Survival Analysis : Glioma Treatment
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Survival analysis of glioma treatment by using R program.
Survival Analysis : Glioma Treatment
- 1. Survival Analysis 覓語 覈 Glioma Treatment 螻 B, 42pt 觜 願 伎 豕ろ . れ蠍
- 2. 1 What is Glioma? 2 Glioma data analysis 3 Conclusion
- 4. 01 Glioma(蟆所譬) 1 Glioma 襯 蟲燕 譟一 Glioma 譬 蟲覿 4
- 5. 01 Glioma(蟆所譬) 5
- 6. 01 Glioma(蟆所譬) 2 Glioma 轟 讌覲 豺 襦 蟇壱 蟆 る (覦 豺襭, 豺襭 覲) 覦覲 10襷覈 2覈 覦 6
- 7. 01 Glioma(蟆所譬) 3 Glioma 轟 朱 讀 蟆所譬 1/3 豐蠍 讀 蟲 讀 7
- 8. 01 Glioma(蟆所譬) 4 Glioma 讌 8
- 9. 01 Glioma(蟆所譬) CT MRI 蟆 る 螳螻 蟆蟆 る 螳螻 殊 覿覿 蟆 覿覿 殊 覿覿 覿覿 (譬 企Μ) (譬 企Μ) MRI 讌 蟆 覦蟆 9
- 10. 01 Glioma(蟆所譬) 5 Glioma 覿襯 (WHO 蠍一) Low-grade Glioma High-grade Glioma Grade III / GBM( Grade IV) (豺襭 譟願鍵螳 50譯 危) 10
- 11. 01 Glioma(蟆所譬) low-grade glioma /GBM GBM patient MRI scanning 11
- 12. 01 Glioma(蟆所譬) 6 Glioma 豺襭 Grade II Glioma覿磯 譯朱 譟一 豺覯 (襦襷 豺 覿螳) 豺襭 RIT (覦豺襭) Radioimmunotherapy 12
- 13. 01 Glioma(蟆所譬) 覦 豺襭 觜蟲 13
- 14. Glioma data Analysis
- 15. 02 Glioma data Analysis 1. >glioma 15
- 16. 02 Glioma data Analysis 2. >?glioma る Yttrium-90-biotin 渚 覦 覦 覃伎豺襭襯 覦 glioma ろ讌 朱 郁規 (2002) 一危 襷 れ 7螳讌 覲 37覈 蟯谿郁 no, 覯 age sex 焔 (M- / F-) histology 磯ジ glioma 炎 (GBM-grade IV / Grade 3-grade III) time ろ-譬蟆 螳 event 一危 蟇碁企 蟲 (False-豺,譟 / True-襷) group RIT(覦ル伎豺襭) / Control(譟郁貴) 16
- 17. 02 Glioma data Analysis 3. 一危 覿 Survival fit plot 蠏碁Μ蠍 Logrank test ろ 暑手骸 豺襭螳 襤一, 蟯蟯螻 覿 17
- 18. Glioma data Analysis 02 > layout(matrix(1:2, ncol = 2)) > g3 <- subset(glioma, histology == "Grade3") > plot(survfit(Surv(time, event) ~ group, data = g3),main = "Grade III Glioma", lty = c(2,1)) > legend("bottomleft", legend=c("Control","Treated"),lty=c(2,1)) > surv_test(Surv(time, event) ~ group, data = g3,distribution = "exact") Exact Logrank Test data: Surv(time, event) by group (Control, RIT) Z = 2.1711, p-value = 0.02877 alternative hypothesis: two.sided > gbm <- subset(glioma, histology == "GBM") > plot(survfit(Surv(time, event) ~ group, data = gbm),main = "Grade IV Glioma", lty = c(2,1)) > legend("topright", legend=c("Control","Treated"),lty=c(2,1)) > surv_test(Surv(time, event) ~ group, data = gbm,distribution = "exact") Exact Logrank Test data: Surv(time, event) by group (Control, RIT) Z = 3.2215, p-value = 0.0001588 alternative hypothesis: two.sided > surv_test(Surv(time, event) ~ group | histology, data = glioma,distribution = approximate(B = 10000)) Approximative Logrank Test data: Surv(time, event) by group (Control, RIT) stratified by histology Z = 3.6704, p-value < 2.2e-16 alternative hypothesis: two.sided 18
- 19. Glioma data Analysis 02 > g3 <- subset(glioma, histology == "Grade3") > plot(survfit(Surv(time, event) ~ group, data = g3),main = "Grade III Glioma", lty = c(2,1)) > legend("bottomleft", legend=c("Control","Treated"),lty=c(2,1)) > surv_test(Surv(time, event) ~ group, data = g3,distribution = "exact") Exact Logrank Test data: Surv(time, event) by group (Control, RIT) Z = 2.1711, p-value = 0.02877 alternative hypothesis: two.sided g3 g3 data RIT ろ覿(group) 磯ジ ろ蠍郁(time)螻 譟伎覿(event) 蟯 survival fit plot 蠏碁 (legend れ) Survival test (logrank test) p-value = 0.02877 < 0.05 (糾朱 RIT螳 Glioma grade 3 豺襭 螻手 ) 19
- 20. Glioma data Analysis 02 > gbm <- subset(glioma, histology == "GBM") > plot(survfit(Surv(time, event) ~ group, data = gbm),main = "Grade IV Glioma", lty = c(2,1)) > legend("topright", legend=c("Control","Treated"),lty=c(2,1)) > surv_test(Surv(time, event) ~ group, data = gbm,distribution = "exact") Exact Logrank Test data: Surv(time, event) by group (Control, RIT) Z = 3.2215, p-value = 0.0001588 alternative hypothesis: two.sided gbm gbm data RIT ろ覿(group) 磯ジ ろ蠍郁(time)螻 譟伎覿(event) 蟯 survival fit plot 蠏碁 (legend れ) Survival test (logrank test) p-value = 0.0001588 < 0.05 (糾朱 RIT螳 Glioma GBM 豺襭 螻手 ) 20
- 21. Glioma data Analysis 02 > surv_test(Surv(time, event) ~ group | histology, data = glioma,distribution = approximate(B = 10000)) Approximative Logrank Test data: Surv(time, event) by group (Control, RIT) stratified by histology Z = 3.6704, p-value < 2.2e-16 alternative hypothesis: two.sided 糾 TEST襯 ろ蠍一 覓 覲語 10000覯 覲旧豢豢 logrank test ろ p-value < 2.2e-16 < 0.05 (糾朱 RIT螳 Glioma 豺襭 螻手 ) 21
- 22. 02 Glioma data Analysis 4. 蠏碁 覿 襷 覦 螳 (螻覈) 豺 : 讌朱 蠏語 襷 (X豢) ろ 覿一 蟆所骸 螳 (殊 蠏碁) Grade III れ survival plot ろ蟲 (1.00.8) / 譟郁貴(1.0 0.3) (るジ讓 蠏碁) Grade IV れ survival plot 譬襭 譟企 Grade III覲企 ろ蟲 (1.0 60螳 0.4) 譟郁軌(1.0 30螳 企 覈 襷) 22
- 23. Conclusion
- 24. 03 Conclusion Glioma / 轟 / 覿襯 讌 / 豺襭 ? Glioma Data Survival fit plot Analysis Logrank test 24
- 25. 03 Conclusion 25
- 26. 03 Conclusion 26
- 27. 03 Conclusion 27
- 28. 03 Conclusion 豺襭 譬 覿豺覲? RIT (覦豺襭) 28
- 29. 螳矧