Developments in Primary Aldosteronism Subtyping Using Steroid Profiling

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.

Report from the HarmoSter study: inter-laboratory comparison of LC-MS/MS measurements of corticosterone, 11-deoxycortisol and cortisone

OBJECTIVES

Liquid chromatography-tandem mass spectrometry (LC-MS/MS) panels that include glucocorticoid-related steroids are increasingly used to characterize and diagnose adrenal cortical diseases. Limited information is currently available about reproducibility of these measurements among laboratories. The aim of the study was to compare LC-MS/MS measurements of corticosterone, 11-deoxycortisol and cortisone at eight European centers and assess the performance after unification of calibration.

METHODS

Seventy-eight patient samples and commercial calibrators were measured twice by laboratory-specific procedures. Results were obtained according to in-house and external calibration. We evaluated intra-laboratory and inter-laboratory imprecision, regression and agreement against performance specifications derived from 11-deoxycortisol biological variation.

RESULTS

Intra-laboratory CVs ranged between 3.3 and 7.7%, 3.3 and 11.8% and 2.7 and 12.8% for corticosterone, 11-deoxycortisol and cortisone, with 1, 4 and 3 laboratories often exceeding the maximum allowable imprecision (MAI), respectively. Median inter-laboratory CVs were 10.0, 10.7 and 6.2%, with 38.5, 50.7 and 2.6% cases exceeding the MAI for corticosterone, 11-deoxycortisol and cortisone, respectively. Median laboratory bias vs. all laboratory-medians ranged from -5.6 to 12.3% for corticosterone, -14.6 to 12.4% for 11-deoxycortisol and -4.0 to 6.5% for cortisone, with few cases exceeding the total allowable error. Modest deviations were found in regression equations among most laboratories. External calibration did not improve 11-deoxycortisol and worsened corticosterone and cortisone inter-laboratory comparability.

CONCLUSIONS

Method imprecision was variable. Inter-laboratory performance was reasonably good. However, cases with imprecision and total error above the acceptable limits were apparent for corticosterone and 11-deoxycortisol. Variability did not depend on calibration but apparently on imprecision, accuracy and specificity of individual methods. Tools for improving selectivity and accuracy are required to improve harmonization.

Integration of artificial intelligence and plasma steroidomics with laboratory information management systems: application to primary aldosteronism

Objectives

Mass spectrometry-based steroidomics combined with machine learning (ML) provides a potentially powerful approach in endocrine diagnostics, but is hampered by limitations in the conveyance of results and interpretations to clinicians. We address this shortcoming by integration of the two technologies with a laboratory information management systems (LIMS) model.

Methods

The approach involves integration of ML algorithm-derived models with commercially available mathematical programming software and a web-based LIMS prototype. To illustrate clinical utility, the process was applied to plasma steroidomics data from 22 patients tested for primary aldosteronism (PA).

Results

Once mass spectrometry data are uploaded into the system, automated processes enable generation of interpretations of steroid profiles from ML models. Generated reports include plasma concentrations of steroids in relation to age- and sex-specific reference intervals along with results of ML models and narrative interpretations that cover probabilities of PA. If PA is predicted, reports include probabilities of unilateral disease and mutations of KCNJ5 known to be associated with successful outcomes of adrenalectomy. Preliminary results, with no overlap in probabilities of disease among four patients with and 18 without PA and correct classification of all four patients with unilateral PA including three of four with KCNJ5 mutations, illustrate potential utility of the approach to guide diagnosis and subtyping of patients with PA.

Conclusions

The outlined process for integrating plasma steroidomics data and ML with LIMS may facilitate improved diagnostic-decision-making when based on higher-dimensional data otherwise difficult to interpret. The approach is relevant to other diagnostic applications involving ML.

