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联合血清肿瘤标志物建立预测厄洛替尼治疗复治非小细胞肺癌生存模型

BACKGROUND AND OBJECTIVE: Molecular targeting therapy is the direction of individualized treatment of lung cancer, scholars has been established targeted therapy prediction models which provide more guidance for clinical individual therapy. This study investigated the relationship among pulmonary su...

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Formato: Online Artículo Texto
Lenguaje:English
Publicado: 中国肺癌杂志编辑部 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6000447/
https://www.ncbi.nlm.nih.gov/pubmed/24854556
http://dx.doi.org/10.3779/j.issn.1009-3419.2014.05.05
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description BACKGROUND AND OBJECTIVE: Molecular targeting therapy is the direction of individualized treatment of lung cancer, scholars has been established targeted therapy prediction models which provide more guidance for clinical individual therapy. This study investigated the relationship among pulmonary surfactant-associated protein D (SP-D), transforming growth factor α (TGF-α), matrix metalloproteinase 9 (MMP-9), tissue polypeptide specific antigen (TPS), and Krebs von den Lungen-6 (KL-6) and response as well as survival in the patients with recurrent non-small cell lung cancer, which Erlotinib was as second line treatment after failure to chemotherapy. This study also established a predictive prognostic model. METHODS: Serum levels of SP-D, TGF-α, MMP-9, TPS, and KL-6 in 114 patients before erlotinib treatment were detected by ELISA method. Combined with clinical factors, these levels were used to investigate the relationship with efficacy in erlotinib treatment and construct a predicted prognostic model by Kaplan-Meier curve and Cox proportional hazard model multivariate analysis. RESULTS: The objective response rate (ORR) and disease control rate (DCR) in the 114 patients, were 22.8% (26/114) and 72.8% (83/114), to Erlotinib treatment respectively. The median progression-free survival (PFS) and one year survival rate with Erlotinib treatment were 5.13 months and 69.3%, respectively. Patients in the SP-D > 110 ng/mL group exhibited more ORR (33.3% vs 13.3%, P=0.011) and DCR (83.3% vs 63.3%, P=0.017) than those in the ≤110 ng/mL group. Patients in the MMP-9≤535 ng/mL group showed more DCR (83.9%) than those in the > 535 ng/mL group (62.1%) (P=0.009). Patients in the TPS < 80 U/L group showed more DCR (82.4%) than those in the ≥80 U/L group (55.0%) (P=0.002). The SP-D > 110 ng/mL (5.95 months vs 3.25 months, P=0.009), MMP-9≤535 ng/mL (5.83 months vs 3.47 months, P=0.046), KL-6 < 500 U/mL (6.03 months vs 3.40 months, P=0.040), and TPS < 80 U/L (6.15 months vs 2.42 months, P=0.014) groups showed better PFS. Multivariate analysis showed that current or ever-smoker, wild style of EGFR status, progression after prior chemotherapy, absence of skin rash, elevated serum LDH level, and TPS≥80 U/L were independent adverse prognostic factors for PFS. These six factors were used in the prognostic model. Patients were categorized into four prognosis risk groups based on the prognostic index from the model, namely, low risk, intermediate low risk, intermediate risk, and high risk groups. The median PFS of good, intermediate, poor, and very poor prognosis groups were 9.12, 6.88, 3.52, and 0.93 months (P < 0.001), respectively. CONCLUSION: The prognostic model based on clinical parameters with TPS will be useful in identifying patients who might be most likely to benefit from Erlotinib therapy in the patients with recurrent non-small cell lung cancer.
