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In an aging population, potentially modifiable factors impacting mortality such as diet quality, body mass index (BMI), and health-related quality of life (HRQOL) are of interest. Surviving members of the Geisinger Rural Aging Study (GRAS) (n = 5,993; aged ?74 years) were contacted in the fall of 2009. Participants in the present study were the 2,995 (1,267 male, 1,728 female; mean age 81.4 ± 4.4 years) who completed dietary and demographic questionnaires and were enrolled in the Geisinger Health Plan over follow-up (mean = 3.1 years). Cox proportional hazards multivariate regression models were used to examine the associations between all-cause mortality and BMI, diet quality, and HRQOL. Compared to GRAS participants with BMIs in the normal range, a BMI < 18.5 was associated with increased mortality (HR 1.85 95%CI 1.09, 3.14, P = 0.02), while a BMI of 25-29.9 was associated with decreased risk of mortality (HR 0.71 95%CI 0.55, 0.91, P =0.007). Poor diet quality increased risk for mortality (HR 1.53 95%CI 1.06, 2.22, P = 0.02). Finally, favorable health-related quality of life was inversely associated with mortality (HR 0.09 95%CI 0.06, 0.13, P < 0.0001). Higher diet quality and HALex scores, and overweight status, were associated with reduced all-cause mortality in a cohort of advanced age. While underweight (BMI < 18.5) increased risk of all-cause mortality, no association was found between obesity and all-cause mortality in this aged cohort.

Objectives Health outcomes instruments assess diverse health concepts. Although item-level concepts are considered fundamental elements, the field lacks structures for evaluating and organizing them for decision making. This article proposes a grammar using item stems, response options, and recall periods to systematically identify item-level concepts. The grammar uses "core concept," "evaluative component," and "recall period" as intuitive terms for communicating with stakeholders. Better characterization of concepts is necessary for classifying instrument content and linking it to treatment benefit. Methods Items in 2 generic and 21 disease-specific instruments were evaluated to develop and illustrate the use of the grammar. Concepts were assigned International Classification of Functioning, Disability and Health codes for exploring the value that the grammar and a classification system add to the understanding of content across instruments. Results The 23 instruments include many core concepts; emotional function is the only concept assessed in all instruments. Concepts in disease-specific instruments show obvious patterns; for example, arthritis instruments focus on physical function. The majority of instruments used the same response options across all items, with five-point scales being the most common. Most instruments used one recall period for all items. Shorter recall periods were used for conditions associated with "flares," such as chronic obstructive pulmonary disease and "skin disease." Every diagnosis, however, showed variation across instruments in the recall period used. Conclusions This analysis indicates the proposed grammar's potential for discerning the conceptual content within and between health outcomes instruments and illustrates its value for improving communication between stakeholders and for making decisions related to treatment benefit.

Background: Patient-reported outcome (PRO) instruments are used to evaluate the effect of medical products on how patients feel or function. This article presents the results of an ISPOR task force convened to address good clinical research practices for the use of existing or modified PRO instruments to support medical product labeling claims. The focus of the article is on content validity, with specific reference to existing or modified PRO instruments, because of the importance of content validity in selecting or modifying an existing PRO instrument and the lack of consensus in the research community regarding best practices for establishing and documenting this measurement property. Methods: Topics addressed in the article include: definition and general description of content validity; PRO concept identification as the important first step in establishing content validity; instrument identification and the initial review process; key issues in qualitative methodology; and potential threats to content validity, with three case examples used to illustrate types of threats and how they might be resolved. A table of steps used to identify and evaluate an existing PRO instrument is provided, and figures are used to illustrate the meaning of content validity in relationship to instrument development and evaluation. Results & Recommendations: Four important threats to content validity are identified: unclear conceptual match between the PRO instrument and the intended claim, lack of direct patient input into PRO item content from the target population in which the claim is desired, no evidence that the most relevant and important item content is contained in the instrument, and lack of documentation to support modifications to the PRO instrument. In some cases, careful review of the threats to content validity in a specific application may be reduced through additional well documented qualitative studies that specifically address the issue of concern. Conclusion: Published evidence of the content validity of a PRO instrument for an intended application is often limited. Such evidence is, however, important to evaluating the adequacy of a PRO instrument for the intended application. This article provides an overview of key issues involved in assessing and documenting content validity as it relates to using existing instruments in the drug approval process.

