ライフサイエンスコーパス: survival analyses

1 Statistical methods included discrete-time survival analyses.

2 ns with generalised estimating equations and survival analyses.

3 xamined through time-dependent covariates in survival analyses.

4 es was evaluated by parametric models and by survival analyses.

5 The Kaplan-Meier method was used for survival analyses.

6 h age-period-cohort models and breast cancer survival analyses.

7 log-rank p=0.12) or 3-6 (log-rank p=0.98) in survival analyses.

8 dard descriptive statistics and Kaplan-Meier survival analyses.

9 w-up data available and were included in the survival analyses.

10 tional hazards models were used for adjusted survival analyses.

11 r AIDS Cohort Study by means of Kaplan-Meier survival analyses.

12 biased exposure effect estimates in standard survival analyses.

13 e of positive prognostic value in univariate survival analyses.

14 Polarity conversions were evaluated by survival analyses.

15 ombined to allow multivariate and stratified survival analyses.

16 t investigate the effect of interventions by survival analyses.

17 nth prospective follow-up were assessed with survival analyses.

18 er evaluated during long-term follow-up with survival analyses.

19 ariate logistic regression, and Kaplan-Meier survival analyses.

20 05 for all but 1 comparison) in Kaplan-Meier survival analyses.

21 rulopathy (TG) development were estimated in survival analyses.

22 -Tree were validated using tumor pathway and survival analyses.

23 of reaching the end points were estimated by survival analyses.

24 inic population through probability-weighted survival analyses.

25 assessed using random-effects Cox regression survival analyses.

26 er operating characteristic (ROC) curves and survival analyses.

27 diagnosis were examined with descriptive and survival analyses.

28 remained significant in univariate-adjusted survival analyses.

29 re identified by univariate and multivariate survival analyses.

30 in 925 RTR using univariate and multivariate survival analyses.

31 orectomy were evaluated using time-dependent survival analyses.

32 variables in Cox regression and Kaplan-Meier survival analyses.

33 completely the effect of FA on multivariate survival analyses.

34 luated using Kaplan-Meier and Cox regression survival analyses.

35 years for renal outcomes and 11.2 years for survival analyses.

36 ssion and Kaplan-Meier methods were used for survival analyses.

37 ortional hazards regression and Kaplan-Meier survival analyses.

38 dates of hospitalization were excluded from survival analyses.

39 in RFS analyses and 5606 patients in overall survival analyses); 3638 patients were analyzed by cytog

40 Univariate and multivariate survival analyses adjusted for patient, disease, and tre

41 Survival analyses, adjusted for propensity score by usin

42 incidence of hyperglycemia was confirmed by survival analyses among C/C, C/T, and T/T carriers durin

43 was tested using univariate and multivariate survival analyses and by receiver-operating-characterist

44 Kaplan-Meier survival analyses and Cox proportional hazards modeling

45 m mortality were assessed using Kaplan-Meier survival analyses and Cox proportional hazards modeling,

46 pe of event (ischemic or hemorrhagic), using survival analyses and Cox proportional hazards models.

47 Survival analyses and Cox regression models revealed tha

48 Stratified survival analyses and Cox regression were used to compar

49 urther data maturation is needed for overall survival analyses and evaluation of the full predictive

50 Survival analyses and inherent log-rank tests showed tha

51 Final survival analyses and updated results are reported.

52 multilevel spatiotemporal exposure model and survival analyses) and short-to-medium-term exposure-mor

53 ed and results of the final progression-free survival analyses are presented here.

54 Propensity-adjusted survival analyses assessed the association of perioperat

55 ring the following 7 years in sex-stratified survival analyses controlling for age.

56 Survival analyses, controlling for age, sex, number of g

57 Survival analyses, correlation analyses, and t tests wer

58 Survival analyses demonstrated that the disease course i

59 sults were compared with those from standard survival analyses (e.g., Weibull regression) with time-u

60 In multivariate survival analyses, elevated CRP was confirmed as an inde

61 In age-adjusted survival analyses for all causes of death, men who were

62 We generated Kaplan-Meier survival analyses for the largest untreated Hutchinson-G

63 itive time-lagged associations were found in survival analyses for virtually all temporally primary l

64 Retrospective cohort studies using survival analyses have reported that fewer than 25% of p

65 Commonly used statistical survival analyses implicitly assume a constant ratio of

66 l-cause mortality by Cox Proportional Hazard survival analyses in 1840 stable RTR derived from the As

67 een January 1980 and June 2005 that provided survival analyses in patients with breast cancer after a

68 The 1-, 2-, and 3-year Kaplan-Meier survival analyses in propensity-matched patients favored

69 Multivariate survival analyses included relevant variables identified

70 Survival analyses included unadjusted Kaplan-Meier plots

71 ant marker of poor prognosis in multivariate survival analyses, including classic prognostic markers,

72 Survival analyses indicate that arrest effects endured u

73 Visual acuity survival analyses indicate that the optimal intervention

74 Survival analyses indicated that each 1g/dl increase in

75 Kaplan-Meier survival analyses indicated that IC significantly delaye

76 Kaplan-Meier survival analyses indicated that the survival estimate,

77 In Kaplan-Meier survival analyses, neither severity of stenosis (P = .80

78 comprehensive clinicobiologic, genetic, and survival analyses of a large cohort of 213 adult patient

79 Survival analyses of groups defined by size of residual

80 Survival analyses of incident AMD versus average running

81 Survival analyses of relapse/recurrence rates, as determ

82 Interestingly, survival analyses of TDP or FUS models show no increase

83 Survival analyses of time to recovery and, subsequently,

84 ll-cohort and propensity-matched comparative survival analyses on our 3-center database of Sprint Fid

