Identifying unilateral disease in Chinese patients with primary aldosteronism by using a modified prediction score

Clinical prediction model for primary aldosteronism subtyping and special focus on adrenal volumetric assessment

PURPOSE

Our aim was to develop a prediction model based on a simple score with clinical, laboratory, and imaging findings for the subtype diagnosis of primary aldosteronism (PA). The contribution of adrenal volumetric assessment to PA subtyping was also investigated.

METHODS

Thirty-five patients with adequate cannulation in adrenal venous sampling (AVS) were included. Laboratory data, the saline infusion test (SIT), and the AVS results of patients with PA were retrospectively evaluated. Volumetric assessment was performed using magnetic resonance imaging (MRI) and the ratio of adrenal volumes was calculated after adjusting for gender- and side-specific mean reference values of both adrenal glands.

RESULTS

The AVS was consistent with unilateral PA in 49% and bilateral in 51% of the patients. Hypertension as a reason for work-up, the highest aldosterone/lowest potassium value higher than 12, the percentage of plasma aldosterone concentration (PAC) reduction after SIT by equal or less than 43.5%, the use of oral potassium replacement, unilateral disease at pre-AVS imaging, and a ratio of adjusted adrenal volumes equal to or below 1.7 were indicative of unilateral disease in univariate logistic regression analysis concerning the distinction of PA subtyping (p < 0.05). Multivariate logistic regression analysis also revealed that adrenal volumetric assessment has an impact on PA subtyping (p < 0.05). In the prediction model, when each of the six parameters that were significant in the univariate logistic regression analysis was assigned one point, < 4 predicted bilateral PA, whereas ≥ 4 predicted unilateral PA (AUC:0.92, p < 0.001).

CONCLUSION

This prediction model before AVS may serve as a convenient and practical approach, while an adjusted adrenal volumetric assessment can make a positive contribution to PA subtyping.

Sex modifies the predictive value of computed tomography combined with serum potassium for primary aldosteronism subtype diagnosis

Objective

We aimed to investigate the predictive value of the CT findings combined with serum potassium levels for primary aldosteronism (PA) subtype diagnosis, with a particular interest in sex differences.

Methods

In this retrospective study, we eventually included 482 PA patients who underwent successful adrenal venous sampling (AVS) and had available data. We diagnosed the subjects as having either unilateral (n = 289) or bilateral PA (n = 193) based on AVS. We analyzed the concordance rate between AVS and adrenal CT combined with serum potassium and performed a logistic regression analysis to assess the prevalence of unilateral PA on AVS.

Results

The total diagnostic concordance rate between CT findings and AVS was 51.5% (248/482). The prevalence of hypokalemia in men and women was 47.96% (129/269) and 40.85% (87/213), respectively. The occurrence of unilateral lesions on CT and hypokalemia was significantly associated with an increased prevalence of unilateral PA [odds ratio (OR) 1.537; 95% confidence interval (CI) 1.364-1.731; p < 0.001]. In male participants, G2 (bilateral lesion on CT and normokalemia), G3 (unilateral lesion on CT and normokalemia), G4 (bilateral normal on CT and hypokalemia), G5 (bilateral lesion on CT and hypokalemia), and G6 (unilateral lesion on CT and hypokalemia) were significantly increased for the prevalence of unilateral PA on AVS (G2: OR 4.620, 95% CI 1.408-15.153; G3: OR 6.275, 95% CI 2.490-15.814; G4: OR 3.793, 95% CI 1.191-12.082; G5: OR 16.476, 95% CI 4.531-59.905; G6: OR 20.101, 95% CI 7.481-54.009; all p < 0.05), compared with G1 (patients with bilateral normal on CT and normokalemia). However, among female participants, we found an increased likelihood for unilateral PA in patients with unilateral lesions on CT and hypokalemia alone (OR 10.266, 95% CI 3.602-29.259, p < 0.001), while no associations were found in other groups (all p > 0.05). Sex had a significant effect on modifying the relationship between unilateral PA and the combination of CT findings and serum potassium (p for interaction <0.001).

