Scholarlink

Background <p>Compared with individuals with other chronic kidney disease (CKD), individuals with autosomal dominant polycystic kidney disease (ADPKD) may face increased fracture risk. This study provides the first clinical evaluation of fracture risk prediction in early-stage ADPKD using the FRAX<sup>®</sup>, QFracture<sup>®</sup>, and Garvan models.</p> Methods <p>In this cross-sectional study, adult ADPKD patients with preserved kidney function were screened for fracture risk. Due to age eligibility criteria and data availability, fracture risk estimates could be calculated in 67 individuals using QFracture<sup>®</sup>, in 46 using FRAX<sup>®</sup>, and in a subgroup of 23 participants using the Garvan calculator. Bone mineral density (BMD) was assessed via DXA, and height-adjusted total kidney volume (HtTKV) was assessed via MRI. Ten-year fracture risks were calculated and compared via correlation, Bland–Altman plots, and regression modeling.</p> Results <p>All evaluated calculators were broadly in agreement at the group level, and the median fracture risk values for major osteoporotic and hip fractures remained consistently low. In our cohort, QFracture<sup>®</sup> appeared most practically applicable because of its broader age range and inclusion of CKD-related variables. Age was the only independent predictor of fracture risk; neither eGFR nor HtTKV was associated with fracture risk in any model. Preserved BMD suggests that DXA-derived measures alone may not fully capture skeletal vulnerability in ADPKD.</p> Conclusions <p>This is the first study to explore the use of online fracture risk calculators in an early-stage ADPKD population. Although fracture risk calculators offer a practical and cost-effective approach for estimating fracture risk, their use in ADPKD requires cautious interpretation. Our findings indicate that age significantly influences the predicted risk, whereas neither the eGFR nor HtTKV, despite their relevance to kidney disease progression, were associated with any of the evaluated models. Future research should aim to refine fracture risk models by incorporating disease-specific variables and validating them in larger, prospective ADPKD cohorts.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Fracture risk assessment in early-stage autosomal dominant polycystic kidney disease: a cross-sectional study using FRAX®, QFracture®, and Garvan models

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月1日

查看全文
  • Helena Kamieniecka,
  • Per Magnusson,
  • Mathias Haarhaus,
  • Magdalena Dzitkowska-Zabielska,
  • Izabella Kuźmiuk-Glembin,
  • Alicja Dębska-Ślizień,
  • Djalila Mekahli,
  • Magdalena Jankowska

摘要

Background

Compared with individuals with other chronic kidney disease (CKD), individuals with autosomal dominant polycystic kidney disease (ADPKD) may face increased fracture risk. This study provides the first clinical evaluation of fracture risk prediction in early-stage ADPKD using the FRAX®, QFracture®, and Garvan models.

Methods

In this cross-sectional study, adult ADPKD patients with preserved kidney function were screened for fracture risk. Due to age eligibility criteria and data availability, fracture risk estimates could be calculated in 67 individuals using QFracture®, in 46 using FRAX®, and in a subgroup of 23 participants using the Garvan calculator. Bone mineral density (BMD) was assessed via DXA, and height-adjusted total kidney volume (HtTKV) was assessed via MRI. Ten-year fracture risks were calculated and compared via correlation, Bland–Altman plots, and regression modeling.

Results

All evaluated calculators were broadly in agreement at the group level, and the median fracture risk values for major osteoporotic and hip fractures remained consistently low. In our cohort, QFracture® appeared most practically applicable because of its broader age range and inclusion of CKD-related variables. Age was the only independent predictor of fracture risk; neither eGFR nor HtTKV was associated with fracture risk in any model. Preserved BMD suggests that DXA-derived measures alone may not fully capture skeletal vulnerability in ADPKD.

Conclusions

This is the first study to explore the use of online fracture risk calculators in an early-stage ADPKD population. Although fracture risk calculators offer a practical and cost-effective approach for estimating fracture risk, their use in ADPKD requires cautious interpretation. Our findings indicate that age significantly influences the predicted risk, whereas neither the eGFR nor HtTKV, despite their relevance to kidney disease progression, were associated with any of the evaluated models. Future research should aim to refine fracture risk models by incorporating disease-specific variables and validating them in larger, prospective ADPKD cohorts.