ライフサイエンスコーパス: survival curve

1 hose without LGE (p < 0.001 for Kaplan-Meier survival curves).

2 p biomicroscopy and analyzed by Kaplan-Meier survival curve.

3 ough no plateau has been demonstrated in the survival curve.

4 than FVB mice evaluated by the Kaplan-Meier survival curve.

5 by obliterating the "shoulder" of radiation survival curve.

6 alysed on an intention-to-treat basis with a survival curve.

7 obliterating the "shoulder" of the radiation survival curve.

8 te evidence of a plateau in the failure-free survival curve.

9 dications, time to failure, and Kaplan-Meier survival curve.

10 mained strong on time-dependent Kaplan-Meier survival curves.

11 ver, different SSPs produced broadly similar survival curves.

12 k procedure was used to compare Kaplan-Meier survival curves.

13 tested by log-rank tests using Kaplan-Meier survival curves.

14 high risk) was used to stratify Kaplan-Meier survival curves.

15 val were analyzed with chi2 and Kaplan-Meier survival curves.

16 econciled through the estimation of expected survival curves.

17 ith the alpha parameter obtained from fitted survival curves.

18 ival rates were estimated using Kaplan-Meier survival curves.

19 nd cancer-free survival was determined using survival curves.

20 ed using proportional hazards regression and survival curves.

21 ibited enhanced and statistically equivalent survival curves.

22 icant, did not have superimposable treatment survival curves.

23 ristic (ROC) curve analysis and Kaplan-Meier survival curves.

24 est) and directly compare covariate-adjusted survival curves.

25 as calculated from standardized Kaplan-Meier survival curves.

26 etermined by comparing adjusted Kaplan-Meier survival curves.

27 Univariate analysis included Kaplan-Meier survival curves.

28 proportional hazards models and Kaplan-Meier survival curves.

29 ft survival was evaluated using Kaplan-Meier survival curves.

30 stent with results from the manual method of survival curve acquisition for several mutants in both s

31 Survival curves adjusted for preoperative differences we

32 te a distinct alteration in the slope of the survival curve after 6 months of lamivudine treatment fo

33 rd to incidence and time to suicide attempt, survival curve analyses were conducted.

34 to be a promising refinement of traditional survival curve analysis and dose response models.

35 By survival curve analysis of DAISY children, the risk of p

36 Kaplan-Meier survival curve analysis revealed that wild-type C57BL/6

37 n status on survival was evaluated utilizing survival curve analysis.

38 m operation (controls) by using Kaplan-Meier survival curve analysis.

39 A Kaplan-Meier survival curve and log-rank test were used for survival

40 vestigators often present crude Kaplan-Meier survival curves and adjusted relative hazards from the C

41 Kaplan-Meier survival curves and area under the receiver-operating ch

42 aplan-Meier estimators were used to generate survival curves and compared by using the log-rank test.

43 Survival curves and covariate adjusted hazard ratio (HR)

44 Survival curves and covariate adjusted hazard ratios (HR

45 between these two groups using Kaplan-Meier survival curves and Cox proportional hazards models.

46 aft survival was analyzed using Kaplan-Meier survival curves and Cox regression analysis.

47 Kaplan-Meier survival curves and Cox regression models were used to c

48 Stratified survival curves and Cox regression were used to evaluate

49 CHOpcDNA3 cells treated with PM had similar survival curves and exhibited no difference in mutation

50 CAS compared with CEA, we used Kaplan-Meier survival curves and fitted mixed-effects logistic regres

51 ession models were used to estimate adjusted survival curves and hazard ratios (HR) with 95% confiden

52 The mice survival curves and histological lesions revealed A/D di

53 erall survival was assessed with Kaplan-Meir survival curves and log-rank testing.

54 Kaplan-Meier survival curves and log-rank tests revealed that high le

55 mes was evaluated by unadjusted Kaplan-Meier survival curves and logistic regression models.

56 We applied Kaplan-Meier analysis for survival curves and mortality rate estimation and Cox re

57 ed by these measurements, using Kaplan-Meier survival curves and multivariate Cox proportional hazard

58 First, we report updated survival curves and organ pathology in Ndufs4 KO mice ex

59 We generated Kaplan-Meier survival curves and performed a multivariable analysis u

60 Survival curves and proportional hazards were computed.

61 The model produces personalized survival curves and quantifies the relationship between

62 dard survival methods including Kaplan-Meier survival curves and sex-by-treatment interaction term to

63 Cellular recovery, as determined by survival curves and the ability to return to growth afte

64 istically significant differences in overall survival curves and time to relapse for the groups.