Conclusion

In conclusion, our results indicated that CT findings combined with serum potassium levels have a great value for predicting the subtype of PA and are stronger in men.

Accuracy of Gallium-68 Pentixafor Positron Emission Tomography-Computed Tomography for Subtyping Diagnosis of Primary Aldosteronism

IMPORTANCE

Adrenal vein sampling (AVS) is the recommended procedure for subtyping primary aldosteronism (PA) as unilateral PA (UPA) or bilateral PA (BPA), with different treatment needed for each: adrenalectomy for UPA and medication for BPA. However, AVS is invasive and technically difficult, and how to subtype PA noninvasively is currently a great challenge.

OBJECTIVE

To evaluate the accuracy of gallium-68 pentixafor positron emission tomography-computed tomography (PET-CT) in subtyping PA using AVS as a reference standard.

DESIGN, SETTING, AND PARTICIPANTS

This diagnostic study was conducted at a tertiary hospital in China among patients diagnosed with PA. Enrollment was started in November 2021, with follow-up ending in May 2022.

EXPOSURES

: Patients were recruited to undergo gallium-68 pentixafor PET-CT and AVS.

MAIN OUTCOMES AND MEASURES

Maximum standardized uptake value (SUVmax) of each adrenal gland during PET-CT was measured to calculate the lateralization index of SUVmax. Area under the receiver operating characteristic curve (AUROC), specificity, and sensitivity were used to analyze the accuracy of the lateralization index based on SUVmax for subtyping PA.

RESULTS

Among 100 patients with PA who completed the study (47 female [47.0%] and 53 male [53.0%]; median [IQR] age, 49 [38-56] years), 43 individuals had UPA and 57 individuals had BPA. Aldosterone-cortisol ratio (Spearman ρ = 0.26; P < .001) in adrenal veins was positively correlated with SUVmax of adrenal glands at 10 minutes during PET-CT. Using lateralization index based on SUVmax at 10 minutes to identify UPA, the AUROC was 0.90 (95% CI, 0.83-0.97). A cutoff value for lateralization index based on SUVmax at 10 minutes set at 1.65 conferred a specificity of 1.00 (95% CI, 0.94-1.00) and sensitivity of 0.77 (95% CI, 0.61-0.88). The diagnostic concordance rate of PET-CT and AVS was 90 patients (90.0%) compared with 54 patients (54.0%) between traditional CT and AVS.

CONCLUSIONS AND RELEVANCE

This study found good diagnostic accuracy of gallium-68 pentixafor PET-CT in differentiating UPA from BPA. These findings suggest that gallium-68 pentixafor PET-CT may be used to avoid invasive AVS in some patients with PA.

Primary aldosteronism - a multidimensional syndrome

Primary aldosteronism is a common cause of hypertension and is a risk factor for cardiovascular and renal morbidity and mortality, via mechanisms mediated by both hypertension and direct insults to target organs. Despite its high prevalence and associated complications, primary aldosteronism remains largely under-recognized, with less than 2% of people in at-risk populations ever tested. Fundamental progress made over the past decade has transformed our understanding of the pathogenesis of primary aldosteronism and of its clinical phenotypes. The dichotomous paradigm of primary aldosteronism diagnosis and subtyping is being redefined into a multidimensional spectrum of disease, which spans subclinical stages to florid primary aldosteronism, and from single-focal or multifocal to diffuse aldosterone-producing areas, which can affect one or both adrenal glands. This Review discusses how redefining the primary aldosteronism syndrome as a multidimensional spectrum will affect the approach to the diagnosis and subtyping of primary aldosteronism.

Development and validation of model for sparing adrenal venous sampling in diagnosing unilateral primary aldosteronism

CONTEXT

Current guidelines recommend adrenal venous sampling (AVS) to identify unilateral primary aldosteronism (UPA) before offering adrenalectomy. However, AVS is costly and technically challenging, limiting its use to expert centres.

OBJECTIVE

To establish a model to predict UPA, and therefore, bypass the need for AVS prior to surgery.

DESIGN AND SETTING

The model was developed in a Chinese cohort and validated in an Australian cohort. Previously published prediction models of UPA were also tested.

