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Nationwide attribute-based cross-classification reveals distinct risk patterns of major complications in ADPKD
Hiroshi Kataoka1,2, Saori Nishio3, Junichi Hoshino4
1Department of Nephrology, Tokyo Women's Medical University, 8-1 Kawada-cho, Shinjuku-ku, Tokyo, 162-8666, Japan. kataoka@twmu.ac.jp.
Background And Hypothesis:
Autosomal dominant polycystic kidney disease (ADPKD) imposes a substantial burden through diverse renal and extrarenal complications; however, risk-based screening strategies remain insufficiently aligned with patient heterogeneity. We hypothesized that attribute-based cross-classification would identify clinically meaningful risk patterns beyond conventional single-factor approaches.
Methods:
We analyzed anonymized nationwide registry data (2015-2021) from 12,466 patients with ADPKD. Multivariable logistic regression assessed associations between six prespecified attributes-sex, age, CKD stage, hypertension, total kidney volume, and annual total kidney volume growth rate-and eight major complications. Attribute-based cross-classification was used to describe absolute prevalence patterns across clinically interpretable subgroups.
Results:
Complication burden was substantial, with liver cysts (86.1%), kidney pain (29.7%), and intracranial aneurysms (18.5%) being most common. Distinct attribute-specific patterns were observed: intracranial aneurysms were more frequent in women and older individuals, whereas intracranial hemorrhage was strongly associated with hypertension. Advanced CKD was associated with multiple complications, whereas liver cysts and kidney pain followed different patterns. Cross-classification identified distinct prevalence patterns, including 25.3% among women aged ≥ 50 years for intracranial aneurysms and 31.9% among patients aged < 50 years with CKD stages 4-5 for gross hematuria/cyst bleeding.
Conclusions:
Attribute-based cross-classification revealed clinically meaningful heterogeneity in ADPKD complications. Distinct combinations of patient attributes defined clinically relevant prevalence patterns that may support risk-stratified screening and monitoring strategies in ADPKD. Importantly, this approach provides a clinically interpretable and scalable framework that may be applicable to routine care without reliance on complex modeling.
