A novel noninvasive formula for predicting cirrhosis in patients with chronic hepatitis C.
Evaluating liver fibrosis is crucial for disease severity assessment, treatment decisions, and hepatocarcinogenic risk prediction among patients with chronic hepatitis C. In this retrospective multicenter study, we aimed to construct a novel model formula to predict cirrhosis. A total of 749 patient...
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2021
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oai:doaj.org-article:e69808e076ea4aec9a7fd56343d31f282021-12-02T20:08:18ZA novel noninvasive formula for predicting cirrhosis in patients with chronic hepatitis C.1932-620310.1371/journal.pone.0257166https://doaj.org/article/e69808e076ea4aec9a7fd56343d31f282021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0257166https://doaj.org/toc/1932-6203Evaluating liver fibrosis is crucial for disease severity assessment, treatment decisions, and hepatocarcinogenic risk prediction among patients with chronic hepatitis C. In this retrospective multicenter study, we aimed to construct a novel model formula to predict cirrhosis. A total of 749 patients were randomly allocated to training and validation sets at a ratio of 2:1. Liver stiffness measurement (LSM) was made via transient elastography using FibroScan. Patients with LSM ≥12.5 kPa were regarded as having cirrhosis. The best model formula for predicting cirrhosis was constructed based on factors significantly and independently associated with LSM (≥12.5 kPa) using multivariate regression analysis. Among the 749 patients, 198 (26.4%) had LSM ≥12.5 kPa. In the training set, multivariate analysis identified logarithm natural (ln) type IV collagen 7S, ln hyaluronic acid, and ln Wisteria floribunda agglutinin positive Mac-2-binding protein (WFA+-Mac-2 BP) as the factors that were significantly and independently associated with LSM ≥12.5 kPa. Thus, the formula was constructed as follows: score = -6.154 + 1.166 × ln type IV collagen 7S + 0.526 × ln hyaluronic acid + 1.069 × WFA+-Mac-2 BP. The novel formula yielded the highest area under the curve (0.882; optimal cutoff, -0.381), specificity (81.5%), positive predictive values (62.6%), and predictive accuracy (81.6%) for predicting LSM ≥12.5 kPa among fibrosis markers and indices. These results were almost similar to those in the validated set, indicating the reproducibility and validity of the novel formula. The novel formula scores were significantly, strongly, and positively correlated with LSM values in both the training and validation data sets (correlation coefficient, 0.721 and 0.762; p = 2.67 × 10-81 and 1.88 × 10-48, respectively). In conclusion, the novel formula was highly capable of diagnosing cirrhosis in patients with chronic hepatitis C and exhibited better diagnostic performance compared to conventional fibrosis markers and indices.Masanori AtsukawaAkihito TsubotaChisa KondoSawako Uchida-KobayashiKoichi TakaguchiAkemi TsutsuiAkito NozakiMakoto ChumaIsao HidakaTsuyoshi IshikawaMotoh IwasaYasuyuki TamaiMaki TobariKentaro MatsuuraYoshihito NaguraHiroshi AbeKeizo KatoKenta SuzukiTomomi OkuboTaeang AraiNorio ItokawaHidenori ToyodaMasaru EnomotoAkihiro TamoriYasuhito TanakaNorifumi KawadaYoshiyuki TakeiKatsuhiko IwakiriPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 9, p e0257166 (2021) |
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DOAJ |
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DOAJ |
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Medicine R Science Q |
| spellingShingle |
Medicine R Science Q Masanori Atsukawa Akihito Tsubota Chisa Kondo Sawako Uchida-Kobayashi Koichi Takaguchi Akemi Tsutsui Akito Nozaki Makoto Chuma Isao Hidaka Tsuyoshi Ishikawa Motoh Iwasa Yasuyuki Tamai Maki Tobari Kentaro Matsuura Yoshihito Nagura Hiroshi Abe Keizo Kato Kenta Suzuki Tomomi Okubo Taeang Arai Norio Itokawa Hidenori Toyoda Masaru Enomoto Akihiro Tamori Yasuhito Tanaka Norifumi Kawada Yoshiyuki Takei Katsuhiko Iwakiri A novel noninvasive formula for predicting cirrhosis in patients with chronic hepatitis C. |