This article deals with the incorporation of patient-reported outcomes (PROs) into clinical trials and focuses on issues associated with the interpretation and reporting of PRO data. The primary focus and context of this information relates to the evidentiary support and reporting for a labeling or advertising claim of a PRO benefit for a new or approved pharmaceutical product. This manuscript focuses on issues associated with assessing clinical significance and common pitfalls to avoid in presenting results related to PROs. Specifically, the questions addressed by this manuscript involve: What are the best methods to assess clinical significance for PROs? How should investigators present PRO data most effectively in a Food and Drug Administration (FDA) application? In labeling or in a scientific publication? Guidelinesfor interpreting clinical significance of PROs and for comprehensively reporting on the methods, measures and results of clinical trials that incorporate PROs are important for clinicians, regulatory agencies, and most of all to patients. Clear specifications for considering a finding on a PRO measure, as clinically meaningful, need to be determined by instrument developers and psychometricians; they need to be reported for all clinical trials involving PRO end points. Clinical trial reports need to be comprehensive, clear, and sufficient to enable any reader to understand the methods, PRO measures, statistical analysis, and results.

Objective Health decision-makers involved with coverage and payment policies are increasingly developing policies that seek information on "real-world" (RW) outcomes. Motivated by these initiatives, the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) created a Task Force on Real-World Data to develop a framework to assist health-care decision-makers in dealing with RW data, especially related to coverage and payment decisions. Methods Task Force cochairs were selected by the ISPOR Board of Directors. Cochairs selected chairs for four working groups on: clinical outcomes, economic outcomes, patient-reported outcomes, and evidence hierarchies. Task Force members included representatives from academia, the pharmaceutical industry, and health insurers. The Task Force met on several occasions, conducted frequent correspondence and exchanges of drafts, and solicited comments on three drafts from a core group of external reviewers and from the ISPOR membership. Results We defined RW data as data used for decision-making that are not collected in conventional randomized controlled trials (RCTs). We considered several characterizations: by type of outcome (clinical, economic, and patient-reported), by hierarchies of evidence (which rank evidenceaccording to the strength of research design), and by type of data source (supplementary data collection alongside RCTs, large simple trials, patient registries, administrative claims database, surveys, and medical records). Our report discusses eight key issues: 1) the importance of RW data; 2) limitations of RW data; 3) the fact that the level of evidence required depends on the circumstance; 4) the need for good research practices for collecting and reporting RW data; 5) the need for good process in using RW data in coverage and reimbursement decisions; 6) the need to consider costs and benefits of data collection; 7) the ongoing need for modeling; and 8) the need for continued stakeholder dialogue on these topics. Conclusion Real-world data are essential for sound coverage and reimbursement decisions. The types and applications of such data are varied, and context matters greatly in determining the value of a particular type in any circumstance. It is critical that policymakers recognize the benefits, limitations, and methodological challenges in using RW data, and the need to consider carefully the costs and benefits of different forms of data collection in different situations.

Context The term “patient-reported outcomes” (PROs) has evolved to include any endpoint derived from patient reports, whether collected in the clinic, in a diary, or by other means, including single-item outcome measures, event logs, symptom reports, formal instruments to measure health-related quality of life (HRQL), health status, adherence, and satisfaction with treatment. This term coincides with the explicit interest from drug development researchers and regulatory authorities in the appropriate utilization and reporting of treatment impact measures. Objective To determine the level and nature of use of PROs compared to other types of effectiveness endpoints in approved product labeling for new drugs recently approved in the United States. Design and sources Review and analysis of effectiveness endpoints as reported in clinical study descriptions in approved product labeling of new molecular entities (NMEs) approved in the United States from 1997 through 2002. Main outcome measures Effectiveness study endpoints reported in approved product labeling that fall into the following categories of measurement: PROs, clinician-reported outcomes (CROs), and laboratory test/device measurement endpoints. Results PROs were reported in 64 (30%) of the 215 product labels reviewed. Clinician-reported outcomes were reported most frequently (62%) followed by laboratory/device endpoints (50%). PROs were the only type of endpoint used in the FDA-approved label for 23 products. Formal multiitem PRO scales were cited 22 times. Use of PROs is most common in antiinflammatory, CNS, gastrointestinal, respiratory, allergic conjunctivitis, and urologic therapy areas. The frequency of reported PRO use over this period did not change. Conclusion PROs, although quite variable as a class of study endpoints, were found to have a significant role in the development and evaluation of new medicines. More formal guidance from the FDA about use of such measures along with continued collaboration by PRO researchers to develop and disseminate standards will enhance the appropriate use of PROs in future drug development and labeling.

