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1 .293; 95% CI, 2.340-11.975; p < 0.001 by Cox proportional hazard model).
2 val, 0.22 to 0.78; P = 0.006 by adjusted Cox proportional-hazards model).
3 een 0.667 and 1.5 for equivalence) and a Cox proportional hazard model.
4 (n=242) groups using a log-rank test and Cox proportional hazard model.
5 ng episodes were analyzed via the use of Cox proportional hazard model.
6 studies (totalling 8273 subjects) using Cox proportional-hazard model.
7 nical predictors of worse outcomes using Cox proportional hazard models.
8 f death was assessed using multivariable Cox proportional hazard models.
9 performed using Kaplan-Meier curves and Cox proportional hazard models.
10 ing Kaplan-Meier estimation and weighted Cox proportional hazard models.
11 d with MFS and OS by using multivariable Cox proportional hazard models.
12 ality were evaluated using multivariable Cox proportional hazard models.
13 mined separately and as a composite with Cox proportional hazard models.
14 h MeDi were estimated using multivariate Cox proportional hazard models.
15 ed kappa value, Kaplan-Meier curves, and Cox proportional hazard models.
16 were estimated using covariate-adjusted Cox proportional hazard models.
17 mined separately and as a composite with Cox proportional hazard models.
18 repetition with Kaplan-Meier methods and Cox proportional hazard models.
19 RNFL (P = .001) predicted VF progression on proportional hazard models.
20 2D incidence through the use of weighted Cox proportional hazard models.
21 elated with MFS and OS using univariable Cox proportional hazard models.
22 ls) and incidence of periodontitis using Cox proportional hazard models.
23 etween DAPT and stroke was analyzed in a cox proportional hazards model.
24 were used to do a survival GWAS using a Cox proportional hazards model.
25 e to progression) were evaluated using a Cox proportional hazards model.
26 ed by the log-rank test and a supportive Cox proportional hazards model.
27 , and their risk was estimated through a Cox proportional hazards model.
28 ups using a stratified log-rank test and Cox proportional hazards model.
29 all survival (OS) were assessed with the Cox proportional hazards model.
30 to the next pregnancy was modeled using Cox proportional hazards models.
31 s, with risk factors determined by using Cox proportional hazards models.
32 ssociations using spatial random-effects Cox proportional hazards models.
33 on rates with Kaplan-Meier estimates and Cox proportional hazards models.
34 ted using Kaplan-Meier and multivariable Cox Proportional Hazards models.
35 surveillance biopsy was evaluated using Cox proportional hazards models.
36 tality were assessed using multiadjusted Cox proportional hazards models.
37 tment, was analyzed using time-dependent Cox proportional hazards models.
38 (MVHRs) and 95% CIs were calculated with Cox proportional hazards models.
39 urvival was estimated using multivariate Cox proportional hazards models.
40 drome we estimated HRs and 95% CIs using Cox proportional hazards models.
41 cular territory, were summarized by marginal proportional hazards models.
42 y (n = 582) using multivariable-adjusted Cox proportional hazards models.
43 zoster risk was analyzed using time-varying proportional hazards models.
44 to the next pregnancy was modelled using Cox proportional hazards models.
45 cidence was estimated with multivariable Cox proportional hazards models.
46 Survival analyses were performed using Cox proportional hazards models.
47 ear and hazard ratios were derived using Cox Proportional Hazards models.
48 using restricted cubic splines based on Cox proportional hazards models.
49 ions were assessed using distributed-lag Cox proportional hazards models.
50 the Harrell C statistic from unadjusted Cox proportional hazards models.
51 a risk factor using linear, logistic, or Cox proportional hazards models.
52 s (HRs) and 95% CIs were estimated using Cox proportional hazards models.
53 Analyses were conducted using Cox proportional hazards models.
54 justed restricted cubic splines based on Cox proportional hazards models.
55 itiation using propensity score-weighted Cox proportional hazards models.
56 evaluated using logistic regression and Cox proportional hazards models.
57 via multi-level regression analyses and Cox Proportional-Hazards Models.
58 s for distant recurrence with the use of Cox proportional-hazards models.
