Value of transfusion independence in severe aplastic anemia from patients’ perspectives – a discrete choice experiment

Study design

This study was designed in two phases: Phase I was a qualitative study to identify important aspects of SAA treatment and to develop the survey questionnaire and Phase II involved the conduct of a one-time, non-interventional anonymous online survey study among adult patients with SAA to elicit patient preferences for attributes associated with treatment of SAA, including transfusion independence. All study materials were approved by the Ethical and Independent Review Services (E&I) Institutional Review Board (E&I study number 15128–01). No compensation was offered and informed consent was obtained from all patients who participated in the survey study.

Phase II included an interactive discrete choice experiment (DCE). The DCE was selected because it is a choice-based survey research methodology that captures patient’s value for specific characteristics of treatment and patient’s willingness to accept tradeoffs between characteristics [12, 23]. It is an established methodology for eliciting patient preferences in regards to treatment characteristics [17, 25, 34]. A patient survey using discrete choice experiment design presents patients with a series of hypothetical choice scenarios between two treatments, characterized by the same set of attributes but where one or more of the attributes have different levels, and requests patients to make a choice between the two options. By presenting patients with a DCE, the study is able to elicit patient preferences without directly asking the patient about their preference, which is indicative of patients’ actual choice regarding potential treatment [9, 23].

The survey questionnaire was developed based on findings from Phase I of this study, which included seven one-time, one-hour long, phone-based focus group discussions (Phase I focus groups). A literature review was performed to assist with the development of the moderator’s guide for the Phase I focus group discussions. Two separate moderator’s guides were developed – one for the clinicians and one for the patients. A list of potential factors that may influence a patient’s value of transfusion independence was summarized from the literature review. Participants were recruited through the physician referrals in the United States and France. The Phase I focus groups aimed to identify and refine a list of attributes that were important to the management and treatment of SAA. Focus groups in the United States and France were conducted separately with physicians (N = 3), a nurse (N = 1), and patients (N = 9) to discuss the illness experience and the treatment and management of SAA, followed by discussion of the value of being transfusion-independent from the patient perspective. Providers and patients gave feedback on the comprehensiveness of the attributes. The most meaningful treatment characteristics to patients were discussed, including frequency of transfusions, symptoms, risks, convenience, and costs. The attributes were rated in terms of importance on a scale from 1 (least important) to 10 (most important) from the perspective of a patient with severe aplastic anemia who is considering treatment/management options. They were asked to focus on the importance of each attribute prior to transfusion independence. The self-rating of each attribute was transformed into a rank based on relative importance and the ratings were reviewed with each respondent. Respondents were given an opportunity to reconsider their ranking and then confirm the ranking of each attribute. Providers were asked to rank and then rate the importance of each attribute from a patient perspective, and provided input on the appropriate wording for the levels for each attribute that would constitute meaningful categories.

In Phase II, the online survey consisted of three parts: 1) study qualification questions and questions collecting general patient characteristics and medical condition, 2) questions aiming to assess potential impacts of achieving transfusion independence on different aspects of patients’ well-being relative to being transfusion dependent, and improvement in quality of life with a new therapy using 5-point Likert-scale rating questions, adapted from the “MDS Patient Quality of Life Survey” that was available online and has been published [29], and 3) an interactive discrete choice experiment (DCE) designed to capture patients’ willingness to accept tradeoffs between hypothetical treatment characteristics. The online survey was designed to be completed in English or French. The survey was designed in English and translated into French based on the efforts of three professional linguists, each chosen based on their knowledge of the language, the subject area, and the target audience. Once the translation was completed, an editor carefully reviewed and refined the document to ensure that it read as if it were originally written in French. A proofreader then provided quality control, checking the translation against the original to verify that it appropriately represented the source.

The key attributes and levels for the DCE experiment, selected based on the findings from the Phase I focus groups, included the following: risk of serious bleeding (low: platelet count > 50,000, moderate: platelet count 10,000–50,000, high: platelet count < 10,000), risk of infection (low: ANC > 1000 cells/mm³, moderate: ANC 500–1000 cells/mm³, high: ANC < 500 cells/mm³), fatigue (none, moderate, severe), and frequency of transfusion (none, 4 per month, 8 per month). These attributes were recommended based on the independence of the attributes relevant to the management of SAA (relative to other attributes initially considered such as convenience, which converged as a concept with frequency of transfusion), importance as rated by clinicians and patients and for their consistent relevance in focus groups with clinicians and patients from the US and France.

