Evaluation of Adherence and Therapeutic Effectiveness of Bi-Flex Versus CPAP in Children With OSA
Evaluation of Adherence and Therapeutic Effectiveness of Bi-Flex Versus CPAP in Children With OSA
Context: The obstructive sleep apnea syndrome (OSAS), i.e., snoring with difficulty breathing
 during sleep, is common in children. Continuous positive airway pressure (CPAP) therapy is
 the usual treatment for children who do not improve following surgery. However, CPAP is
 uncomfortable and is often not tolerated. We therefore plan to study a modification of
 bilevel positive airway pressure therapy, BiPAP with Bi-Flex that may be more comfortable.

 Objectives: The primary objective of this study is to determine whether BiPAP with Bi-Flex
 results in improvement in adherence as compared to CPAP. The secondary objective is to
 determine whether Bi-Flex has similar therapeutic efficacy compared to CPAP, as determined by
 sleep study. Additional objectives include comparing CPAP and Bi-Flex effects on comfort and
 determining which parameters predict adherence.

 Study Design/Setting/Participants: A single center, randomized controlled double-blind study
 of Bi-Flex vs CPAP use in children with OSAS over a 3 month period.

 Intervention: Bi-Flex vs CPAP Study Measures: Objective compliance recordings, sleep study
 results, subjective questionnaire results. .
STUDY RATIONALE The obstructive sleep apnea syndrome (OSAS) affects approximately 2% of
 children and results in significant morbidity. Continuous positive airway pressure (CPAP) is
 the standard therapy for children who fail tonsillectomy and adenoidectomy, or for those in
 whom surgery is not indicated. However, CPAP is uncomfortable and is often not tolerated by
 children. Thus, a more comfortable technology that would enhance adherence would be highly
 desirable. This proposal aims to compare a new technology, Bi-Flex, to standard CPAP therapy.

 Bilevel positive airway pressure (BiPAP): Whereas conventional CPAP therapy delivers a
 constant, steady pressure during inspiration and expiration, BiPAP therapy is intended to
 respond to both inspiration and expiration by the patient and to deliver a set amount of
 pressure when the patient begins spontaneous inhalation, and decreasing pressure when
 exhalation begins. Exhaling against lower pressure is thought to be more comfortable for most
 patients than the continuous pressure delivered by conventional CPAP therapy, although it has
 not been shown objectively to improve adherence. The BiPAP waveform is fixed in that it
 provides for set inspiratory and expiratory pressures. For example, the patient's clinically
 prescribed BiPAP pressures may be set at an Inspiratory Positive Airway Pressure (IPAP) =12
 cm water (H2O), and Expiratory Positive Airway Pressure (EPAP) = 8 cm H2O.

 The Bi-Flex® feature provides a variation of conventional BiPAP that provides a reduction in
 the inspiratory positive airway pressure (IPAP) provided toward the end of the inspiratory
 portion of the breathing cycle when the patient's inspiratory airflow normally diminishes,
 compared with the level of pressure provided during the majority of inspiration, and also
 allows reduction in the expiratory positive airway pressure (EPAP) during the initial portion
 of exhalation compared with that provided during the latter portion of expiration. The
 purpose of this modification is to provide pressure relief for the patient to smooth the
 transition period between the end of IPAP and the beginning of EPAP to allow for a more
 comfortable delivery of PAP therapy. Because Bi-Flex provides both a lower expiratory
 pressure and pressure relief, it has the potential to be the most comfortable mode of
 positive pressure therapy delivery available, and therefore to improve adherence. However,
 there have been no studies of adherence to therapy using Bi-Flex in either children or
 adults.

 STUDY OBJECTIVES

 1. To determine whether BiPAP with Bi-Flex as compared to CPAP results in improvement in
 adherence of > 30 minutes a night averaged over 3 months of home use.

 2. To determine whether BiPAP with Bi-Flex as compared to CPAP results in a lower study
 dropout rate.

 3. To determine whether Bi-Flex has similar therapeutic efficacy compared to CPAP, as
 determined by polysomnographic measurements of OSAS.

 4. To determine whether Bi-Flex, compared to CPAP, results in improved subjective comfort
 and improved quality of life.

 5. To determine whether objective parameters (including demographic and polysomnographic
 variables) or subjective parameters predict adherence.

