Measurement and Analysis of Patient-Reported Outcomes to Provide the 'Patient Voice'


Applied Clinical Trials

Clinical trials today are more commonly assessing quality of life and other PRO measures as part of post-approval studies to present evidence on treatment effectiveness. It is crucial, therefore, that clinical teams have a strong plan for the capture and analysis of PROs data, and the resources required to draw clinically meaningful extrapolations.

Today, there is heightened awareness among healthcare professionals (HCPs), consumers, payers, and regulatory authorities on the benefits and risks of products, with all interested parties demanding more evidence than just safety and efficacy data from clinical trials. Once a product is in the market, other important measurements include treatment effectiveness and comparative effectiveness relative to other therapies. These require real-world data, such as patient-reported outcomes (PROs) that are based on longer follow-up and a more representative sample of the patient population.

Sources of this data are claims databases, disease registries, and electronic health records (EHRs). However, the quality of readily available real-world data may be poor due to missing data and inadequate validation. More outcomes data has to be generated in a planned manner to provide comprehensive evidence of the value of the drug.

PROs and other similar tools are used to capture quality of life (QoL) data along the range of clinical development, post-approval studies, and patient registries, which are more compelling than, for example, survival or even progression-free survival data. QoL data rose into prominence a number of years back, with the increase in incidence of oncology indications, high drug prices, and small incremental gains in survival rates offered by new drugs. QoL data is also equally relevant for lifestyle diseases such as diabetes and asthma. The fundamental premise now is that health-related QoL and well-being of patients is a core co-primary endpoint in clinical research and clinical care.

Many companies use PRO data to measure the impact and effectiveness of their drugs even during Phase II and Phase III clinical trials. In fact, some companies are using PROs at the very start of the drug development process.1 Early observational and epidemiology studies can identify unmet clinical needs and potentially profitable drug markets. For example, PRO health surveys can be used to quantify the physical health burden of a particular type of disease.

Better decision-making

End results of medical treatment and care are available from outcomes research studies, in terms of the effect on health and well being of patients and the populations. The area of outcomes research encompasses studies that evaluate effectiveness of treatments, development and use of tools to measure health status, and analysis and dissemination of the results. Outcomes research evaluates the results of healthcare process in the real world through effectiveness research rather than using efficacy studies, and assesses which treatments for specific problems work best for whom by also factoring in patient preferences and patient satisfaction. Governments, insurance companies, employers and consumers are all looking for outcomes research data for better decision-making.

Regulators are making approval decisions based on outcomes data. For example, when NICE (National Institute for Health and Care Excellence) reviewed Novartis’s asthma drug Xolair, it considered data from the Asthma QoL questionnaire in observational studies and overturned an earlier decision to reject Xolair.2 PRO health surveys have also been used for label claims (e.g., Humira, Allegra, Lyrica).3 PRO data can help influence pharmacy benefit managers and insurers to include a drug in their formularies. Health surveys can also be used to answer any questions regarding comparative effectiveness in order to build an economic basis for formulary inclusion, thus helping to lower claim costs over time. Companies successfully use PROs to prove the positive impact of a product on patient health and, ultimately, health expenses.

Public and private sector interest in outcomes research has grown dramatically in the past several years, in large part because of its potential to address the interrelated issues of cost and quality of healthcare. Outcomes research touches all aspects of healthcare delivery, from the clinical encounter itself to aspects of the organization, financing, and regulation of the healthcare system. Each of these factors plays a role in the outcome of care, or the ultimate health status of the patient. Understanding how the different factors interact requires collaboration among a broad range of health services researchers, such as physicians and nurses, economists, sociologists, political scientists, operations researchers, biostatisticians, and epidemiologists.

Standardizing patient perspectives

The primary challenges of real-world data are that these data are not controlled; they may be collected and measured anywhere. The main sources are computerized databases, EHRs, and PROs. The PRO data measure health status and consumer preferences and capture the patient perspective of the impact of intervention on quality of life and ability to function. It is a challenge to quantify and calibrate these data. Collection of such data requires tools (PRO instruments) that provide scientifically valid assessments of physical and mental health, to measure health and well-being from the patient point of view. There are a few tools that offer a standardized way to measure health outcomes for individuals and large populations, as statistically valid patient-centered measures. Health status is measured as physical functional status, role functioning, social functioning, physical and mental well-being, measured in terms of mental health (mood, depression, anxiety), health perceptions (own view of general health), and pain and life satisfaction (QoL), all of which require an individual evaluation.4

In December 2009, the FDA released guidance for the industry on PRO measures.5 This guidance reviews and evaluates PRO instruments used to support claims in approved medical product labelling. A PRO instrument (such as a questionnaire plus the information and documentation that support its use) is defined as a means to capture PRO data used to measure treatment benefit or risk of medical products.


The adequacy of any PRO instrument, as a measure to support medical product labelling claims, depends on whether its characteristics, conceptual framework, content validity, and other measurement properties are satisfactory. The FDA will review documentation of PRO instrument development and testing in conjunction with clinical trial results to determine whether a labelling claim is substantiated. The type of PRO information sponsors should provide to the FDA to facilitate instrument review is listed in the guidance document

The use of electronic PRO instruments, however, may pose a problem when direct control over source data has to be maintained by the sponsor or the contract research organization (CRO) and not by the clinical investigator. Sponsors need to plan to establish appropriate system and security controls, as well as cyber-security and system maintenance plans that address how to ensure data integrity during network attacks and software updates. Capture of PROs may also be web-based or through IVR-compatible tools.

