Definition of a Patient-Reported Outcome

A PRO is any measure of a patient’s health status that reflects how he/she functions, feels, or survives, as reported by the patient him/herself. Health-related quality of life (HRQoL) measures are one type of PRO that include “profiles” of functioning across several domains (e.g., respiratory symptoms, physical functioning, treatment burden). These instruments measure aspects of functioning that are known only to the patient, including his/her symptoms, behaviors, and daily functioning. PROs can be used for several purposes: (1) as primary or secondary outcomes in clinical trials of new medications and treatments (including behavioral interventions), (2) to characterize the course of the disease and its progression, (3) to assess the effects of a disease on multiple aspects of patient functioning, and (4) to develop individualized treatment plans.

To date, 27% of registered clinical trials include a PRO as either a primary or secondary endpoint. This has nearly doubled from 14% in 2009 and is expected to increase as new PROs are developed. This trend has been attributed to the movement toward collaborative care, as well as the complexities and burdens of treating and managing chronic conditions. In the period from 2006 to 2010, 17% of new drugs approved by the FDA used a PRO as a primary endpoint. In 2009, Aztreonam for Inhalation was approved on the basis of a PRO (Cystic Fibrosis Questionnaire-Revised Respiratory [CFQ-R] Symptom Scale). This was the first time a respiratory drug was approved using a PRO as the primary endpoint, highlighting the importance of the patient’s perspective.

Development and Utilization of Patient-Reported Outcomes

To utilize a PRO in a drug registration trial, it must be developed using patient and stakeholder input and meet strict psychometric criteria (e.g., reliability, validity, responsivity). A conceptual framework links the relevant concepts identified by qualitative data to the label claim (e.g., improvement in respiratory symptoms). This claim must also be hypothesized and tested, followed by calculation of several types of reliability and validity ( Table 13.1 ). PROs must be sensitive to change on both an individual and group level.

To interpret the magnitude of this change, several qualitative and statistical methods have been developed. The minimal important difference (MID) score establishes the smallest, clinically meaningful, change that a patient can reliably detect. The MID can be established using a visual analog scale, which asks the patient to indicate the amount of change he/she has experienced (i.e., anchor-based method). The MID can also be determined using statistical methods, such as calculation of standard deviation (SD) of change or 1 standard error of measurement. These analyses are bolstered by triangulating these values to establish the MID for a particular scale. A new term, the clinically important difference (CID), can also be used to identify clinically relevant changes in scores between two treatment groups. This should be followed by a response distribution curve mapping individual changes for the two groups; ideally, there should be maximal separation between these curves.

Health-Related Quality of Life Measures

HRQoL measures are one of the most frequently used types of PROs first characterized by the World Health Organization’s 1946 definition of health, which was “a state of complete physical, mental, and social well-being, and not merely the absence of disease or infirmity.” HRQoL measures are multidimensional, profile instruments focusing on several aspects of daily functioning. Typically, HRQoL measures evaluate four core domains: (1) disease state and physical symptoms, (2) functional status (e.g., performing daily activities), (3) psychological and emotional functioning, and (4) social functioning. Patient’s scores are likely to differ across different domains of functioning and, thus, a total score should not be calculated. HRQoL instruments can track the natural progression of a disease, evaluate responsivity to pharmacological or behavioral interventions, and facilitate shared medical decision-making. For example, if a patient starts a new treatment for asthma, an HRQoL measure can assess its effectiveness in reducing asthma symptoms, such as wheezing. The tool can also be used to evaluate whether this new treatment is burdensome if this domain is measured.

HRQoL instruments can be either generic or disease-specific. Generic measures are composed of general items that are relevant to populations with and without a chronic illness. Examples include the Pediatric Quality of Life Inventory, the Child Health and Illness Profile, and the Youth Quality of Life Instrument. Generic HRQoL measures can be utilized across patient populations to compare the impact of a disease on different patient groups or to perform cost utility analyses (e.g., EuroQol-Five Dimensions Questionnaire [EQ-5D]). However, these measures are not specific to the symptoms experienced by patients with a particular illness; therefore, they are less sensitive to their effects on daily functioning and are not acceptable to test the efficacy of new medications.

