ライフサイエンスコーパス: Kaplan-Meier survival analysis

1 stepwise Cox proportional hazards model and Kaplan-Meier survival analysis.

2 g a more clinically informative picture than Kaplan-Meier survival analysis.

3 Results were assessed using Kaplan-Meier survival analysis.

4 2 years were 6% and 15%, respectively, using Kaplan-Meier survival analysis.

5 ow vision and blindness were estimated using Kaplan-Meier survival analysis.

6 ngitudinal shedding rates were determined by Kaplan-Meier survival analysis.

7 receiver operator characteristic curves and Kaplan-Meier survival analysis.

8 Survival probabilities were estimated by Kaplan-Meier survival analysis.

9 Recurrence rates were evaluated using Kaplan-Meier survival analysis.

10 x proportional hazards regression models and Kaplan-Meier survival analysis.

11 Graft success was assessed by Kaplan-Meier survival analysis.

12 t contrast-enhanced CT was analyzed by using Kaplan-Meier survival analysis.

13 overall survival (OS) were calculated using Kaplan-Meier survival analysis.

14 urvival in the 3 groups was calculated using Kaplan-Meier survival analysis.

15 We calculated seroconversion using Kaplan-Meier survival analysis.

16 icular cascade stage at a specific time with Kaplan-Meier survival analysis.

17 ventricular pacing quartiles with the use of Kaplan-Meier survival analysis.

18 rs were related to patient survival by using Kaplan-Meier survival analysis.

19 s in recipient subgroups were compared using Kaplan-Meier survival analysis.

20 model parameters, fixed-point mortality, and Kaplan-Meier survival analysis.

21 rvival was evaluated for up to 9 weeks using Kaplan-Meier survival analysis.

22 Using a Kaplan-Meier survival analysis, 1-, 5-, and 10-year dise

23 In Kaplan-Meier survival analysis, all-cause mortality amon

24 >/=80% of HIV QIs and mortality rates using Kaplan-Meier survival analysis and adjusted Cox proporti

25 Kaplan-Meier survival analysis and ANOVA were performed.

26 rgan Sharing dataset from 1994 to 1999 using Kaplan-Meier survival analysis and Cox modeling.

27 ing, and thromboembolism were examined using Kaplan-Meier survival analysis and Cox proportional haza

28 Kaplan-Meier survival analysis and Cox proportional haza

29 ive-year overall survival was examined using Kaplan-Meier survival analysis and Cox proportional haza

30 of recurrent GBM tumors were analyzed using Kaplan-Meier survival analysis and Cox proportional haza

31 Kaplan-Meier survival analysis and Cox proportional haza

32 Kaplan-Meier survival analysis and Cox regression analys

33 Importantly, Kaplan-Meier survival analysis and log-rank test reveale

34 0), or poor (ypT3-4 or N+) response by using Kaplan-Meier survival analysis and multivariate Cox prop

35 oma skin cancers), which was evaluated using Kaplan-Meier survival analysis and proportional hazards

36 Kaplan-Meier survival analysis and risk factors associat

37 We conducted Kaplan-Meier survival analysis and used Cox proportional

38 overall survival (OS) were calculated using Kaplan-Meier survival analysis, and differences between

39 sis performed include the Fisher exact test, Kaplan-Meier survival analysis, and log-rank test.

40 Corneal graft survival was calculated using Kaplan-Meier survival analysis, and survival distributio

41 Kaplan-Meier survival analysis at follow-up demonstrated

42 A case-control, Kaplan-Meier survival analysis between HPS patients and

43 oring with matched pairs was used to perform Kaplan-Meier survival analysis comparing patients who un