PARTICIPANTS

primary aldosteronism patients with a definite subtyping diagnosis based on AVS and/or surgery.

MAIN OUTCOME MEASURE

Diagnostic value of the model.

RESULTS

In the development cohort (268 UPA and 88 bilateral primary aldosteronism), combinations of different levels of low serum potassium (≤3.0 or 3.5 mmol/l), high PAC (≥15-30 ng/dl), low PRC (≤2.5-10 μIU/ml) and presence of unilateral nodule on adrenal CT (>8-15 mm in diameter) showed specificity of 1.00 and sensitivity of 0.16-0.52. The model of serum potassium 3.5 mmol/l or less, PAC at least 20 ng/dl, PRC 5 μIU/ml or less plus a unilateral nodule at least 10 mm had the highest sensitivity of 0.52 (0.45-0.58) and specificity of 1.00 (0.96-1.00). In the validation cohort (84 UPA and 117 bilateral primary aldosteronism), the sensitivity and specificity of the model were 0.13 (0.07-0.22) and 1.00 (0.97-1.00), respectively. Ten previous models were tested, and only one had a specificity of 1.00 in our cohorts but with a very low sensitivity [0.07 (0.04-0.10) and 0.01 (0.00-0.06) in our development and validation cohorts, respectively].

CONCLUSION

A combination of high PAC, low PRC, low serum potassium and unilateral adrenal nodule could accurately determine primary aldosteronism subtype in 13-52% of patients with UPA and obviate the need for AVS before surgery.

External Validation of Clinical Prediction Models in Unilateral Primary Aldosteronism

BACKGROUND

Targeted treatment of primary aldosteronism (PA) is informed by adrenal vein sampling (AVS), which remains limited to specialized centers. Clinical prediction models have been developed to help select patients who would most likely benefit from AVS. Our aim was to assess the performance of these models for PA subtyping.

METHODS

This external validation study evaluated consecutive patients referred for PA who underwent AVS at a tertiary care referral center in Alberta, Canada during 2006–2018. In alignment with the original study designs and intended uses of the clinical prediction models, the primary outcome was the presence of lateralization on AVS. Model discrimination was evaluated using the C-statistic. Model calibration was assessed by comparing the observed vs. predicted probability of lateralization in the external validation cohort.

RESULTS

The validation cohort included 342 PA patients who underwent AVS (mean age, 52.1 years [SD, 11.5]; 201 [58.8%] male; 186 [54.4%] with lateralization). Six published models were assessed. All models demonstrated low-to-moderate discrimination in the validation set (C-statistics; range, 0.60–0.72), representing a marked decrease compared with the derivation sets (range, 0.80–0.87). Comparison of observed and predicted probabilities of unilateral PA revealed significant miscalibration. Calibration-in-the-large for every model was >0 (range, 0.35–1.67), signifying systematic underprediction of lateralizing disease. Calibration slopes were consistently <1 (range, 0.35–0.87), indicating poor performance at the extremes of risk.

CONCLUSIONS

Overall, clinical prediction models did not accurately predict AVS lateralization in this large cohort. These models cannot be reliably used to inform the decision to pursue AVS for most patients.

Outcome-Based Decision-Making Algorithm for Treating Patients with Primary Aldosteronism

BACKGROUND

Optimal management of primary aldosteronism (PA) is crucial due to the increased risk of cardiovascular and cerebrovascular diseases. Adrenal venous sampling (AVS) is the gold standard method for determining subtype but is technically challenging and invasive. Some PA patients do not benefit clinically from surgery. We sought to develop an algorithm to improve decision- making before engaging in AVS and surgery in clinical practice.

METHODS

We conducted the ongoing Korean Primary Aldosteronism Study at two tertiary centers. Study A involved PA patients with successful catheterization and a unilateral nodule on computed tomography and aimed to predict unilateral aldosterone-producing adenoma (n=367). Study B involved similar patients who underwent adrenalectomy and aimed to predict postoperative outcome (n=330). In study A, we implemented important feature selection using the least absolute shrinkage and selection operator regression.