59 f PNI with DFS and OS was analyzed using Cox proportional-hazards models.
60 nd cardiovascular death was evaluated by Cox proportional hazards modeling.
61 and patient survival were analyzed using Cox proportional hazards modeling.
62 ssociated with ALI were identified using Cox proportional hazards modeling.
63 re assessed with hazard ratios (HRs) and Cox proportional hazards modeling.
64 with CLAD-free survival was assessed by Cox proportional hazards modeling.
65 nd socioeconomic position (wealth) using Cox proportional hazards modelling.
66 ram-negative bloodstream infection using Cox proportional hazards modelling.
67 val [CI], 4.0 to 11.7; hazard ratio in a Cox proportional-hazards model, 0.04; 95% CI, 0.01 to 0.18;
68 dent AF, stroke, and heart failure using Cox proportional hazards modeling, 5-year AF discrimination
69 constructed standard and time-dependent Cox proportional hazards models accounting for competing ris
71 function on 28-day sepsis survival using Cox proportional hazard models adjusted for age and sex in t
72 intake and cancer risk were assessed by Cox proportional hazard models adjusted for known risk facto
75 cardiovascular death were assessed using Cox proportional hazards models adjusted for age, sex, regio
76 isease-free survival were assessed using Cox proportional hazards models adjusted for age, stage, gra
77 5-year mortality using Kaplan-Meier and Cox proportional hazards models adjusted for baseline comorb
79 ion into Cancer and Nutrition (EPIC) and Cox proportional hazards models adjusted for other risk fact
80 ulated by the Kaplan-Meier method, and a Cox proportional-hazards model adjusted for baseline differe
81 ) for febuxostat versus allopurinol in a Cox proportional hazards model (adjusted for the stratificat
82 ofile was associated with mortality in a Cox proportional hazards model (adjusted hazard ratio [aHR]
83 s (HRs) and 95% CIs were estimated using Cox proportional hazards models, adjusted for age, sex, cale
84 ortality rate ratios were estimated with Cox proportional hazards models, adjusted for age, sex, ethn
86 death were evaluated using multivariate Cox proportional hazards models, adjusted for individual- an
91 Aeq24 and LAeqNight using random-effects Cox proportional hazards models adjusting for individual- an
92 tween nsSNP mismatch and graft loss in a Cox proportional hazard model, adjusting for HLA mismatch an
93 ) and overall retransplant-free survival via proportional hazards modeling, adjusting for age, gender
97 analysis included paired-sample t test, Cox proportional hazard models, Akaike information criterion
98 mortality hazard analysis using both the Cox proportional hazard model and Kaplan-Meier curves each s
99 d ratios (HRs) were calculated using the Cox proportional hazard model and tested using the log-rank
101 s between 16 and 34 years of age using a Cox proportional hazards model and an Aalen hazards differen
102 rse data and yield results comparable to Cox proportional hazards model and kernel Cox regression.
103 harge 30-day stroke were assessed with a Cox proportional hazards model and propensity-score matching
104 2012) were evaluated using multivariable Cox proportional hazards modeling and propensity score-match
106 months after AMI was evaluated by using Cox proportional hazards models and area under the receiver
107 isk of ovarian cancer was estimated with Cox proportional hazards models and further adjusted for kno
110 AL) and tooth survival were assessed via Cox proportional-hazards models and multivariate generalized
112 rd ratios (HR) of EOS according to BMI using proportional hazard models, and identified potential med
113 contribution of bolus to mortality using Cox proportional hazard models, and used Bayesian clustering
114 ristics and time to ART initiation using Cox proportional hazard models, and, in a post-hoc analysis,
116 the Kaplan-Meier method, log-rank test, Cox proportional hazards models, and propensity score-matche
117 by NT-proBNP category at baseline using Cox proportional-hazards models, and at any time during the
118 ase event was entered into multivariable Cox proportional hazard models as a time-varying exposure to
122 aracterized the performance of penalized Cox proportional hazard models built using either pathway- o
125 Multivariable logistic regression and Cox proportional hazards models controlled for confounding b
129 recurrence of disease; a multivariate Cox's proportional hazard model defined recurrence risk for di
132 rvival, was examined using multivariable Cox proportional hazards models employing an interaction ter
