Study design
This is a clinical trial involving a behavioral intervention focused on patients (with and without an intervention booster), which will be evaluated with a longitudinal between-subjects randomized controlled trial in which patients will be randomized to intervention or usual care groups, and outcomes are compared between groups. All study procedures have been approved by Wayne State University’s (WSU) IRB (IRB-20-2836). SPIRIT guidelines were used to report this protocol.84
Participants and setting
This trial will be conducted at WSU/Karmanos Cancer Institute (KCI), a NCI-designated comprehensive cancer center located in Detroit, Michigan, USA, which serves a highly diverse population. We will recruit up to 15 medical oncologists and medical oncology fellows at the beginning of data collection, prior to patient recruitment. Medical oncologists are eligible to participate if they treat patients with breast, prostate, lung, or colorectal cancers at KCI. To recruit oncologists, research staff will explain the study at clinic program meetings and meet with interested oncologists individually to answer questions and obtain consent. Oncologists who consent will agree to 1) complete a baseline survey, 2) inform (or designate a clinical member of the study team to inform) their eligible new patients (via a phone call, e-mail, or face-to-face conversation) about the study prior to their initial appointment to discuss treatment, 3) have interactions with participating patients video recorded, and 4) complete a brief survey following interactions with participating patients. Upon recruitment, oncologists will receive a “tip sheet” to help prepare them for treatment cost discussions with patients (Figure 4). Oncologists will continue their participation throughout the study period (approximately 4 years), and they will receive a $30 gift card upon consent for their participation in the study.
We will recruit up to 240 (120 men, 120 women) White and Black patients from various socioeconomic statuses, and ages. Patients are eligible if they are > 18 years of age, identify as either Black or White, are able to read and write in English, have an email account, and are newly diagnosed with breast, prostate, lung or colorectal cancer (stage I-IV) for which systemic therapy is a likely recommended treatment. Strata will be created to ensure recruited patients vary by race, income, age, and sex. Eligible patients will be identified by research staff who will review participating oncologists’ schedules weekly. Patients will be contacted via phone call, face-to-face, or email from the participating oncologist’s clinical staff to inform them of the study and assess interest. If interested, patients will be contacted by research staff via a phone call or in person in the clinic prior to a scheduled appointment. The research staff member will explain the study and obtain consent and collect baseline data. Patient participants will be 1) asked to arrive 30 minutes early to their next scheduled appointment with their oncologist, 2) randomized to one of the study arms, 3) asked to complete a brief survey following the video-recorded interactions with a participating oncologist, 4) asked to have up to two of their clinical interactions video recorded, and 5) asked to complete up to four follow-up surveys at 1, 3, 6, and 12 months after their last video-recorded interaction. All patients will provide baseline socio-demographic information at the time of consent. We will ask patients for their preferred method of contact for follow-up surveys.
Procedures
Just prior to the second patient-oncologist visit to finalize treatment plans, but before treatment begins, using data collection software (Qualtrics), a research assistant will randomize patients into one of three study arms. Patients in Arm 1 will receive usual care, patients in Arm 2 will receive the intervention, and patients in Arm 3 will receive the intervention and an intervention booster. Patients in Arms 2 and 3 will receive the DISCO App. Patients in Arm 3 will receive an intervention booster provided two months after receiving the DISCO App. For all patients, we will video record the second patient-oncologist interactions using our established, unobtrusive video recording system.48,53,85,86
Just before the second patient-oncologist interaction, patients in Arms 2 and 3 will access the DISCO App73 on an iPad. Our research demonstrates that patients are comfortable with iPads, especially if they are assisted.53,87 Research assistants will show patients the DISCO App with an explanation, instructions, and demonstration. Staff will be trained NOT to answer questions nor discuss cost, but to encourage patients to ask questions during their clinical interaction. These meetings will be audio-recorded to assess fidelity to the protocol. Based on feasibility data from our pilot study, we anticipate that using the DISCO App will take <20 minutes. Since patients in Arms 2 and 3 may bring the print out and/or iPad into the interaction, oncologists will not be blind to study arm. Thus, we will give patients in Arm 1 treatment information on a printout for their meeting with their oncologist. Immediately after the recorded interactions, patients and oncologists will complete brief surveys assessing any cost discussions that occurred. Patients in Arms 2 and 3 will also complete assessments of the DISCO App (e.g. “The app helped me ask my treatment cost questions”) after the second interaction.