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spelling pubmed-60004472018-07-06 联合血清肿瘤标志物建立预测厄洛替尼治疗复治非小细胞肺癌生存模型 Zhongguo Fei Ai Za Zhi 临床研究 BACKGROUND AND OBJECTIVE: Molecular targeting therapy is the direction of individualized treatment of lung cancer, scholars has been established targeted therapy prediction models which provide more guidance for clinical individual therapy. This study investigated the relationship among pulmonary surfactant-associated protein D (SP-D), transforming growth factor α (TGF-α), matrix metalloproteinase 9 (MMP-9), tissue polypeptide specific antigen (TPS), and Krebs von den Lungen-6 (KL-6) and response as well as survival in the patients with recurrent non-small cell lung cancer, which Erlotinib was as second line treatment after failure to chemotherapy. This study also established a predictive prognostic model. METHODS: Serum levels of SP-D, TGF-α, MMP-9, TPS, and KL-6 in 114 patients before erlotinib treatment were detected by ELISA method. Combined with clinical factors, these levels were used to investigate the relationship with efficacy in erlotinib treatment and construct a predicted prognostic model by Kaplan-Meier curve and Cox proportional hazard model multivariate analysis. RESULTS: The objective response rate (ORR) and disease control rate (DCR) in the 114 patients, were 22.8% (26/114) and 72.8% (83/114), to Erlotinib treatment respectively. The median progression-free survival (PFS) and one year survival rate with Erlotinib treatment were 5.13 months and 69.3%, respectively. Patients in the SP-D > 110 ng/mL group exhibited more ORR (33.3% vs 13.3%, P=0.011) and DCR (83.3% vs 63.3%, P=0.017) than those in the ≤110 ng/mL group. Patients in the MMP-9≤535 ng/mL group showed more DCR (83.9%) than those in the > 535 ng/mL group (62.1%) (P=0.009). Patients in the TPS < 80 U/L group showed more DCR (82.4%) than those in the ≥80 U/L group (55.0%) (P=0.002). The SP-D > 110 ng/mL (5.95 months vs 3.25 months, P=0.009), MMP-9≤535 ng/mL (5.83 months vs 3.47 months, P=0.046), KL-6 < 500 U/mL (6.03 months vs 3.40 months, P=0.040), and TPS < 80 U/L (6.15 months vs 2.42 months, P=0.014) groups showed better PFS. Multivariate analysis showed that current or ever-smoker, wild style of EGFR status, progression after prior chemotherapy, absence of skin rash, elevated serum LDH level, and TPS≥80 U/L were independent adverse prognostic factors for PFS. These six factors were used in the prognostic model. Patients were categorized into four prognosis risk groups based on the prognostic index from the model, namely, low risk, intermediate low risk, intermediate risk, and high risk groups. The median PFS of good, intermediate, poor, and very poor prognosis groups were 9.12, 6.88, 3.52, and 0.93 months (P < 0.001), respectively. CONCLUSION: The prognostic model based on clinical parameters with TPS will be useful in identifying patients who might be most likely to benefit from Erlotinib therapy in the patients with recurrent non-small cell lung cancer. 中国肺癌杂志编辑部 2014-05-20 /pmc/articles/PMC6000447/ /pubmed/24854556 http://dx.doi.org/10.3779/j.issn.1009-3419.2014.05.05 Text en 版权所有©《中国肺癌杂志》编辑部2014 https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 3.0) License. See: https://creativecommons.org/licenses/by/3.0/
spellingShingle 临床研究
联合血清肿瘤标志物建立预测厄洛替尼治疗复治非小细胞肺癌生存模型
title 联合血清肿瘤标志物建立预测厄洛替尼治疗复治非小细胞肺癌生存模型
title_full 联合血清肿瘤标志物建立预测厄洛替尼治疗复治非小细胞肺癌生存模型
title_fullStr 联合血清肿瘤标志物建立预测厄洛替尼治疗复治非小细胞肺癌生存模型
title_full_unstemmed 联合血清肿瘤标志物建立预测厄洛替尼治疗复治非小细胞肺癌生存模型
title_short 联合血清肿瘤标志物建立预测厄洛替尼治疗复治非小细胞肺癌生存模型
title_sort 联合血清肿瘤标志物建立预测厄洛替尼治疗复治非小细胞肺癌生存模型
topic 临床研究
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6000447/
https://www.ncbi.nlm.nih.gov/pubmed/24854556
http://dx.doi.org/10.3779/j.issn.1009-3419.2014.05.05
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