Reassessment of Postural Stimulation Testing as a Simple Tool to Identify a Subgroup of Patients With Unilateral Primary Aldosteronism

CONTEXT

Adrenal vein sampling (AVS) represents the current diagnostic gold standard for differentiation between unilateral and bilateral primary aldosteronism (PA). Postural stimulation testing (PST) has been used to provide additional diagnostic information.

OBJECTIVE

This work aimed to evaluate the diagnostic utility of PST in the differential diagnosis of PA.

METHODS

This cohort study was conducted at a single tertiary reference center. We analyzed 106 PST performed between 2008 and 2020. Diagnosis of PA and cause of PA were determined according to the Endocrine Society Clinical Practice Guideline, taking into account results of saline infusion testing, AVS, preoperative imaging, and outcome after medical or surgical treatment. The suggested cutoffs for the diagnosis of unilateral PA were revisited and optimized for high specificity using receiver operating characteristics (ROC) analysis.

RESULTS

A total of 106 patients had confirmed PA (unilateral PA: n = 55, bilateral PA: n = 29, AVS unsuccessful/declined by patients: n = 22). Based on decreased aldosterone plasma concentration of 28% or more after 4 hours in the upright position, the PST showed a sensitivity of 36.4% at a specificity of 100% to identify unilateral disease (area under the curve [AUC] = 0.72; 95% CI, 0.62-0.83; P = .001). In patients with valid testing (drop of cortisol of 10% or more after 4 hours, n = 53) the sensitivity of PST rose to 51.4% at a specificity of 100% (AUC = 0.77; 95% CI, 0.65-0.90; P = .001).

CONCLUSION

The high specificity of 100% for the detection of unilateral PA in patients with decreased aldosterone by at least 28% after 4 hours makes PST a simple, noninvasive contribution to subtype differentiation in PA.

Urine steroid profile as a new promising tool for the evaluation of adrenal tumors. Literature review

PURPOSE

To review the literature assessing the diagnostic performance of urinary steroid profiling (USP) by high-performance liquid chromatography (LC-MS) or gas chromatography (GC) coupled to mass spectrometry (MS) in the evaluation of adrenal lesions, both in terms of functionality and malignancy.

RESULTS

The evaluation of adrenal incidentalomas (AI) aims to rule out malignancy and hormone excess. Current diagnostic protocols have several limitations and include time consuming and relatively complicated multi-step processes in most cases. On the contrary, USP by LC-MS/MS or LC-GC/MS offer an easy, comprehensive and non-invasive assessment of adrenal steroid secretion. USP complements current workups used in the evaluation of AIs by improving our ability to identify malignancy and/or autonomous hormone secretion.

CONCLUSIONS

Urine steroid profiling by LC-MS/MS and GC-MS allows a thorough, non-invasive, assessment of adrenal steroidogenesis as a whole which complement the current evaluation of AIs, and holds a promising role in the diagnosis of autonomous cortisol secretion, primary aldosteronism, and adrenal malignancy.

Progress in Primary Aldosteronism 2019: New Players on the Block?

Primary aldosteronism (PA) is characterized by hypertension caused by inappropriately high adrenal aldosterone secretion, consecutively low plasma renin, and an elevated aldosterone to renin ratio. It is nowadays the universally accepted main cause of endocrine hypertension. According to the most recent epidemiological data, PA is present in 5.8% of unselected hypertensives in primary care, 6-12% of hypertensives treated in hypertension centers, and up to 30% in subjects with resistant hypertension 1. Despite this high prevalence, a recent survey demonstrated that screening for PA is not universally followed. Renin and aldosterone measurements, the basis for PA screening, are currently performed by only 7% of general practitioners in Italy and 8% in Germany 2. Accordingly, the prevalence of PA was low with 1% among hypertensives in Italy and 2% in Germany. In a retrospective cohort study of 4660 patients with resistant hypertension in California the screening rate for PA was 2.1% 3. Based on these data, it is clear that we still miss the majority of PA cases, despite advances in diagnosis and therapy.