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Multivariate prognostic factors analysis for second-line chemotherapy in advanced biliary tract cancer
BACKGROUND: The role of second-line chemotherapy (CT) is not established in advanced biliary tract cancer (aBTC). We investigated the outcome of aBTC patients treated with second-line CT and devised a prognostic model. METHODS: Baseline clinical and laboratory data of 300 consecutive aBTC patients w...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4007244/ https://www.ncbi.nlm.nih.gov/pubmed/24714745 http://dx.doi.org/10.1038/bjc.2014.190 |
Sumario: | BACKGROUND: The role of second-line chemotherapy (CT) is not established in advanced biliary tract cancer (aBTC). We investigated the outcome of aBTC patients treated with second-line CT and devised a prognostic model. METHODS: Baseline clinical and laboratory data of 300 consecutive aBTC patients were collected and association with overall survival (OS) was investigated by multivariable Cox models. RESULTS: The following parameters resulted independently associated with longer OS: Eastern Cooperative Oncology Group performance status of 0 (P<0.001; hazard ratio (HR), 0.348; 95% confidence interval (CI) 0.215–0.562), CA19.9 lower than median (P=0.013; HR, 0.574; 95% CI 0.370–0.891), progression-free survival after first-line CT ⩾6 months (P=0.027; HR, 0.633; 95% CI 0.422–0.949) and previous surgery on primary tumour (P=0.027; HR, 0.609; 95% CI 0.392–0.945). We grouped the 249 patients with complete data available into three categories according to the number of fulfilled risk factors: median OS times for good-risk (zero to one factors), intermediate-risk (two factors) and poor-risk (three to four factors) groups were 13.1, 6.6 and 3.7 months, respectively (P<0.001). CONCLUSIONS: Easily available clinical and laboratory factors predict prognosis of aBTC patients undergoing second-line CT. This model allows individual patient-risk stratification and may help in treatment decision and trial design. |
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