Abstract
Background:
Patients taking adjuvant endocrine therapy (AET) after breast cancer face adherence challenges and symptom-related distress. We conducted a randomized trial to evaluate the feasibility, acceptability, and preliminary efficacy of a telehealth intervention (STRIDE) for patients taking AET.
Methods:
From 10/2019 to 6/2021, 100 patients reporting difficulty with AET were randomly assigned to either STRIDE or a Medication Monitoring (MedMon) control group. STRIDE included six weekly small-group videoconferencing sessions and two individual calls. We defined feasibility as having >50% of eligible patients enroll, >70% complete the 12-week assessment, and >70% of STRIDE patients complete ≥4/6 sessions. We monitored adherence with the Medication Event Monitoring System Caps (MEMS Caps). At baseline and 12- and 24-weeks post-baseline, patients self-reported adherence (Medication Adherence Report Scale), AET satisfaction (Cancer Therapy Satisfaction Questionnaire), symptom distress (Breast Cancer Prevention Trial-Symptom Checklist), self-management of symptoms (Self-efficacy for Symptom Management-AET), coping (Measure of Current Status), quality of life (QOL; Functional Assessment of Cancer Therapy-Breast), and mood (Hospital Anxiety and Depression Scale). We used linear mixed effects models to assess the effect of STRIDE on longitudinal outcomes.
Results:
We enrolled 70.9% (100/141) of eligible patients; 92% completed the 12-week assessment, and 86% completed ≥4/6 STRIDE sessions. Compared to MedMon, STRIDE patients reported less symptom distress (B[difference]=−1.91; 95% CI[−3.29, −0.52], p=.007) and better self-management of AET symptoms, coping, QOL, and mood. We did not observe significant differences in AET satisfaction or adherence.
Conclusions:
STRIDE is feasible and acceptable, showing promise for improving outcomes in patients taking AET after breast cancer.
Keywords: Endocrine Therapy, Breast Cancer, Telehealth, Adherence, Symptoms, Side Effects, Distress, Psychosocial Intervention
Lay Summary:
Patients taking adjuvant endocrine therapy (AET) after breast cancer may face challenges while following their treatment regimen. In this randomized controlled trial of 100 patients taking AET, a brief, small-group virtual intervention (STRIDE) was well-received by patients and led to improvements in how upset patients were due to symptoms, how confident they were in managing symptoms, and how well they could cope with stress. Thus, STRIDE is a promising intervention and should be tested in future multi-site trials.
Precis:
A brief, small group telehealth intervention (STRIDE) that combines adherence counseling, self-efficacy for self-management of symptoms, and coping skills for distress is feasible and acceptable for patients taking adjuvant endocrine therapy (AET) after breast cancer. Patients in the STRIDE intervention, compared to a medication monitoring control group, experienced improvements in symptom distress, quality of life, coping skills, anxiety symptoms, and self-efficacy for managing symptoms across the study period.
Introduction
While breast cancer is the second leading cause of cancer-related deaths among women,1 adjuvant endocrine therapy (AET) is a lifesaving treatment for early-stage, hormone-sensitive breast cancer.2 Up to 80% of breast malignancies are hormone sensitive3 and treated with AET (e.g., tamoxifen or an aromatase inhibitor) for 5–10 years, effectively reducing patients’ recurrence risk by 40–50%3,4 and improving 15-year survival by one third.4 Despite these benefits, patients live with AET-related physical and emotional sequelae that interfere with quality of life (QOL) and ability to take the medication daily as prescribed. The most prominent symptoms include myalgias/arthralgias, hot flashes, sleep disturbances/insomnia, sexual dysfunction, fatigue, weight gain, cognitive impairment, and mood fluctuations.5–10 Given patients’ difficulties managing these symptoms, adherence to AET (i.e., taking medication as prescribed) is alarmingly low and presents an ongoing concern in breast cancer care.11–13
Up to 59% of patients are not adherent to their AET regimen,14,15 and adherence declines each year following treatment initiation.16 The negative effects of AET non-adherence have been consistently documented, including increases in breast cancer recurrence,17 breast cancer mortality,18 and overall mortality.19 Accordingly, the American Society of Clinical Oncology (ASCO) recommends that clinicians manage AET-related symptoms to reduce barriers to medication-taking and enhance adherence.3,5 However, efficacious interventions to improve adherence to AET are lacking, and only five published trials have targeted this behavior. The limitations of prior trials and interventions are well-documented and include the lack of focus on improving self-management of AET symptoms as the primary barrier to adherence and the absence of theory informed and evidence-based intervention strategies.20–22
To address this need, we followed the NIH Stage Model for Behavioral Intervention Development23 to develop an evidence-based, telehealth intervention: Symptom-Targeted Randomized Intervention for Distress and Adherence to Adjuvant Endocrine Therapy (STRIDE).24,25 We conducted a single-center pilot randomized controlled trial to examine the feasibility and acceptability of the STRIDE intervention, compared to a Medication Monitoring (MedMon) control condition, as well as explore preliminary effects of the intervention.26
Methods
Study Design
We conducted a randomized controlled pilot trial of a brief, small-group telehealth intervention (STRIDE) for patients taking AET after breast cancer, compared to a MedMon control group (ClinicalTrials.gov identifier: NCT03837496). This study took place at the Massachusetts General Hospital (MGH) Cancer Center in Boston, Massachusetts and three community affiliates. The Dana-Farber Harvard Cancer Center Institutional Review Board reviewed and approved the study protocol prior to initiation.