RESULTS

We developed a unilateral PA prediction model using logistic regression analysis: lowest serum potassium level ≤3.4 mEq/L, aldosterone-to-renin ratio ≥150, plasma aldosterone concentration ≥30 ng/mL, and body mass index <25 kg/m2 (area under the curve, 0.819; 95% confidence interval, 0.774 to 0.865; sensitivity, 97.6%; specificity, 25.5%). In study B, we identified female, hypertension duration <5 years, anti-hypertension medication <2.5 daily defined dose, and the absence of coronary artery disease as predictors of clinical success, using stepwise logistic regression models (sensitivity, 94.2%; specificity, 49.3%). We validated our algorithm in the independent validation dataset (n=53).

CONCLUSION

We propose this new outcome-driven diagnostic algorithm, simultaneously considering unilateral aldosterone excess and clinical surgical benefits in PA patients.

Aldosterone-potassium ratio predicts primary aldosteronism subtype

OBJECTIVE

Prediction models have been developed to predict either unilateral or bilateral primary aldosteronism, and these have not been validated externally. We aimed to develop a simplified score to predict both subtypes and validate this externally.

METHODS

Our development cohort was taken from 165 patients who underwent adrenal vein sampling (AVS) in two Asian tertiary centres. Unilateral disease was determined using both AVS and postoperative outcome. Multivariable analysis was used to construct prediction models. We validated our tool in a European cohort of 97 patients enrolled in the SPARTACUS trial who underwent AVS. Previously published prediction models were also tested in our cohorts.

RESULTS

Backward stepwise logistic regression analysis yielded a final tool using baseline aldosterone-to-lowest-potassium ratio (APR, ng/dl/mmol/l), with an area under receiver-operating characteristic curve of 0.80 (95% CI 0.70-0.89). In the Asian development cohort, probability of bilateral disease was 90.0% (with APR <5) and probability of unilateral disease was 91.4% (with APR >15). Similar results were seen in the European validation cohort. Combining both cohorts, probability of bilateral disease was 76.7% (with APR <5), and probability for unilateral was 91.7% (with APR >15). Other models had similar predictive ability but required more variables, and were less sensitive for identifying bilateral PA.

CONCLUSION

The novel aldosterone-to-lowest-potassium ratio is a convenient score to guide clinicians and patients of various ethnicities on the probability of primary aldosteronism subtype. Using APR to identify patients more likely to benefit from AVS may be a cost-effective strategy to manage this common condition.

Recent Development toward the Next Clinical Practice of Primary Aldosteronism: A Literature Review

For the last seven decades, primary aldosteronism (PA) has been gradually recognized as a leading cause of secondary hypertension harboring increased risks of cardiovascular incidents compared to essential hypertension. Clinically, PA consists of two major subtypes, surgically curable and uncurable phenotypes, determined as unilateral or bilateral PA by adrenal venous sampling. In order to further optimize the treatment, surgery or medications, diagnostic procedures from screening to subtype differentiation is indispensable, while in the general clinical practice, the work-up rate is extremely low even in the patients with refractory hypertension because of the time-consuming and labor-intensive nature of the procedures. Therefore, a novel tool to simplify the diagnostic flow has been recently in enormous demand. In this review, we focus on recent progress in the following clinically important topics of PA: prevalence of PA and its subtypes, newly revealed histopathological classification of aldosterone-producing lesions, novel diagnostic biomarkers and prediction scores. More effective strategy to diagnose PA based on better understanding of its epidemiology and pathology should lead to early detection of PA and could decrease the cardiovascular and renal complications of the patients.

Development and Validation of Prediction Models for Subtype Diagnosis of Patients With Primary Aldosteronism

CONTEXT

Primary aldosteronism (PA) comprises unilateral (lateralized [LPA]) and bilateral disease (BPA). The identification of LPA is important to recommend potentially curative adrenalectomy. Adrenal venous sampling (AVS) is considered the gold standard for PA subtyping, but the procedure is available in few referral centers.

OBJECTIVE

To develop prediction models for subtype diagnosis of PA using patient clinical and biochemical characteristics.

