index date were 5.3% and 4.4% in CKD and control groups, respectively (Table 3 ). Table 3 Bone mineral density measurements and prescriptions for osteoporosis and bone metabolism-related drugs after the index date by CKD stage Control CKD ( n = 38,299) G3–5 ( n = 38,299) G3a ( n = 10,111) G3b ( n = 12,763) G4–5 ( n = 15,425) Bone mineral density measurements 1,699 (4.4) 2,020 (5.3) 431 (4.3) 542 (4.2) 1,047 (6.8) Osteoporosis and bone metabolism-related drugs 1,697 (4.4) 3,821 (10.0) 477 (4.7) 833 (6.5) 2,511 (16.3) SERMs 70 (0.2) 99 (0.3) 24 (0.2) 24 (0.2) 51 (0.3) Bazedoxifene acetate 29 (0.1) 50 (0.1) 14 (0.1) 9 (0.1) 27 (0.2) Raloxifene hydrochloride 44 (0.1) 60 (0.2) 11 (0.1) 15 (0.1) 34 (0.2) Ipriflavone 1 (0.0) 2 (0.0) 0 (0.0) 1 (0.0) 1 (0.0) Calcium drugs 75 (0.2) 89 (0.2) 13 (0.1) 28 (0.2) 48 (0.3) Calcium hydrogen phosphate hydrate 1 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) Calcium L-aspartate hydrate 74 (0.2) 89 (0.2) 13 (0.1) 28 (0.2) 48 (0.3) Calcitonin drugs 52 (0.1) 86 (0.2) 13 (0.1) 23 (0.2) 50 (0.3) Elkatonin 52 (0.1) 86 (0.2) 13 (0.1) 23 (0.2) 50 (0.3) Calcitonin (salmon) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) Bisphosphonates 910 (2.4) 843 (2.2) 247 (2.4) 295 (2.3) 301 (2.0) Alendronate (P.O.) 516 (1.3) 558 (1.5) 173 (1.7) 211 (1.7) 174 (1.1) Ibandronate (P.O.) 33 (0.1) 27 (0.1) 8 (0.1) 13 (0.1) 6 (0.0) Etidronate (P.O.) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) Minodronic acid (P.O.) 182 (0.5) 151 (0.4) 45 (0.4) 52 (0.4) 54 (0.4) Risedronate (P.O.) 209 (0.5) 111 (0.3) 37 (0.4) 39 (0.3) 35 (0.2) Alendronate (I.V.) 11 (0.0) 17 (0.0) 5 (0.0) 4 (0.0) 8 (0.1) Ibandronate (I.V.) 30 (0.1) 55 (0.1) 5 (0.0) 12 (0.1) 38 (0.2) Zoledronate (I.V.) 17 (0.0) 5 (0.0) 4 (0.0) 1 (0.0) 0 (0.0) Vitamin K 2 drugs (menatetrenone) 34 (0.1) 65 (0.2) 11 (0.1) 16 (0.1) 38 (0.2) Parathyroid hormone drugs 145 (0.4) 97 (0.3) 18 (0.2) 34 (0.3) 45 (0.3) Abaloparatide acetate 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) Teriparatide acetate 74 (0.2) 49 (0.1) 7 (0.1) 16 (0.1) 26 (0.2) Teriparatide (genetical recombination) 74 (0.2) 48 (0.1) 11 (0.1) 18 (0.1) 19 (0.1) Female hormone drugs 62 (0.2) 38 (0.1) 13 (0.1) 15 (0.1) 10 (0.1) Estradiol 2 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) Estriol 60 (0.2) 38 (0.1) 13 (0.1) 15 (0.1) 10 (0.1) Anti-RANKL antibodies (denosumab) 154 (0.4) 123 (0.3) 26 (0.3) 52 (0.4) 45 (0.3) Anti-sclerostin antibody drugs (romosozumab) 48 (0.1) 20 (0.1) 4 (0.0) 7 (0.1) 9 (0.1) Active vitamin D 3 drugs 886 (2.3) 3,001 (7.8) 225 (2.2) 556 (4.4) 2,220 (14.4) Alfacalcidol 411 (1.1) 2,410 (6.3) 145 (1.4) 411 (3.2) 1,854 (12.0) Eldecalcitol 536 (1.4) 402 (1.0) 91 (0.9) 143 (1.1) 168 (1.1) Calcitriol 14 (0.0) 453 (1.2) 10 (0.1) 52 (0.4) 391 (2.5) Data are n (%) CKD chronic kidney disease, I.V. intravenous administration, P.O. oral administration, RANKL receptor activator of nuclear factor-kappa B ligand, SERMs selective estrogen receptor