In contrast, disease-specific instruments are designed to assess the unique symptoms and challenges of a particular patient population. For example, a hallmark symptom of cystic fibrosis (CF) is excess mucus production. This symptom would not appear on a generic measure or one focused on a different respiratory condition, such as asthma. Thus, inclusion of items that are most relevant to a specific condition leads to greater sensitivity to treatment effects and is more informative for clinical care. This is the rationale for using disease-specific instruments for the purposes of drug registration trials.

Developmental Considerations

Developing HRQoL measures for children poses unique challenges, ranging from differences in reading ability to the shifting importance of peers, school, and parents over the course of development. Comprehension and the ability to respond to items require several cognitive skills, such as focused attention, receptive and expressive language, and a conceptual understanding of the illness. All of these skills emerge gradually and at different points across development. Furthermore, the relevance and importance of a given domain is likely to change over the course of childhood and adolescence. For example, social functioning is integral to adolescents’ overall quality of life but is less relevant for preschoolers. Thus measures created within a developmental age group are more valid than measures downwardly extended from adult instruments. This ensures that the most relevant areas of functioning are measured in a developmentally appropriate way for a particular age group.

HRQoL measures for children must undergo rigorous testing to ensure that individuals in the target age understand the vocabulary and concepts contained in the questionnaire. Research shows that children between 2 and 6 years have a more limited understanding of medical terms and concepts. Children in this age group are able to report on observable areas of health, such as symptoms and levels of pain, using a pictorial format. They may, however, have more difficulty reporting on their emotional and social functioning. By school age, children demonstrate a better understanding of the interplay between their health status and daily functioning. In fact, several studies have found that school-age children are able to provide reliable reports of their symptoms and functioning.

Changes in cognitive and attentional capacity across development underscore the importance of response options and mode of administration when eliciting information from children. PROs can be administered electronically (computer, tablet), accompanied by colorful, animated pictures to increase understanding and attention. Alternatively, to reduce errors based on reading difficulties and distractibility, measures can be administered to young children by an interviewer. For preschoolers, the CFQ-R Preschool version is administered by an interviewer using pictures to represent the items and rating scale options. In addition, because young children tend to select response options at endpoints rather than using the full range of responses, a forced choice format is a useful alternative. Research shows that children as young as 3 years old can make forced choices. To make it more interactional and rewarding, we also use concrete rewards, such as stickers, to maintain their focus ( Fig. 13.1 ).

(A–D) Example of CFQ-R response choices for the preschool version. The interviewer asks “Do you cough up mucus or phlegm or spit?” Children are asked to first choose between the extreme choices (1 and 4) and then to discriminate between the extreme and less extreme choice (e.g., 1 and 2, “Do you think you cough up very, very much phlegm, or a bit of phlegm?”).

Use of Proxy-Respondents

Parents or other caregivers can also complete HRQoL measures for young children to provide a different perspective. Parent reports tend to correlate better with child reports for observable phenomena, such as physical functioning and symptom frequency (e.g., climbing stairs, coughing), but more poorly for emotional and social functioning (e.g., sadness). Findings have suggested that children endorse more emotional distress, somatic complaints, and physical difficulties than their parents. Thus, proxy measures cannot typically be substituted for patient reports. However, proxy respondents may be particularly useful for infants, patients with severe disease, or those with significant cognitive limitations. In addition, differences between respondents may inform the focus of a clinic visit, medical decision-making, and health care utilization. Although proxy measures for health care providers have been developed, their validity is limited, because providers spend less time with their patients and observe them across fewer contexts.

Clinical Utility

Use of HRQoL measures in routine practice facilitates systematic, efficient collection of information about patients’ ratings of their daily functioning. These data serve several purposes: (1) promoting communication between the patient and provider, (2) identifying frequently overlooked problems (e.g., school functioning), (3) monitoring disease progression and treatment burden, and (4) tailoring interventions to key aspects of a patient’s daily life. Thus both quality of life and health outcomes may improve as a result of integrating information from these instruments into routine care. Enhanced communication and monitoring symptoms are the best established benefits of this integration.