A commonly used PRO instrument to measure functional health status is the Short Form (SF) Health Survey (SF-36v2® Health Survey of 36 questions and the shorter SF-12v2® Health Survey of 12 questions). This measures health status across eight domains and are summarized into physical and mental health scores.



Statistical complexities

Variables defined from PROs may be the main variables that will be analyzed to yield the key conclusion from the study, or they may be add-on variables while the main variables may be based on clinical data. In either case, when PRO data are collected, it becomes difficult to identify a single variable as the most important. Therefore, two or more variables have to be considered equally important while making inferences from the statistical analysis, hence, multiple comparisons have to be carried out. Appropriate statistical methods have to be applied to handle this multiplicity and adjustments need to be made to control the overall rate of false positives. Adherence to blinding and randomization requirements is critical in order for the analysis of the PRO endpoints to be valid since the patient-reported outcomes are inherently subjective in nature. 

A PRO instrument (tool or questionnaire used to capture PRO data) comprises of multiple domains (e.g., physical and mental, social and work-related), some of which may be combined to define the variables on which the statistical methods are applied. Analysis of such variables and interpretation of the results is challenging, especially when a conclusion has to be made on individual components of the variable. PRO data are often measured at regular intervals over a period of time and statistical models have to factor in the dependency in the data since it’s measured on the same individuals at different time points. When outcomes have to be captured over a period of time, the possibility of some data being missing is quite high, and this could lead to bias in the results. Sensitivity analysis has to be carried out by replacing missing data with substitute values. Since the PROs measure well-being of patients, cross-cultural comparability of data can be a major issue even when validated translated versions of the PRO instrument are used.

Thus, the analysis of PRO data involves substantial statistical complexities. Moreover, clinical interpretation of results and assessment of clinical significance can also be very challenging. It is important to use the right skills to design, analyse, and report PRO endpoints. Outcomes research is often a specialized and separate group within the R&D or commercial organizations of pharmaceutical companies. There is increased recognition that PRO data, even when it is collected in the post-approval phase, is challenging to capture, analyse, interpret, and report. With the increasing volume of outcomes research data, sponsor organizations often need to outsource some of the analysis. Many CROs and other niche providers have been building expertise in handling PRO data to cater to this need. Outsourcing to the right provider will give an edge to the sponsor organization in this increasingly important and complex area of data analysis and reporting.

Benefits of PRO

PRO health surveys generate information that is tailor-made for the marketing of a product. Consumers want to know what a drug does and how well it works. PRO results can be used to convey the value of a drug and encourage patients to ask their doctor about a product. Marketing professionals can use PRO data to create well-defined marketing communications such as advertising, brochures, and educational materials to increase brand awareness and promote sales. Companies are also using online PRO health surveys to generate web traffic in order to engage and educate consumers. Such methods help create ongoing dialogue and relationship with a large number of consumers. They educate consumers on disease and treatments, which, in turn, leads people to talk about the products to their doctors.



Companies try to protect the safety of consumers through post-marketing surveillance, however, once a new drug is made available outside of the controlled environment of clinical trials, it can be difficult to monitor drug response and effects. By using PRO surveys at every stage of the drug development and commercialization process, a drug company can accumulate an impressive body of data that can enable it to meet the demands of all interested parties, from the FDA and health insurers, to doctors and patients. A company can also solidify its position as an industry leader by consistently finding and cultivating profitable new markets. Through innovative uses of PRO health surveys, drug developers can meet the ever-growing challenges created by increased competition and regulatory requirements in a world where the trial never ends.


It has become more and more common in clinical trials to assess QoL and other PROs as part of post-approval studies to provide the “patient voice” in evidence on treatment effectiveness. PROs are relevant to many primary care research questions and play a significant role in drug approval and labeling decisions. Thus, it is crucial to have a robust plan for capture and analysis of PRO data that sufficiently addresses all challenges of capturing reliable and validated data, as well as statistical complexities involved in analysis of the data and drawing clinically meaningful extrapolations.

Both logistical and scientific issues should be addressed to ensure that the PRO data is of a high quality, as PROs are often inadequately reported in trials, which limits the value of these data. CONSORT (CONsolidated Standards of Reporting Trials) lacks guidance on the reporting of PROs, which is addressed through development of the CONSORT PRO extension based on the methodological framework for guideline development proposed by the Enhancing the QUAlity and Transparency Of health Research (EQUATOR) Network.6 Improved reporting of PRO data will facilitate robust interpretation of the results from clinical studies and informed patient care. It is only through outsourcing these activities to a provider with rich expertise and best-in-class processes for handling PRO data that scientists and clinicians will overcome the challenges associated with the time and resource required to interpret and present complex data in an effective and efficient manner.


Chitra Lele is Chief Scientific Officer at Sciformix Corporation, email:



1.  Peter Mansell, 2012. “Pharma needs to take strategic approach to patient-reported outcomes, says report.” Published online,

2.  Nick Taylor, 2014. “Analyzing real-world data for lifecycle management.” Published online,

3.  Gus Gardner, 2009. “The Trial Never Ends.” Published online,

4.  Foundation for Health Services Research, 1994. HEALTH OUTCOMES RESEARCH: A PRIMER.

5.  US FDA Guidance for Industry on PRO measures, December 2009,

6.  Melanie Calvert. “Evaluation of patient reported outcomes in clinical trials: systematic review of trial protocols.”

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