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Finding the optimal candidate for shock wave lithotripsy: external validation and comparison of five prediction models
We aimed to externally validate five previously published predictive models (Ng score, Triple D score, S(3)HoCKwave score, Kim nomogram, Niwa nomogram) for shock wave lithotripsy (SWL) single-session outcomes in patients with a solitary stone in the upper ureter. The validation cohort included patie...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10082105/ https://www.ncbi.nlm.nih.gov/pubmed/37027057 http://dx.doi.org/10.1007/s00240-023-01444-4 |
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author | Popiolek, Marcin Jendeberg, Johan Sundqvist, Pernilla Wagenius, Magnus Lidén, Mats |
author_facet | Popiolek, Marcin Jendeberg, Johan Sundqvist, Pernilla Wagenius, Magnus Lidén, Mats |
author_sort | Popiolek, Marcin |
collection | PubMed |
description | We aimed to externally validate five previously published predictive models (Ng score, Triple D score, S(3)HoCKwave score, Kim nomogram, Niwa nomogram) for shock wave lithotripsy (SWL) single-session outcomes in patients with a solitary stone in the upper ureter. The validation cohort included patients treated with SWL from September 2011 to December 2019 at our institution. Patient-related variables were retrospectively collected from the hospital records. Stone-related data including all measurements were retrieved from computed tomography prior to SWL. We estimated discrimination using area under the curve (AUC), calibration, and clinical net benefit based on decision curve analysis (DCA). A total of 384 patients with proximal ureter stones treated with SWL were included in the analysis. Median age was 55.5 years, and 282 (73%) of the sample were men. Median stone length was 8.0 mm. All models significantly predicted the SWL outcomes after one session. S(3)HoCKwave score, Niwa, and Kim nomograms had the highest accuracy in predicting outcomes, with AUC 0.716, 0.714 and 0.701, respectively. These three models outperformed both the Ng (AUC: 0.670) and Triple D (AUC: 0.667) scoring systems, approaching statistical significance (P = 0.05). Of all the models, the Niwa nomogram showed the strongest calibration and highest net benefit in DCA. To conclude, the models showed small differences in predictive power. The Niwa nomogram, however, demonstrated acceptable discrimination, the most accurate calibration, and the highest net benefit whilst having relatively simple design. Therefore, it could be useful for counselling patients with a solitary stone in the upper ureter. |
format | Online Article Text |
id | pubmed-10082105 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-100821052023-04-09 Finding the optimal candidate for shock wave lithotripsy: external validation and comparison of five prediction models Popiolek, Marcin Jendeberg, Johan Sundqvist, Pernilla Wagenius, Magnus Lidén, Mats Urolithiasis Research We aimed to externally validate five previously published predictive models (Ng score, Triple D score, S(3)HoCKwave score, Kim nomogram, Niwa nomogram) for shock wave lithotripsy (SWL) single-session outcomes in patients with a solitary stone in the upper ureter. The validation cohort included patients treated with SWL from September 2011 to December 2019 at our institution. Patient-related variables were retrospectively collected from the hospital records. Stone-related data including all measurements were retrieved from computed tomography prior to SWL. We estimated discrimination using area under the curve (AUC), calibration, and clinical net benefit based on decision curve analysis (DCA). A total of 384 patients with proximal ureter stones treated with SWL were included in the analysis. Median age was 55.5 years, and 282 (73%) of the sample were men. Median stone length was 8.0 mm. All models significantly predicted the SWL outcomes after one session. S(3)HoCKwave score, Niwa, and Kim nomograms had the highest accuracy in predicting outcomes, with AUC 0.716, 0.714 and 0.701, respectively. These three models outperformed both the Ng (AUC: 0.670) and Triple D (AUC: 0.667) scoring systems, approaching statistical significance (P = 0.05). Of all the models, the Niwa nomogram showed the strongest calibration and highest net benefit in DCA. To conclude, the models showed small differences in predictive power. The Niwa nomogram, however, demonstrated acceptable discrimination, the most accurate calibration, and the highest net benefit whilst having relatively simple design. Therefore, it could be useful for counselling patients with a solitary stone in the upper ureter. Springer Berlin Heidelberg 2023-04-07 2023 /pmc/articles/PMC10082105/ /pubmed/37027057 http://dx.doi.org/10.1007/s00240-023-01444-4 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Research Popiolek, Marcin Jendeberg, Johan Sundqvist, Pernilla Wagenius, Magnus Lidén, Mats Finding the optimal candidate for shock wave lithotripsy: external validation and comparison of five prediction models |
title | Finding the optimal candidate for shock wave lithotripsy: external validation and comparison of five prediction models |
title_full | Finding the optimal candidate for shock wave lithotripsy: external validation and comparison of five prediction models |
title_fullStr | Finding the optimal candidate for shock wave lithotripsy: external validation and comparison of five prediction models |
title_full_unstemmed | Finding the optimal candidate for shock wave lithotripsy: external validation and comparison of five prediction models |
title_short | Finding the optimal candidate for shock wave lithotripsy: external validation and comparison of five prediction models |
title_sort | finding the optimal candidate for shock wave lithotripsy: external validation and comparison of five prediction models |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10082105/ https://www.ncbi.nlm.nih.gov/pubmed/37027057 http://dx.doi.org/10.1007/s00240-023-01444-4 |
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