Participants
Eligible patients were female, age ≥21 years, diagnosed with early-stage hormone receptor-positive breast cancer (Stage 0-IIIB), finished with primary treatment, within one week to 36 months of starting AET, and English speaking. They also had to have an Eastern Cooperative Oncology Group (ECOG) performance status of ≤2. Patients completed an adapted National Comprehensive Cancer Network (NCCN) distress thermometer27 and were eligible if they scored ≥4 (range=0–10) on any of three questions: 1) How upset are you by having to take hormonal therapy? 2) How bothered are you by the symptoms? 3) How difficult is it for you to take your hormonal therapy medication every day? Patients were not eligible if they were enrolled in a clinical trial, psychosocial intervention study, or other group psychotherapy; were undergoing primary treatment for another cancer; or had a condition that would affect study participation (e.g., uncontrolled psychosis, active suicidal ideation, psychiatric hospitalization within the year, or cognitive impairment). Patients without access to an electronic device (e.g., smartphone, computer) for the virtual study sessions were offered a study tablet.
Study Procedures
From 10/12/2019 to 6/4/2021, study staff reviewed the electronic health records (EHR) of patients in the breast oncology clinic and called potentially eligible patients after obtaining permission from their oncology clinician. Interested patients with AET-related distress ≥4 were offered participation. Study staff obtained informed consent electronically via REDCap, a HIPAA-approved online survey tool. We paused recruitment from mid-March 2020 through May 2020 due to the COVID-19 pandemic. Once consented, all patients completed baseline questionnaires electronically and received the Medication Event Monitoring System pill bottle and cap (MEMS Caps)28 by mail. After storing AET in the MEMS Caps for a one-week period to capture a baseline adherence rate, patients were randomized 1:1 to the STRIDE intervention or the MedMon control group using a computer-generated randomization scheme. We stratified randomization by level of distress on the baseline Hospital Anxiety and Depression Scale subscales29 (HADS; high [≥8] vs. low [<8]). Patients randomly assigned to STRIDE were placed in small groups of two to three participants based on scheduling availability. All patients repeated questionnaires at 12 weeks and 24 weeks post-baseline and continued using the MEMS Caps throughout the study. They were remunerated $20 per completed assessment.
MedMon Control
Patients randomly assigned to MedMon received care as usual and monitored their medication-taking using the MEMS Caps throughout the study. They were offered the STRIDE workbook after their final study assessment.
STRIDE Intervention
Patients randomly assigned to STRIDE also received care as usual and monitored their medication-taking using the MEMS Caps throughout the study. STRIDE is a brief, manualized, telehealth intervention. A description of STRIDE is summarized in Table 2 and published elsewhere.24 Using the NIH Stage Model for Behavioral Intervention Development,23 we developed STRIDE based on 1) our systematic review of interventions for oral anticancer therapy adherence,30 2) our qualitative analysis of patients’ perceptions of AET,25 3) efficacious interventions for treatment adherence31 and stress management in breast cancer,32 4) theoretical models including Murray’s Framework for Medication Adherence33 and the Cognitive Model for Menopausal Symptoms,34 5) expert input from breast oncologists and behavioral scientists, and 6) an open pilot study.24
Table 2.