In the questionnaire, patients were asked to choose between pairs of hypothetical treatments characterized by a common set of attributes in order to estimate values for the attributes. To reduce the burden on the patient in responding to multiple hypothetical treatment comparisons, each patient reviewed 12 comparison cards. An opt-out option was not included, as receiving no treatment does not mirror the real-life experience of patients with SAA. The DCE design was generated using Sawtooth Software’s Balanced Overlap method [26]. This method minimizes the frequency respondents will have to compare the same levels throughout the tasks, but allows that in a given task both treatment options can compare the same level for an attribute, which results in more plausible choice options. All presented treatment profiles with different levels of attributes are plausible (e.g., low level of transfusions and low levels of symptoms/risks, high levels of transfusions and low levels of symptoms/risks, etc.). Versions of the design that included a dominant comparison, where one treatment was better in all attributes than the alternative, were removed. The final DCE design consisted of 20 versions, each with 12 comparison cards that compared two treatments. An example of the comparison card is shown in Fig. 1.

Data source

Patients who participated in this study were recruited through announcements in the newsletter of the Aplastic Anemia and Myelodysplastic Syndromes International Foundation and referrals from clinical sites in the US and France. Thirty patients qualified for the study and completed the online survey anonymously between February 2, 2016 and April 15, 2016. Patients did not receive a monetary incentive for completion of the survey.

Study population

Patients who completed the survey were screened to meet the following criteria to qualify for this study: age 18 years or older, diagnosed with SAA by a doctor or healthcare provider, prescribed IST with antithymocyte globulin but had an insufficient response, required blood transfusions at least monthly for a period of at least three months over the previous two years, and not currently pregnant.

Outcomes and statistical analysis

Demographic and SAA-related characteristics questions (country, age, gender, race [asked in the USA only], education level, employment status, health insurance coverage, history of treating SAA with drugs, transfusions, and iron chelation therapy) consisting of categorical variables were analyzed using descriptive statistics, and the number and proportion of patients were reported. Questions in which the patient rated their current condition and characteristics related to being transfusion independent were also analyzed using descriptive statistics, and the number and proportion of patients with top-two box (most favorable) Likert-scale ratings were reported.

Predicted utility scores associated with different levels of transfusion frequency were also estimated to understand the effect of transfusion frequency on choice. The predicted utility scores with different levels of transfusion frequency were estimated using the parameter estimates from the conditional logit model and out of sample prediction of utility scores assuming scenarios where all treatment alternatives required 0, 4, and 8 transfusions per month, respectively.

All analyses were performed using SAS 9.4. DCE analyses were validated using Stata 14.1.

Patient characteristics

Treatment history and experience with transfusion

The most common treatment patients received was IST (96.7%), followed by steroids (80.0%), targeted therapy (56.7%), and antibiotics (56.7%) (Table 2). Fewer than half of the patients were treated with antifungals (46.7%) or erythropoiesis-stimulating agents/growth factors (30.0%), or received a bone marrow transplant (33.3%). In the 3 months before the time of survey completion, 53.3% of patients had not received red blood cell or whole blood transfusions, while 13.3% had received transfusions once every 31–90 days, 16.7% had received transfusions once every 15–30 days, and 16.7% had received transfusions once every 8–14 days. In regards to platelet transfusion in the past 3 months, 70.0% answered they had not received white blood cell transfusions in the past 3 months, while 10.0% had received transfusions once every 31–90 days, 10.0% had received transfusions once or twice per month, and 10.0% had received transfusions once per week. 36.7% of patients had received iron chelation therapy in the past. When asked to rate agreement on statements related to their condition in the past week, over half of the patients (60.0%) reported feeling fatigued, 46.7% agreed with being frustrated by not being able to do their usual activities, and 43.3% reported bruising easily.

Opinions about transfusion independence

Most patients agreed that achieving transfusion independence would result in less burden in terms of time and costs, greater quality of life and life enjoyment, less fatigue, and greater control despite their health condition (each noted by 86.7% of patients) when asked to rate agreement on statements about their opinion on the impact of achieving transfusion independence on their well-being (not shown). Patients most often noted the following as important when they were asked to rate the importance of several ways to improve their quality of life with a new therapy: less frequent transfusions, less fatigue, and better emotional well-being (each endorsed by 96.7% of patients). Lower risk of infection and lower risk of serious bleeding were also of high importance to patients (each noted by 90.0% of patients).

