Construction and Verification the Nomogram Prediction Model for Primary Aldosteronism Based on Glomerular Filtration Rate

Subjects: Medicine, Pharmacy >> Clinical Medicine submitted time 2023-12-06 Cooperative journals: 《中国全科医学》

CHANG Yupeng GENG Xixi HUO Rui SUN Kan CHANG Xiangyun LI Jun ZHU Lingyun DONG Yujie LUO Lina

Abstract： Background　Aldosterone-producing adenoma（APA） is a common type of primary aldosteronism. For those with unilateral adrenocortical adenoma，although expert consensus recommends plasma aldosterone-to-renin ratio（ARR） as a screening indicator for APA，the range of ARR cut-off values varies widely due to the lack of unified detection method and diagnostic process. Therefore，there is a clinical need for a reliable and rapid predictive model to assist in identifying APA. Objective　To explore the correlation between glomerular filtration rate（GFR） and APA，construct and validate the nomogram prediction model of APA. Methods　A total of 493 patients with with pathologic results of unilateral adrenal mass who underwent surgical treatment after evaluation of adrenal endocrine hormones in the first affiliated hospital of Shihezi University from 2012 to 2022 were collected，155 patients were ultimately included in the APA group and 113 patients in nonfunctioning adrenal adenoma combined with essential hypertension group according to the diagnostic criteria of APA and nonfunctioning adrenal adenoma. The patients' clinical data and biochemical data were collected. The patients were grouped according to GFR quartiles，and the correlation between GFR and APA was analyzed. The risk factors for APA were screened by multivariate Logistic regression analysis and a nomogram prediction model was constructed. Receiver operating characteristic（ROC） curve was used to analyze the discrimination of the prediction model，a consistency index（C-index） was used to evaluate the predictive accuracy of the model，Hosmer Lemeshow test was used to verify the fit of model，and the diagnostic efficacy of the model was evaluated using decision curve and clinical benefit curve. Results　The patients were grouped according to GFR quartiles （Q1 to Q4 groups），Q1 group： ≥ 107.4 ml·min-1·（1.73 m2 ）-1（n=67），Q2 group：99.7-107.3 ml·min-1·（1.73 m2 ）-1 （n=67），Q3 group：88.6-99.6 ml·min-1·（1.73 m2 ）-1（n=67） and Q4 group： ≤ 88.5 ml·min-1·（1.73 m2 ）-1 （n=67），and the proportion of APA in each group was 47.8%（32/67），53.7%（36/67），58.2%（39/67） and 71.6% （48/67）. Logistic regression trend test suggested that the risk of APA tended to increase as GFR levels decreased（P<0.001）. Multivariate Logistic regression analysis showed that systolic blood pressure>160mmHg（OR=5.209，95%CI=2.531-10.720）， hypertension duration ≥ 59 months（OR=4.326，95%CI=1.950-9.595），blood potassium<3.25mmol/L（OR=4.714， 95%CI=2.046-10.860），GFR［Q4 gourp： ≤ 88.5 ml·min-1·（1.73 m2 ）-1］（OR=4.106，95%CI=1.492-11.300）， blood aldosterone>13.42 ng/dL（OR=8.756，95%CI=4.320-17.749） were independent risk factors for the occurrence of APA （P<0.050）. The Nomogram prediction model was constructed based on the above variables of multivariate regression with an AUC of 0.898（95%CI=0.859-0.936） and a C-index of 0.898，indicating a good prediction accuracy. The Hosmer-Lemeshow test showed that the model had a good fit（χ2 =14.059，P=0.080）. The model had a significant predictive efficacy at prediction probability thresholds of 0.10 to 0.90. Conclusion　The risk of APA prevalence tends to increase with decreasing GFR levels. The APA prediction model constructed based on five factors，including systolic blood pressure，hypertension course，blood potassium，GFR quartile grouping and plasma aldosterone，has good predictability，consistency and clinical practicality，which can help identify APA and contribute to clinical decision making.

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