STRIDE Intervention Content, Targets, and Underlying Theoretical Frameworks
| Session Theoretical Framework |
Behavioral Targets | Topics |
|---|---|---|
|
Session 1 MFMA CMMS |
AET psychoeducation Optimize adherence Relaxation training |
|
|
Session 2 CMAC |
Cognitive reframing of AET-related thoughts/beliefs |
|
|
Session 3 CMAC CMMS |
Coping effectiveness & mindfulness for AET distress |
|
|
Session 4 CMMS MFMA |
AET side effect self-management Relaxation training |
|
|
Session 5 CMMS CMAC MFMA |
AET side effect self-management Acceptance skills |
|
|
Session 6 CMMS CMAC |
AET side effect self-management Coping w/ uncertainty |
|
Note: MFMA = Murray’s Framework for Medication Adherence; CMAC = Cognitive Model of Adjustment to Cancer; CMMS = Cognitive Model for Menopausal Symptoms
Those randomly assigned to STRIDE received usual care in addition to six weekly one-hour virtual sessions in small groups of two to three participants and two individual 20-minute phone calls at four- and five-months post-baseline, respectively. The two phone calls served as brief booster sessions to review ongoing use of skills and to determine the need for any additional referrals (e.g., nutrition, psychiatry, rehabilitation medicine). These were conducted individually for ease of scheduling and to maximize efficiency when offering referrals and skills’ review. Licensed clinical psychologists or psychology fellows delivered sessions via a HIPAA-compliant videoconferencing software (Zoom). Patients were encouraged to practice skills using audio recordings between sessions, and therapists rated patients’ homework completion (0=not complete; 7=complete). Therapists participated in weekly supervision. To assess fidelity, study staff reviewed 10% of sessions, stratified by therapist, for content with a goal of >90% of topics covered per session.
Measures
At baseline, study staff reviewed the EHR to obtain clinical information about breast cancer and treatment, while patients self-reported sociodemographic characteristics. To assess intervention acceptability, patients in STRIDE completed the Client Satisfaction Questionnaire (CSQ-3).35
We administered the Medication Adherence Report Scale (MARS-5)36 to assess self-reported adherence to AET, as well as the MEMS Caps for an objective measure, which electronically records bottle openings as a proxy for taking medication.25 Patients used a medication diary as a supplement. Study staff documented medication breaks or changes per patient report. We administered the Cancer Therapy Satisfaction Questionnaire (CTSQ)37 to assess satisfaction with AET, the Breast Cancer Prevention Trial Symptom Scale (BCPT)38 with corresponding subscales (e.g., hot flashes) to measure symptoms distress, and the Functional Assessment of Cancer Therapy-Breast Cancer (FACT-B)39 to examine QOL, and the HADS29 to evaluate mood (i.e., anxiety and depressive symptoms). We assessed perceived ability to cope with stress via relaxation and cognitive skills using the Measure of Current Status (MOCS-A)40 and patients’ confidence in their ability to manage AET symptoms with the Self-Efficacy for Managing AET Symptoms Questionnaire (SESM-AET).41 See Supplemental Material for full measure descriptions.
Statistical Analysis
We performed statistical analyses using SAS version 9.4. We used an intention-to-treat approach for all randomized patients. Data were assessed for patterns of normality, statistical assumptions, and missingness.42 We defined feasibility based on rates of enrollment (>50%), retention (i.e., assessment completion >70%), and intervention attendance (≥70% of patients attending ≥4 of 6 sessions). Acceptability was defined as >75% of patients reporting satisfaction scores greater than the midpoint of the CSQ-3.35 With feasibility as the primary endpoint, power calculations were conducted based on a sample of 80 patients, with an anticipated enrollment rate of at least 60% and retention and attendance rates of 80%. With these estimates, if 134 patients were approached and 80 were enrolled, the lower limit for an exact, one-sided 95% confidence interval for the enrollment rate would be 53%, and 71% for retention and attendance rates. After 14 months of recruitment, we expanded the accrual goal to 100 patients to ensure that at least 40 patients per group completed the study.
For secondary outcomes, we first generated descriptive statistics for baseline characteristics and identified any group imbalances. We then conducted Analysis of Covariance (ANCOVA) to compare mean scores between groups on patient-reported outcomes at 12 weeks, controlling for baseline values of the outcome, distress level (given that the sample was stratified by distress43), and ovarian suppression (given group imbalance). We considered two-sided p-values <0.05 to be statistically significant and calculated effect sizes (Cohen’s d) for changes in outcomes. Next, we fit linear mixed effects models with random intercepts to examine differences between groups in average outcome trajectories across the baseline, 12-, and 24-week assessments, adjusting for the same covariates. Finally, we computed a weekly and monthly adherence score (% of days that AET was taken) for each patient using the MEMS Caps data of daily openings and fit linear mixed models to examine the between group differences in adherence trajectories across the 24 weeks.