Prescription osteoporosis medication status after the index date according to CKD stage and other characteristics are summarized in Table 3 . Overall, prescription rates for osteoporosis medications were 10.0% and 4.4% in CKD and control groups, respectively. Regarding bisphosphonate, the use of oral alendronate decreased with increasing CKD stage. For active vitamin D 3 preparations, the use of alfacalcidol and calcitriol increased with increasing CKD stage. For other medications, no differences by CKD stage existed.

The incidence of all-cause mortality was higher in the CKD group vs the control group: HR 1.413 [95% CI 1.330–1.501, P < 0.001 (Fig. 4 ). Fig. 4 Incidence of all-cause mortality after the index date CI confidence interval, CKD chronic kidney disease, HR hazard ratio calculated using the Cox proportional hazards model

Discussion

To the best of our knowledge, this retrospective database study is the first of its kind to investigate fracture risk, osteoporosis treatment status, and mortality in Japanese patients with CKD stages G3–5 (eGFR < 60 mL/min/1.73 m 2 ) compared with control patients (eGFR ≥ 60 mL/min/1.73 m 2 ). A previous Japanese study on fracture risk included only patients undergoing hemodialysis [ 12 ]. The present study addressed this evidence gap by identifying fracture risk for patients with a wide range of renal dysfunction (CKD stages G3–5).

This study found that the risk of all fractures was similar between the CKD and control groups, but hip fracture risk was significantly higher in the CKD group (1.415-fold increase). The increased hip fracture risk was more notable in patients ≤ 80 years old. Despite this increased hip fracture risk, most patients did not receive BMD measurements and osteoporosis medications. Additionally, the mortality risk was higher (1.413-fold increase) in the CKD group compared with the control group.

In the present study, the CKD group had a fracture risk of HR 1.022 (95% CI 0.952–1.098) for all fractures, HR 1.415 (95% CI 1.234–1.622) for hip fractures, HR 0.962 (95% CI 0.854–1.083) for vertebral fractures, and HR 1.057 (95% CI 0.973–1.148) for non-vertebral fractures. Hip fractures are expected to increase in CKD because the cortical bone deterioration increases due to cortical porosity partly caused by secondary hyperparathyroidism of uremia. [ 25 ]. Vertebral fractures are generally more common than other types of fractures, but were not significantly increased in the CKD group in this study. In addition, there were also no significant differences in the incidences of non-vertebral fractures, including hip fractures, between the groups in this study. Thus, it is likely that this was not a significant contributor to the total number of fractures. These results are similar to those of previous non-Japanese studies that found that hip fracture risk increased in patients with eGFR < 60 mL/min/1.73 m 2 [ 15 , 16 , 18 , 26 , 27 ].

There are limited number of previous Japanese studies that can be compared with our study, however, our results were generally consistent with a study of patients with prior osteoporotic fracture, in which CKD grade 4/5 was associated with 1-year subsequent fracture risk (HR 1.30 [1.16–1.46]) [ 28 ]. Conversely, the fracture incidence observed in the present study was lower than in a previous Japanese study that included patients on hemodialysis (CKD stage G5D) [ 12 ]. In that study, the standardized incidence ratios of hip fractures were compared between hemodialysis patients vs the general population, with overall incidence and standardized incidence ratios of 7.57/1000 person-years and 6.2 [95% CI 5.7–6.8] in male patients and 17.43/1000 person-years and 4.9 [95% CI 4.6–5.3] in female patients, respectively [ 12 ]. Excluding patients with a history of kidney transplant, renal dialysis, decreased bone density, or osteoporosis medication prescriptions in our study may have resulted in a lower fracture incidence.

In this study, hip fracture risk increased with age regardless of CKD status and renal function. In addition, younger female patients had increased hip fracture risk in the CKD group vs the control group and this difference became notable with younger age, while the risk was similar between older (≥ 90 years) patients with and without CKD. This suggests that CKD may have a greater impact on hip fracture risk in younger patients, but in older populations the impact of factors other than CKD, such as patient age, may become more important. This finding is generally consistent with a previous study [ 16 ] that found that female patients with an eGFR ≤ 60 mL/min/1.73 m 2 , especially those with eGFR < 45 mL/min/1.73 m 2 had higher risk of hip fracture (HR 2.32) than those with eGFR 45–59 mL/min/1.73 m 2 (HR 1.57, P for trend = 0.02).