65 age covariate-adjusted SPK- and KTA-specific survival curves (and 10-year area under the curve; ie, r

66 atency was described by using a Kaplan-Meier survival curve, and number of catheter days were compare

67 Kaplan-Meier estimation was used to generate survival curves, and a multivariate Cox proportional haz

68 jection within 90 days by chi2, Kaplan Meier survival curves, and by multivariable logistic regressio

69 ysis included chi-square tests, Kaplan-Meier survival curves, and Cox proportional-hazards models.

70 he Kaplan-Meier method was used to construct survival curves, and the log-rank statistic was used to

71 ox proportional hazards models, Kaplan-Meier survival curves, and the log-rank test.

72 ve statistics, incidence rates, Kaplan-Meier survival curves, and the RR of NLP outcomes among eyes w

73 The survival curves appeared to cross over at approximately

74 ulation using an area under the Kaplan-Meier survival curve approach that combined trial-specific haz

75 isual record of individual deaths from which survival curves are constructed and validated, producing

76 5A mice display a similar tumor spectrum and survival curve as p53+/- mice, tumors from p53+/515A mic

77 urvival hazards and plotted the Kaplan-Meier survival curves as well as the net chance of a longer su

78 Kaplan-Meier survival curves assessed the timing of initial diagnosis

79 The difference between the survival curves associated with large (>3 cm) and small

80 ition to providing accurate and reproducible survival curves at a considerably reduced labor, this ap

81 To enable the rapid acquisition of survival curves at an arbitrary statistical resolution,

82 pneumococcal meningitis, using Kaplan-Meier survival curves, bacteriological and histological studie

83 m IRD kidneys, and illustrates how estimated survival curves based on a clinical decision can be pres

84 Survival curves based on Kaplan-Meier estimates are pres

85 ovide a graphical representation of adjusted survival curves based on regression estimates and the av

86 A plateau in the survival curve began at approximately 3 years.

87 The survival curve began to plateau around year 3, with foll

88 o 10.0 months), with a plateau at 21% in the survival curve beginning around year 3.

89 We observed a plateau in the survival curve, beginning at approximately 3 years, whic

90 Survival curves between 25 and 35 days were consistent f

91 There was also no significant difference in survival curves between groups; intentionally injured pa

92 as no significant difference in relapse-free survival curves between the treatment and control groups

93 Survival curves between the two groups of animals began

94 n the first and second breakpoints in the CR survival curve (between 21 and 31 months of age), tumors

95 Several clinical (i.e., survival curves, blood and tissue bacterial burdens, and

96 in one patient in the Epi-group (event-free survival curves by Grey-test, P=0.03).

97 s of remaining life expectancy and long-term survival curves can also be produced.

98 Kaplan-Meier survival curves compared time to death for the groups wi

99 Kaplan-Meier method, with the differences in survival curves compared using a log-rank test.

100 survival is represented using a Kaplan-Meier survival curve comparing (1) locally procured and import

101 Survival curves constructed using the Kaplan-Meier metho

102 ucose oxidase (P = 0.002 by log-rank test of survival curves constructed using the Kaplan-Meier metho

103 Other analyses, such as generation of survival curves, construction of Cox regression models,

104 Survival curves converged at 3.5 years for the 50 cells/

105 However, a survival curve corrected for age of the patients at the

106 Data were analyzed by Kaplan-Meier survival curves, Cox regression, and binary logistic reg

107 lan-Meier analysis was performed to plot the survival curve; cox regression models were employed to d

108 When the survival curves cross, there is a trade-off between the

109 With more than 10 years of follow-up, the survival curves demonstrate a plateau indicating a poten

110 aplan-Meier major adverse cardiac event-free survival curves demonstrated a significant benefit for a

111 Furthermore, survival curves demonstrated that the probability of dyi

112 Survival curves demonstrated that youths with T1DM devel

113 was similar in the two cohorts, although the survival curves did not converge until after 3 years.

114 lowing for the possibility that the adjusted survival curves differ in shape.