Results
Baseline Characteristics
Between 10/2019 and 06/2021, we offered participation to 141 eligible patients with AET-related distress, and 70.9% (100/141) enrolled (see Figure 1). Most patients were White (91%) and partnered (73%). On average, they were 56 years old (SD=10.9, range=31–81) and had been taking AET for approximately 18 months (SD=8.64; see Table 1). More patients in the MedMon control were receiving ovarian suppression compared to those in STRIDE (Fisher’s Exact Test=0.998, p=.014). All enrolled patients had access to their own technology for the virtual sessions; therefore, no one required a study tablet. Enrolled patients did not differ from those who declined study participation with respect to age, cancer stage, or AET type.
Figure 1.
Study Flow Diagram
Notes:
Screened-in: Patient scored ≥4 on at least one of the adapted NCCN distress thermometer questions.
Ineligible post-consent: One patient did not complete the baseline assessment within window and became ineligible to reconsent due to her length of time on AET (>36 months). One patient became ineligible due to changes to restrictions regarding providing virtual care to out of state patients.
Declined post-consent: Two patients declined to enroll after consenting (one due to feeling too overwhelmed and one due to new health issues that prevented her from participating).
Withdrawn post-consent by study team: One patient signed consent after the accrual goal was reached due to staff error.
Table 1.
Sociodemographic, Clinical, and Treatment Characteristics at Baseline
| STRIDE Intervention N = 50 | Medication Monitoring N = 50 | Full Sample N = 100 | |
|---|---|---|---|
| Mean (Standard Deviation) | |||
| Age (years; range = 31–81) | 57.2 (10.6) | 54.9 (11.2) | 56.1 (10.9) |
| Months on AET (AET start to enrollment) | 17.70 (8.87) | 18.13 (8.49) | 17.91 (8.64) |
| N (%) | |||
| Gender | |||
| Women | 50 (100) | 50 (100) | 100 (100) |
| Race | |||
| White | 47 (94) | 44 (88) | 91 (91) |
| Asian | 0 (0) | 4 (8) | 4 (4) |
| Black or African American | 1 (0) | 0 (0) | 1 (1) |
| Other | 1 (2) | 2 (4) | 3 (3) |
| Not Reported | 1 (2) | 0 (0) | 1 (1) |
| Ethnicity | |||
| Hispanic or Latino/a | 1 (2) | 2 (4) | 3 (3) |
| Not Hispanic or Latino/a | 47 (94) | 47 (94) | 94 (94) |
| Not Reported | 2 (4) | 1 (2) | 3 (3) |
| Education | |||
| Advanced Professional Degree | 3 (6) | 6 (12) | 9 (9) |
| Master’s Degree | 16 (32) | 16 (32) | 32 (32) |
| College Graduate | 19 (38) | 15 (30) | 34 (34) |
| Some college/Technical School | 9 (18) | 7 (14) | 16 (16) |
| High school graduate/GED | 3 (6) | 5 (10) | 8 (8) |
| 11th grade or less | 0 (0) | 1 (2) | 1 (1) |
| Relationship Status | |||
| Married/Cohabitating | 38 (76) | 35 (70) | 73 (73) |
| Non-cohabitating relationship | 1 (2) | 2 (4) | 3 (3) |
| Single, never married | 5 (10) | 4 (8) | 9 (9) |
| Divorced/separated | 6 (12) | 6 (12) | 12 (12) |
| Loss of long-term partner/widowed | 6 (12) | 3 (6) | 9 (9) |
| Employment Status | |||
| Full-time/part-time work or student | 33 (66) | 29 (58) | 62 (62) |
| Caring for home or family | 4 (8) | 6 (12) | 10 (10) |
| Unemployed | 1 (2) | 3 (6) | 4 (4) |
| Not working due to illness/disability | 0 (0) | 2 (4) | 2 (2) |
| Retired | 9 (18) | 9 (18) | 18 (18) |
| Other or missing | 3 (6) | 2 (4) | 5 (5) |
| Income | |||
| $25,000-$49,999 | 2 (4) | 5 (10) | 7 (7) |
| $50,000-$99,999 | 11 (22) | 11 (22) | 22 (22) |
| $100,000-$149,999 | 9 (18) | 9 (18) | 18 (18) |
| > $150,000 | 27 (54) | 23 (46) | 50 (50) |
| Declined to respond | 1 (2) | 2 (4) | 3 (3) |