 STUDY DESIGN This will be a 3-month, double-blinded, randomized trial of BiPAP with Bi-Flex
 vs CPAP in children with OSAS in whom CPAP is medically indicated Subjects will undergo a
 baseline diagnostic sleep study as part of their routine clinical care, prior to study
 enrollment. Those who agree to participate will then be consented and assented to participate
 in this study. They will be randomized to either a Bi-Flex or CPAP treatment arm, in a three
 to one fashion. In each arm, each subject will undergo a clinical Bi-Flex or CPAP titration
 sleep study.

 Following these studies, the subjects in both arms will be asked to use their respective
 machines, in either the BiPAP with Bi-Flex or CPAP mode, at home for 3 months. During that
 time, they will have monthly visits to assess adherence as well as subjective measures of
 comfort and quality of life. A repeat sleep study will be performed at the end of 3 months on
 the mode assigned (Bi-Flex or CPAP). Subjects will complete standardized questionnaires
 regarding symptoms and quality of life throughout the study.

 EFFICACY EVALUATIONS Adherence will be assessed by the mean nightly usage as determined by
 the equipment compliance recording. Drop-out will be assessed by determining which subjects
 are using the device < 2 hours a night. Efficacy of treatment will be assessed using
 polysomnographic parameters such as the apnea hypopnea index.

 SAFETY EVALUATIONS Polysomnographic parameters such as the apnea hypopnea index, arterial
 oxygen saturation and end-tidal PCO2 will be monitored.

 STATISTICAL AND ANALYTIC PLAN The primary effectiveness endpoint is the hours of device use
 per night over a three month period, as determined from the equipment software.

 Analysis Populations

 Two analysis populations will be evaluated. An intent-to-treat (ITT) analysis will include
 all patients in the trial by their assigned treatment and will be used for effectiveness and
 safety. For patients with missing data, values will be imputed as described below. A second
 analysis will be done on evaluable patients, i.e., those who have complete data and these
 patients will be evaluated for effectiveness.

 Primary Safety Analysis

 The rate of adverse events will be compared between the two groups by assessing the
 proportion of subjects who experience at least one adverse event by Fisher's exact test. If
 the test is statistically significant, then this univariate analysis will be followed by a
 multivariate logistic regression analysis.

 Screening of possible covariates will be done by a method similar to that described in Hosmer
 and Lemeshow 25 for logistic regression models. A complete list of clinically relevant
 variables to be screened will be provided in a detailed statistical analysis plan formulated
 prior to database lock but will include age, gender, height, weight, and others. The
 variables on this list will be augmented with variables found to be out of balance between
 the treatment groups from the comparability analysis described above. Models will be fit for
 each possible covariate to include treatment, the covariate, and the interaction between the
 covariate and treatment will be used. Any covariate or interaction significant at a P-value
 of 0.15 or lower from the screening analysis will allow the variable to enter the backward
 elimination procedure for the final model. If the interaction is significant, then both the
 covariate and its interaction need to be included in the model.

 The backward elimination will be done manually starting with the interaction with the highest
 P-value. Interaction terms will be removed from the model first and then non-significant main
 effects. Variables will be retained in the model if the P-value for the variable or its
 interaction is 0.05 or less. This analysis is intended to demonstrate that the treatment
 affect adjusted for possible covariates is still statistically significant.

 Secondary Safety Analyses The secondary safety analysis will include a descriptive
 presentation of individual adverse events each tested with Fisher's exact test. Serious
 adverse events will be presented separately with narratives of the events.

 Primary Effectiveness Analysis

 The primary effectiveness variable is the hours of use per night over three months. This
 variable will be summarized with mean, median, standard deviation, minimum and maximum. The
 one-sided lower 95% confidence interval will be computed for the Bi-Flex treated subjects and
 the upper one-sided 95% confidence interval will be computed for the CPAP treated subjects.
 These two intervals will be visually compared to determine if either interval excludes the
 mean of the other treatment. Such exclusion will provide suggestive evidence that the Bi-Flex
 treatment leads to higher compliance than the CPAP treatment.

 Further, a mixed models analysis of hours of use will be done through three months. This
 multivariate analysis incorporating clinically important covariates will screen variables for
 inclusion in a manner similar to that described above. Screening of possible covariates will
 be done by a method similar to that described in Hosmer and Lemeshow 25 for logistic
 regression models as discussed above. The same set of potential covariates as described in
 the safety analysis above will be screened. Models will be fit for each possible covariate to
 include treatment, the covariate, and the interaction between the covariate and treatment
 will be used. Any covariate or interaction significant at a P-value of 0.15 or lower from the
 screening analysis will allow the variable to enter the backward elimination procedure for
 the final model. If the interaction is significant, then both the covariate and its
 interaction need to be included in the model.

