Establishment and Validation of a Nomogram for Primary Aldosteronism Patients: Using the Least Absolute Shrinkage and Selection Operator (LASSO)-Logistic Regression Model
Authors' conclusion
We identified 4 independent risk factors for PA using LASSO-logistic regression, including OSAHS, serum potassium, aldosterone (upright), and renin (upright). Furthermore, the nomogram model constructed in this study demonstrates good clinical utility for the early diagnosis of PA patients.
Study context
- Population
- Patients undergoing etiological screening for hypertension at one hospital after referral from primary hospitals or outpatient consultation, January 2024 to March 2025
- Participants
- 325 patients
- Comparison
- Primary aldosteronism (PA) vs essential hypertension
- PAn = 212
- Essential hypertensionn = 113reference
- Outcome
- Independent risk factors for PA (multivariate logistic regression)
Methodological detailsLASSO-logistic regression, nomogram, training and validation sets
- LASSO-logistic regression
- Nomogram
- Training and validation sets
Performance
As reported in the abstract
Obstructive sleep apnea hypopnea syndrome (OSAHS): OR (95% CI 1.366-11.749), P = .011
4.006
Potassium: OR (95% CI 0.068-0.940), P = .040
0.253
Aldosterone (upright): OR (95% CI 1.147-1.433), P < .001
1.282
Renin (upright): OR (95% CI 0.668-0.808), P < .001
0.735
Further findings
Nomogram discrimination (AUC)
- AUC, training set
- 0.976 (95% CI 0.958-0.995)
- AUC, validation set
- 0.924 (95% CI 0.859-0.990)
Nomogram calibration
- Hosmer-Lemeshow test, both sets
- P > 0.05
- Calibration curves of both sets close to ideal curves
Original publication
Establishment and Validation of a Nomogram for Primary Aldosteronism Patients: Using the Least Absolute Shrinkage and Selection Operator (LASSO)-Logistic Regression Model. Endocr Pract. Published 15 October 2025. doi:10.
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