| Breast Cancer Stage | |||
| Stage 0 | 5 (10) | 3 (6) | 8 (8) |
| Stage I | 36 (72) | 41 (82) | 77 (77) |
| Stage II | 6 (12) | 10 (20) | 16 (16) |
| Stage III | 3 (6) | 2 (4) | 5 (5) |
| Type of AET | |||
| Aromatase Inhibitor | 28 (56) | 32 (64) | 60 (60) |
| Tamoxifen | 22 (44) | 18 (36) | 40 (40) |
| Primary Treatment Type | |||
| Surgery only | 10 (20) | 13 (26) | 23 (23) |
| Surgery & Radiation | 25 (50) | 23 (46) | 48 (48) |
| Surgery & Chemotherapy | 2 (4) | 6 (12) | 8 (8) |
| Surgery, Chemotherapy, & Radiation | -- | 8 (16) | 21 (21) |
| Node Status | |||
| Node Positive | 10 (20) | 12 (24) | 22 (22) |
| Node Negative | 36 (72) | 34 (68) | 70 (70) |
| Not Evaluated | 4 (8) | 4 (8) | 8 (8) |
| Menopausal Status | |||
| Pre- or Peri-menopausal | 18 (36) | 18 (36) | 36 (36) |
| Post-menopausal | 25 (50) | 23 (46) | 48 (48) |
| Not Reported | 7 (14) | 9 (18) | 16 (16) |
| HER2/neu Status | |||
| HER2/neu Positive | 5 (10) | 8 (16) | 13 (13) |
| HER2/neu Negative | 40 (80) | 40 (80) | 80 (80) |
| Not Reported | 5 (10) | 2 (4) | 7 (7) |
| Ovarian Suppression | |||
| Receiving Ovarian Suppression | 8 (16) | 20 (40) | 28 (28) |
| Not Receiving Ovarian Suppression | 42 (84) | 30 (60) | 72 (72) |
Note: AET = Adjuvant Endocrine Therapy
Feasibility and Acceptability
We enrolled 70.9% (100/141) of eligible patients in the study. Of these 100 patients, 92% completed the 12-week and 91% completed the 24-week assessment. Of the patients randomized to STRIDE (n=50), 86% (43/50) completed 6/6 sessions. A total of 78% (39/50) and 72% (36/50) completed the first and second follow-up calls, respectively. Eighty-three patients (83%) returned the MEMS bottle at study close (MedMon=41; STRIDE=42). Most patients in STRIDE were placed in groups of two due to availability, and five patients completed the sessions individually (n=3 due to scheduling conflicts; n=2 due to personal preference after sessions had begun).
On the CSQ-3, 41/43 (95%) patients reported an average satisfaction score ≥2 (the scale’s midpoint). Forty-two patients (98%) indicated that most or almost all their needs were met by the program. Forty patients (93%) were mostly or very satisfied with the program, and 40 (93%) would return to the program if needed. The weekly sessions were 58 minutes long, on average. Sixty-three percent of patients randomized to STRIDE received a score ≥5 (range=0–7) for homework completion. In terms of intervention fidelity, an average of 91% of topics were covered across sessions (range=83%−96%).
Patient-reported Outcomes
Compared to patients assigned to MedMon, those assigned to STRIDE reported less symptom distress related to hot flashes (BCPT-Hot Flashes; Adjusted Mdiff=−0.72, 95% CI[−1.43, −0.01], Cohen’s d=0.31, p=.048) and better ability to use stress coping skills (MOCS; Adjusted Mdiff =4.41, 95% CI[1.39, 7.43], Cohen’s d =0.48, p=.005) at the 12-week follow-up. Those assigned to STRIDE also reported marginally better QOL (FACT-B; 95% CI[−0.11, 8.67]) and ability to self-manage symptoms (SESM-AET; 95% CI[−0.05, 1.41]), compared to patients assigned to MedMon (see Table 3A for all 12-week results); however, these differences did not reach statistical significance. On the individual SESM-AET items, patients assigned to STRIDE did report significantly greater self-efficacy for managing specific symptoms at 12 weeks, such as hot flashes (p=.019), sleep difficulties (p=.016), and weight gain (p=.010). We did not observe 12-week group differences in self-reported adherence (MARS-5), satisfaction with AET (CTSQ), or mood (HADS).
Table 3A.