In this study, most patients did not undergo BMD measurements (CKD patients: 5.3%, controls: 4.4%) or receive osteoporosis medication (CKD patients: 10.0%, controls: 4.4%). According to the Japanese 2015 guidelines for prevention and treatment of osteoporosis [ 29 ], if an osteopenic patient with “no fragility fracture and BMD greater than 70% and less than 80% in young adult mean [YAM] value” has CKD (eGFR < 60 mL/min/1.73 m 2 ), the initiation of pharmacological treatment for fracture risk should be considered. However, the timing of BMD measurement in patients with CKD is not mentioned in this guideline and is dependent on the judgment of the physician in clinical practice. Therefore, the results of this study may reflect the status of the guideline.

Although the populations were different, the BMD measurement rate in this study was similar to the osteoporosis screening (interview + bone mass measurement) rate of 5.3% reported in 2021 by the Japan Osteoporosis Foundation [ 30 , 31 ]. The osteoporosis screening rate is calculated by dividing the number of persons aged 40, 45, 50, 55, 60, 65, and 70 years who underwent osteoporosis screening by the total Japanese female population in the same age categories. Conversely, the target osteoporosis screening rate set in 2032 in the Japanese Government’s Health Japan 21 guideline (the third stage, basic policy, and health promotion plan based on the Health Promotion Law of Japan) [ 32 ] is set at 15%, which is much higher than the BMD measurement rate observed in our study.

Japanese CKD practice guidelines [ 33 ] specify the use of osteoporosis medications for CKD patients already diagnosed with osteoporosis, but do not include a treatment policy for the prevention of osteoporosis onset associated with reduced renal function. Therefore, the rate of BMD measurements and osteoporosis treatment in CKD patients may be lower than is ideal. The Glucocorticoid-Induced Osteoporosis (GIOP) Practice Guidelines (2014) [ 34 ] recommend BMD measurements and the administration of osteoporosis medications for patients taking glucocorticoids, considering the risk of osteoporosis-related fractures. Before this 2014 guideline revision, the rate of bone densitometry in GIOP patients was 5.5% in 2011, slightly increasing to 6.6% in 2018, while the rate of osteoporosis medication prescriptions increased even more, from 40.0% to 51.8% at the same time points. These increases may be due to a change in the recommended requirement for starting GIOP treatment of bone density measurement in 2004 [ 35 ] to a scoring system in the 2014 GIOP guidelines. It is hoped that studies such as this one will increase awareness of the risks of fractures in CKD patients due to osteoporosis and that, in future, osteoporosis screening and treatment rates will increase in this patient population.

The risk of hip fracture in the CKD group was higher than in the control group in the present study, and if a hip fracture actually occurred, it would significantly reduce the quality of life of patients [ 11 ]. Therefore, patients with CKD stages G3–5 require more frequent or regular BMD measurements to start appropriate pharmacological treatment and prevent fractures. It should be noted that active vitamin D 3 drugs, which had the highest prescription rate in our study, may have been used to prevent hypocalcemia and/or secondary hyperparathyroidism due to reduced renal function, rather than as a treatment for osteoporosis. In fact, the proportion of patients receiving such prescriptions increased in proportion to the progression of CKD stage. Therefore, the actual rate of prescription for the treatment of osteoporosis in this patient population may be even lower.

This study had some limitations and inherent risk of bias due to the data source and study design. The period for which pre-existing fractures were identifiable was limited to the period of data extraction. Fractures that occurred at other medical institutions were not able to be tracked. Thus, there is no information on treatment and prescription history prior to the visit, or visits to other hospitals, even during the follow-up period. The MDV database mainly comprises of data from relatively large acute care hospitals. The patients in this study were limited to those who attended acute care hospitals and had laboratory values recorded, which may have potential bias for patient selection, and the findings may not be generalizable because of the database composition. The control group was also enrolled from patients visiting the hospital, and thus was not representative of a healthy population. Another limitation of our study is that we did not assess parathyroid hormone values. The use of drugs such as teriparatide and abaloparatide may affect parathyroid hormone levels, persistently high levels of which promote bone resorption and affect fracture risk [ 36 , 37 ]. Future analyses should include parathyroid hormone values to assess their influence on fracture events.