115 In clinical follow-up, the AIDS-free survival curves differed by HIV-1 subtype.

116 Survival curves differed significantly among the four gr

117 The Kaplan-Meier survival curves differed significantly for patients with

118 nction of mean activity per cell showed that survival curves differed substantially when the activity

119 Disease-free patient survival curves displayed a moderate decline with BRAF V

120 ilation was not reached and the Kaplan-Meier survival curve diverged from a published natural history

121 was calculated by integrating the predicted survival curve estimated in the Cox model.

122 Kaplan-Meier survival curves estimated the time from initial diabetes

123 dherence-adjusted hazard ratios and CHD-free survival curves estimated through inverse probability we

124 l hazards model, log-rank test, Kaplan-Meier survival curve, Fisher exact test, and t test.

125 ver a broad range of binding conditions, the survival curve followed a model in which viruses binding

126 Mean RBC age was calculated from the RBC survival curve for all circulating RBCs and for labeled

127 In contrast, the observed survival curve for carboplatin was far superior to the e

128 carboplatin was far superior to the expected survival curve for CP (P <.01).

129 sis data, was used to construct the expected survival curve for each treatment arm of the ICON2 trial

130 The survival curve for the placebo patients can be divided i

131 17%, 30%, and 49% (P < 0.001), respectively; survival curves for admission to a skilled-nursing facil

132 Survival curves for BMT show that at least half of the p

133 a mathematical model to predict Kaplan-Meier survival curves for chemotherapy combined with radiation

134 .99) for the first 8 years, and the CHD-free survival curves for continuous use and no use of estroge

135 Kaplan-Meier survival curves for each cohort were not significantly d

136 Lifetime survival curves for each group in the decision-analytic

137 Post hoc analysis showed that survival curves for GA-treated male patients diverged ea

138 HT mortality rates were based on survival curves for HT 1982 to 2001.

139 The survival curves for many pediatric sarcomas have remaine

140 is provided for estimating Kaplan-Meier-type survival curves for marginal structural models.

141 Kaplan-Meier survival curves for overall survival showed a statistica

142 Survival curves for patients initially treated with pent

143 om TCGA (global log-rank P = .02 comparing 3 survival curves for patients with 0-2, 3-4, and 5-7 dosa

144 ll within the 95% confidence bands of actual survival curves for patients.When the predictor variable

145 -free survival, and comparison of event-free survival curves for prognostic-score risk strata.

146 As such, determining whether survival curves for the 2 groups are different may not t

147 Kaplan-Meier survival curves for the 2 procedures were compared using

148 However, the survival curves for the beta-pol(+/+) and beta-pol(+/-)

149 Survival curves for the mutation-positive and -negative

150 ll within the 95% confidence bands of actual survival curves for the patients.

151 A log-rank test comparing survival curves for these two populations yields a two-s

152 ood separation of tertile-based Kaplan-Meier survival curves for these variables.

153 tients were stratified by TNM stage, overall survival curves for those with TNP breast cancer matched

154 re entered into the algorithm, the predicted survival curves for time to death fell within the 95% co

155 ely to reach the end point is then consulted.Survival curves for time to need for care equivalent to

156 Survival curves for underweight and normal weight patien

157 d/lost were calculated using direct adjusted survival curves (for participants 40+ years of age), wit

158 Survival curves found that patients with increased PDW h

159 The 9 lowest risk deciles had linear survival curves from 0 to 365 postoperative days, with t

160 ed to calculate the parameters of the growth/survival curves from the distributions of the respective

161 CA was associated with consistently inferior survival curves from year 3 onward.

162 h modern therapy, the long-term disease-free survival curves have not reached a plateau.

163 rification group also showed a better 90-day survival curve (Hazard ratio=0.260) compared to the cont

164 id not result in a significant separation of survival curves (HR, 1.4; 95% confidence interval [CI]:

165 essor, is proposed: (i) determination of the survival curve; (ii) measurement of the mitotic index in

166 standard for adjusting an exposed group, the survival curve in the exposed group is adjusted to the c

167 survival curves were compared with observed survival curves in the ICON2 trial at all time points us

168 Kaplan-Meier survival curves indicated a 33% 5-year survival for pati

169 Analysis of survival curves indicated that ir-HGF levels higher than

170 a new method to obtain multivariate adjusted survival curves is described.