Effect of the STRIDE Intervention on Patient-Reported Outcomes at 12 Weeks: Results of Analysis of Covariance Models (n=92)
| Patient-Reported Outcome | Adjusted Mean at 12 weeks [95% CI] | ||||
|---|---|---|---|---|---|
| Medication Monitoring | STRIDE Intervention | Beta [95% CI] | Cohen’s d | p-value | |
| Self-Reported Adherence (MARS-5) | 23.86 [23.49, 24.23] | 23.99 [23.61, 24.36] | 0.13 [−0.40, 0.66] | 0.07 | .630 |
| Symptom Distress (BCPT) | 20.67 [18.82, 22.53] | 19.89 [17.98, 21.79] | −0.79 [−3.49, 1.91] | 0.08 | .562 |
| Hot Flashes Distress (BCPT) | 3.38 [2.89, 3.87] | 2.67 [2.17, 3.17] | −0.72 [−1.43, −0.01] | 0.31 | .048 * |
| Satisfaction with Therapy (CTSQ) | 63.94 [61.30, 66.58] | 66.53 [63.82, 69.23] | 2.58 [−1.27, 6.44] | 0.21 | .186 |
| Quality of Life (FACT-B) | 107.68 [104.66, 110.71] | 111.96 [108.88, 115.04] | 4.28 [−0.11, 8.67] | 0.23 | .056 + |
| Coping Skills (MOCS-A) | 28.49 [26.42, 30.57] | 32.90 [30.78, 35.02] | 4.41 [1.39, 7.43] | 0.48 | .005 ** |
| Symptom Self-Management (SESM-AET) | 5.34 [4.84, 5.85] | 6.03 [5.51, 6.54] | 0.68 [−0.05, 1.41] | 0.35 | .067 + |
| Depressive Symptoms (HADS-D) | 4.26 [3.56, 4.96] | 3.87 [3.17, 4.58] | −0.38 [−1.39, 0.63] | 0.12 | .451 |
| Anxiety Symptoms (HADS-A) | 6.59 [5.66, 7.51] | 6.54 [5.61, 7.47] | −0.05 [−1.38, 1.29] | 0.01 | .946 |
Note: CI = Confidence Interval; Beta = Difference in adjusted mean score (STRIDE minus Medication Monitoring); All analyses are adjusted for Ovarian Suppression Receipt (Yes vs. No), Baseline Distress Level (Elevated vs. Not Elevated [Elevated= HADS anxiety or depression subscale ≥ 8]), and Baseline Value of the Outcome of Interest.
p<.1,
p<.05,
p<.01,
p<.001
Abbreviations: MARS = Medication Adherence Rating Scale; BCPT = Breast Cancer Prevention Trial Checklist; CTSQ = Cancer Therapy Satisfaction Questionnaire; FACT = Functional Assessment of Cancer Therapy (Breast); MOCS-A = Measure of Current Status Part A; SESM-AET = Self-Efficacy for Managing Symptoms of Adjuvant Endocrine Therapy; HADS = Hospital Anxiety and Depression Scale [A = Anxiety; D = Depression).
Using linear mixed effects models to examine group differences across the entire 24-week study period (Table 3B), patients assigned to STRIDE reported lower AET symptom-related distress (difference in slope per 12 weeks=−1.91, 95% CI[−3.29, −0.52], p=.007), including distress related to hot flashes (slope difference=−0.47, 95% CI[−0.84, −0.10], p=.013), compared to those assigned to MedMon. Across the 24 weeks, patients assigned to STRIDE also reported significantly better QOL (slope difference=4.66, 95% CI[2.28, 7.05], p<.001), increased ability to use stress coping skills (slope difference=2.25, 95% CI[0.83, 3.67], p=.002), and reductions in anxiety symptoms (slope difference=−0.77, 95% CI[−1.44, −0.10], p=.024), compared to those assigned to MedMon (see Figures 2A–2D). Compared to patients assigned to MedMon, those in STRIDE reported increases in self-management of symptoms (95% CI[−0.02, 0.79]) and reductions in depressed mood (95% CI[−0.92, 0.04]) that did not reach statistical significance. We did not observe group differences in self-reported adherence or satisfaction with AET across the 24 weeks.
Table 3B.