Conclusions

This study fills an evidence gap by identifying fracture risk for Japanese patients with wide ranges of renal dysfunction by CKD stage. The incidence of all fractures was not higher in patients with CKD than those without, but the risk of hip fracture was higher in patients with CKD. In addition, most patients with CKD did not receive osteoporosis treatment or undergo BMD measurements. Hip fractures tend to confine patients to bed and may lead to disuse syndrome, which requires additional care. Therefore, more appropriate management of fracture risk in CKD patients is considered to be a future priority in CKD care.

Supplementary Information

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Acknowledgements

The authors would like to express their deepest appreciation to Dr. Hirotaka Komaba (Tokai University School of Medicine, Isehara, Japan) and Dr. Masatomo Taniguchi (Fukuoka Renal Clinic, Fukuoka, Japan) for their advice on this study and manuscript from a specialization perspective. The authors also wish to thank Keyra Martinez Dunn, MD, of Edanz for providing medical writing support, which was supported by Daiichi Sankyo Co., Ltd., in accordance with Good Publication Practice (GPP) 2022 guidelines ( https://www.ismpp.org/gpp-2022 ). Artificial intelligence software was used to translate language during the preparation of this manuscript, but was not used for manuscript writing.

Author contributions

YI contributed to the conception, study design, interpretation of data for this study. ST, HY, RK, AS contributed to the study design, and the interpretation, acquisition, and formal analysis of data. SK, TI and NO contributed to the study design, interpretation of data, and planning of data analysis. All authors contributed to writing and reviewing the manuscript, and approved the manuscript to be published.

Funding

Daiichi Sankyo Co., Ltd., provided the funding for this study.

Data availability

The deidentifed participant data and the study protocol will be shared on a request basis for up to 36 months after the publication of this article. Researchers who make the request should include a methodologically sound proposal on how the data will be used; the proposal may be reviewed by the responsible personnel at Daiichi Sankyo Co., Ltd., and the data requestors will need to sign a data access agreement. Please directly contact the corresponding author to request data sharing.

Declarations

Conflict of interest statement

Employment: S. Kodama, T. Ito, and N. Okubo (Daiichi Sankyo Co., Ltd.), Consultancies: S. Taniuchi, H. Yoshida, and R. Kawai (Chugai Pharmaceutical Co., Ltd., Daiichi Sankyo Co., Ltd., and Kyowa Kirin Co., Ltd.); H. Yoshida (Kyowa Kirin Co., Ltd.); A. Shintani and/or her institution (Chugai Pharmaceutical Co., Ltd., Daiichi Sankyo Co., Ltd., Kyowa Kirin Co., Ltd., Takeda Pharmaceutical Co., Ltd., Shionogi & Co., Ltd., and Mallinckrodt Pharma K.K.), Honoraria: Y. Imanishi (Daiichi Sankyo Co., Ltd., Teijin Healthcare Ltd., Kyowa Kirin Co., Ltd., and Asahi Kasei Pharma Corporation); A. Shintani (AbbVie G.K., Asahi Kasei Pharma Corporation, AstraZeneca K.K., Astellas Pharma Inc., Bayer Yakuhin, Ltd., Bristol-Myers Squibb K.K., Chugai Pharmaceutical Co., Ltd., Daiichi Sankyo Co., Ltd., Eisai Co., Ltd., Janssen Pharmaceutical K.K., Kissei Pharmaceutical Co., Ltd., Kyowa Kirin Co., Ltd., Mallinckrodt Pharma K.K., Merck Biopharma Co., Ltd., Maruho Co., Ltd., Mitsubishi Tanabe Pharma Corporation, Nipro Corporation, Novo Nordisk Pharma Ltd., Nippon Shinyaku Co., Ltd., Ono Pharmaceutical Co., Ltd., Pfizer Japan Inc., Takeda Pharmaceutical Co., Ltd., Taisho Pharmaceutical Co., Ltd., Torii Pharmaceutical Co., Ltd., Sanofi K.K., Nippon Kayaku Co., Ltd., JCR Pharmaceuticals Co., Ltd., and MSD K.K.), Stock ownership or options: None reported, Grants received: Y. Imanishi, S. Taniuchi, H. Yoshida, R. Kawai, A. Shintani (Daiichi Sankyo Co., Ltd.); H. Yoshida (Organization for Clinical Medicine Promotion).