First, HRQoL measures can provide a systematic way to facilitate discussions between patients and providers. Depending on the patient, he/she may report some symptoms (i.e., frequent cough), but disclose others only when directly asked (e.g., fatigue or absences from school or work). Research shows that both patients and physicians find these assessments helpful in identifying patient concerns, which has important implications for health outcomes. Numerous studies have found that discussions of both physical and psychosocial issues during medical visits lead to improved treatment adherence, higher patient satisfaction, and fewer symptoms.

A second benefit is the identification of frequently overlooked symptoms and problems that are important to the patient (e.g., depression, treatment burden). This is particularly critical in the management of chronic respiratory diseases, because multiple domains of functioning are affected typically and treatment regimens are both time- and energy-intensive. For example, patients with CF may spend 2 to 4 hours each day completing prescribed treatments, leading to social isolation and depression. In addition, physiological measures, such as lung function and nutritional status, correlate modestly with HRQoL measures that assess symptom frequency, physical functioning, daily activities, or emotional functioning. Thus, HRQoL data may alert providers to these critical issues, which are not captured by traditional medical assessments. Note that most of this research has been conducted with adults, highlighting a need for research in pediatric populations.

When given at regular intervals, HRQoL measures can monitor disease course, both in terms of natural progression and response to drug or behavioral interventions. Monitoring disease progression can lead to early identification of new concerns (e.g., weight loss) or ongoing challenges (e.g., increased fatigue). In addition, HRQoL assessment can measure the patient’s responsivity to a new treatment. Because these instruments are multidimensional, they allow for differentiation of the benefits of a new medication (e.g., improvement in respiratory symptoms) from its side effects (e.g., increased treatment burden). It is also possible that patients with the same lung function score may report very different levels of functioning in physical, social, or emotional domains.

HRQoL feedback can be used by providers to inform their treatment decisions and ensure that they are patient-centered, considering the individual’s perceptions of their treatments, how they affect daily functioning, and their priorities. HRQoL feedback has been shown to impact clinical decision-making in CF patients listed for lung transplant, arthritis, epilepsy, and cancer. Furthermore, if data are collected systematically on HRQoL instruments and included in national and international registries, trends identified in these data can be used to (1) predict health outcomes for individuals (e.g., lung function decline, number of exacerbations), (2) predict an individual’s response to a new treatment, (3) conduct comparative effectiveness studies of similar medications (e.g., inhaled antibiotics), and (4) identify which treatments are most likely to maximize benefits and minimize costs.

Studies testing the feasibility of integrating HRQoL and physiologic measures in routine care for respiratory disorders are just beginning but demonstrate considerable promise. For example, adult patients with CF are using home spirometers that are linked to their pulmonary center along with daily symptom diaries. Utilizing HRQoL and medical measures together may allow the CF team to identify early signs of an exacerbation, prompting a prescription for antibiotics or a visit to the clinic. A study by Santana and colleagues demonstrated that administration of HRQoL measures was feasible in a lung transplant clinic and did not prolong clinic visits. Results also demonstrated improved communication between patients and health care providers and better patient management (e.g., medication changes). Furthermore, preliminary findings in pediatric and adult asthma clinics indicated that patients and providers were satisfied with implementation of an electronic quality of life (e-QOL) questionnaire about asthma during their routine visits. The feasibility of routine assessment of quality of life is improving given technological advances (e.g., web- and computer-based applications) that increase the efficiency of measure completion and scoring.

Summary

In summary, as the medical community transitions toward a patient-centered model of care, PROs will become a central mechanism for improving patient-provider communication, measuring health outcomes in chronic respiratory conditions, obtaining regulatory approval for new medications, and informing clinical decision-making. To move the field forward, we need to develop and utilize HRQoL instruments that are disease-specific and demonstrate good psychometric properties (e.g., reliability, validity). The following section reviews the strengths and limitations of disease-specific HRQoL measures for several pediatric respiratory disorders (i.e., aerodigestive disorders, asthma, bronchopulmonary dysplasia, CF, primary ciliary dyskinesia, and sleep apnea). Based on this information, we have recommended the best instrument for each condition.