Longitudinal Effects of the STRIDE Intervention on Patient-Reported Outcomes Over 24 Weeks: Results of Mixed Linear Effect Models
| Patient-Reported Outcome | Rate of Change per 12 weeks (Slope) [95% CI] |
Difference in Slope (Beta) | 95% CI | p-value | |
|---|---|---|---|---|---|
| Medication Monitoring | STRIDE Intervention | ||||
| Self-Reported Adherence (MARS-5) | −0.01 [−0.25, 0.24] | 0.03 [−0.21, 0.28] | 0.04 | [−0.31, 0.39] | .833 |
| Symptom Distress (BCPT) | 0.40 [−0.58, 1.38] | −1.50 [−2.48, −0.53] | −1.91 | [−3.29, −0.52] | .007 * |
| Hot Flashes Distress (BCPT) | 0.05 [−0.22, 0.31] | −0.43 [−0.69, −0.16] | −0.47 | [−0.84, −0.10] | .013 * |
| Satisfaction with Therapy (CTSQ) | 0.19 [−1.39, 1.78] | 1.88 [0.30, 3.46] | 1.68 | [−0.55, 3.92] | .139 |
| Quality of Life (FACT-B) | −0.78 [−2.47, 0.91] | 3.89 [2.21, 5.57] | 4.66 | [2.28, 7.05] | <.001 *** |
| Coping Skills (MOCS-A) | 0.35 [−0.66, 1.35] | 2.59 [1.59, 3.60] | 2.25 | [0.83, 3.67] | .002 ** |
| Symptom Self-Management (SESM-AET) | 0.27 [−0.02, 0.56] | 0.66 [0.37, 0.94] | 0.39 | [−0.02, 0.79] | .060 + |
| Depressive Symptoms (HADS-D) | −0.01 [−0.35, 0.33] | −0.45 [−0.79, −0.11] | −0.44 | [−0.92, 0.04] | .071 + |
| Anxiety Symptoms (HADS-A) | −0.22 [−0.69, 0.25] | −0.99 [−1.46, −0.52] | −0.77 | [−1.44, −0.10] | .024 * |
Note: CI = Confidence Interval; All analyses use maximum likelihood estimation to account for missing data. Analyses are adjusted for Ovarian Suppression Receipt (Yes vs. No), Baseline Distress Level (Elevated vs. Not Elevated [Elevated= HADS anxiety or depression subscale ≥ 8]), and Baseline Value of the Outcome of Interest.
p<.1,
p<.05,
p<.01,
p<.001
Abbreviations: MARS = Medication Adherence Rating Scale; BCPT = Breast Cancer Prevention Trial Checklist; CTSQ = Cancer Therapy Satisfaction Questionnaire; FACT = Functional Assessment of Cancer Therapy (Breast); MOCS-A = Measure of Current Status Part A; SESM-AET = Self-Efficacy for Managing Symptoms of Adjuvant Endocrine Therapy; HADS = Hospital Anxiety and Depression Scale [A = Anxiety; D = Depression).
Figure 2.
Study group differences in select patient-reported outcomes across 24 weeks
2A. Symptom Distress (BCPT)
2B. Quality of Life (FACT-B)
2C. Coping skills (MOCS-A)
2D. Anxiety symptoms (HADS-A)
Objective Adherence Outcome
As measured by MEMS caps, we observed significant decreases in monthly adherence scores in patients in both the STRIDE intervention (slope=−4.44%, 95% CI [−5.79%, −3.08%] p<.0001) and the MedMon control (slope=−3.78%, 95% CI [−5.15%, −2.41%, p<.0001). However, there was no difference in the rate of change between the study groups (slope difference=−.066%, 95% CI [−2.59%, 1.27%], p=.504); see Figure 3. The weekly adherence scores followed a similar pattern.
Figure 3.
Study group differences in MEMS Caps monthly adherence scores
Discussion
This trial demonstrates that a brief, small-group telehealth intervention focused on symptom management, adherence, and distress is feasible and acceptable with promising efficacy for patients taking AET after breast cancer. More than two thirds of eligible patients enrolled in the study, with more than 90% completing the follow-up assessments and 86% completing all intervention sessions. Furthermore, STRIDE led to improvements in symptom distress, QOL, coping skills, anxiety symptoms, and self-efficacy for symptom management. However, we observed no differences in adherence or satisfaction with AET. These promising findings substantiate further investigation in a large-scale, fully powered efficacy trial.
We demonstrated strong feasibility of the study design and intervention, with high rates of enrollment, retention, and session completion. Remarkably, we continued to accrue rapidly during the height of the COVID-19 pandemic, with only a short pause. Patients’ high satisfaction and enthusiasm for the intervention material and support is notable. The high acceptability and homework completion scores indicate patients’ willingness and desire to receive more formal support while on AET regimens that are disruptive to QOL, yet necessary for survival. No in-person study visits were required, which likely optimized attendance, engagement, and retention, especially for this population of patients adapting to life after breast cancer. The entirely virtual nature of the STRIDE intervention enhances the scalability and potential for dissemination across clinical care settings.