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee at which the studies were conducted (Medical Corporation TOUKEIKAI Kitamachi Clinic Ethical Review Board, approved 24 May 2023) and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was not obtained for this study because patient data were anonymized.

References

1. Kovesdy CP Epidemiology of chronic kidney disease: an update 2022 Kidney Int Suppl 2011 2022 12 7 11 10.1016/j.kisu.2021.11.003 PMC9073222 35529086 Kovesdy CP. Epidemiology of chronic kidney disease: an update 2022. Kidney Int Suppl. 2011;2022(12):7–11. 10.1016/j.kisu.2021.11.003 PMC9073222 35529086

2. Go AS Chertow GM Fan D Chronic kidney disease and the risks of death, cardiovascular events, and hospitalization N Engl J Med 2004 351 1296 1305 10.1056/NEJMoa041031 15385656 Go AS, Chertow GM, Fan D, et al. Chronic kidney disease and the risks of death, cardiovascular events, and hospitalization. N Engl J Med. 2004;351:1296–305. 15385656 10.1056/NEJMoa041031

3. Imai E Horio M Watanabe T Prevalence of chronic kidney disease in the Japanese general population Clin Exp Nephrol 2009 13 621 630 10.1007/s10157-009-0199-x 19513802 Imai E, Horio M, Watanabe T, et al. Prevalence of chronic kidney disease in the Japanese general population. Clin Exp Nephrol. 2009;13:621–30. 19513802 10.1007/s10157-009-0199-x

4. Takeuchi M Shinkawa K Yanagita M Prevalence, recognition and management of chronic kidney disease in Japan: population-based estimate using a healthcare database with routine health checkup data Clin Kidney J 2021 14 2197 2202 10.1093/ckj/sfab016 34676073 PMC8528067 Takeuchi M, Shinkawa K, Yanagita M, et al. Prevalence, recognition and management of chronic kidney disease in Japan: population-based estimate using a healthcare database with routine health checkup data. Clin Kidney J. 2021;14:2197–202. 34676073 10.1093/ckj/sfab016 PMC8528067

5. Kanazawa I Inaba M Inoue D Executive summary of clinical practice guide on fracture risk in lifestyle diseases J Bone Miner Metab 2020 38 746 758 10.1007/s00774-020-01149-3 32892240 Kanazawa I, Inaba M, Inoue D, et al. Executive summary of clinical practice guide on fracture risk in lifestyle diseases. J Bone Miner Metab. 2020;38:746–58. 32892240 10.1007/s00774-020-01149-3

6. Masson P Webster AC Hong M Chronic kidney disease and the risk of stroke: a systematic review and meta-analysis Nephrol Dial Transplant 2015 30 1162 1169 10.1093/ndt/gfv009 25681099 Masson P, Webster AC, Hong M, et al. Chronic kidney disease and the risk of stroke: a systematic review and meta-analysis. Nephrol Dial Transplant. 2015;30:1162–9. 25681099 10.1093/ndt/gfv009

7. GBD Chronic Kidney Disease Collaboration Global, regional, and national burden of chronic kidney disease, 1990–2017: a systematic analysis for the global burden of disease study 2017 Lancet 2020 395 709 733 10.1016/S0140-6736(20)30045-3 32061315 PMC7049905 GBD Chronic Kidney Disease Collaboration. Global, regional, and national burden of chronic kidney disease, 1990–2017: a systematic analysis for the global burden of disease study 2017. Lancet. 2020;395:709–33. 32061315 10.1016/S0140-6736(20)30045-3 PMC7049905

8. Naylor KL McArthur E Leslie WD The three-year incidence of fracture in chronic kidney disease Kidney Int 2014 86 810 818 10.1038/ki.2013.547 24429401 Naylor KL, McArthur E, Leslie WD, et al. The three-year incidence of fracture in chronic kidney disease. Kidney Int. 2014;86:810–8. 24429401 10.1038/ki.2013.547

9. Evenepoel P Cunningham J Ferrari S European consensus statement on the diagnosis and management of osteoporosis in chronic kidney disease stages G4–G5D Nephrol Dial Transplant 2021 36 42 59 10.1093/ndt/gfaa192 33098421 Evenepoel P, Cunningham J, Ferrari S, et al. European consensus statement on the diagnosis and management of osteoporosis in chronic kidney disease stages G4–G5D. Nephrol Dial Transplant. 2021;36:42–59. 33098421 10.1093/ndt/gfaa192

