Preferences of Patients with Acute Myeloid Leukemia and Other Myeloid Malignancies on Cancer Treatment: Effect of Patient- and Treatment-Characteristics?

Background

In an era of precision medicine, patient preferences play a pivotal role in determining personalized treatment for patients with cancer. Understanding patient preferences is crucial for shared decision-making and fostering better understanding and trust between patients and their providers. Recent years have witnessed remarkable advancements in cancer treatment, leading to multiple therapeutic options that vary in safety, efficacy, and other critical characteristics. We developed a self-reported questionnaire, Therapy Preference Scale (TPS), to provide valuable insight into preferences of each unique patient to formulate the best personalized treatment strategies to meet patient’s goals and expectations.

Methods:

Therapy Preference Scale

TPS includes a total of 30 questions (Future Oncol 17 (01), 37-44). Three questions evaluate patients' preferences on the intent of therapy (cure, extension of life, or relief of symptoms), acceptable maximum annual out-of-pocket expenses ($1000, $5000, $10,000, $15,000, or $20,000), and minimum increase in life expectancy to accept cancer treatment (3, 6, 9, 12, or 15 months). Eight questions focus on the importance of various treatment characteristics, and 19 focus on patient's preferences for safety, quality of life, and treatment effectiveness.

Data collection and analysis

We included a total of 300 patients >18 years with a cancer diagnosis from the University of Nebraska Medical Center. Patients were asked to complete TPS based on their current opinion. We use descriptive statistics with patient-, cancer-, and treatment-related data for analysis. We analyzed data on patients with myeloid malignancies, including acute myeloid leukemia (AML), myelodysplastic syndrome, and myeloproliferative neoplasms and patients with AML only.

Results

Patient characteristics

A total of 72 patients had myeloid malignancies, of which 35 (49%) had AML. The median age of patients was 62 years (range 20-86 years); 42% were female, 91% were white, and 96% were non-Hispanic. The median age of patients with AML was 54 (23-86); 51% were female, 94% were white, and 91% were non-Hispanic.

Efficacy of treatment

Sixty-three percent of patients identified cure, 34% identified increased life expectancy, and 3% identified symptom relief as their preferred intent of therapy. Among patients with AML, 63% identified cure, 33% identified increased life expectancy, and 3% identified symptom relief as their preferred intent of therapy.

Treatment characteristics

Eighty percent of patients would rather live a shorter life than permanently lose their cognitive ability or ability to do daily activities, similar to patients with AML (Table 1). Seventy percent of all patients, compared to 63% with AML, preferred to avoid effective treatment that would result in poor quality of life. Thirty-eight percent of total patients, compared to 30% with AML, were likely to avoid an effective treatment that results in financial burden, including debt. More than 30% of patients in both groups would avoid an effective treatment that will result in side effects such as life-threatening infections. More than 70% of patients in both groups would undergo treatment that could maintain or improve quality of life but does not help them live longer.

Out-of-pocket expenses and life expectancy gain

An annual out-of-pocket expense of more than $5000 was unacceptable to 23% of all patients compared to 30% of patients with AML (Table 2). Forty-nine percent of total patients and 44% with AML would not find a harsh cancer treatment worthwhile if the likelihood of an increase in life expectancy were less than 12 months.

Conclusion

While most patients sought cancer treatment to achieve a cure or increase in life expectancy, many patients would not prefer an effective but harsh treatment that had a high potential to cause long-term impairment in cognitive or physical function, quality of life, or financial burden. Conversely, many patients would undergo treatment that could improve their quality of life but may not extend survival. Our study provides initial data on further exploration of treatment preferences based on cancer type and their specific therapeutic options.