Development and validation of subtype prediction scores for the workup of primary aldosteronism

JPAS Study Group

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Objectives: A subtype prediction score for primary aldosteronism has not yet been developed and validated using a large dataset. This study aimed to develop and validate a new subtype prediction score and to compare it with existing scores using a large multicenter database. Methods: In total, 1936 patients with primary aldosteronism were randomly assigned to the development and validation datasets, constituting 1290 and 646 patients, respectively. Three prediction scores were generated with or without confirmatory tests, using logistic regression analysis. In the validation dataset, new and existing prediction scores were compared using receiver operating characteristic curve, net reclassification improvement, and integrated discrimination improvement analyses. Results: The new prediction score is simply calculated using serum potassium levels [>3.9 mmol/l (four points); 3.5-3.9 mmol/l (three points)], the absence of adrenal nodules during computed tomography (three points), a baseline plasma aldosterone concentration of <210.0 pg/ ml (two points), a baseline aldosterone/renin ratio of less than 620 (two points), and female sex (one point). Using the validation dataset, we found that a new subtype prediction score of at least 8 had a positive predictive value of 93.5% for bilateral hyperaldosteronism. The new prediction score for bilateral hyperaldosteronism was better than the existing prediction scores in the receiver operating characteristic curve and net reclassification improvement analyses. Conclusion: The new prediction score has clear advantages over the existing prediction scores in terms of diagnostic accuracy, feasibility, and the potential for generalization in a large population. These data will help healthcare professionals to better select patients who require adrenal venous sampling.

Original languageEnglish
Pages (from-to)2269-2276
Number of pages8
JournalJournal of hypertension
Volume36
Issue number11
DOIs
Publication statusPublished - Jan 1 2018
Externally publishedYes

Fingerprint

Hyperaldosteronism
Aldosterone
ROC Curve
Renin
Potassium
Logistic Models
Tomography
Regression Analysis
Databases
Delivery of Health Care
Datasets
Serum
Population

All Science Journal Classification (ASJC) codes

  • Internal Medicine
  • Physiology
  • Cardiology and Cardiovascular Medicine

Cite this

Development and validation of subtype prediction scores for the workup of primary aldosteronism. / JPAS Study Group.

In: Journal of hypertension, Vol. 36, No. 11, 01.01.2018, p. 2269-2276.

Research output: Contribution to journalArticle

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title = "Development and validation of subtype prediction scores for the workup of primary aldosteronism",
abstract = "Objectives: A subtype prediction score for primary aldosteronism has not yet been developed and validated using a large dataset. This study aimed to develop and validate a new subtype prediction score and to compare it with existing scores using a large multicenter database. Methods: In total, 1936 patients with primary aldosteronism were randomly assigned to the development and validation datasets, constituting 1290 and 646 patients, respectively. Three prediction scores were generated with or without confirmatory tests, using logistic regression analysis. In the validation dataset, new and existing prediction scores were compared using receiver operating characteristic curve, net reclassification improvement, and integrated discrimination improvement analyses. Results: The new prediction score is simply calculated using serum potassium levels [>3.9 mmol/l (four points); 3.5-3.9 mmol/l (three points)], the absence of adrenal nodules during computed tomography (three points), a baseline plasma aldosterone concentration of <210.0 pg/ ml (two points), a baseline aldosterone/renin ratio of less than 620 (two points), and female sex (one point). Using the validation dataset, we found that a new subtype prediction score of at least 8 had a positive predictive value of 93.5{\%} for bilateral hyperaldosteronism. The new prediction score for bilateral hyperaldosteronism was better than the existing prediction scores in the receiver operating characteristic curve and net reclassification improvement analyses. Conclusion: The new prediction score has clear advantages over the existing prediction scores in terms of diagnostic accuracy, feasibility, and the potential for generalization in a large population. These data will help healthcare professionals to better select patients who require adrenal venous sampling.",
author = "{JPAS Study Group} and Hiroki Kobayashi and Masanori Abe and Masayoshi Soma and Yoshiyu Takeda and Isao Kurihara and Hiroshi Itoh and Hironobu Umakoshi and Mika Tsuiki and Takuyuki Katabami and Takamasa Ichijo and Norio Wada and Takanobu Yoshimoto and Yoshihiro Ogawa and Junji Kawashima and Masakatsu Sone and Nobuya Inagaki and Katsutoshi Takahashi and Minemori Watanabe and Yuichi Matsuda and Hirotaka Shibata and Kohei Kamemura and Toshihiko Yanase and Michio Otsuki and Yuichi Fujii and Koichi Yamamoto and Atsushi Ogo and Kazutaka Nanba and Akiyo Tanabe and Tomoko Suzuki and Mitsuhide Naruse",
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T1 - Development and validation of subtype prediction scores for the workup of primary aldosteronism

