A simplified primary aldosteronism surgical outcome score is a useful prediction model when target organ damage is unknown – Retrospective cohort study

Abstract

Background Cure of hypertension after adrenalectomy for primary aldosteronism is no certainty and therefore preoperative patient counseling is essential. The Primary Aldosteronism Surgical Outcome (PASO) Score is a useful prediction model with an area under the curve (AUC) of 0.839. The PASO Score includes ‘Target Organ Damage’ (TOD) (i.e., left ventricular hypertrophy and/or microalbuminuria), which is often unavailable during preoperative counseling and might therefore limit its use in clinical practice. We hypothesized that the PASO score would still be useful if TOD is unknown at time of counseling. Therefore, we aimed to examine the predictive performance of the simplified PASO Score, without taking TOD into account. Materials and methods In this retrospective cohort study, patients who underwent unilateral adrenalectomy between 2010 and 2016 in 16 medical centers from North America, Europe and Australia were included. TOD was unknown in our database and therefore assigned as absent. Patients were classified as complete, partial or absent clinical success using the PASO consensus criteria. Results A total of 380 (73.9%) patients were eligible for analysis. Complete, partial and absent clinical success were observed in 29.5%, 55.8% and 14.7% of patients, respectively. The simplified PASO Score had an AUC of 0.730 (95% confidence interval 0.674–0.785) in our total cohort. Conclusion Without taking TOD into account, the simplified PASO Score had a lower predictive value as compared to the original derivation cohort. Ideally, the complete PASO Score should be used, but when data on TOD are not readily available, the simplified PASO Score is a useful and reasonable alternative.

Prognostic models to predict complete resolution of hypertension after adrenalectomy in primary aldosteronism: A systematic review and meta‐analysis

“…Models without external validation studies Fisher discriminant model 20 Simplified primary aldosteronism surgical outcome score 23 Leung et al's scoring system 14 Wang et al's model 30 …”

“…For prognostic models with less than 3 external validation studies, 9 models were developed to predict CRH, 14,15,18,20,21,29,30,43 of which 1 23 was a simplified version of the PASO score. Due to the limited information on the predictive performance outside the model development setting, we would not yet consider these models ready for use in clinical practice.…”

“…Except for the aldosteronoma resolution score (ARS) model, we were unable to perform prespecified subgroup analysis for the other models due to the low number of studies. | 23 was estimated using equations proposed by Debray et al 46 Where the AUC was not reported, we did not estimate it.…”

“…Several presurgical prognostic factors have been identified that portend a favourable clinical outcome, including younger age, female sex, lower body mass index, a short history of hypertension, number of antihypertensive drugs and/or chronic kidney disease 6,10–12,14–22 . These factors have often been combined through statistical modelling methods to develop a weighted prognostic models that is able to accurately and reliably predict the likelihood of surgical and clinical outcomes 14–21,23 . Such models help clinicians assess the prognosis for an individual patient and enhance a shared decision‐making process.…”

“…6,[10][11][12][14][15][16][17][18][19][20][21][22] These factors have often been combined through statistical modelling methods to develop a weighted prognostic models that is able to accurately and reliably predict the likelihood of surgical and clinical outcomes. [14][15][16][17][18][19][20][21]23 Such models help clinicians assess the prognosis for an individual patient and enhance a shared decision-making process. To identify the bestperforming tool for prognostication of adrenalectomy in UPA, a comprehensive evaluation of all currently available prognostic models along with a meta-analysis of their predictive performance in external validation studies is urgently needed.…”