140 Propensity-matched cohort analysis and Cox proportional hazard model evaluating thrombocytopenia ov
141 HDL markers were analyzed in adjusted Cox proportional hazard models for MI and ischemic stroke.
142 We used hazard ratios (HRs) derived from Cox proportional hazard models for time-to-first event endpo
143 random variables, a multivariable mixed Cox proportional hazards model for graft failure revealed th
146 nidazole compared with vancomycin, using Cox proportional hazards models for time to 30-day all-cause
148 hock stage using logistic regression and Cox proportional-hazards models for hospital and 1-year mort
150 overall survival (OS) in a multivariable Cox proportional hazard model (hazard ratio [HR] with 95% co
153 We conducted the primary analyses using Cox proportional hazards models in those with no previous CV
154 All analyses were performed with the use of proportional-hazards models in the per-protocol populati
155 Elderly study using confounder-adjusted Cox proportional hazards models (including gait speed and da
157 rying confounding through time-dependent Cox proportional hazards models may provide biased estimates
159 he course of ETU care, a marginal structural proportional hazards model (MSPHM) with inverse probabil
162 e associated with all-cause mortality in Cox proportional hazard model (OR 1.7, 95% CI 1.2-2.4, p&0<0
172 for independent outcome prediction using Cox proportional-hazards model showed that protein-activity
173 report time-to-event outcomes using the Cox proportional hazards model so that a treatment effect is
175 predict 2-year survival in multivariable Cox proportional hazards models that included weight and bod
179 ependent OAT exposure was modelled using Cox proportional hazards models (time to first charge) and A
185 Multivariate analyses which employed Cox's proportional Hazard-Model to adjust for numerous variabl
187 usted Kaplan-Meier survival curves and a Cox proportional hazards model to derive an adjusted hazard
190 (HDL-P) subfractions across groups, and Cox proportional hazards modeling to determine associations
193 were evaluated using log-rank tests and Cox proportional hazards models to adjust for known adverse
194 entinoids and used linear regression and Cox proportional hazards models to assess the associations o
196 nd follow-up duration, and used adjusted Cox proportional hazards models to compare diabetes medicati
203 ed standardized-mortality-ratio-weighted Cox proportional hazards models to estimate the association
208 We used logistic regression and adjusted Cox proportional hazards models to identify risk factors for
209 up to four annual eGFR assessments, and Cox proportional hazards models to investigate the associati
211 ed Kaplan-Meier curves and used adjusted Cox proportional-hazards models to examine the differences b
213 essed with the Kaplan-Meier method, with Cox proportional hazard models used to identify factors asso
214 mpared by treatment arm and region, with Cox proportional hazards modeling used to evaluate predictor
215 s with AWM, we trained and cross-validated a proportional hazards model using bone marrow infiltratio
217 d gene-level and pathway-level penalized Cox proportional hazards models using SPM and CNV data for 2
218 ed using an inverse probability weighted Cox proportional hazards model, using a propensity score bas
226 aplan-Meier methods, and a multivariable Cox proportional hazards model was used to identify independ
232 mary efficacy end point, assessed with a Cox proportional-hazards model, was the time to the first pe
240 Kaplan-Meier method and multivariable Cox proportional hazard models were used for data analysis.
261 aluated using Kaplan-Meier analysis, and Cox proportional hazards models were used for subgroup and m
263 Kaplan-Meier curves and multivariable Cox proportional hazards models were used to assess survival
285 variate stepwise logistic regression and Cox proportional-hazard models were used to identify predict
286 ivation dataset (n = 159), the following Cox proportional-hazards models were constructed, each adjus
289 istic and linear regressions, as well as Cox proportional hazard models, were used to analyze the ass
291 es (Qs) of the SDI and weight change and Cox proportional hazard models with different levels of adju
295 gression; for maternal outcomes we applied a proportional hazards model with time-updated IPT exposur
296 benefit was estimated using a mixed-effects proportional hazards model with transplant as a time-dep
297 for 30-day mortality was determined in 3 Cox-proportional hazards models with (1) no CNS, (2) observe