Background: Currently, information to improve health status and quality of life is derived from independently designed data systems that range from population-based health surveys to health records used in managing individual patient care. But there is no coherent strategy for using these data sources in concert across diverse applications. Thus, it is frequently difficult to compare or combine results across studies to provide population-level inferences based on findings from specific subpopulations. Objective: The Health Outcomes Framework is an analytic structure to provide more comprehensive information about the health status and quality-of-life impact of disease and its treatment. This framework consists of three components: (1) a core set of health, lifestyle, and economic questionnaires that collect data from an individual’s perspective; (2) applications that range from population to patient care levels; and (3) time. Although health is the outcome of interest, lifestyle behaviors and economic and political factors are important determinants of health, which also need to be studied using standardized procedures; thus, they are included in the core. This article focuses on the nature and application of a core health status and quality-of-life instrument. To be useful across a range of applications, such a core instrument needs to have three conceptual characteristics: (1) a theoretical model that regards health as a continuum of states; (2) domains that represent policy-relevant aspects of impairment, disability, and handicap; and (3) a set of societal preferences for these domains. In addition, the core needs to address three practical concerns: (1) brevity, (2) methods of administration that are suitable for respondents with diverse capabilities, and (3) documentation that is publicly available. These features are discussed using examples from currently available, multi-domain generic instruments, each of which has some, but not all, of the necessary features of the core instrument. Conclusion: The Health Outcomes Framework is intended to be a cooperative effort. It is proposed that the National Cancer Institute and the Centers for Disease Control and Prevention take leadership roles not only by adopting a core health status and quality-of-life instrument for use in current and future cancer data collection activities but also in encouraging industry and academic investigators to implement this core instrument in their cancer studies. Having a vertically integrated core instrument can lead to more representative data for informing decision making and ultimately for obtaining a more equitable distribution of health. [J Natl Cancer Inst Monogr 2004;33:168–77]

Chronic medical conditions drastically affect the lives of those afflicted, leading to pain, disability, and disruption. Comorbid depression can exacerbate the effects of medical illness and may be an independent source of suffering and disability. Data from the Epidemiological Follow-Up Study (NHEFS) of the first National Health and Nutrition Examination Survey (NHANES I) are used to examine the manner in which depression and comorbid medical conditions interact to affect health-related quality of life (HRQOL). The findings suggest a) that the effects of depression are comparable with those of arthritis, diabetes, and hypertension; and b) that depression and chronic medical illnesses interact to amplify the effects of the medical illness. The data also support the merit of adopting a multidimensional approach to HRQOL rather than treating it unidimensionally.

To determine the associations between diet quality, body mass index (BMI), and health-related quality of life (HRQOL) as assessed by the health and activity limitation index (HALex) in older adults.Multivariate linear regression models were used to analyze associations between Dietary Screening Tool (DST) scores, BMI and HALex score, after controlling for gender, age, education, living situation, smoking, disease burden and self-vs. proxy reporting.Geisinger Rural Aging Study, Pennsylvania.5,993 GRAS participants were mailed HRQOL and DST questionnaires with 4,009 (1,722 male, 2,287 female; mean age 81.5 ± 4.4) providing complete data.HALex scores were significantly lower for participants with dietary intakes categorized as unhealthy (60) (0.70, 95% CI 0.69, 0.72, p0.05) or borderline (60-75) (0.71, 95% CI 0.70, 0.73, p0.05) compared to those scoring in the healthy range (75) (0.75, 95% CI 0.73, 0.77) based on DST scores. HALex scores were significantly lower for underweight (0.67, 95% CI 0.63, 0.72, p0.05), obese class II (0.68, 95% CI 0.66, 0.71, p0.05) and class III participants (0.62 95% CI 0.57, 0.67, p0.05) compared to those with BMI 18.5-24.9.Poor diet quality, as assessed by the DST, is associated with lower HRQOL in adults ≥ 74 years of age.

This paper briefly discusses the rationale and methods for developing and evaluating the Health and Activity Limitation Index (HALex), a generic measure of health that consists of two attributes: perceived health and activity limitation. Using a multiattribute utility scoring system, information from these attributes was combined to form a single score that represents health-related quality of life (QoL) on a 0.0-1.0 continuum. The construct and incremental validity are evaluated using data from a sample of over 40,000 adults who participated in the 1990 US National Health Interview Survey. The health state distributions for known groups, defined in terms of personal or lifestyle characteristics such as sex, age and smoking status, were comparable to those for similarly defined states that have been studied by other researchers. Of the regression models examined in this analysis, age, years of schooling and being in a high-risk group based on body mass index (BMI) were found to have the largest impact on health as measured by the HALex. Although this measure was developed to be combined with mortality data to form a quality-adjusted life year (QALY) for detecting changes in the health of the US population from 1990 to 2000, it may also be useful for inclusion in clinical studies, in particular as the national data are readily available for use as norms.