10. Bellorin-Font E Rojas E Martin KJ Bone disease in chronic kidney disease and kidney transplant Nutrients 2022 15 167 10.3390/nu15010167 36615824 PMC9824497 Bellorin-Font E, Rojas E, Martin KJ. Bone disease in chronic kidney disease and kidney transplant. Nutrients. 2022;15:167. 36615824 10.3390/nu15010167 PMC9824497

11. Bliuc D Nguyen ND Milch VE Mortality risk associated with low-trauma osteoporotic fracture and subsequent fracture in men and women JAMA 2009 301 513 521 10.1001/jama.2009.50 19190316 Bliuc D, Nguyen ND, Milch VE, et al. Mortality risk associated with low-trauma osteoporotic fracture and subsequent fracture in men and women. JAMA. 2009;301:513–21. 19190316 10.1001/jama.2009.50

12. Wakasugi M Kazama JJ Taniguchi M Increased risk of hip fracture among Japanese hemodialysis patients J Bone Miner Metab 2013 31 315 321 10.1007/s00774-012-0411-z 23292163 Wakasugi M, Kazama JJ, Taniguchi M, et al. Increased risk of hip fracture among Japanese hemodialysis patients. J Bone Miner Metab. 2013;31:315–21. 23292163 10.1007/s00774-012-0411-z

13. Shukuri T Nakai K Tanaka S Angiotensin II receptor blockers and bone fracture in chronic kidney disease patients: the fukuoka kidney disease registry study Clin Exp Nephrol 2023 27 919 927 10.1007/s10157-023-02385-3 37498346 Shukuri T, Nakai K, Tanaka S, et al. Angiotensin II receptor blockers and bone fracture in chronic kidney disease patients: the Fukuoka kidney disease Registry Study. Clin Exp Nephrol. 2023;27:919–27. 37498346 10.1007/s10157-023-02385-3

14. Dukas L Schacht E Stähelin HB In elderly men and women treated for osteoporosis a low creatinine clearance of <65 ml/min is a risk factor for falls and fractures Osteoporos Int 2005 16 1683 1690 10.1007/s00198-005-1903-7 15933802 Dukas L, Schacht E, Stähelin HB. In elderly men and women treated for osteoporosis a low creatinine clearance of <65 ml/min is a risk factor for falls and fractures. Osteoporos Int. 2005;16:1683–90. 15933802 10.1007/s00198-005-1903-7

15. Nickolas TL McMahon DJ Shane E Relationship between moderate to severe kidney disease and hip fracture in the United States J Am Soc Nephrol 2006 17 3223 3232 10.1681/ASN.2005111194 17005938 Nickolas TL, McMahon DJ, Shane E. Relationship between moderate to severe kidney disease and hip fracture in the United States. J Am Soc Nephrol. 2006;17:3223–32. 17005938 10.1681/ASN.2005111194

16. Ensrud KE Lui LY Taylor BC Renal function and risk of hip and vertebral fractures in older women Arch Intern Med 2007 167 133 139 10.1001/archinte.167.2.133 17242313 Ensrud KE, Lui LY, Taylor BC, et al. Renal function and risk of hip and vertebral fractures in older women. Arch Intern Med. 2007;167:133–9. 17242313 10.1001/archinte.167.2.133

17. Fried LF Biggs ML Shlipak MG Association of kidney function with incident hip fracture in older adults J Am Soc Nephrol 2007 18 282 286 10.1681/ASN.2006050546 17167115 Fried LF, Biggs ML, Shlipak MG, et al. Association of kidney function with incident hip fracture in older adults. J Am Soc Nephrol. 2007;18:282–6. 17167115 10.1681/ASN.2006050546

18. LaCroix AZ Lee JS Wu L Cystatin-C, renal function, and incidence of hip fracture in postmenopausal women J Am Geriatr Soc 2008 56 1434 1441 10.1111/j.1532-5415.2008.01807.x 18662213 PMC2891241 LaCroix AZ, Lee JS, Wu L, et al. Cystatin-C, renal function, and incidence of hip fracture in postmenopausal women. J Am Geriatr Soc. 2008;56:1434–41. 18662213 10.1111/j.1532-5415.2008.01807.x PMC2891241