All patients will be contacted via their preferred method of contact to complete follow-up measures including questions about their disease and treatment status, whether they received a referral for SW/FN, if they followed up on that referral, self-efficacy managing treatment cost, perceived short-term financial toxicity (perceived material hardship and cost distress) in the first follow-up, actual financial toxicity in the remaining follow-ups, and treatment adherence. Follow-up will occur at 1, 3, 6, and 12 months after the second recorded interaction. Patients who receive the intervention booster will also complete booster assessments (e.g. “The email reminded me of helpful information”).
Intervention
The DISCO App
The DISCO App (Figure 3) is displayed on an iPad provided to intervention patients in a private room just prior to their second interaction with their oncologist to discuss and finalize treatment plans. The DISCO App opens with an introduction screen. First, patients watch a 3-minute educational video featuring a communication scientist, medical oncologist and a patient using the DISCO App. The video summarizes the types of treatment costs patients may incur (e.g., copayments, transportation/parking costs, time away from work) and ways to manage those costs (e.g., talk with an oncologist or social worker, contact pharmaceutical companies, seek clarification from insurance provider). The video ends by emphasizing to patients that the best way to start managing treatment costs is to discuss them with their oncologist who can answer their questions or refer them to someone who can assist. Second, after the video, the QPL is introduced with the following text: “There is a lot to consider when it comes to treating cancer. One thing many patients don’t think about is the cost of treatment and other expenses.” The text continues to explain that the DISCO App includes a short survey, which will lead to some cost-related questions the patient can consider asking the oncologist. This section asks patients to enter their demographic information and their financial characteristics. Specifically, patients respond to 17 questions (e.g., “How much do you know about your insurance coverage?”, “Are you currently employed?”, “Is there anyone who helps you when you’re sick or need help of any kind?”). Based on patient responses, an individually-tailored QPL with up to 18 cost-related questions in 7 categories is generated (Table 1). For example, patients who indicate they are employed will be prompted to ask: “Can I schedule my treatment around my job?”, patients who indicate transportation concerns will be prompted to ask: “are services available if I can’t find someone to drive me?”, Patients who indicate they are unfamiliar with their insurance coverage will be prompted to ask: “Is there someone I can talk to about my insurance and treatment cost questions?” All patients will be provided with four diagnosis questions (e.g., “What is my diagnosis?”), have the option of adding in any of their own questions, and then either take the iPad or a printed question list into the meeting with the oncologist. Thus, the DISCO App arms patients with concrete information about the types of out-of-pocket and indirect costs they may incur while undergoing treatment, specific actions they can take to begin to address those costs, and a list of individually tailored cost-focused questions they can take with them to the clinic visit to ask their oncologist. This information and individualized prompting is something few patients with cancer currently receive, on any topic.
Financial toxicity is multifaceted and long-term. We expect the DISCO App to influence short-term outcomes, but we expect it may need reinforcement to influence longer-term outcomes (e.g., financial toxicity, treatment adherence). Thus, we will explore the effects of a booster to reinforce the effects of the DISCO App. Patients in Arm three will receive the booster two months after receiving the DISCO App. The booster will be a tailored email or text message reminding patients of 1) the content in the educational video, 2) the questions they selected, and 3) that treatment costs are something they can discuss with their oncologist.
Table 1. The DISCO App’s Prompted Questions by Question Type
Cost of appointments and treatments
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1. How much will I have to pay for my treatment?
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2. Is there a less expensive drug, like a generic, that will be equally effective?
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3. How many visits will I have? I may have to pay each time I come to the cancer center (co-pay, parking, etc.).
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4. What happens if I can’t pay for some of my treatment costs?
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Help with understanding my treatment costs and what my insurance covers
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5. Do I need additional or supplemental insurance coverage?
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6. Do I have a co-pay every time I come to the cancer center?
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7. Is there someone I can talk to about my questions about my insurance and treatment costs?
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Transportation to and parking at the cancer center
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8. Does someone need to drive me to treatment appointments?
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9. Are services available if I can’t find someone to drive me?
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10. How much does parking cost?
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Living far from the cancer center
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11. Is it possible for me to receive my treatment closer to where I live?
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12. Are there free or reduced-cost hotels nearby for me and my family?
