kwic
clinical
clinical
right
off
ON
78
1
100
500
strict
ELIZA cgi-bash version rev. 1.90
- Medical English LInking keywords finder for the PubMed Zipped Archive (ELIZA) -
return
kwic search for clinical out of >500 occurrences
554339 occurrences (No.20 in the rank) during 5 years in the PubMed. [no cache] 500 found
--- ABSTRACT ---
--- ABSTRACT END ---
[frequency of next (right) word to clinical]
554339 occurrences (No.20 in the rank) during 5 years in the PubMed. [no cache] 500 found
| 78) In the absence of placebo-controlled trials, determining the non-inferiority (NI) margin for comparing an experimental treatment with an active comparator is based on carefully selected well-controlled historical clinical trials. |
| PMID:23913880 DOI:10.1002/pst.1588 |
| 2015 Pharmaceutical statistics |
| * Bayesian approach to the design and analysis of non-inferiority trials for anti-infective products. |
| - In the absence of placebo-controlled trials, determining the non-inferiority (NI) margin for comparing an experimental treatment with an active comparator is based on carefully selected well-controlled historical clinical trials. With this approach, information on the effect of the active comparator from other sources including observational studies and early phase trials is usually ignored because of the need to maintain active comparator effect across trials. This may lead to conservative estimates of the margin that translate into larger sample-size requirements for the design and subsequent frequentist analysis, longer trial durations, and higher drug development costs. In this article, we provide methodological approaches to determine NI margins that can utilize all relevant historical data through a novel power adjusted Bayesian meta-analysis, with Dirichlet process priors, that puts ordered weights on the amount of information a set of data contributes. We also provide a Bayesian decision rule for the non-inferiority analysis that is based on a broader use of available prior information and a sample-size determination that is based on this Bayesian decision rule. Finally, the methodology is illustrated through several examples. |
[
right
kwic]
(1)36  and |
(17)5 application |
(33)3 attachment |
(49)2 grading |
| (2)26 practice |
(18)5 data |
(34)3 course, |
(50)2 interventions |
| (3)22 trials |
(19)5 efficacy |
(35)3 examination, |
(51)2 literature |
| (4)19 trial |
(20)5 features |
(36)3 experience |
(52)2 measures |
| (5)14 research |
(21)5 outcome |
(37)3 information |
(53)2 nurse |
| (6)14 studies |
(22)5 picture |
(38)3 manifestations |
(54)2 observations |
| (7)10 use |
(23)5 relevance |
(39)3 significance |
(55)2 point |
| (8)8 parameters |
(24)5 symptoms |
(40)3 variables |
(56)2 practice, |
| (9)8 settings |
(25)5 translation |
(41)2 benefits |
(57)2 presentation, |
| (10)8 signs |
(26)5 trials, |
(42)2 cases |
(58)2 process |
| (11)8 study |
(27)5 utility |
(43)2 conditions |
(59)2 results |
| (12)7 examination |
(28)4 characteristics |
(44)2 context |
(60)2 sample, |
| (13)7 implications |
(29)4 evaluation |
(45)2 decision-making |
(61)2 situation |
| (14)7 presentation |
(30)4 management |
(46)2 decisions |
(62)2 situations, |
| (15)6 applications |
(31)4 outcomes |
(47)2 diagnosis |
(63)2 success |
| (16)6 course |
(32)4 signs, |
(48)2 findings |
(64)2 tooth |
add keyword
--- WordNet output for clinical ---