19. Medical Data Vision. About MDV Database. Accessed 20 February 2024. http://www.mdv.co.jp/

20. Matsuzaki T Watanabe Y Tanaka A Prognosis and incidence of infections in chronic kidney disease patients with membranous nephropathy enrolled in a large Japanese clinical claims database BMC Nephrol 2023 24 126 10.1186/s12882-023-03190-6 37142947 PMC10161415 Matsuzaki T, Watanabe Y, Tanaka A, et al. Prognosis and incidence of infections in chronic kidney disease patients with membranous nephropathy enrolled in a large Japanese clinical claims database. BMC Nephrol. 2023;24:126. 37142947 10.1186/s12882-023-03190-6 PMC10161415

21. Liyanage T Toyama T Hockham C Prevalence of chronic kidney disease in Asia: a systematic review and analysis BMJ Glob Health 2022 7 e007525 10.1136/bmjgh-2021-007525 35078812 PMC8796212 Liyanage T, Toyama T, Hockham C, et al. Prevalence of chronic kidney disease in Asia: a systematic review and analysis. BMJ Glob Health. 2022;7:e007525. 35078812 10.1136/bmjgh-2021-007525 PMC8796212

22. Kashihara N Kohsaka S Kanda E Hyperkalemia in real-world patients under continuous medical care in Japan Kidney Int Rep 2019 4 1248 1260 10.1016/j.ekir.2019.05.018 31517144 PMC6734103 Kashihara N, Kohsaka S, Kanda E, et al. Hyperkalemia in real-world patients under continuous medical care in Japan. Kidney Int Rep. 2019;4:1248–60. 31517144 10.1016/j.ekir.2019.05.018 PMC6734103

23. Matsuo S Yasuda Y Imai E Current status of estimated glomerular filtration rate (eGFR) equations for Asians and an approach to create a common eGFR equation Nephrology (Carlton) 2010 15 Suppl 2 45 48 10.1111/j.1440-1797.2010.01313.x 20586948 Matsuo S, Yasuda Y, Imai E, et al. Current status of estimated glomerular filtration rate (eGFR) equations for Asians and an approach to create a common eGFR equation. Nephrology (Carlton). 2010;15(Suppl 2):45–8. 20586948 10.1111/j.1440-1797.2010.01313.x

24. Fine JP Gray RJ A proportional hazards model for the subdistribution of a competing risk J Am Stat Assoc 1999 94 496 509 10.1080/01621459.1999.10474144 Fine JP, Gray RJ. A proportional hazards model for the subdistribution of a competing risk. J Am Stat Assoc. 1999;94:496–509.

25. Kidney Disease: Improving Global Outcomes (KDIGO) CKD-MBD Work Group. KDIGO clinical practice guideline update for the diagnosis, evaluation, prevention, and treatment of chronic kidney disease-mineral and bone disorder (CKD-MBD) Kidney Int Suppl 2017 2017 7 1 59 10.1016/j.kisu.2017.04.001 PMC6340919 30675420 Kidney Disease: Improving Global Outcomes (KDIGO) CKD-MBD Work Group. KDIGO. clinical practice guideline update for the diagnosis, evaluation, prevention, and treatment of chronic kidney disease-mineral and bone disorder (CKD-MBD). Kidney Int Suppl. 2017;2017(7):1–59. 10.1016/j.kisu.2017.04.001 PMC6340919 30675420

26. Desbiens LC Goupil R Madore F Incidence of fractures in middle-aged individuals with early chronic kidney disease: A population-based analysis of CARTaGENE Nephrol Dial Transplant 2020 35 1712 1721 10.1093/ndt/gfz259 31951261 Desbiens LC, Goupil R, Madore F, et al. Incidence of fractures in middle-aged individuals with early chronic kidney disease: A population-based analysis of CARTaGENE. Nephrol Dial Transplant. 2020;35:1712–21. 31951261 10.1093/ndt/gfz259

27. Vilaca T Salam S Schini M Risks of hip and nonvertebral fractures in patients with CKD G3a–G5D: a systematic review and meta-analysis Am J Kidney Dis 2020 76 521 532 10.1053/j.ajkd.2020.02.450 32654892 Vilaca T, Salam S, Schini M, et al. Risks of hip and nonvertebral fractures in patients with CKD G3a–G5D: a systematic review and meta-analysis. Am J Kidney Dis. 2020;76:521–32. 32654892 10.1053/j.ajkd.2020.02.450

