Indonesian
Albanian
Arabic
Armenian
Azerbaijani
Belarusian
Bengali
Bosnian
Catalan
Czech
Danish
Deutsch
Dutch
English
Estonian
Finnish
Français
Greek
Haitian Creole
Hebrew
Hindi
Hungarian
Icelandic
Indonesian
Irish
Italian
Japanese
Korean
Latvian
Lithuanian
Macedonian
Mongolian
Norwegian
Persian
Polish
Portuguese
Romanian
Russian
Serbian
Slovak
Slovenian
Spanish
Swahili
Swedish
Turkish
Ukrainian
Vietnamese
Български
中文(简体)
中文(繁體)
Frontiers of Medicine 2015-Sep

Exploring the diagnosis markers for gallbladder cancer based on clinical data.

Hanya pengguna terdaftar yang dapat menerjemahkan artikel
Masuk daftar
Tautan disimpan ke clipboard
Lingqiang Zhang
Runchen Miao
Xiude Zhang
Wei Chen
Yanyan Zhou
Ruitao Wang
Ruiyao Zhang
Qing Pang
Xinsen Xu
Chang Liu

Kata kunci

Abstrak

Presently, no effective markers are available to facilitate gallbladder cancer (GBC) diagnosis. This study aims to explore available markers for GBC diagnosis. Clinical data of 144 GBC and 116 cholelithiasis patients were retrospectively reviewed. Logistic regression analysis was performed to evaluate GBC risk factors. A receiver operating characteristic (ROC) curve was used to assess the diagnosis value of the risk factors. By comparing the characteristic of GBC and cholelithiasis patients, the following factors exhibited statistical difference: age, gender, gallstones, total bilirubin (TB), alkaline phosphatase (ALP), aspartate aminotransferase (AST), alanine aminotransferase (ALT), platelet count (PLT), CA125 (carcinoembryonic antigen 125), and CA199 (carbohydrate antigen 199). Logistic regression analysis indicated that age [odds ratio (OR), 1.032; 95%confidence interval (95% CI), 1.004 to 1.061; P = 0.024], gender (OR, 0.346; 95% CI, 0.167 to 0.716; P = 0.004), gallstones (OR, 0.027; 95% CI, 0.007 to 0.095; P < 0.001), ALP (OR, 1.003; 95% CI, 1.000 to 1.006; P = 0.032), TB (OR, 1.004; 95% CI, 1.000 to 1.009; P = 0.042), and CA125 (OR, 1.007; 95% CI, 1.002 to 1.013; P = 0.011) were independent risk factors for GBC. According to the ROC curve, CA125 [area under curve (AUC), 0.720], ALP (AUC, 0.713), TB (AUC, 0.636), and age (AUC, 0.573) were valuable diagnosis markers. Additionally, based on the independent risk factors, the GBC diagnosis model was established. Age, TB, ALP, and CA125 can be used as auxiliary diagnosis factors of GBC. The diagnosis model provides a quantitative tool for GBC diagnosis when comprehensively considering various risk factors.

Bergabunglah dengan
halaman facebook kami

Database tanaman obat terlengkap yang didukung oleh sains

  • Bekerja dalam 55 bahasa
  • Pengobatan herbal didukung oleh sains
  • Pengenalan herbal melalui gambar
  • Peta GPS interaktif - beri tag herba di lokasi (segera hadir)
  • Baca publikasi ilmiah yang terkait dengan pencarian Anda
  • Cari tanaman obat berdasarkan efeknya
  • Atur minat Anda dan ikuti perkembangan berita, uji klinis, dan paten

Ketikkan gejala atau penyakit dan baca tentang jamu yang mungkin membantu, ketik jamu dan lihat penyakit dan gejala yang digunakan untuk melawannya.
* Semua informasi didasarkan pada penelitian ilmiah yang dipublikasikan

Google Play badgeApp Store badge