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Working during treatment
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13. Can I keep working during treatment? If not, when can I go back to work?
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14. Can I schedule my treatment around my job?
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15. Do I need to file Family and Medical Leave Act (FMLA) paperwork? If so, how?
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Assistance programs
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16. Are assistance programs available to help me with treatment costs or other expenses or needs?
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17. If I need a wig or other supplies, is there somewhere I can get them free or at a reduced cost?
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Family and living responsibilities
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18. Can I schedule my treatment around my family’s schedule?
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General questions about cancer and treatment (all patients will get these)
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19. What is my diagnosis and stage?
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20. Is it possible to cure my cancer?
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21. What is my treatment plan?
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22. Are there clinical trials I can participate in? I fso, will this cost more or less than standard treatment?
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Oncologist Tip Sheet
During DISCO App73 acceptability testing, some participants thought the DISCO App would be useful for patients to prompt treatment cost discussions with their oncologist and gain important information for their treatment. However, they expressed the concern that oncologists may be unprepared to answer cost questions. In response, we designed an oncologist “tip sheet,” which emphasizes oncologists’ role in cost discussions (as recommended by ASCO) and provides ways to overcome identified barriers to cost discussions (Figure 4).88,89 For example, oncologists report concern that they will be unable to answer questions about treatment costs. It is impractical to expect oncologists to know the complexities of treatment cost so the tip sheet provides language, including “if a patient asks about cost and you do not know the answer, you can simply say: “I’m glad you brought this up, because it’s important for me to know what concerns you have about your treatment. I’m not an expert in this area, but if you have questions about costs, I can arrange for you to meet with a social worker who can help after we’re done here.’”104
We designed the tip sheet to be a two-sided, tri-fold document that fits in physicians’ white lab coats.
Intervention Booster
Two months after receiving the DISCO App, patients in Arm 3 will receive an intervention booster. The booster will be an email or text message (depending on patient preference) to remind patients 1) of the content in the education video, 2) the questions they selected from the DISCO App, and 3) that treatment costs are something they can discuss with their oncologist or other providers. The email or text message will include a “Read Receipt” so we can track whether patients view the email or text message.
Measures
Data include patient and oncologist self-report, video-recorded patient-oncologist treatment discussions, and medical chart data. Video recording allows us to use our validated coding systems48,53,90 to assess outcomes that occur during the interaction.
Most of the measures in this study have been used with cancer patients, including in the DISCO App’s feasibility pilot, with high completion rates and few complaints about burden. However, the first ten patients who complete all measures will be specifically queried about burden. Measures will be adjusted if necessary.
Baseline measures.Baseline measures from patients and oncologists will be used as moderators and covariates in analyses of the intervention’s effects. Patients: After providing consent, patients will provide socio-demographics including age, race/ethnicity, gender, education, marital/personal status, income, employment, and financial situation (e.g., It is difficult for me to live on my total household income right now).15 They will also complete measures eliciting their diagnosis, their recommended treatment (if known), insurance type, their self-efficacy in patient-physician interactions (PEPPI a=.91, e.g., How confident are you in your ability to know what questions to ask your doctor?), patient-practitioner orientation (e.g., The doctor is the one who should decide what gets talked about during a visit), their self-efficacy in managing cost of treatment (adapted from a validated scale, e.g., I am confident I can pay for the direct costs of my treatment),126 their level of treatment cost distress (e.g., I am concerned about how much my cancer treatment will cost me), and their anticipated material hardship due to their cancer treatment (e.g., I know that I have enough money in savings, retirement, or assets to cover the costs of my treatment).91Oncologists: After providing consent, oncologists will complete a one-time assessment of their socio-demographic and professional information, including race/ethnicity, gender, age and years in practice. Oncologists will also complete measures of patient-practitioner orientation (e.g., The doctor is the one who should decide what gets talked about during a visit), their perceptions of the oncologists’ role in treatment cost discussions (e.g., Oncologists should be discussing treatment cost with their patients), and their self-efficacy with discussing treatment cost.
Medical records: We will use patients’ medical records to abstract information on cancer diagnosis, co-morbidities, and their zip code.