Health-related quality-of-life (HRQOL) measures are becoming increasingly important for evaluating the effectiveness of medical interventions and assessing the health of populations. Preference-based instruments, a subset of HRQOL measures, allow comparisons of overall health status in populations and in clinical settings, and are suitable for economic analyses; but validity studies have used selected samples, mostly examining morbidity. This study compared the performance of a preference-based instrument with self-rated health in predicting subsequent self-rated health, hospitalization, and mortality in a national cohort. A version of the Health Utility Index (HUI), constructed from questions in the 1982 to 1984 National Health and Examination Survey I Epidemiologic Follow-up Study (NHEFS), was used to develop scores for the 1982 to 1984 survey sample. The relationship between both the NHEFS-HUI and self-rated health in 1982 to 1984, and subsequent decline in self-rated health, hospitalizations, and mortality experienced by 1987 were examined using survival analyses. The analyses adjusted for sociodemographic variables (age, sex, race, education, and income), medical conditions, and smoking status reported at the 1982 to 1984 NHEFS interview. Results indicated that NHEFS-HUI and self-rated health scores were worse in older persons, persons with one or more medical conditions, African Americans, and those with less education and lower incomes. The effects of all 19 chronic conditions and smoking were reflected in lower self-rated health scores, whereas the NHEFS-HUI did not capture the effects of two of the conditions or smoking status. Both measures made independent contributions to predicting hospitalizations and mortality by 1987; in addition, the NHEFS-HUI predicted decline in subsequent self-rated health. The NHEFS-HUI also predicted health outcomes in the subgroup of those in initial excellent or very good self-rated health. A preference-based instrument demonstrated predictive validity in three relevant domains of health status outcomes across all sociodemographic groups examined in this cohort. Self-rated health was better able to capture concurrent decrements in health associated with certain chronic illnesses and smoking. It is concluded that preference-based measures capturing both functional status and health perceptions should be incorporated explicitly into national surveys to assess the health of populations.

In assessing quality of life, the most important goal is to develop a strategy that produces useable and useful information for decision making. Assessment design is complex, and whether an assessment is developed from scratch, or 1 or more portions of existing instruments are adapted, the focus must be on the quality of the theoretical and operational elements of the particular line of inquiry and its environment. The necessary and most often discussed focus on the theoretical dimensions of validity, reliability and responsiveness is not sufficient to insure that the data are of the requisite high quality. There is also a need, almost universally given little attention in the literature, to look at operational aspects, such as design, format, flow, appearance, and response-stimulus, of each assessment instrument. Searching for guidance in the quality-of-life (QOL) literature remains a challenge even with computers, modems, keywords, static guidebooks and bibliographic systems. The On-Line Guide to Quality-of-Life Assessments (OLGA) is presented as a personal computer-based system that is updated 3 times a year to provide QOL researchers and assessment developers with 2 databases: assessments providing full descriptions and contact information; and references providing fully keyed citations to the assessment use literature. These databases are made more useful by decision-logical programs that identify relevant assessments and supporting research literature. OLGA can thus save time and other resources by helping investigators concentrate on the most relevant elements of the existing literature. This focus will assist them in avoiding the problems of ending up with the right answers to the wrong questions.

This article is part of a series of manuscripts dealing with the incorporation of patient-reported outcomes (PROs) into clinical trials. The issues dealt with in this manuscript concern the common pitfalls to avoid in statistical analysis and interpretation of PROs. Specifically, the questions addressed by this manuscript involve the analysis pitfalls with PRO data in clinical trials and how can they be avoided (e.g.,missing data, multiplicity, null results etc.). The manuscript provides key literature for existing resources and proposes new guidelines.