Review of Disease-Specific Respiratory Health-Related Quality of Life Measures

Asthma

There are currently 13 disease-specific HRQoL measures for children with asthma. While most of these measures demonstrate good internal consistency and test-retest reliability, they vary in their clinical utility and responsiveness to change ( Table 13.3 ). Specifically, only the pediatric asthma quality of life questionnaire (PAQLQ) has an established MID, enhancing its clinical utility in assessing meaningful change to pharmacological or behavioral interventions. These measures vary with respect to informant type, age range, and practical utility (e.g., language translations, respondent burden). While several measures have corresponding child and parent versions, few include self-report versions for children under 5. Translations into multiple languages exist for three measures (childhood asthma questionnaires [CAQ], DISABKIDS-Asthma Module, and PAQLQ).

Table 13.3

Health-Related Quality of Life Measures for Children With Asthma

Measure	Number of Items and Domains	Age Range and Respondent	Psychometrics: Reliability	Psychometrics: Validity
ASTHMA
AMA	Number of items = 55 Domains: Total score only	6–12 years Child No parent version	α = .93 Test-retest = .57	▪ Moderately correlates with the PAQLQ ▪ Responsive to a week-long asthma day camp
AAQOL	Number of items = 32 Domains (6): Symptoms, medication, physical activities, emotion, social interaction, and positive effects	12–17 years Child No parent version	α = .70–.93 Test-retest = .76–.90	▪ High correlation with PAQLQ (r = .81) ▪ Weak to moderate correlation with patient-rated symptom severity, number of hospitalizations, severity of coughing, and severity of wheezing (r’s = .25–.65)
ARQOLS	Number of items = 35 Domains (5): Restriction of social life, physical disturbances, limitations in physical activity, daily inconveniences in managing the disease, and emotional distress	6–13 years Child No parent version	α = .81–.96	▪ Responsive to pharmacological intervention
CAQ	CAQ-A—Number of items=14 Domains (2): QOL and distress CAQ-B—Number of items=22 Domains (4): Active QOL, passive QOL, severity, and distress CAQ-C—Number of items=31 Domains (5): Active QOL, passive QOL, severity, distress, and reactivity	4–7 years Child (CAQ-A) 8–11 years Child (CAQ-B) 12–16 years Child (CAQ-C) No parent version	α = .60–.63 (CAQ-A) α = .57–.84 (CAQ-B) α = .50–.80 (CAQ-C) Test-retest (Pearson Coefficient) = .59–.63 (CAQ-A); .73–.75 (CAQ-B); .73–.84 (CAQ-C) Test-retest (ICC) = .59–.63 (CAQ-A); .72–.75 (CAQ-B); .68–.84 (CAQ-C)	▪ Discriminates between asthmatic and nonasthmatic children ▪ Correlates with parent ratings of asthma severity
CHSA	Child Version—Number of items = 25 Domains (3): Physical health, child activities, and emotional health Parent Version—Number of items = 48 Domains (5): Physical health, activity (child), activity (family), emotional health (child), and emotional health (family)	7–16 years Child 5–12 years Parent	α = .74–.81 (child) Test-retest = .88–.91 α = .81–.92 (parent) Test-retest = .60–.85 No cross-informant reliability reported	▪ Correlates with parent reports of their children’s health status, and treatment burden as measured by the Asthma Symptom Day-14 (ASD-14) ▪ Parent version correlates with disease severity as measured by symptom activity (e.g., number of days wheezing, coughing, tightness of chest) and medication use (e.g., number of times child used inhaler, nebulizer, bronchodilator)
DISABKIDS—Asthma Module	Number of items = 37 Generic domains (6): Medication, emotion, social inclusion, social exclusion, limitation, and treatment Number of items = 11 Asthma-specific domains (2): Impact (consists of limitations and symptoms) and worry	“Smileys” version for children ages 4–7 years child 8–14 years child	α = .86–.92 (generic) α = .83–.84 (asthma module) Test-retest = .42–.53	▪ Correlates with symptoms (cough), frequency of doctor visits, and use of inhaled medications ▪ Discriminates between levels of disease severity ▪ Linked to International Classification of Functioning, Health and Disability (ICF)