28. Fujiwara S Buchanan-Hughes A Ng A Real-world evaluation of osteoporotic fractures using the Japan Medical Data Vision database Osteoporos Int 2022 33 2205 2216 10.1007/s00198-022-06472-1 35779100 Fujiwara S, Buchanan-Hughes A, Ng A, et al. Real-world evaluation of osteoporotic fractures using the Japan Medical Data Vision database. Osteoporos Int. 2022;33:2205–16. 35779100 10.1007/s00198-022-06472-1

29. Japan Osteoporosis Society, The Japanese Society for Bone and Mineral Research, Japan Osteoporosis Foundation (eds). Japanese 2015 guidelines for prevention and treatment of osteoporosis. Tokyo: Life Science Publishing; 2015 (In Japanese).

30. Japan Osteoporosis Foundation. Number and rate of osteoporosis screening. Accessed 10 June 2024. https://www.jpof.or.jp/Portals/0/pdf/screening_rate/screeningrate_2021.pdf (In Japanese).

31. Japan Osteoporosis Foundation. Osteoporosis screening. Accessed 10 June 2024. https://www.jpof.or.jp/osteoporosis/inspection_treatment/tabid252.html (In Japanese).

32. Ministry of Health, Labour and Welfare in Japan. Explanatory material for the promotion of Healthy Japan 21 (the third term) (part 2). Accessed 10 June 2024. https://www.mhlw.go.jp/content/001158871.pdf (In Japanese).

33. Japanese Society of Nephrology Essential points from evidence-based clinical practice guideline for chronic kidney disease 2023 Clin Exp Nephrol 2024 8 473 495 10.1007/s10157-024-02497-4 PMC11116248 38713253 Japanese Society of Nephrology. Essential points from evidence-based clinical practice guideline for chronic kidney disease 2023. Clin Exp Nephrol. 2024;8:473–95. 10.1007/s10157-024-02497-4 PMC11116248 38713253

34. Suzuki Y Nawata H Soen S Guidelines on the management and treatment of glucocorticoid-induced osteoporosis of the Japanese Society for Bone and Mineral Research: 2014 update J Bone Miner Metab 2014 32 337 350 10.1007/s00774-014-0586-6 24818875 Suzuki Y, Nawata H, Soen S, et al. Guidelines on the management and treatment of glucocorticoid-induced osteoporosis of the Japanese Society for Bone and Mineral Research: 2014 update. J Bone Miner Metab. 2014;32:337–50. 24818875 10.1007/s00774-014-0586-6

35. Nawata H Soen S Takayanagi R Subcommittee to study diagnostic criteria for glucocorticoid-induced osteoporosis. guidelines on the management and treatment of glucocorticoid-induced osteoporosis of the Japanese Society for Bone and Mineral Research (2004) J Bone Miner Metab 2005 23 105 109 10.1007/s00774-004-0596-x 15750687 Nawata H, Soen S, Takayanagi R, et al. Subcommittee to study diagnostic criteria for glucocorticoid-induced osteoporosis. guidelines on the management and treatment of glucocorticoid-induced osteoporosis of the Japanese Society for Bone and Mineral Research (2004). J Bone Miner Metab. 2005;23:105–9. 15750687 10.1007/s00774-004-0596-x

36. Komaba H Imaizumi T Hamano T Lower parathyroid hormone levels are associated with reduced fracture risk in Japanese hemodialysis patients Kidney Int Rep. 2024 10.1016/j.ekir.2024.07.008 39430172 PMC11489479 Komaba H, Imaizumi T, Hamano T, et al. Lower parathyroid hormone levels are associated with reduced fracture risk in Japanese hemodialysis patients. Kidney Int Rep. 2024. 10.1016/j.ekir.2024.07.008. 39430172 10.1016/j.ekir.2024.07.008 PMC11489479

37. Yamamoto S Jørgensen HS Zhao J Alkaline phosphatase and parathyroid hormone levels: international variation and associations with clinical outcomes in the DOPPS Kidney Int Rep 2024 9 863 876 10.1016/j.ekir.2024.01.002 38765600 PMC11101738 Yamamoto S, Jørgensen HS, Zhao J, et al. Alkaline phosphatase and parathyroid hormone levels: international variation and associations with clinical outcomes in the DOPPS. Kidney Int Rep. 2024;9:863–76. 38765600 10.1016/j.ekir.2024.01.002 PMC11101738