Anatomic Stage 0 Breast Cancer AJCC v8, Anatomic Stage IA Breast Cancer AJCC v8, Anatomic Stage IB Breast Cancer AJCC v8, Anatomic Stage I Breast Cancer AJCC v8, Prognostic Stage 0 Breast Cancer AJCC v8, Prognostic Stage IA Breast Cancer AJCC v8, Prognostic Stage IB Breast Cancer AJCC v8, Prognostic Stage I Breast Cancer AJCC v8
Conditions
Brief summary
This clinical trial studies how well hypnosedation works in relaxing and reducing the need for general anesthesia in patients who are undergoing breast cancer surgery. Hypnosedation is a technique that places patients under conscious sedation where they remain awake and numbed during surgery and involves the use of words and images to help patients relax and to affect their thoughts about what is happening during surgery.
Detailed description
PRIMARY OBJECTIVES: I. Determine the feasibility of conducting a randomized controlled trial (RCT) of hypnosedation (HS) during breast cancer surgery. SECONDARY OBJECTIVES: I. Assess the preliminary efficacy of HS with local anesthesia versus (vs) opioid based general anesthesia (GA) on reducing self-reported anxiety, pain, nausea, vomiting, cancer-related symptoms, and surgical complication rates. II. Preliminarily evaluate changes in immune markers (natural killer cell function, cytokines, and resolution of inflammatory response markers) and endocrine function (epinephrine, norepinephrine, and cortisol). III. Preliminarily identify changes in neurological activity as assessed through electroencephalogram (EEG) activity. IV. Preliminarily evaluate the group differences in medical costs. OUTLINE: Patients are randomized to 1 of 2 groups. GROUP I: Patients undergo hypnosedation performed by a mind-body specialist before surgery begins and continuing until after surgery is complete. GROUP II: Patients speak to a mind-body specialist before surgery and prior to receiving general anesthesia. After completion of study intervention, patients are followed up at days 1, 3, 5, 7, and 14.
Interventions
BEHAVIORALHypnosedation
Undergo hypnosedation
OTHERQuestionnaire Administration
Ancillary studies
BEHAVIORALVerbal Support
Speak with min-body specialist
Sponsors
M.D. Anderson Cancer Center
National Cancer Institute (NCI)
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
SUPPORTIVE_CARE
Masking
NONE
Eligibility
Sex/Gender
FEMALE
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Female clinical stage 0/1 breast cancers patients scheduled to undergo a unilateral, segmental mastectomy +/- sentinel lymph node dissection * Able to read, speak, and write English or Spanish
Exclusion criteria
* A significant anxiety disorder * Significant pain during core biopsy as reported by the patient * Received neoadjuvant chemotherapy, any autoimmune or immunological disease or taking any immune suppression drugs * Plastic surgery involvement for oncoplastic reconstruction * If surgery is likely greater than 3 hours
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Hypnosedation (HS) feasibility | Up to 1 day | Will be determined by two criteria: overall accrual and successful delivery of HS. The intervention will be deemed feasible if: 1) \>= 30% of enrolled patients consent and \>= 60% of enrolled patients in HS complete surgery without the need of general anesthesia. The study will calculate rates, frequencies, and 90% confidence intervals (CIs), as applicable. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Efficacy of HS | Up to 1 day | Will estimate the mean differences of these outcomes between groups and corresponding 90% confidence intervals at specified points in time (baseline, during the procedure, if applicable, and post-procedure), as well as across time points, using linear mixed models (LMMs). Will similarly evaluate the difference in the slope of change for these outcomes between arms. Baseline covariates such as those used in the minimization will be controlled for in our analyses. Time-varying predictors (such as electroencephalograms \[EEGs\]) may be controlled for in additional exploratory analyses. Standard model diagnostics will be applied to check for model assumptions, such as normality of the residual distribution. |
| Assessment of changes in immune markers and endocrine function | Up to 14 days post-surgery | Will estimate the mean differences of these outcomes between groups and corresponding 90% confidence intervals at specified points in time (baseline, during the procedure, if applicable, and post-procedure), as well as across time points, using linear mixed models (LMMs). Will similarly evaluate the difference in the slope of change for these outcomes between arms. Baseline covariates such as those used in the minimization will be controlled for in our analyses. Time-varying predictors (such as electroencephalograms \[EEGs\]) may be controlled for in additional exploratory analyses. Standard model diagnostics will be applied to check for model assumptions, such as normality of the residual distribution. |
| Changes in EEG activity as assessed using standardized low-resolution brain electromagnetic tomography (sLORETA) | Baseline up to 14 days post-surgery | One test for each of the nine frequency band pass regions will be conducted as well as voxel-by-voxel t-tests computed for the whole data set. For each subject, power means within the frequency bands will be summed across all electrode sites in both absolute and relative power. Within-group differences will be examined using paired-sample t-tests. Between-group differences will be examined using analysis of covariance (ANCOVA) with the condition as the fixed variable, baseline EEG scores as the covariate, and post intervention scores as the dependent variable. Percent signal changes will be computed at all six time points of interest in our predetermined regions of interest (ROIs). |
| Group differences in medical costs | From the date of surgery up to 14 days | Will obtain detailed billing records from the date of surgery to the point of discharge at 14 days (+/- 5 days) and quantify medical costs in two ways. The first method is to apply cost-to-charge ratio to convert charges on the billing records to cost. The second method will identify from the study's institutional database each billing code appearing in patient's professional and technical charges, and calculate costs using Medicare reimbursement rates corresponding to current procedural terminology (CPT) codes. Because medical costs are highly skewed, the study will apply the non-parametric bootstrapping method to compare difference in medical costs between groups. |
Countries
United States
Contacts
PRINCIPAL_INVESTIGATORLorenzo Cohen
M.D. Anderson Cancer Center
Outcome results
None listed