Discrete choice experiment analysis

Based on the logit model, risk of bleeding was found to be the most important factor in patient treatment preferences with a relative importance of 0.30, followed by risk of infection (0.28), fatigue (0.23), and frequency of transfusions (0.20) (Fig. 2; no statistical comparison of relative importance between attributes was conducted). Figure 3 illustrates the relationship between the probability of selection (also referred to as part-worth utility or preference weight) and the attribute levels. A positive coefficient indicates high choice probability, whereas a negative coefficient indicates low choice probability. From Fig. 3, levels of “low” and “moderate” risk of serious bleeding and risk of infection, levels of “none” and “moderate” fatigue, and “none” for frequency of transfusion had positive coefficients which showed there was a high probability of selection. Levels of “high” risk of serious bleeding and risk of infection, “severe” fatigue, and “8 per month” transfusions resulted in negative coefficients indicating low probability of selection. To illustrate this concept, for the attribute frequency of transfusion, receiving more transfusions per month was associated with low probability in treatment selection. In particular, a large utility decrease was found for increasing the frequency of transfusions from 4 to 8 per month: the part-worth utility decreased from 0.48 associated with 0 transfusions per month to 0.20 associated with 4 transfusions per month, to − 0.68 associated with 8 transfusions per month (Fig. 3). This showed that receiving 8 transfusions per month had a negative influence on patient preferences, while no transfusions per month had high probability of selection. The mean utility score estimated by only varying the frequency of transfusion and keeping all other attributes constant was 0.58 associated with 0 transfusions per month, 0.57 associated with 4 transfusions per month, and 0.35 associated with 8 transfusions per month (Fig. 4). Prior to performing the data analysis, responses were checked for straight-lining. No such survey completion was found in the data.

Similarly to the frequency of transfusions, larger declines in part-worth utilities were estimated between the moderate and high/severe levels of risk of serious bleeding, risk of infection, and fatigue, compared to the decrease in utilities between the low/no and moderate levels (Fig. 3). All evaluated attribute levels had statistically significant part-worth utility coefficients at the 95% confidence level, except for moderate risk of infection and 4 transfusions per month.

To describe potential heterogeneity of preferences, the following descriptive analyses were conducted. Conditional logit models and relative importance of attributes to treatment preferences were estimated for patient subgroups by age (age 18–49, n = 10; age 50 and older, n = 20), years since first diagnosis with SAA (≤2 years ago, n = 15; 3 or more years ago, n = 15), experiencing bleeding since diagnosis (Yes, n = 16; No, n = 14), experiencing infection requiring hospitalization since diagnosis (Yes, n = 16; No, n = 14); and having any transfusions in the past 3 months (Yes, n = 14; No, n = 16). No statistical test of heterogeneity was performed.

Risk of bleeding and risk of infection had the highest relative contributions to treatment preferences but depending on the subgroup, their order in the treatment preferences differed. For example, risk of bleeding had numerically higher relative contribution to treatment preferences among patients who were younger (relative contribution 0.36 for age 18–49 years vs. 0.27 for patients 50 and older); were diagnosed with SAA more recently (relative contribution 0.33 for SAA diagnosis ≤2 years ago vs. 0.28 for SAA diagnosis 3 or more years ago), experienced bleeding since diagnosis (relative contribution 0.34 among patients who experienced bleeding vs. 0.26 among patients who did not), and experienced infection requiring hospitalization (relative contribution 0.35 among patients who experienced infection vs. 0.26 among patients who did not). Risk of infection had numerically higher relative contribution to treatment preferences among patients who were older (relative contribution 0.21 for age 18–49 years vs. 0.32 for patients 50 and older), were diagnosed with SAA longer ago (relative contribution 0.30 for SAA diagnosis ≤2 years ago vs. 0.26 for SAA diagnosis 3 or more years ago), did not experience bleeding since diagnosis (relative contribution 0.23 among patients who experienced bleeding vs. 0.33 among patients who did not), and did not experience infection since diagnosis (relative contribution 0.25 among patients who experienced infection vs. 0.30 among patients who did not). While the result that risk of bleeding had higher relative contribution than infection among patients who experienced infection may seem counter-intuitive, 10 out of 16 patients (62.5%) who had infection also experienced bleeding. Similar to the overall analysis, fatigue and frequency of transfusion generally had lower but meaningful relative contribution (fatigue relative contribution ranged from 0.21 among patients diagnosed 3 or more years ago and patients who did not experience bleeding to 0.24 among patients who experienced bleeding). Among patients who did not have any transfusions in the past 3 months (proxy for transfusion independence), the relative contribution of the frequency of transfusions (0.25) was numerically higher than among patients who had transfusions in the past 3 months (0.14). While risk of bleeding had the highest relative contribution to preferences among patients without transfusion in the past 3 months (0.28), frequency of transfusion had a relative contribution, which was similar to that of risk of infection (0.25) and higher than that for fatigue (0.22).