85 the consideration of a continuous series of survival analyses over 7 decades at Massachusetts Genera

86 Survival analyses revealed a set of approximately 70 gen

87 Survival analyses revealed that chromosome 1q and 11p ga

88 Survival analyses revealed that even when controlling fo

89 Survival analyses revealed that, in addition to these di

90 In this context, survival analyses show that BAX mutations are indicators

91 Survival analyses showed a significantly (P = 0.002) hig

92 The adjusted survival analyses showed a significantly higher survival

93 Survival analyses showed a time-dependent significant as

94 For all data sets, Kaplan-Meier survival analyses showed significant differences in rela

95 Survival analyses showed significant effects of pretreat

96 The Kaplan-Meier (KM) survival analyses showed that 69%, 54% and 44% of these

97 Survival analyses showed that patients who developed cut

98 Survival analyses showed that the estimated risk for eve

99 x and/or National Death Index, with adjusted survival analyses starting at 24 months after ART initia

100 Lung cancer-specific survival analyses suggest that NSCLC tumor behavior may

101 Survival analyses suggest that symptomatic improvements

102 Main Outcomes and Measures: Using survival analyses techniques, incidence rate ratios were

103 Survival analyses that accounted for competing risks wer

104 In survival analyses that accounted for competing risks, pa

105 Thus, time to disease survival analyses that censor disease-free individuals a

106 ically significant according to Kaplan-Meier survival analyses that included 131 (95%) of 138 POWs an

107 For the purpose of survival analyses, the baseline survival time was set to

108 .012), and, when tropism was included in the survival analyses, the effect of the SDF1-3'A allele on

109 On survival analyses, the only variable associated with the

110 The authors used survival analyses to estimate the risk of natural menopa

111 sure records are available in TCGA, existing survival analyses typically did not consider drug exposu

112 We completed survival analyses using an as-treated approach.

113 We performed survival analyses using Cox proportional hazards models.

114 sequent hypomania or mania was determined in survival analyses using Cox proportional hazards regress

115 Survival analyses using intent-to-treat principles and m

116 dence intervals when performing Kaplan-Meier survival analyses, we recommend adjusting for dependence

117 resonance imaging and histopathological and survival analyses, we show that tumor progression was si

118 All survival analyses were adjusted for sex, age, calendar y

119 receiver-operating characteristic curves and survival analyses were applied.

120 Survival analyses were carried out in 112 patients.

121 Survival analyses were conducted for patients with adeno

122 Survival analyses were conducted using Kaplan-Meier esti

123 Differences in survival analyses were determined using the log-rank tes

124 Retrospective survival analyses were done on 283 CCALD patients identi

125 haracteristics of patients were compared and survival analyses were done to evaluate the effect of in

126 Survival analyses were employed to identify variables as

127 levels in this cohort, statistical power for survival analyses were limited.

128 Multivariate survival analyses were performed by proportional hazards

129 Kaplan-Meier survival analyses were performed for 80 patients from th

130 Log-rank survival analyses were performed for each trial, and ove

131 Survival analyses were performed for patients whose tumo

132 Response and survival analyses were performed on posttreatment sample

133 Multivariate survival analyses were performed using Cox proportional

134 Survival analyses were performed using Cox proportional

135 Univariate and multivariate survival analyses were performed using Cox proportional

136 Univariate and multivariate survival analyses were performed using Cox regression.

137 Survival analyses were performed using Cox's proportiona

138 Uni- and multivariate survival analyses were performed using Cox-proportional

139 Survival analyses were performed using models adjusted f

140 Multivariate survival analyses were performed using proportional haza

141 Survival analyses were performed using the Kaplan-Meier

142 Survival analyses were performed using the Kaplan-Meier

143 Survival analyses were performed with adjustment for bas

144 Survival analyses were performed with adjustment for bas

145 Survival analyses were performed with Cox proportional h

146 Survival analyses were performed with models adjusted fo

147 re investigated at 3 mo after treatment, and survival analyses were performed with the Kaplan-Meier m

148 Survival analyses were performed with weighted Cox model

149 Survival analyses were performed, including 451,151 part

150 iptive statistics, correlation analyses, and survival analyses were performed.

151 Comparative and survival analyses were performed.

152 using Cox regression models and incremental survival analyses were performed.

153 eier and Cox proportional hazards regression survival analyses were performed.

154 Univariate and multivariate survival analyses were performed.

155 Kaplan-Meier and Cox multivariate survival analyses were performed.

156 Survival analyses were repeated for tumor FASN expressio

157 These results were consistent when the survival analyses were restricted to stage III disease:

158 Definitions of events for survival analyses were tooth loss, loss of > or = 2 mm c

159 Survival analyses were used to account for potential dif

160 Survival analyses were used to calculate the duration of

161 Survival analyses were used to calculate the RR of all-c

162 Kaplan-Meier survival analyses were used to compare survival times be

163 Bivariate and survival analyses were used to delineate patterns and co

164 Univariate and multivariate survival analyses were used to determine the predictive

165 Survival analyses were used to evaluate their prognostic

166 alysis of variance, multilevel modeling, and survival analyses, where appropriate.

167 Survival analyses with and without risk adjustment were

168 Survival analyses with respect to the rate of progressio

169 We did survival analyses with the Kaplan-Meier estimator and ev

170 internalizing and externalizing disorders in survival analyses, with time-lagged associations consist