This study examined the hypothesis that a single global item can be substituted for an index of a multi-item assessment and lead to equivalent interpretative outcomes. Substitutability would be demonstrated if: (1) the two measures were strongly correlated, and regression analysis showed that the same variables accounted for variation in each measure, and (2) difference scores between multi-item and global scores were close to zero and remained so as socio-demographic and co-morbid conditions varied. A multi-item assessment was constructed by mapping items from the NHANES I Epidemiologic Follow-up Study (NHEFS), using available data for persons with and without diabetes, onto the health-status classification system of the Health Utilities Index Mark 1 (HUI), creating the NHEFS-HUI. NHEFS-HUI data, when correlated to the self-assessed health status (SAHS) item, revealed a coefficient of 0.55. Regression analyses identified 9 of 14 variables contributed to the variability of each health status index, but differences existed in which variables were significant for which measure. Five of the possible 14 difference scores for persons with diabetes and non-diabetics approached zero. Persons with diabetes had lower NHEFS-HUI scores than non-diabetics. These data were considered insufficient for demonstrating substitutability. Suggestions were made on how optimal substitutability could be achieved.

Introduction In response to the increasing demand for high quality, affordable health care, policy makers are beginning to consider the burden of disease on patients and their families, as well as on society, more generally.– Within the continuum of cancer care, these concerns are often expressed in terms of health promotion and disease prevention initiatives, evaluations of alternative treatments or other interventions, and provision of compassionate care for survivors of cancer or those living with terminal illness. Traditionally, morbidity and mortality measures have been used for assessing disease and policy impacts, but as more people are living longer, many with chronic disease such as cancer, decision makers are recognizing the need for indicators that inform them not only about quantity of life but also about multiple aspects of quality of life such as physical, social, and mental well-being. Over the past 30 years, instruments have been developed that provide decision makers with profiles of scores that indicate people's capacity or performance on important domains and subdomains of health status and quality of life. Profiles, rather than a battery of single indicators, have the advantage of using a single scoring system so that domain scores can be easily compared, thereby giving clinicians and policy makers systematic information about well-being and function across the key domains. Generic profiles, such as the Sickness Impact Profile– and the short forms from the Medical Outcomes Study,– are used in demographically and diagnostically diverse populations, whereas general cancer measures, e.g., the European Organization for Research and Treatment of Cancer Core Quality of Life Questionnaire (EORTC QLQ-C30) and the Functional Assessment of Cancer Therapy (FACT-G), have been developed for use across the spectrum of cancer diagnoses.

WORKSHOP OBJECTIVE: The purpose of this workshop is to develop skills for evaluating alternative measurement strategies for assessing health outcomes and health-related quality of life in clinical trials and pharmacoeconomic studies. A key to having an assessment strategy that leads to meaningful results is the selection of instruments that measure domains of health-related quality of life that are relevant for the purpose of study and target population. We will present and discuss an approach for systematically evaluating questionnaires, rating scales and classification systems for use, singly or in combination, in different types of studies. PARTICIPANTS WHO WOULD BENEFIT: Pharmacoeconomic and health outcomes researchers who want to increase their understanding of the issues involved in selecting meaningful and responsive quality of life instruments for use in clinical trials and other evaluative studies. Health outcomes and quality-of-life assessment is becoming increasingly important in the evaluation of pharmaceutical products, in terms of labeling claims and product promotion as well as in terms of formulary decisions. Each of these applications requires an assessment strategy that provides information relevant for decision-making. How is a successful assessment strategy developed? What criteria, including reliability, validity and responsiveness, should be used when evaluating instruments for use in a clinical trial or pharmacoeconomic study? This workshop will address these questions and introduce an analytic framework that participants can apply in their daily experience.

Purpose: Women live longer than men but experience high morbidity during later years. We attempt to represent life expectancy with adjustments for quality of life for men and women in the United States. Data Sources: Survival estimates were obtained from Vital Statistics of the United States Life Tables. Quality-of-life data were obtained for 12,220 participants, aged 32–85 years, in the 1982–1984 National Health and Nutrition Examination Survey I Epidemiologic Follow-Up Study (NHEFS). Method: Using public data tapes, scores for the Health-Utilities Index (HUI) were imputed for NHEFS. These scores were calculated separately for men and women in the United States population and broken down by age. Using mortality data, the quality-adjusted life expectancy was calculated separately for men and women. Results: The current life expectancy among men aged 32 years was 39.45 years. For women aged 32 years it was 44.83 years, suggesting a 5.38 female life-expectancy advantage. The life expectancy, adjusted for quality of life, was 31.8 years for men versus 33.1 years for women. Adjustment for quality of life reduced the 5.38-year female advantage to 1.3 years. Conclusions: Although women enjoy longer life expectancies than do men, this advantage is reduced when quality adjustments are used. The finding reflects high levels of morbidity among older women.