 The backward elimination will be done manually starting with the interaction with the highest
 P-value. Interaction terms will be removed from the model first and then non-significant main
 effects. Variables will be retained in the model if the P-value for the variable or its
 interaction is 0.05 or less. This analysis is intended to demonstrate that the treatment
 affect adjusted for possible covariates is still statistically significant.

 Secondary Effectiveness Analyses The drop out rate will be compared between the two groups
 will be estimated. The rate for each group will be tabulated and computed with 95% exact
 binomial confidence intervals.

 The objective sleep parameters of Apnea Hypopnea Index (AHI), arterial oxygen saturation
 nadir, time with elevated end-tidal partial pressure of Carbon Dioxide (PCO2) and the arousal
 index will be presented descriptively by treatment group. The tables will include the mean,
 standard deviation, median, minimum and maximum.

 The subjective sleep measures of OSA 18 score, modified Epworth Sleepiness Scale, the NOSE,
 and pediatric quality of life index (PedQL) will be presented descriptively by treatment
 group. The tables will include the mean, standard deviation, median, minimum and maximum.

 Additional Analysis Exploratory analyses of the relationships of study variables to outcomes
 will be done to determine if there is the treatment difference is particularly strong is
 specific sub-groups.

 Patient Accountability and Missing Data The number and proportion of patients eligible for
 and compliant with each follow-up examination will be presented. Patients who withdraw from
 the study will be tabulated with the reasons for the withdrawal. If the proportion of
 patients withdrawn is larger than the 15% from either arm, an analysis of the demographic and
 prognostic characteristics will be made between patients who withdraw and those who remain in
 the study. For continuous variables, parametric or non-parametric analysis of variance will
 be used. For categorical variables, Chi-square or Fisher's exact test will be applied.

 The evaluation of withdrawn patients presents a special concern. All clinical studies analyze
 the results based on the evaluable patients, i.e., those who complete the study. Because
 withdrawn patients do not have final data, they present a problem. The statistical community
 26-29 recommends that multiple sensitivity analyses be conducted to determine the robustness
 of the result in patients who complete the study. The intention of these analyses is to
 demonstrate that the results obtained from the evaluable patients are not biased.

 As a result, sensitivity analyses using multiple imputation analyses will be conducted to
 evaluate the robustness of the study result accounting for missing observations. The
 imputation will be a non-parametric multiple imputation in which patients withdrawn from the
 study will be randomly assigned outcomes by grouping on demographic and prognostic
 characteristics including treatment assignment maintaining masking, matching the
 characteristics to the withdrawn patients, and randomly selecting the result for the missed
 observation from the results for patients with similar characteristics by method such as "hot
 deck" imputation or imputation by regression 30. All imputations will be stochastic
 imputations to preserve the variability of the imputed value. Also, imputations will be done
 in a manner that is consistent with the assumptions of multiple imputation theory including
 missing at random to the extent possible. If the missing at random assumption is clearly
 violated by the data, other procedures including selection modeling and pattern mixture
 modeling will be considered.

 Detailed Analysis Plan Prior to database lock a detailed statistical analysis plan will be
 written to provide a detailed description of the statistical analysis to be used in the final
 analysis. This plan will incorporate lists of relevant clinical variables to be tested as
 possible covariates and will incorporate any protocol changes that would affect the analysis.

 Statistical Software

 The statistical analyses will be done using SAS version 9.1 or later, statistical software
 (StatXact Version 7 or later, and Systat 10 or later). Each of these software packages
 provides special features that will be exploited to provide a comprehensive analysis with
 excellent graphics support.
Inclusion Criteria:

 1. Males or females aged 2 to 16 years.

 2. OSAS diagnosed on polysomnography.

 3. Positive airway pressure therapy indicated by patient's physician because surgery was
 either contraindicated or ineffective.

 4. No plans for upper airway surgery in the next 3 months.

 Exclusion Criteria:

 1. Age less than 2 years, as infants and toddlers have different pulmonary mechanics from
 older children, and may require intense behavioral modification programs prior to CPAP
 use.

 2. Age greater or equal to 16 years, as results may be similar to adult studies in these
 older patients.

 3. Previous use of CPAP / bilevel ventilation.

 4. Unable to read / understand English. -