Value of a run-in period in a drug trial during pregnancy

Blackwelder, William C.; Hastings, Betty K.; Lee, Molly L.F.; Deloria, Maria A.

doi:10.1016/0197-2456(90)90013-r

Cited by 19 publications

(13 citation statements)

References 7 publications

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“…This correlates with data from the run‐in for the Physicians' Health Study; adherence during their 18‐week run‐in period was the strongest predictor of adherence to aspirin throughout the trial 1,20 . Although run‐in periods are expensive and decrease the amount of available follow‐up time, 21 they may result in increased efficiency and decreased overall cost 20,22 …”

Section: Discussionmentioning

confidence: 52%

Inclusion of Older Women in Randomized Clinical Trials: Factors Associated with Taking Study Medication in the Fracture Intervention Trial

Buist

LaCroix

Black

et al. 2000

J American Geriatrics Society

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Section: Discussionmentioning

confidence: 52%

Inclusion of Older Women in Randomized Clinical Trials: Factors Associated with Taking Study Medication in the Fracture Intervention Trial

Buist

LaCroix

Black

et al. 2000

J American Geriatrics Society

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“…16 Those who took less than two-thirds of the allotted placebo pills during the run-in, who did not return to the clinic or refused further participation were not randomized. Patients who successfully completed the run-in, had none of the exclusion criteria, and were <30 weeks gestation were randomized as described previously.…”

Section: Clinical Trial Methodsmentioning

confidence: 99%

Double-blind placebo-controlled treatment trial ofChlamydia trachomatis endocervical infections in pregnant women

Martín

Eschenbach

Cotch

et al. 1997

Infect. Dis. Obstet. Gynecol.

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Objective: The purpose of this study was to determine if treatment of pregnant women with Chlamydia trachomatis infection would lower the incidence of preterm delivery and/or low birth weight.Methods: Pregnant women between the 23rd and 29th weeks of gestation were randomized in double-blind fashion to receive either erythromycin 333 mg three times daily or an identical placebo.The trial continued until the end of the 35th week of gestation.Results: When the results were examined without regard to study site, erythromycin had little impact on reducing low birth weight (8% vs. 11%, P 0.4) or preterm delivery (13% vs. 15%, P 0.7). At the sites with high persistence of C. trachomatis in the placebo-treated women, low birth weight infants occurred in 9 (8%) of 114 erythromycin-treated and 18 (17%) of 105 placebo-treated women (P 0.04) and delivery <37 weeks occurred in 15 (13%) of 115 erythromycin-treated and 18 (17%) of 105 placebo-treated women (P 0.4).Conclusions: The results of this trial suggest that the risk of low birth weight can be decreased by giving erythromycin to some women with C. trachomatis. Due to the high clearance rate of C.

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“…Moreover, as applied in Tables 111 and IV, the inequalities show that if a run-in is expensive, the savings following randomization must be substantial for the run-in to be worthwhile. While it is clear that a high screened to eligible ratio should make it difficult for a run-in to be cost-effective, inequalities (7) and (8) underscore the magnitude of the impact of this ratio. For example, if R = 0.9 and E = 1.3, these inequalities show that if a run-in is to be cost-effective, a trial with a screened to eligible ratio of 50 will require a cost ratio that is greater by a magnitude of 120 than a corresponding trial with a screened to eligible ratio of 10.…”

Section: General Conclusion -Cost-effectivenessmentioning

confidence: 99%

A comprehensive algorithm for determining whether a run‐in strategy will be a cost‐effective design modification in a randomized clinical trial

Schechtman

Gordon

1993

Statistics in Medicine

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In randomized clinical trials, poor compliance and treatment intolerance lead to reduced between-group differences, increased sample size requirements, and increased cost. A run-in strategy is intended to reduce these problems. In this paper, we develop a comprehensive set of measures specifically sensitive to the effect of a run-in on cost and sample size requirements, both before and after randomization. Using these measures, we describe a step-by-step algorithm through which one can estimate the cost-effectiveness of a potential run-in. Because the cost-effectiveness of a run-in is partly mediated by its effect on sample size, we begin by discussing the likely impact of a planned run-in on the required number of randomized, eligible, and screened subjects. Run-in strategies are most likely to be cost-effective when: (1) per patient costs during the post-randomization as compared to the screening period are high; (2) poor compliance is associated with a substantial reduction in response to treatment; (3) the number of screened patients needed to identify a single eligible patient is small; (4) the run-in is inexpensive; (5) for most patients, the run-in compliance status is maintained following randomization and, most importantly, (6) many subjects excluded by the run-in are treatment intolerant or non-compliant to the extent that we expect little or no treatment response. Our analysis suggests that conditions for the cost-effectiveness of run-in strategies are stringent. In particular, if the only purpose of a run-in is to exclude ordinary partial compliers, the run-in will frequently add to the cost of the trial. Often, the cost-effectiveness of a run-in requires that one can identify and exclude a substantial number of treatment intolerant or otherwise unresponsive subjects.

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Value of a run-in period in a drug trial during pregnancy

Cited by 19 publications

References 7 publications

Inclusion of Older Women in Randomized Clinical Trials: Factors Associated with Taking Study Medication in the Fracture Intervention Trial

Inclusion of Older Women in Randomized Clinical Trials: Factors Associated with Taking Study Medication in the Fracture Intervention Trial

Double-blind placebo-controlled treatment trial ofChlamydia trachomatis endocervical infections in pregnant women

A comprehensive algorithm for determining whether a run‐in strategy will be a cost‐effective design modification in a randomized clinical trial

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