Level 1: Patient Outcome Measures:Immediately after the video-recorded interactions, patients will complete the following measures: self-efficacy in patient-physician interactions,127 self-efficacy in managing cost of treatment,126 knowledge of types of treatment cost (e.g., Cancer treatment may cost me in the following ways), and ways to manage those costs (e.g., The following are ways I can manage treatment cost), perceived financial toxicity, comprised of treatment cost distress (5-items, e.g., I am worried about how much my cancer treatment will cost) and perceived material hardship (7-items, e.g., Do you anticipate having to borrow money to pay for cancer treatment? Do you anticipate having to take unpaid time off from work for treatment?).15 Intervention patients will also provide perceptions of the DISCO App after the interaction (5 items, e.g., The DISCO App helped me ask my doctor my cost questions).92
At the 1, 3, 6, and 12 month follow-ups, patients will be contacted via their preferred method by research staff to complete measures on their disease and treatment status (e.g., disease status, type of treatment) to help account for any differences observed in the outcome measures. Patients will also complete measures assessing self-efficacy in patient-physician interactions,127 self-efficacy in managing cost of treatment,126 their employment status, and actual financial toxicity using the 11-item COST scale (a=.90, e.g., My out-of-pocket medical expenses are more than I thought they would be).128 At the three month follow-up, patients who received the booster will be asked if they received the booster and their perceptions (e.g., The reminder email or text message was helpful with my cost questions and concerns).
Level 2: Patient-Oncologist Interaction Outcome Measures:Immediately after the video-recorded interactions, patients and oncologists will complete measures of perceived presence of treatment cost discussion(s) (3 items, e.g., Did you and your oncologist (patient) discuss the cost of your (his/her) cancer treatment today?) and satisfaction with treatment cost discussion(s) (3 items, e.g., I am satisfied with how my oncologist (patient) and I discussed treatment cost today).
Observational measures: Trained research assistants (RAs), blind to research questions, will observe and rate video-recorded interactions using our established procedures to ensure acceptable inter-rater reliability.48,53,93-95 To assess the frequency and quality of a cost discussion, RAs will determine if a treatment cost discussion occurred (e.g., any verbal expression of perceived direct or indirect costs for the patient for cancer treatment), who initiated the cost discussion (e.g., patient, oncologist), and what topics were discussed (e.g., insurance, transportation, etc.).48 RAs will also rate the quality of the interaction through assessing patient active participation (e.g., the patient asked a lot of questions)90 and oncologists’ patient-centered communication (12 items, a=.75, e.g., the doctor encouraged the patient to express concerns and worries).90 Another team of trained RAs will assess if the DISCO App or printout is present and/or used53 and interaction length.53
Level 3: Health Utilization Outcomes:Immediately after the video-recorded interactions, patients will complete measures of: whether they wanted and/or received a SW/FN referral, and, if so, if they followed up on the referral.
Oncologists will complete measures on whether they made a SW/FN referral for the patient.
At the 1, 3, 6, and 12 month follow-ups, patients will be contacted by their preferred method of contact by research staff to complete measures, including whether they wanted a SW/FN referral, and if so, whether they followed up on that referral, treatment adherence (Medical Outcomes Study General Adherence, e.g., I had a hard time doing what the doctor suggested I do for treating my cancer) and treatment cost-related adherence (e.g., Was there a time in the past 12 months when you needed to see a doctor for your cancer but could not because of cost?),131 and clinical appointment adherence.
Using medical records, we will assess whether the oncologist made a SW/FN referral, and, if so, if the patient followed up on the referral, treatment adherence, and clinic appointment adherence.
