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Development and validation of a novel diagnostic nomogram model to predict primary aldosteronism in patients with hypertension

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Abstract

Purpose

Primary aldosteronism (PA) remains, to a large extent, an under-diagnosed disease. We aimed to develop and validate a novel clinical nomogram to predict PA based on routine biochemical variables including new ones, calcium-phosphorus product.

Methods

Records from 806 patients with hypertension were randomly divided into 70% (n = 564) as the training set and the remaining 30% (n = 242) as the validation set. Predictors for PA were extracted to construct a nomogram model based on regression analysis of the training set. An internal validation was performed to assess the nomogram model’s discrimination and consistency using the area under the curve for receiver operating characteristic curves and calibration plots. The diagnostic accuracy was compared between nomogram and other known prediction models, using receiver operating characteristics (ROC) and decision curve analyses (DCA).

Results

Female gender, serum potassium, serum calcium-phosphorus product, and urine pH were adopted as predictors in the nomogram. The nomogram resulted in an area under the curve of 0.73 (95% confidence interval: 0.68–0.78) in the training set and an area under the curve of 0.68 (0.59–0.75) in the validation set. Predicted probability and actual probability matched well in the nomogram (p > 0.05). Based on ROC and DCA, 21–70% threshold to predict PA in the nomogram model was clinically useful.

Conclusions

We have developed a novel nomogram to predict PA in hypertensive individuals based on routine biochemical variables. External validation is needed to further demonstrate its predictive ability in primary care settings.

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Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Code availability

SPSS Statistics v.22.0 (IBM, Armonk, NY) or R Software v.4.0.2 (The R Project for Statistical Computing, www.r-project.org).

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Acknowledgements

This study was feasible because of the support of our clinical PA team. We thank Dr. Ting Wu from the Hypertension Institute of Xinjiang for her assistance in endocrine monitoring.

Funding

This work was supported by the Non-profit Central Research Institute Fund of the Chinese Academy of Medical Sciences [Grant No. 2019PT330003].

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Authors and Affiliations

  1. Hypertension Center of People’s Hospital of Xinjiang Uygur Autonomous Region; Xinjiang Hypertension Institute, National Health Committee Key Laboratory of Hypertension Clinical Research, No. 91 Tianchi Road Urumqi, 830001, Xinjiang, China

    Meng-hui Wang, Nan-fang Li, Qin Luo, Guo-liang Wang, Mulalibieke Heizhati, Ling Wang, Lei Wang & Wei-wei Zhang

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  1. Meng-hui Wang
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Contributions

All authors have read and agreed to the final version of the paper. Conceptualization, N-f.L. and M-h.W.; Methodology, M-h.W., Q.L. and L.W.; Resources and data curation, L.W. and W-w.Z.; Writing—original draft preparation, M-h.W. and M.H.; Software, G-l.W. and L.W.; Project administration and funding acquisition, N-f.L.

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Correspondence to Nan-fang Li.

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Wang, Mh., Li, Nf., Luo, Q. et al. Development and validation of a novel diagnostic nomogram model to predict primary aldosteronism in patients with hypertension. Endocrine 73, 682–692 (2021). https://doi.org/10.1007/s12020-021-02745-7

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