171 s ratio 7.17 [95% CI 1.5-34.5]; Kaplan-Meier survival curve, log-rank statistic 9.11 [p=003]).

172 Analyses included: Kaplan-Meier survival curves, Log-Rank tests, and Cox proportional ha

173 rvival data were analyzed using Kaplan-Meier survival curves, log-rank tests, and proportional hazard

174 Kaplan-Meier survival curves, log-rank tests, and Weibull survival mo

175 pses) conditions had significantly different survival curves (Mantel-Cox statistic chi(2)1 = 10.47, P

176 st 3 years; however, a potentially diverging survival curve may portend higher mortality at 5 years.

177 Separation of the survival curves occurred at 3 years after initial testin

178 ficantly different from the linear quadratic survival curve of MCF7 /: HER2-18 cells exposed to gamma

179 Kaplan-Meier survival curves of MDI-based risk classes showed signifi

180 chnique was used to compare the Kaplan-Meier survival curves of patients with local recurrences, sate

181 Within each case-mix stratum, survival curves of the patients admitted to hospitals in

182 The survival curves of the two groups showed further separat

183 entified variables, we compared Kaplan-Meier survival curves of transplanted and control patients str

184 studies contrasted (unadjusted) Kaplan-Meier survival curves or, if covariate-adjusted, reported haza

185 kelihood identified the point at which the 2 survival curves overlapped; the 95% confidence interval

186 dose of B. dermatitidis yeasts (Kaplan-Meier survival curve P values of 0.027 to 0.0002) and also pro

187 ive PC3 tumor xenografts in cytotoxicity and survival curves (P > 0.05).

188 isk groups yielded distinct progression-free survival curves (P < 0.0001).

189 , 95% CI: 3.3, 17.4) resulted in similar ICH survival curves (P = 0.979).

190 Radiobiological survival curve parameters confirmed an interactive cytot

191 Observed median survival times, Kaplan-Meier survival curves, proportional death hazard ratios, and r

192 urine models of zygomycosis by assessment of survival curves, pulmonary fungal burdens, and expressio

193 but that in order to match the experimental survival curves quantitatively, it is necessary that the

194 Kaplan-Meier survival curves rapidly declined with increasing age in

195 tended follow-up as evidenced by the overall survival curves remaining separated.

196 The shape of the survival curve remains; the highest hazard remains the f

197 Kaplan-Meier survival curves, results of log rank tests, and cumulati

198 Adjusted Kaplan-Meier survival curves revealed that at any point in time the p

199 Further dissection of the sgs1 and srs2 survival curves reveals two distinct phenomena.

200 noncodeleted tumors also benefited from CRT; survival curves separated after the median had been reac

201 A single-hit, multi-target crypt survival curve showed a significant increase in crypt pr

202 Kaplan-Meier survival curves showed better survival in PLG-SAS than i

203 Survival curves showed improved survival for patients in

204 A comparison of the Kaplan-Meier 180-day survival curves showed no difference between treatment g

205 m(2) for LAVI and -15% for GLS, Kaplan-Meier survival curves showed significant better survival for p

206 Kaplan-Meier survival curves showed that the uninsured group had bett

207 Kaplan-Meier survival curves showed that these events occurred more f

208 Kaplan-Meier survival curves showed the 20-30-year-old age group and

209 nction of RLS, and it displays features of a survival curve such as changes in hazard rate with age.

210 The survival curves suggest a more aggressive cancer than pa

211 In that study, Kaplan-Meier survival curves suggested worse cardiovascular disease s

212 alternative approaches to obtaining adjusted survival curves that have been proposed.

213 rences in gene expression profiles and Abeta survival curves, that deeper layer neurons are significa

214 onstruct inverse probability weight-adjusted survival curves; the findings did not change.

215 The 8-year survival curve to first appropriate shocks was 94%, 57%,

216 We used Kaplan-Meier survival curves to display the time to joint surface col

217 e D(o) dose for *IUdR can be determined from survival curves versus the mole amount of *IUdR incorpor

218 In addition, a 10-day survival curve was conducted following CLP and cecal exc

219 No significant difference in survival curves was found between treatment groups (log

220 ssessed by log rank analyses of Kaplan-Meier survival curves was significantly lower for NVE isolates

221 een active (n = 2365) and placebo (n = 2371) survival curves, was 105 days (95% CI, -39 to 242; P = .