This chapter is reproduced with permission from the book, Coronary Bypass Surgery in the Elderly: Ethical, Economical and Quality of Life Aspects, edited by Paul J. Walter, and published by Kluwer Academic Publishers. For further information on the book format see the advertisement appearing on page 37 of the July/August 1996 issue of AJGC.

Coronary artery bypass graft surgery is being performed with increasing frequency. Although fewer than 100,000 were done in 1980, the number of grafts performed in short-stay hospitals throughout the United States increased fourfold in the ensuing decade [1]. This rapid expansion suggests that not only is the procedure safer and more available but, also, that different types of patients are now being considered for surgery. One example of the expanding case mix is that the procedure is increasingly being performed among persons 65 years and older [2]. These older patients have been found to have the same functional and emotional benefits after undergoing coronary artery bypass surgery as do patients who are less than 65 years of age [3]. Walter and colleagues extended this analysis by examining persons 75 years and older; these researchers also found that age was not a significant factor in determining benefits gained from bypass surgery [4].

Health-care professionals from many specialties and disciplines are becoming increasingly aware that one of the major goals of medical care and technology is to improve patients’ quality of life. Enhancing quality of life is as important as other goals of health and medical care, such as preventing disease, effecting a cure, alleviating symptoms or pain, averting complications, providing humane care, and prolonging life.

The approach taken to assess quality of life depends on both the purpose of measurement and the characteristics of the population being assessed. Measurement strategies differ if the aim is to monitor the population’s level of health, investigate determinants of health, allocate resources or evaluate the impact of different treatment interventions. For either monitoring or epidemiological investigation, a measure that combines both mortality and morbidity, such as quality-adjusted life years, may be the most suitable measure. For resource allocation, measures that include trade-offs between different levels of health-related quality of life are needed. Clinical trials that follow persons over relatively short periods and require detailed information about changes in functioning attributable to the intervention being studied are more likely to require batteries or profiles of health-related quality of life assessments.

In populations where both tuberculosis and strong sensitization to nontuberculous mycobacteria are common, determining the proportion infected with M. tuberculosis is difficult. We skin tested 488 unvaccinated young Nigerian workers, typical of tropical populations having high prevalences of tuberculosis, with 4 low-dose Mantoux tests (PPD-RT-23, PPD-Tuberculin, PPD-Battey, and PPD-Gause) and with concentrated (2 mg/ml) PPD by the Heaf multiple-puncture method. Reactions (greater than or equal to 2 mm) to all 4 Mantoux sensitins (elicitins) unexpectedly were normal in distribution; however, the midpoint values (13 mm) of the RT-23 and PPD-T distributions were lower than the midpoints typically seen in groups of tuberculosis patients. Established methods for estimating the proportion tuberculous-infected (cutting point, dual-test, and curve-reconstruction) yielded a wide range, 32%-62%. Combining the 3 methods provided consistent estimates near 50%, despite interference due to strong sensitivity to PPD-B and especially to PPD-G in 80%-90%. PPD-T correlated well with RT-23 (r = .84), yet more closely resembled published PPD-S reaction distributions than did RT-23. All diagnostic-accuracy measures for the Heaf test, considering only grades 3 and 4 positive, exceeded 80%.

Objective To facilitate development and evaluation of a PRO instrument conceptual framework, we propose two tools—a PRO concept taxonomy and a PRO instrument hierarchy. FDA's draft guidance on patient reported outcome (PRO) measures states that a clear description of the conceptual framework of an instrument is useful for evaluating its adequacy to support a treatment benefit claim for use in product labeling the draft guidance, however does not propose tools for establishing or evaluationg a PRO instrument's conceptual framework. Methods We draw from our review of PRO concepts and instruments that appear in prescription drug labeling approved in the United States from 1997 to 2007. Results We propose taxonomy terms that define relationships between PRO concepts, including "family," "compound concept," and "singular concept." Based on the range of complexity represented by the concepts, as defined by the taxonomy, we propose nine instrument orders for PRO measurement. The nine orders range from individual event counts to multiitem, multiscale instruments. Conclusion This analysis of PRO concepts and instruments illustrates that the taxonomy and hierarchy are applicable to PRO concepts across a wide range of therapeutic areas and provide a basis for defining the instrument conceptual framework complexity. Although the utility of these tools in the drug development, review, and approval processes has not yet been demonstrated, these tools could be useful to improve communication and enhance efficiency in the instrument development and review process.