DESIGN, PATIENTS AND SETTING

Patients referred to a tertiary hypertension unit. Diagnostic algorithms were built and tested in a training (N = 150) and in an internal validation cohort (N = 65), respectively. The models were validated in an external independent cohort (N = 118).

MAIN OUTCOME MEASURE

Regression analyses and supervised machine learning algorithms were used to develop and validate 2 diagnostic models and a 20-point score to classify patients with PA according to subtype diagnosis.

RESULTS

Six parameters were associated with a diagnosis of LPA (aldosterone at screening and after confirmatory testing, lowest potassium value, presence/absence of nodules, nodule diameter, and computed tomography results) and were included in the diagnostic models. Machine learning algorithms displayed high accuracy at training and internal validation (79.1%-93%), whereas a 20-point score reached an area under the curve of 0.896, and a sensitivity/specificity of 91.7/79.3%. An integrated flowchart correctly addressed 96.3% of patients to surgery and would have avoided AVS in 43.7% of patients. The external validation on an independent cohort confirmed a similar diagnostic performance.

CONCLUSIONS

Diagnostic modelling techniques can be used for subtype diagnosis and guide surgical decision in patients with PA in centers where AVS is unavailable.

Abdominal aortic calcification is more severe in unilateral primary aldosteronism patients and is associated with elevated aldosterone and parathyroid hormone levels

Primary aldosteronism (PA) is associated with a higher prevalence of abdominal aortic calcification (AAC). Unilateral and bilateral PA are the most common subtypes of PA. However, no studies have addressed the difference in the prevalence of AAC between the two subtypes. In addition to aldosterone, parathyroid hormone (PTH), an important regulator of calcium metabolism, was also reported to be elevated in individuals with unilateral PA. Therefore, we hypothesized that the prevalence of AAC may be higher in individuals with unilateral PA, which may be related to the plasma aldosterone concentration (PAC) and PTH levels. We included 156 PA patients who underwent adrenal venous sampling and 156 with essential hypertension (EH) matched by age and sex. Of the former, 76 were diagnosed with unilateral PA, and 80 were diagnosed with bilateral PA. The aortic calcification index (ACI) presented the severity of AAC and was measured by adrenal computed tomography scan. Our results showed that compared with the EH group, the prevalence and severity of AAC were higher in PA patients (32.7 vs. 19.6%; 4.32 ± 3.61% vs. 2.53 ± 2.42%, respectively). In the PA subgroup analysis, unilateral PA was associated with a higher and more severe AAC than bilateral PA (40.7 vs. 25.0%; 5.12 ± 4.07% vs. 3.08 ± 2.34%, respectively). Moreover, PAC and PTH levels were higher in individuals with unilateral PA than in those with bilateral PA (P < 0.05). After risk adjustment, multivariate regression analysis revealed that PAC and PTH were positively-associated with AAC in patients with PA (P < 0.05). In conclusion, unilateral PA patients exhibited a higher prevalence of AAC and more severe AAC due to elevated PAC and PTH levels.

Application of strict criteria in adrenal venous sampling increases the proportion of missed patients with unilateral disease who benefit from surgery for primary aldosteronism

OBJECTIVES

Adrenal vein sampling (AVS) is intended to confirm unilateral forms of primary aldosteronism, which are amenable to surgical cure. Excessively strict AVS criteria to define lateralization may result in many patients incorrectly categorized as bilateral primary aldosteronism and opportunity for surgical cure missed.

METHODS

Retrospective review of an AVS-primary aldosteronism database in which surgical cases are verified by standardized outcomes. Having used 'less strict' AVS criteria for lateralization, we examined the distribution of AVS lateralization indices in our confirmed unilateral primary aldosteronism cases both with and without cosyntropin stimulation. The proportion of proven unilateral cases that would have been missed with stricter AVS interpretation criteria was calculated. Particular focus was given to the proportion of missed cases according to use of international guidelines. False-positive lateralization with 'less strict' interpretation was also calculated.

