Cost-Efficient Multiply Matched Case-Control Study Designs.

In multiply matched case-control studies, a number of cases and controls may be included in each matched set. However, when per-participant costs between cases and controls differ, investigators should be aware of how the numbers of cases and controls per matched set affect the overall total study cost. Traditional statistical approaches to designing case-control studies do not account for study costs. Given an effect size, the power to detect differences is typically a function of the numbers of cases and controls within each matched set. Therefore, the same level of statistical power will be achieved based on various combinations of the numbers of cases and controls. Typical matched case-control studies match a case to a number of controls by levels of 1 or more known factors. Several authors have shown that for study designs with 1 case per matched set, the optimal number of controls within each matched set that minimizes the total study cost is the square root of the ratio of the cost of a case to the cost of a control. Herein, we extend this result to the setting of a multiply matched case-control study design, when 1 or more cases are matched to controls within each matched set. A Shiny web application implementation of the proposed methods is presented.

Cost-efficient clinical studies with continuous time survival outcomes.

Time-to-event outcomes are common in clinical studies. For example, the time to a first major adverse cardiovascular event (MACE, defined as CVD death, nonfatal myocardial infarction, or stroke) is a commonly used outcome in cardiovascular outcome trials. Owing to the lengthy time frame and other factors, the high costs of conducting such studies has been identified as one of the major obstacles in conducting clinical trials in the United States. However, typical approaches for designing clinical trials with time-to-event outcomes do not consider study costs. For a given effect size (eg, hazard ratio), the power to detect differences between two groups is typically a function of the total number of events observed in the study. Therefore, the same level of power will be achieved based on various combinations of the total number of participants, length of enrollment and total follow-up times, and group allocation probability. Herein, we provide a general framework for designing cost-efficient studies comparing treatments with respect to continuous time-to-event outcomes. Among the various designs that achieve the desired level of power to detect a given effect size for a fixed type-I error level, the optimal cost-efficient design is the design that minimizes the expected total study cost. The method is general and can be used for Cox proportional hazards models or Aalen additive models, and under various recruitment and censoring assumptions. The proposed approach for designing cost-efficient studies is illustrated for a Weibull time-to-event outcome with uniform recruitment and exponentially distributed censoring time. The case of an additive hazards model is also described. A Shiny web application implementation of the proposed methods is presented.

Cost of Elective Labor Induction Compared With Expectant Management in Nulliparous Women.

OBJECTIVE: To compare the actual health-system cost of elective labor induction at 39 weeks of gestation with expectant management. METHODS: This was an economic analysis of patients enrolled in the five Utah hospitals participating in a multicenter randomized trial of elective labor induction at 39 weeks of gestation compared with expectant management in low-risk nulliparous women. The entire trial enrolled more than 6,000 patients. For this subset, 1,201 had cost data available. The primary outcome was relative direct health care costs of maternal and neonatal care from a health system perspective. Secondary outcomes included the costs of each phase of maternal and neonatal care. Direct health system costs of maternal and neonatal care were measured using advanced costing analytics from the time of randomization at 38 weeks of gestation until exit from the study up to 8 weeks postpartum. Costs in each randomization arm were compared using generalized linear models and reported as the relative cost of induction compared with expectant management. With a fixed sample size, we had adequate power to detect a 7.3% or greater difference in overall costs. RESULTS: The total cost of elective induction was no different than expectant management (mean difference +4.7%; 95% CI -2.1% to +12.0%; P=.18). Maternal outpatient antenatal care costs were 47.0% lower in the induction arm (95% CI -58.3% to -32.6%; P<.001). Maternal inpatient intrapartum and delivery care costs, conversely, were 16.9% higher among women undergoing labor induction (95% CI +5.5% to +29.5%; P=.003). Maternal inpatient postpartum care, maternal outpatient care after discharge, neonatal hospital care, and neonatal care after discharge did not differ between arms. CONCLUSION: Total costs of elective labor induction and expectant management did not differ significantly. These results challenge the assumption that elective induction of labor leads to significant cost escalation.

Cost-effectiveness of Antenatal Corticosteroid Therapy vs No Therapy in Women at Risk of Late Preterm Delivery: A Secondary Analysis of a Randomized Clinical Trial.

Importance: Administration of corticosteroids to women at high risk for delivery in the late preterm period (34-36 weeks' gestation) improves short-term neonatal outcomes. The cost implications of this intervention are not known. Objective: To compare the cost-effectiveness of treatment with antenatal corticosteroids with no treatment for women at risk for late preterm delivery. Design, Setting, and Participants: This secondary analysis of the Antenatal Late Preterm Steroids trial, a multicenter randomized clinical trial of antenatal corticosteroids vs placebo in women at risk for late preterm delivery conducted from October 30, 2010, to February 27, 2015. took a third-party payer perspective. Maternal costs were based on Medicaid rates and included those of betamethasone, as well as the outpatient visits or inpatient stay required to administer betamethasone. All direct medical costs for newborn care were included. For infants admitted to the neonatal intensive care unit, comprehensive daily costs were stratified by the acuity of respiratory illness. For infants admitted to the regular newborn nursery, nationally representative cost estimates from the literature were used. Effectiveness was measured as the proportion of infants without the primary outcome of the study: a composite of treatment in the first 72 hours of continuous positive airway pressure or high-flow nasal cannula for 2 hours or more, supplemental oxygen with a fraction of inspired oxygen of 30% or more for 4 hours or more, and extracorporeal membrane oxygenation or mechanical ventilation. This secondary analysis was initially started in June 2016 and revision of the analysis began in May 2017. Exposures: Betamethasone treatment. Main Outcomes and Measures: Incremental cost-effectiveness ratio. Results: Costs were determined for 1426 mother-infant pairs in the betamethasone group (mean [SD] maternal age, 28.6 [6.3] years; 827 [58.0%] white) and 1395 mother-infant pairs in the placebo group (mean [SD] maternal age, 27.9 [6.2] years; 794 [56.9%] white). Treatment with betamethasone was associated with a total mean (SD) woman-infant-pair cost of $4681 ($5798), which was significantly less than the mean (SD) amount of $5379 ($8422) for women and infants in the placebo group (difference, $698; 95% CI, $186-$1257; P = .02). The Antenatal Late Preterm Steroids trial determined that betamethasone use is effective: respiratory morbidity decreased by 2.9% (95% CI, -0.5% to -5.4%). Thus, the cost-effectiveness ratio was -$23 986 per case of respiratory morbidity averted. Inspection of the bootstrap replications confirmed that treatment was the dominant strategy in 5000 samples (98.8%). Sensitivity analyses showed that these results held under most assumptions. Conclusions and Relevance: The findings suggest that antenatal betamethasone treatment is associated with a statistically significant decrease in health care costs and with improved outcomes; thus, this treatment may be an economically desirable strategy.