HAY	Number of items = 32 Generic Domains (4): Physical activities, cognitive activities, social activities, and physical complaints Number of items = 40 Asthma-Specific Domains (4): Asthma symptoms, emotions related to asthma, self-concept, and self-management	8–12 years Child No parent version	α = .71–.83 (generic) α = .61–.81 (asthma module) Test-retest = within-subject SD for differences between first and second measurement differed significantly on “self-management,” “physical activities,” and “social activities”	▪ Discriminates between healthy and asthmatic children in terms of physical and social activities ▪ Correlates with the Child Attitude Toward Illness Scale ▪ Responsive to illness severity over time
ITG-CASF	Number of items = 8 Domains (3): Daytime symptoms, nighttime symptoms, & functional limitations	2–17 years Parent only	α = .84–.92 No test-retest reliability reported	▪ Correlates with asthma severity ( P = .002), dyspnea ( P = .03), and emergency room visits ▪ Correlates with the number of days of school missed or limited activities for the child (r = −.45) and parent (r = −.25) ▪ Responsive to illness severity over time
LAQ	Number of items = 71 Domains (7): Physical, work, outdoor, emotions and emotional behavior, home care, eating and drinking, and miscellaneous	5–17 years Child No parent version	α = .97 Test-retest = .76	▪ Not reported
a PAQLQ	Number of items = 23 Domains (3): Activity limitations, symptoms, and emotional function	7–17 years Child Pictorial version for ages 5–7 in development	Test-retest (ICC) = .84–.95 Cross informant r = .61 No internal consistency reported	▪ Discriminates between levels of disease severity ▪ Established MID (0.5 on a 7 point scale) ▪ Converges with issues from asthma focus groups conducted by independent investigators ▪ Responsive to pharmacological and behavioral interventions ▪ Used in clinical trials
a Pediatric Asthma Caregiver’s Quality of Life Questionnaire	Number of items = 13 Domains (2): Activity limitations and emotional function	7–17 years Parent	Test-retest (ICC) = .80–.85 No internal consistency or cross-informant reliability reported	▪ Discriminates between levels of disease severity ▪ Established MID (0.5 on a 7-point scale) ▪ Responsive to pharmacological intervention ▪ Used in clinical trials
PedsQL-Asthma Module	Number of items = 23 Generic Domains (4): Physical functioning, emotional functioning, social functioning, school functioning Number of items = 28 Asthma-Specific Domains (4): Asthma symptoms, treatment problems, worry, communication	5–18 years Child 2–18 years Parent	α = .74–.90 (child) α = .77–.91 (parent) α = .58–.85 (child) α = .82–.91 (parent) Parent-Child agreement (ICC) = .29–.87 No test-retest reliability reported	▪ Discriminates between healthy children and children with asthma ▪ Correlates with the PAQLQ ▪ Responsive to an evidence-based asthma management intervention (N = 10)
TACQOL-Asthma	Number of items = 68 Domains (5): Complaints (spontaneous asthma symptoms), situations (that provoke symptoms), treatment (visits to doctors), medication (use of), and emotions (negative emotions)	8–16 years Child Parent	α = .60–.85 (child) α = .64–.82 (parent) Parent-Child agreement (ICC) = .64–.76 No test-retest reliability reported	▪ Discriminates between levels of disease severity, except in the complaint domain ▪ Responsive to a behavioral intervention to promote medication adherence ▪ Correlates with the PAQLQ

Only gold members can continue reading. Log In or Register to continue

Share this:

• Click to share on Twitter (Opens in new window)
• Click to share on Facebook (Opens in new window)

Related

Related posts:

1. Bronchopulmonary Dysplasia
2. The Pulmonary Mycoses
3. Lung Injury Caused by Pharmacologic Agents
4. Pediatric Lung Transplantation

Stay updated, free articles. Join our Telegram channel

Join