Sample size calculation/analyses
For the first primary objective (A, B, C in Figure 5), we expect that the presence of a cost discussion will influence the other outcomes. Thus, the presence of cost discussions was used to estimate the sample size and power justification for other outcomes. The rates of occurrence for cost discussions and SW/FN referrals will be calculated and the outcomes will be compared between usual care (Arm 1) vs. both DISCO App and DISCO App + booster (Arms 2+3). The sample size ratio was assumed to 1:2 since Arms 2 and 3 will be the same in the intervention evaluation. We are employing a between-subjects design with patients nested within oncologists (e.g., accounting for oncologists seeing multiple patients). The unit of analysis is the patient-oncologist interaction and data from these interactions will likely be more similar within oncologists than between oncologists. Thus, we used multi-linear models (MLM) with a binary outcome (i.e., discussed cost or did not discuss cost) to determine the sample size justification and power analyses using an MLM cluster-randomized design for two proportions.96,97 The effect of intra-cluster correlation (ICC) was further examined using ICC estimation from the random intercept logistic model.139 Based on our previous observational study,48 we assume that the ICC will be ≤0.04 (hereafter, for the sake of the worst scenario and the sample size estimation, we assumed that ICC is zero, which produces the largest sample size) and the rate of cost discussions without the DISCO App will be 45%. Our pilot study found that the cost discussion rate with the DISCO App is 100% (95% CI, 0.86 to 1). Based on findings from our observational and pilot studies, in this study, we expect that the rate of cost discussions will be at least 75% with the DISCO App, and the minimally meaningful difference between two groups will be 30%.48,98 We consider each oncologist a “block” and assume a Bonferroni-corrected 2-sided 1.7% level (= 5%/3 primary endpoints). Thus, 180 patients (10 oncologists X 3 arms × 6 patients) will achieve at least 90% power to detect 30% difference in the rate between two arms. This is also what we will need to detect a difference in the primary outcome at the healthcare utilization level (SW/FN referral). A total of 180 patients will allow us to detect an effect size of ≥0.58 for the patient-level outcome (self-efficacy for managing treatment cost) with 90% power at a 2-sided 1.7% level. With 20% attrition, we will need 240 (10 oncologists x 3 arms x 8 patients) patients to maintain a balanced design.
For first, second, and third secondary objectives (i.e., interactions by each of race (Black [B] vs. White[W]), income (high vs. low), and age (<65 vs. ≥65)) (D, E, F in Fig. 4), 180 patients will produce more than 89% power to detect any of three interactions for binary outcomes when the group proportions under the alternative hypothesis are 0.45, 0.45, 0.45, and 0.75 (e.g., for Arm1-W, Arm 1-B, Arms 2-3-W, Arms 2-3-B, respectively) using a z-test from a GEE analysis of a logistic model at a 2-sided 1.7% level. This will allow us to detect an interaction difference of at least 1.64 for continuous outcomes with 90% power at a 2-sided 1.7% level when an estimated SD of subjects is one.
For the fourth secondary objective (G, H, I, J, K in Fig. 4), 180 patients will allow us to detect a difference of at least 0.23 between two proportions for binary outcomes as well as to detect an effect size of at least 0.72 for continuous outcomes with 90% power at a 2-sided 0.1% level.
For the second primary objective (L, M, N in Fig. 4), outcomes will be measured at 5 time points (baseline, 1, 3, 6, 12 months post intervention) and the power was justified using longitudinal logistic and continuous MLM. 180 patients will have 90% power to detect a difference of 0.18 in slopes for continuous outcomes as well as to detect a difference of at least 0.13 for binary outcomes between Arms 2+3 vs. Arm 1 at a 2-sided 1.7% level when the autocorrelation is assumed to be zero.
For the fifth secondary objective (O in Fig. 4), 180 patients will allow us to detect an interaction between race and slope of at least 0.52 for continuous outcomes with 90% power at a 2-sided 1.7% level. A total of 180 patients will produce more than 90% power to detect any interactions with race for binary outcomes when the group proportions under the alternative hypothesis are 0.45, 0.45, 0.45, and 0.75 (e.g., for Arm1-W, Arm 1-B, Arms 2-3-W, Arms 2-3-B, respectively) using a normal test from a generalized estimating equations (GEE) analysis at a 2-sided 1.7% level when the autocorrelation is assumed to be zero.
For the sixth secondary objective (P, Q, R in Fig. 4), 180 patients will give us 90% power to detect a difference in slopes for continuous outcomes between Arm 3 vs. Arm 2 of 0.21 at a 2-sided 1.7% level. These patients will allow us to detect a difference of at least 0.16 for binary outcomes between Arms 3 vs. Arm 2 at a 2-sided 0.9% level when the autocorrelation is assumed to be zero.
All sample size and power justifications were performed by PASS 2020 (NCSS LLC, Kaysville, UT, USA). The primary analyses will be based on complete data without missing values. As a sensitivity analysis, we will also perform the hypothesis testing after multiple imputation. For time-independent variables (e.g., baseline attributes), multiple imputation will be performed using chained equations (MICE)99 and for the time-dependent variables, Amelia II will be used to consider time trends of a variable.100,101