44 Standard Kaplan-Meier survival analysis confirmed the prognostic

45 We used Kaplan-Meier survival analysis, Cox proportional hazards

46 Kaplan-Meier survival analysis demonstrated significantl

47 Kaplan-Meier survival analysis demonstrated that nuclear

48 Kaplan-Meier survival analysis did not demonstrate a dif

49 Kaplan-Meier survival analysis did not demonstrate a sig

50 A Kaplan-Meier survival analysis evaluated survival experi

51 Kaplan-Meier survival analysis failed to demonstrate an

52 A Kaplan-Meier survival analysis gives a median time of 40

53 Cox regression and Kaplan-Meier survival analysis identified that amplifica

54 A Kaplan-Meier survival analysis indicated a significantly

55 Importantly, Kaplan-Meier survival analysis indicated that elevated K

56 Kaplan-Meier survival analysis indicated that the isolat

57 Kaplan-Meier survival analysis is available, including c

58 A Kaplan-Meier survival analysis of the cohort found that

59 Kaplan-Meier survival analysis of the primary end point

60 was predictive for a lower survival using a Kaplan-Meier survival analysis (P < 0.001).

61 mulative survival, 63 months vs not reached, Kaplan-Meier survival analysis; P <.03, log-rank test).

62 Kaplan-Meier survival analysis predicts an 82% survival

63 Kaplan Meier survival analysis showed significantly shor

64 A Kaplan-Meier survival analysis showed a 44% reduction in

65 Kaplan-Meier survival analysis showed a reduction of 48

66 A Kaplan-Meier survival analysis showed a significant diff

67 More importantly, Kaplan-Meier survival analysis showed a significant surv

68 Kaplan-Meier survival analysis showed a significantly hi

69 Kaplan-Meier survival analysis showed a significantly hi

70 Kaplan-Meier survival analysis showed better survival in

71 Kaplan-Meier survival analysis showed combined (P = 0.00

72 Kaplan-Meier survival analysis showed decreased 5-year d

73 Kaplan-Meier survival analysis showed increased risk of

74 Propensity-matched Kaplan-Meier survival analysis showed no difference in g

75 th those without pouchitis (72% vs. 45%) and Kaplan-Meier survival analysis showed that allele 2 carr

76 Kaplan-Meier survival analysis showed that different sut

77 The Kaplan-Meier survival analysis showed that IMT significa

78 Kaplan-Meier survival analysis showed that subsequent to

79 Kaplan-Meier survival analysis showed that this differen

80 Kaplan-Meier survival analysis showed that whereas all L

81 ng multivariable Cox regression analysis and Kaplan-Meier survival analysis, taking into account age,

82 In Kaplan-Meier survival analysis, TCC patients with >20% p

83 Using Kaplan-Meier survival analysis, the estimated annual eve

84 By Kaplan-Meier survival analysis, the first versus the fir

85 By Kaplan-Meier survival analysis, the only significant pre

86 On Kaplan-Meier survival analysis there was a nonsignifican

87 We used Kaplan-Meier survival analysis to adjust for censorship

88 tional Health Interview Survey (NHIS), using Kaplan-Meier survival analysis to estimate cumulative pr

89 study period were compared using unadjusted Kaplan-Meier survival analysis to estimate risk of and t

90 We used Kaplan-Meier survival analysis to estimate time to first

91 We used Kaplan-Meier survival analysis to examine the distributi

92 Kaplan Meier survival analysis was done looking at trans

93 tive primary venographic patency by means of Kaplan-Meier survival analysis was 55% at 6 months and 5

94 A Kaplan-Meier survival analysis was done for incident epi

95 Kaplan-Meier survival analysis was performed for aggress

96 A Kaplan-Meier survival analysis was performed on the basi

97 Kaplan-Meier survival analysis was performed to examine

98 Kaplan-Meier survival analysis was performed using a tum

99 Kaplan-Meier survival analysis was performed, with renal

100 Kaplan-Meier survival analysis was used to assess genoty

101 Kaplan-Meier survival analysis was used to plot genotype

102 Using Kaplan-Meier survival analysis, we estimated that the me

103 Using Kaplan-Meier survival analysis, we found 30-day mortalit

104 Outcomes for autoislet recipients by Kaplan-Meier survival analysis were compared with those

105 edictors of LMNA mutation carrier status and Kaplan-Meier survival analysis were performed.

106 Kaplan-Meier survival analysis, which takes varying leng

107 Kaplan-Meier survival analysis with log-rank testing was

108 ormed using chi(2) analysis, Student t test, Kaplan-Meier survival analysis with the log-rank test, a