Clinical Prognostic Factors in Gastric Cancer in Chinese Patients: Experience from the Cancer Hospital/Institute, Chinese Academy of Medical Sciences Yuankai.

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Presentation transcript:

Clinical Prognostic Factors in Gastric Cancer in Chinese Patients: Experience from the Cancer Hospital/Institute, Chinese Academy of Medical Sciences Yuankai Shi, M.D. Department of Medical Oncology, Cancer Hospital/Institute, Chinese Academy of Medical Sciences (CAMS)

Background 4th most common cancer, 2nd most common cause of death, 2/3 patients in developing countries, 42% of them in China Gastric cancer worldwide in 2002: Parkin DM, et al. CA Cancer J Clin. 2005;55:74

5-year overall survival: 15%-54% Parkin DM, et al. CA Cancer J Clin. 2005;55:74

Gastric cancer in China in 2005  Incidence: 376,000 new cases 376,000 new cases Third most common cancer Third most common cancer  Mortality: 24.71/ /10 5 Third from cancer Third cause of death from cancer Behind Lung cancer and Liver cancer Behind Lung cancer and Liver cancer

Objective   To evaluate the therapeutic effects and prognostic factors in patients with operable gastric cancer   To construct a prognostic model

Materials and methods  Identify prognostic factors with data from 1043 pts treated with combined modality therapy based on gastrectomy, between 1999 and 2002, in the Cancer Hospital, CAMS  Construct prognostic model with data from 1284 pts with combined modality treatment based on gastrectomy, between , in the Cancer Hospital, CAMS  Statistical analysis Life Table, Cox hazard proportional model, Logistic regression model Life Table, Cox hazard proportional model, Logistic regression model

Results 5-year 39% 15% 5-year OS 100% 91% 84% 61% 33% 19% 5%  Median survival: 39.5 mo  median relapse-free survival: 22.7 mo  5-y OS: 39%  5-y RFS: 15% 1043 pts with operable gastric cancer median follow-up: 51.6 mo

Univariate analysis in 1043 pts

Independent prognostic factors

All pts n=1284 Training sample n=963 Testing sample n=321 Randomized Prognostic equation Prognostic index Prognostic model Construct Validate

Fig. Overall survival (OS) and relapse-free survival (RFS) for 1284 patients. Overall survival and relapse-free survival Median follow-up: 35.7 mo 5-y OS: 40% 5-y RFS: 12%

Univariate analysis in 1284 pts

Independent prognostic factors of OS in training sample

Prognostic model LNM: Lymphonode metastases; PCI: peritoneal cavity involvement. FactorsScore Age>60y1 Proximal1 Stage Ⅲ / Ⅳ 2 LNM ratio>1/3 2 PCI2 Risk group Score Low risk (L) 0-1 Low intermediate (LI) 2-3 High intermediate (HI) 4-5 High risk (H) 6-8

Risk model defined by prognostic index

Risk model in age group 5-year OS 82% 60% 27% 7% 5-y OS 81% 48% 20% 0 P< y OS 82% 60% 27% 7%

Risk model in stage

Survival curve according to risk model LI L L

Risk model in treatment

Discussion Lagarde SM, et al. J Clin Oncol, 2006, 24:4347

AuthorTimeNPatients Independent prognostic factors Zhan curative Stage, Size, Perioperative chemotherapy Yolota operable Site, T category, LNM Schwarz operableIIIA-IV Age, Site, Number of LNM, T category, Sex The present study1043operable Age, Site, Size, Stage, Ratio of LNM, PCI, Curative resection, Combined therapy Comparison in gastric cancer prognostic factors Zhan YQ, et al. Ai Zheng 2005,24:596; Yokota T, et al. Anticancer Res 2002,22:3673; Schwarz RE et al. Ann Surg Oncol 2007,14:317

Conclusion  This risk model could identify various outcomes in pts with the same stage from IB to IV  This risk model also could identify different outcomes in pts with the same treatment status  Prospective study are warranted to validate these findings.

Acknowledgements Dept. of Abdominal Surgical Oncology Zhi-xiang Zhou Zhi-xiang Zhou Hai-zeng Zhang Hai-zeng Zhang Yi Shan Yi Shan Ping Zhao Ping Zhao Xiang Wang Xiang Wang Jian-xiong Wu Jian-xiong Wu Yong-fu Zhao Yong-fu Zhao Dept. of Medical Oncology Jing Wang Jing Wang Jin-wan Wang Jin-wan Wang Hong-gang Zhang Hong-gang Zhang Yu-sheng Li Yu-sheng Li Jing Huang Jing Huang Xiao-hui He Xiao-hui He Xiao-hong Han Xiao-hong Han Dept. of Pathology Xun Zhang Xun Zhang Yan Song Yan Song Shang-mei Liu Shang-mei Liu Dept. of Imaging Diagnosis Chun-wu Zhou Chun-wu Zhou Li-ming Jiang Li-ming Jiang Zhu Wang Zhu Wang

Thank you for your attention!