AU - JPAS Study Group

AU - Kobayashi, Hiroki

AU - Abe, Masanori

AU - Soma, Masayoshi

AU - Takeda, Yoshiyu

AU - Kurihara, Isao

AU - Itoh, Hiroshi

AU - Umakoshi, Hironobu

AU - Tsuiki, Mika

AU - Katabami, Takuyuki

AU - Ichijo, Takamasa

AU - Wada, Norio

AU - Yoshimoto, Takanobu

AU - Ogawa, Yoshihiro

AU - Kawashima, Junji

AU - Sone, Masakatsu

AU - Inagaki, Nobuya

AU - Takahashi, Katsutoshi

AU - Watanabe, Minemori

AU - Matsuda, Yuichi

AU - Shibata, Hirotaka

AU - Kamemura, Kohei

AU - Yanase, Toshihiko

AU - Otsuki, Michio

AU - Fujii, Yuichi

AU - Yamamoto, Koichi

AU - Ogo, Atsushi

AU - Nanba, Kazutaka

AU - Tanabe, Akiyo

AU - Suzuki, Tomoko

AU - Naruse, Mitsuhide

PY - 2018/1/1

Y1 - 2018/1/1

N2 - Objectives: A subtype prediction score for primary aldosteronism has not yet been developed and validated using a large dataset. This study aimed to develop and validate a new subtype prediction score and to compare it with existing scores using a large multicenter database. Methods: In total, 1936 patients with primary aldosteronism were randomly assigned to the development and validation datasets, constituting 1290 and 646 patients, respectively. Three prediction scores were generated with or without confirmatory tests, using logistic regression analysis. In the validation dataset, new and existing prediction scores were compared using receiver operating characteristic curve, net reclassification improvement, and integrated discrimination improvement analyses. Results: The new prediction score is simply calculated using serum potassium levels [>3.9 mmol/l (four points); 3.5-3.9 mmol/l (three points)], the absence of adrenal nodules during computed tomography (three points), a baseline plasma aldosterone concentration of <210.0 pg/ ml (two points), a baseline aldosterone/renin ratio of less than 620 (two points), and female sex (one point). Using the validation dataset, we found that a new subtype prediction score of at least 8 had a positive predictive value of 93.5% for bilateral hyperaldosteronism. The new prediction score for bilateral hyperaldosteronism was better than the existing prediction scores in the receiver operating characteristic curve and net reclassification improvement analyses. Conclusion: The new prediction score has clear advantages over the existing prediction scores in terms of diagnostic accuracy, feasibility, and the potential for generalization in a large population. These data will help healthcare professionals to better select patients who require adrenal venous sampling.

AB - Objectives: A subtype prediction score for primary aldosteronism has not yet been developed and validated using a large dataset. This study aimed to develop and validate a new subtype prediction score and to compare it with existing scores using a large multicenter database. Methods: In total, 1936 patients with primary aldosteronism were randomly assigned to the development and validation datasets, constituting 1290 and 646 patients, respectively. Three prediction scores were generated with or without confirmatory tests, using logistic regression analysis. In the validation dataset, new and existing prediction scores were compared using receiver operating characteristic curve, net reclassification improvement, and integrated discrimination improvement analyses. Results: The new prediction score is simply calculated using serum potassium levels [>3.9 mmol/l (four points); 3.5-3.9 mmol/l (three points)], the absence of adrenal nodules during computed tomography (three points), a baseline plasma aldosterone concentration of <210.0 pg/ ml (two points), a baseline aldosterone/renin ratio of less than 620 (two points), and female sex (one point). Using the validation dataset, we found that a new subtype prediction score of at least 8 had a positive predictive value of 93.5% for bilateral hyperaldosteronism. The new prediction score for bilateral hyperaldosteronism was better than the existing prediction scores in the receiver operating characteristic curve and net reclassification improvement analyses. Conclusion: The new prediction score has clear advantages over the existing prediction scores in terms of diagnostic accuracy, feasibility, and the potential for generalization in a large population. These data will help healthcare professionals to better select patients who require adrenal venous sampling.

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