Similar to previous intervention studies,44 we did not observe group differences in self-reported adherence or objective adherence scores on the MEMS Caps. Self-reported adherence on the MARS-5 was high in both groups, which may indicate a ceiling effect as well as the tendency for self-report methods to overestimate adherence.21 While there were differences in MEMS Caps adherence rates in the STRIDE vs. MedMon groups that may be clinically meaningful (e.g., 92.5% vs. 87.3% at Month 2; 90.3% vs. 85.8% at Month 3), the lack of statistical significance in these differences may be a result of low power as well as high variability in these scores. The absence of a gold standard and the inherent flaws in current adherence measurement continues to complicate our assessment of adherence optimizing interventions.45 Our future work will entail tests of moderation to investigate whether certain subgroups of patients benefited from the intervention based on sociodemographic and/or clinical characteristics. For example, based on prior reviews, certain demographic or clinical characteristics, such as age, cancer stage, and number of concomitant medications, may be associated with adherence to oral anti-cancer therapies.30 In addition, adherence may be different for patients taking tamoxifen vs. aromataste inhibitors given that these medications have slightly different side effect profiles.
In this pilot trial, we demonstrated preliminary efficacy of STRIDE for improving AET-related symptom distress, QOL, coping skills, and anxiety symptoms, with small to medium effect sizes. STRIDE led to more modest improvements in self-efficacy for symptom management and depressive symptoms that approached significance. These findings are notable given the length of time that patients take these medications, struggle with side effects, and experience deteriorations in QOL. These findings are also critical given that symptom distress, mood, and QOL are associated with adherence to oral anticancer treatment.46 Among those with breast cancer, symptoms are the primary factor contributing to suboptimal adherence to AET.5,13 While evidence-based approaches for symptom management exist,47 patients lack self-efficacy and skills to manage AET symptoms on their own48 and receive no formal support to do so throughout the 5–10-year regimen.49 Relatedly, a recent systematic review concluded that self-efficacy, a modifiable factor most consistently associated with adherence, should be a target for interventions to improve AET adherence.50 Although this study was not powered to detect differences in adherence, future fully-powered work should investigate patients’ self-efficacy for managing and coping with AET symptoms as a path to reducing symptom distress, improving QOL and mood, and ultimately enhancing adherence.
Some limitations are worth noting, including the minimal socioeconomic and racial-ethnic diversity of the sample, as well as the large proportion of patients with stage I disease, which restricts the generalizability of these findings. Furthermore, all enrolled patients owned their own devices to access the virtual sessions, further illustrating the limited representation of our sample compared to the larger breast cancer population. In addition, study staff and participants were not blinded to randomization, potentially introducing bias. While most patients participated in pairs and reported benefitting from the group setting, some preferred individual sessions or were unable to be in a group due to scheduling conflicts. Flexibility in individual or group-based participation should be considered as a factor affecting implementation in a clinical setting. All therapists were clinical psychologists or psychology fellows; however, future work could examine the feasibility of training mental health clinicians from diverse disciplines.
In conclusion, a brief, small-group telehealth intervention for patients taking AET after breast cancer is highly feasible and acceptable, with promising benefits for improving symptom distress, QOL, coping skills, mood, and self-efficacy for symptom management. These findings warrant the efficacy testing of this intervention in a multi-site trial while exploring potential mediators and moderators of intervention effects. Future trials will enroll patients from different geographic regions with greater racial, ethnic, and socioeconomic diversity that represents the socioeconomic and demographic make-up of the true breast cancer population. These trials will also employ specific recruitment strategies (e.g., partnerships with community organizations, purposeful recruitment and enrollment monitoring, diverse representation in recruitment materials) to ensure enrollment of a diverse sample. Finally, using data from semi-structured interviews with patients from a racial or ethnic minority background that completed the study, the intervention and telehealth approach will be culturally adapted to ensure cultural humility and relevance for patients from various sociodemographic backgrounds.
Supplementary Material
Acknowledgments:
We thank all study participants and study therapists.
Funding:
This work was supported by the National Cancer Institute: K07CA211107 (Jacobs)
Footnotes
Conflict of Interest: JJ and JG are consultants for Blue Note Therapeutics™.
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