Patient Centricity in Comparative Effectiveness Research
May 1, 2025
Inclusion of the patient voice in clinical research is becoming increasingly important. Oncology trials, for example, may be shifting toward a more patient-centered approach to outcomes, such as quality of life and time to symptomatic progression,1 as endpoints like progression-free survival and response rate may not be meaningful to patients in the absence of symptom alleviation.2
The primary purpose of a patient-centric approach to clinical research is to improve patient outcomes, which include well-being and quality of life.3 As part of that endeavor, here we discuss increasing patient centricity in comparative effectiveness research by including patient-reported outcome data in indirect treatment comparison analyses.
What are patient-reported outcomes (PRO)?
One way of increasing patient centricity in clinical trials is by incorporating patient-reported outcomes (PRO) as trial endpoints. A PRO is “any report of the status of a patient’s health condition that comes directly from the patient without interpretation of the patient’s response by a clinician or anyone else.”4 PRO measures assess broad concepts like health-related quality of life (HRQoL) as well as specific symptoms, such as pain or fatigue. However, there are concerns regarding the extent to which PRO results are published.5 That is, in addition to growing interest in measuring PRO, there are also ongoing efforts to promote the reporting of PRO findings from clinical trials. Specifically, the Consolidated Standards of Reporting Trials (CONSORT) PRO extension guidelines recommend that PRO results be reported in peer-reviewed publications, ideally with a trial’s primary endpoints.6
Benefits to publishing PRO findings
There are various benefits of publishing PRO findings from clinical trials. These PRO data can be used to:
- Facilitate shared decision-making between patients and providers, and
- Influence treatment guidelines and drug approvals.7
Additionally, health technology assessment (HTA) agencies recognize patient-reported HRQoL and treatment satisfaction data when confirming clinical benefits and supporting reimbursement decisions.8,9 Specifically, the inclusion of PRO data in peer-reviewed publications is considered especially influential.8 It has been recommended that in order for PRO data to have the largest possible impact, they must be maximized.7 One way to enhance the impact of PRO data from clinical trials is to include them in comparative effectiveness research.
What are indirect treatment comparisons (ITC)?
Indirect treatment comparison (ITC) analyses can be used to evaluate the efficacy and safety of interventions that have not been compared in a head-to-head trial. Several ITC methods are available with network meta-analysis (NMA) being the most common.10 Other techniques include those that adjust for patient differences, such as population-adjusted indirect comparison (PAIC). Specifically, PAIC utilizes individual patient-level data (IPD) from one trial (i.e., the index trial) and published aggregate data for comparator trials.10 Using PAIC as an example, the PRO IPD from the index trial would be utilized along with published aggregated PRO data from comparator trials. This would be contingent upon PRO data being publicly available for the comparator(s) of interest, which is one limitation of conducting comparative effectiveness analyses for PRO data. Moreover, the definition and assessment criteria would need to be similar.
What does the intersection of PRO and ITC look like?
Examples can be found in the oncology literature. Specifically, ITC analyses of PRO have been published for HR+/HER2- breast cancer. In one study, palbociclib + fulvestrant was associated with better outcomes than abemaciclib + fulvestrant in terms of changes from baseline in several domains of a common oncology PRO measure, the EORTC QLQ-C30 (overall quality of life, emotional functioning, nausea/vomiting, appetite, and diarrhea).11 Another study utilized a matching-adjusted indirect comparison to evaluate time to symptom deterioration, revealing favorable outcomes for ribociclib over abemaciclib in the EORTC QLQ-C30 domains of appetite, diarrhea, and fatigue.12
Including PRO data in ITC analyses
Although patient engagement is at the center of conversations about clinical research, incorporating the patient perspective in a meaningful manner remains challenging. As efforts to increase patient centricity continue, including PRO data in ITC analyses may represent an overlooked area of opportunity. Specifically, long before a clinical trial begins, resources are used to select optimal PRO measures, determine when and how they will be administered, and develop an analytical plan. During the trial, patients devote their time and energy to participation, including the completion of PRO measures. When considering all the work that goes into this one component of the clinical trial, it only makes sense that using these data as comprehensively as possible is a way of honoring patients and researchers who share a common goal. As stated earlier, these data should be maximized by including them in comparative effectiveness research.
Including PRO data in ITC analyses both begins and ends with dissemination: that is, only when PRO results from clinical trials are publicly available can they be included in ITC analyses. Along the same lines, the results of the ITC analyses should also be published, ideally in an open-access format, so that patients and providers alike can utilize the findings to develop treatment plans. Additional recommendations beyond dissemination include ongoing collaboration between patients, HTA agencies, and health economics and outcomes research (HEOR) specialists to align on goals and enhance decision-making for the adoption of new technologies.
Final takeaway
Although patient-centered comparative effectiveness research is only one piece of the puzzle, it contributes to the larger endeavor of increasing patient centricity in clinical research and may also shed light on other areas previously viewed as separate from these efforts.
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Julia Poritz
Senior Research Consultant, Patient-Reported Outcomes
Julia Poritz, PhD, is Senior Research Consultant, Patient-Reported Outcomes at Cytel. Julia holds a PhD in Counseling Psychology from Texas A&M University and is a Licensed Psychologist with specialties in health psychology and rehabilitation psychology. Prior to joining Cytel, she worked at the University of Texas Medical Branch as a Clinical Assistant Professor in the Department of Obstetrics and Gynecology. Before this, she completed a postdoctoral fellowship at the Brain Injury Research Center at TIRR Memorial Hermann with a focus on the development and implementation of patient-reported outcomes for individuals with traumatic brain injuries. In addition to utilizing patient-reported outcome measures as part of routine clinical practice, she has also conducted research on the validation of existing psychological assessments as well as the creation and evaluation of new tools for special populations.
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Loraine Monfort
Associate Director
Loraine Monfort, PharmD, is Associate Director on the Comparative Effectiveness team, specializing in evidence synthesis projects and advanced methodologies like indirect treatment comparisons. With over 10 years of experience in consulting firms, and pharmaceutical companies, Loraine cultivated expertise in global market access including value messages and developing economic tools for specialty drugs. Loraine spearheaded over 12 Canadian HTA submissions across therapeutic areas such as specialty medicines, oncology, and rare diseases with a commitment to ensuring that evidence used in decision-making reflects both scientific rigor and clinical relevance. Loraine holds a PharmD from the Université Libre de Bruxelles and a M.Sc. in Health Economics from the Université Paris-Est Créteil.
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Hoora Moradian
Director, Comparative Effectiveness
Hoora Moradian, PhD, Director of Comparative Effectiveness at Cytel, has over 15 years of experience in machine learning, data science and indirect treatment comparisons, with more than 50 publications and numerous HTA submissions. She developed MAIC with random forest weighting and compared this approach with G-Computation and their respective use cases. She has published extensively on random forest methods.
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Nathalie Horowicz-Mehler
Global Head of Value
Nathalie brings more than 25 years of experience in health economics and real-world evidence to Cytel’s Evidence, Value and Access business. She has a proven track record of driving growth by leading teams of scientist entrepreneurs and applies her clinical expertise as an epidemiologist and experience with HEOR, RWE/RWD and advanced analytics to catalyze innovations in public health.
Nathalie has held leadership roles at IQVIA, Concert AI, and Exponent. As Senior Vice President GM at ConcertAI, she leveraged her expertise to successfully establish their health economics and epidemiology practice. Most recently, she served as Principal Scientist at Exponent, focusing on pharmaceutical sector advancements and healthcare innovation.
Nathalie has an MS from Tufts University School of Medicine, and both an MPH and PhD from Columbia University Mailman School of Public Health.
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