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The 57th American Society of Hematology (ASH) Annual Meeting & Exposition

How Do You Develop, and Successfully Incorporate, PROs in Hematology? Experts Chime in at ASH

Surabhi Dangi-Garimella, PhD
Presenters at an education session, titled Patient-Reported Outcomes in Hematology, addressed the importance of embracing the patient perspective in healthcare delivery, on the second day of the annual meeting of the American Society of Hematology, being held December 5-8, in Orlando, Florida.
A patient-reported outcome (PRO) is defined as the measurement of a patient’s perception of a health condition and its treatment. A session on PROs and the importance of embracing the patient perspective in healthcare delivery witnessed a healthy discussion between a developer of these tools, a representative of the FDA who reviews these tools when used by drug developers, and a clinician who is the end-user of PROs in clinical practice. These presenters were participants in an education session on Patient-Reported Outcomes in Hematology on the second day of the annual meeting of the American Society of Hematology, being held December 5-8, in Orlando, Florida.

David Cella, PhD, from the Feinberg School of Medicine, Northwestern University, began the session, introducing The Science behind Developing a Patient-Reported Outcome Measure. Cella has been a pioneer in developing The Patient Reported Outcomes Measurement Information System (PROMIS), which has seen wide-scale adoption in clinical practice. PROMIS is a National Insitutes of Health (NIH)-funded measurement system that uses item response theory and provides researchers and clinicians the ability to determine PROs using precise and reliable tools.
Although Cella is involved in developing these outcomes measures across a range of therapeutic areas, he geared his talk to present the hematology context, outlining fatigue as an indexed symptom for patient-reported outcomes measures (PROMs), the promise of PROMs, and where he sees the future for these measures.

“There’s value in asking systematic questions on patient outcomes. The series of endpoints, such as tumor response, progression-free survival (PFS), disease progression, which are commonly used as outcomes measures, may not always relate with overall survival (OS),” Cella said. “However, if we place a value on tumor response and PFS that makes sense to people, including patients’ treatment experience, it can significantly contribute to the value proposition of a regimen,” he explained.

Providers can gather outcomes such as disease symptoms, side-effect burden, and tolerability throughout the treatment. These measures may be strongly associated with patient preference. However, in order to help patients make informed treatment decisions, there’s a need to assess these measures through well-controlled studies, Cella said. It is important to realize that “Treatment benefit can be measured as a combination of treatment efficacy and treatment toxicity,” he added.

Explaining fatigue as a therapeutic index, Cella informed the audience that there are 3 international prognostic scoring systems that are well established: WHO-classification-based Prognostic Scoring System (WPSS), the International Prognostic Scoring System (IPSS), and the IPSS-revised. He then shared data from a recent paper in Lancet Oncology that evaluated self-reported fatigue in patients with myelodysplastic syndrome as an outcomes measure for OS, beyond IPSS. The researchers found that self-reported fatigue indeed provides prognostic information for survival, independent of the god-standard classifications, creating a case for fatigue to be included in routine diagnostic investigation in randomized clinical trials.

“However, what we are currently lacking is a single metric to standardize measures like fatigue—1 gold standard like blood pressure,” said Cella.

That’s how the PROMIS trial came about, he explained—PROMIS is domain-specific, not disease specific. A domain is the specific function, feeling, or perception that you want to measure, and it includes physical, social, and mental health measures. Each domain, such as fatigue, is measured using multiple “item banks,” explained Cella. The data can be collected through survey questions or computerized adaptive testing or CAT, which is an adaptive tool that is response-based.

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