Establishment and Validation of a Nomogram for Primary Aldosteronism Patients: Using the Least Absolute Shrinkage and
Wen-Xiu Xu1, Ji-Hong Duan2, Fan Wu1
1Department of Pharmacy, Fuwai Yunnan Hospital, Chinese Academy of Medical Sciences, Affiliated Cardiovascular Hospital of Kunming Medical University, Kunming, China.
Objective:
Primary aldosteronism (PA) is a clinical syndrome caused by endocrine disorders. This study developed a risk prediction nomogram model for patients with PA based on least absolute shrinkage and selection operator (LASSO)-logistic regression and evaluated the predictive performance of this nomogram model.
Methods:
A total of 325 patients who underwent etiological screening for hypertension at our hospital after referral from primary hospitals or outpatient consultation from January 2024 to March 2025 were included, including 212 with PA and 113 with essential hypertension. The LASSO regression model was used to screen variables, and multivariate logistic regression analysis was performed to identify independent risk factors for PA, with a corresponding nomogram model constructed. The discriminative ability of the model was evaluated using receiver operating characteristic curves, while the calibration of the model was assessed via the Hosmer-Lemeshow goodness-of-fit test and calibration curves.
Results:
The LASSO regression identified a total of 14 potential risk factors, including age, smoking, family history of hypertension, coronary heart disease, obstructive sleep apnea hypopnea syndrome (OSAHS), etc. Logistic regression analysis revealed that OSAHS (odds ratio [OR] = 4.006, 95% CI = 1.366-11.749, P = .011), potassium (OR = 0.253, 95% CI = 0.068-0.940, P = .040), aldosterone (upright) (OR = 1.282, 95% CI = 1.147-1.433, P < .001), and renin (upright) (OR = 0.735, 95% CI = 0.668-0.808, P < .001) were independent risk factors for PA (P < .05). A nomogram model was constructed based on the above results. The area under the curve values of the training and validation sets were 0.976 (95% CI = 0.958-0.995) and 0.924 (95% CI = 0.859-0.990), respectively. The calibration curves of both sets were close to the ideal curves. For both sets, the Hosmer-Lemeshow test showed P > .05, indicating good clinical utility.
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.