222 Survival curves were almost identical for the 3 observer

223 Kaplan-Meier survival curves were also compared after stratifying pat

224 Kaplan-Meier survival curves were also generated.

225 Complex survival curves were analyzed using radiation target the

226 Kaplan Meier survival curves were analyzed with the log rank test.

227 e rate and the Mantel-Haenszel statistic for survival curves were calculated for each group.

228 Survival and morbidity-free survival curves were calculated, and risk factors were d

229 Survival and morbidity-free survival curves were calculated.

230 of a cardiovascular event, and Kaplan-Meier survival curves were calculated.

231 Age-based survival curves were compared in a sequential bivariate

232 Survival curves were compared using the log-rank test an

233 Expected survival curves were compared with observed survival cur

234 Kaplan-Meier survival curves were compared with the two-sided log-ran

235 Kaplan-Meier survival curves were computed for risk score quartiles.

236 Kaplan-Meier survival curves were constructed and multivariate Cox re

237 Kaplan-Meier survival curves were constructed to assess retention pro

238 Kaplan-Meier survival curves were constructed to depict cumulative su

239 Overall survival curves were constructed using Kaplan-Meier meth

240 Kaplan-Meier survival curves were constructed using mean miRNA expres

241 Kaplan-Meier survival curves were constructed, and Cox proportional h

242 Age-adjusted survival curves were constructed, and Cox proportional-h

243 Survival curves were derived by the Kaplan-Meier method,

244 Exponential survival curves were derived from trial data and adjuste

245 Survival curves were derived using the Kaplan-Meier meth

246 Survival curves were derived with Kaplan-Meier methods;

247 Survival curves were developed using the Kaplan-Meier me

248 Kaplan-Meier survival curves were drawn for midterm outcomes.

249 os (HRs) were estimated from Cox models, and survival curves were estimated by the Kaplan-Meier metho

250 ank and Cox proportional hazards models, and survival curves were estimated using the Kaplan-Meier me

251 Survival curves were estimated with Kaplan-Meier product

252 Survival curves were estimated with the Kaplan-Meier met

253 Kaplan-Meier survival curves were examined for differences in surviva

254 Survival curves were found not to differ significantly (

255 confidence intervals (CIs), and Kaplan-Meier survival curves were generated by gender and etiology.

256 Kaplan-Meier survival curves were generated for each gender and compa

257 Cell survival curves were generated from the fraction of cell

258 Survival curves were generated using the Kaplan-Meier me

259 oduced by lung leukocytes were measured, and survival curves were generated.

260 rain was determined to assess clearance, and survival curves were generated.

261 Cumulative rate of endophthalmitis and survival curves were measured using Cox-proportional haz

262 Kaplan-Meier survival curves were obtained by the log-rank test.

263 this approach to numerous experiments where survival curves were obtained for different cell lines a

264 Actuarial survival curves were plotted according to the Kaplan-Mei

265 Kaplan-Meier survival curves were plotted for renal allograft and pat

266 Kaplan-Meier survival curves were plotted to determine continuation r

267 aluated by using the Kaplan-Meier method and survival curves were plotted.

268 Actuarial survival curves were plotted.

269 The log-rank test showed that the survival curves were significantly different (P<0.001).

270 Survival curves were significantly different using this

271 If reinterventions were not required, survival curves were similar.

272 ced cell death (i.e., reproductive failure), survival curves were simulated with different electron e

273 The differences between survival curves were tested for significance by log-rank

274 Kaplan-Meier survival curves were used to analyze the data.

275 Kaplan-Meier survival curves were used to compare graft and patient s

276 For all eligible articles, reported survival curves were used to determine the relative risk

277 Kaplan-Meier survival curves were used to estimate age-specific PD ri

278 al hazard regression models and Kaplan-Meier survival curves were used to identify predictors for alc

279 tastasis models, and the indirect nature of "survival" curves when studying brain metastases.

280 h versus the absorbed dose followed a linear survival curve with alpha = 0.51 +/- 0.05 Gy(-1) and R(2

281 nalyses revealed a flat PTC-specific patient survival curve with neither mutation, a modest decline i

282 Using Kaplan-Meier survival curves with log-rank tests, health outcomes wer

283 Survival curves with the ROC optimal cutoff for each met