RESULTS

Of 80 surgical primary aldosteronism cases, 10-23% would have been missed with AVS lateralization indices of 3 : 1 to 5 : 1, with or without cosyntropin. If strict selectivity indices (for confirmation of catheterization) were combined with strict lateralization indices, up to 70% of unilateral primary aldosteronism cases could have been missed. Use of Endocrine Society AVS guidelines would have missed 21-43% of proven unilateral cases. 'Less strict' AVS interpretation yielded one case (1.2%) of false lateralization.

CONCLUSION

Excessively strict AVS interpretation criteria will result in a high rate of missed unilateral primary aldosteronism with subsequent loss of opportunity for intervention. Use of more lenient lateralization criteria will improve the detection rate of unilateral primary aldosteronism with very low false-positive rate.

A novel clinical nomogram to predict bilateral hyperaldosteronism in Chinese patients with primary aldosteronism

CONTEXT

Adrenal venous sampling (AVS) is recommended as the gold standard for subtype classification in primary aldosteronism (PA); however, this approach has limited availability.

OBJECTIVE

We aimed to develop a novel clinical nomogram to predict PA subtype based on routine variables, thereby reducing the number of candidates for AVS.

PATIENTS AND METHOD

Patients were randomly divided into a training set (n = 185) and a validation set (n = 79). Risk factors for idiopathic hyperaldosteronism (IHA) differentiating from aldosterone-producing adenoma (APA) were identified using logistic regression analysis. A nomogram was constructed to predict the probability of IHA. A receiver operating characteristic (ROC) curve and a calibration plot were applied to assess the predictive value. Then, 115 patients were prospectively enrolled, and a nomogram was used to predict the subtypes before AVS.

RESULTS

Body mass index (BMI), serum potassium and computed tomography (CT) finding were adopted in the nomogram. The nomogram presented an area under the ROC (AUC) of 0.924 (95% CI: 0.875-0.957), sensitivity of 86.59% and specificity of 87.38% in the training set and an AUC of 0.894 (95% CI: 0.804-0.952), sensitivity of 82.86% and specificity of 84.09% in the validation set. Predicted probability and actual probability matched well in the nomogram (Hosmer-Lemeshow test: P > 0.05). Using the nomogram as a surrogate to predict IHA in the prospective set before AVS, the specificity reached 100% when we increased the threshold to a probability of 90%.

CONCLUSION

We have developed a tool that is able to predict IHA in patients with PA and potentially avoid AVS.

Clinical characteristics of snoring patients with primary aldosteronism and obstructive sleep apnea-hypopnea syndrome

The 2016 guideline on the work-up of primary aldosteronism recommended that patients with obstructive sleep apnea–hypopnea syndrome (OSAS) be screened. This study aimed to identify the clinical characteristics of snoring patients with primary aldosteronism (PA) complicated by OSAS. Sixty-eight self-reported or witnessed snoring patients and 609 non-snoring patients diagnosed with PA between 2010 and 2015 were recruited in this retrospective study. Compared to non-snoring patients, snoring patients had significantly (P < 0.05) higher body mass index (BMI), diastolic blood pressure (DBP), and serum and urinary sodium, as well as lower estimated glomerular filtration rate (eGFR). Moreover, snoring patients exhibited significantly (P < 0.01) higher plasma renin activity levels and lower plasma aldosterone levels and aldosterone-to-renin activity ratios (ARRs) than patients with PA alone. When age, sex, duration of hypertension, and BMI were matched between groups, snoring patients still showed significantly (P < 0.05) higher plasma renin activity, serum and urinary sodium, and lower ARR and eGFR than those in the PA-only group. All 68 snoring patients underwent polysomnography, with 7 having mild (apnea–hypopnea index (AHI) ≥ 5 and <15), 21 moderate (AHI ≥ 15 and <30), and 40 severe (AHI ≥ 30) OSAS. The BMI of patients with OSAS was negatively correlated with the lowest SaO₂ (r = −0.318, P = 0.018) but not with the AHI. In conclusion, snoring patients with PA tend to have increased BMI and DBP, as well as decreased eGFR and ARR. Snoring patients with PA had higher prevalence of moderate-to-severe OSAS.