| description |
Evaluating liver fibrosis is crucial for disease severity assessment, treatment decisions, and hepatocarcinogenic risk prediction among patients with chronic hepatitis C. In this retrospective multicenter study, we aimed to construct a novel model formula to predict cirrhosis. A total of 749 patients were randomly allocated to training and validation sets at a ratio of 2:1. Liver stiffness measurement (LSM) was made via transient elastography using FibroScan. Patients with LSM ≥12.5 kPa were regarded as having cirrhosis. The best model formula for predicting cirrhosis was constructed based on factors significantly and independently associated with LSM (≥12.5 kPa) using multivariate regression analysis. Among the 749 patients, 198 (26.4%) had LSM ≥12.5 kPa. In the training set, multivariate analysis identified logarithm natural (ln) type IV collagen 7S, ln hyaluronic acid, and ln Wisteria floribunda agglutinin positive Mac-2-binding protein (WFA+-Mac-2 BP) as the factors that were significantly and independently associated with LSM ≥12.5 kPa. Thus, the formula was constructed as follows: score = -6.154 + 1.166 × ln type IV collagen 7S + 0.526 × ln hyaluronic acid + 1.069 × WFA+-Mac-2 BP. The novel formula yielded the highest area under the curve (0.882; optimal cutoff, -0.381), specificity (81.5%), positive predictive values (62.6%), and predictive accuracy (81.6%) for predicting LSM ≥12.5 kPa among fibrosis markers and indices. These results were almost similar to those in the validated set, indicating the reproducibility and validity of the novel formula. The novel formula scores were significantly, strongly, and positively correlated with LSM values in both the training and validation data sets (correlation coefficient, 0.721 and 0.762; p = 2.67 × 10-81 and 1.88 × 10-48, respectively). In conclusion, the novel formula was highly capable of diagnosing cirrhosis in patients with chronic hepatitis C and exhibited better diagnostic performance compared to conventional fibrosis markers and indices. |
| format |
article |
| author |
Masanori Atsukawa Akihito Tsubota Chisa Kondo Sawako Uchida-Kobayashi Koichi Takaguchi Akemi Tsutsui Akito Nozaki Makoto Chuma Isao Hidaka Tsuyoshi Ishikawa Motoh Iwasa Yasuyuki Tamai Maki Tobari Kentaro Matsuura Yoshihito Nagura Hiroshi Abe Keizo Kato Kenta Suzuki Tomomi Okubo Taeang Arai Norio Itokawa Hidenori Toyoda Masaru Enomoto Akihiro Tamori Yasuhito Tanaka Norifumi Kawada Yoshiyuki Takei Katsuhiko Iwakiri |
| author_facet |
Masanori Atsukawa Akihito Tsubota Chisa Kondo Sawako Uchida-Kobayashi Koichi Takaguchi Akemi Tsutsui Akito Nozaki Makoto Chuma Isao Hidaka Tsuyoshi Ishikawa Motoh Iwasa Yasuyuki Tamai Maki Tobari Kentaro Matsuura Yoshihito Nagura Hiroshi Abe Keizo Kato Kenta Suzuki Tomomi Okubo Taeang Arai Norio Itokawa Hidenori Toyoda Masaru Enomoto Akihiro Tamori Yasuhito Tanaka Norifumi Kawada Yoshiyuki Takei Katsuhiko Iwakiri |
| author_sort |
Masanori Atsukawa |
| title |
A novel noninvasive formula for predicting cirrhosis in patients with chronic hepatitis C. |
| title_short |
A novel noninvasive formula for predicting cirrhosis in patients with chronic hepatitis C. |
| title_full |
A novel noninvasive formula for predicting cirrhosis in patients with chronic hepatitis C. |
| title_fullStr |
A novel noninvasive formula for predicting cirrhosis in patients with chronic hepatitis C. |
| title_full_unstemmed |
A novel noninvasive formula for predicting cirrhosis in patients with chronic hepatitis C. |
| title_sort |
novel noninvasive formula for predicting cirrhosis in patients with chronic hepatitis c. |
| publisher |
Public Library of Science (PLoS) |
| publishDate |
2021 |
| url |
https://doaj.org/article/e69808e076ea4aec9a7fd56343d31f28 |
| work_keys_str_mv |
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| _version_ |
1718375213612138496 |