Purpose: To evaluate two generic and two disease-specific measures of health-related quality of life (QOL) using prerandomization data from the National Emphysema Treatment Trial (NETT).
Method: The analyses used data collected from the 1,218 subjects who were randomized in the NETT. Patients completed evaluations before and after completion of the prerandomization phase of the NETT pulmonary rehabilitation program. Using data obtained prior to participation in the rehabilitation program, QOL measures were evaluated against physiologic and functional criteria using correlational analysis. The physiologic criteria included estimates of emphysema severity based on FEV1 and measures of Pao2 obtained with the subject at rest and breathing room air. Functional measures included the 6-min walk distance (6MWD), maximum work, and hospitalizations in the prior 3 months.
Results: Correlation coefficients between QOL measures ranged from −0.31 to 0.70. In comparison to normative samples, scores on general QOL measures were low, suggesting that the NETT participants were quite ill. All QOL measures were modestly but significantly correlated with FEV1, maximum work, and 6MWD. Patients who had stayed overnight in a hospital in the prior 3 months reported lower QOL on average than those who had not been hospitalized. There were significant improvements for all QOL measures following the rehabilitation program, and improvements in QOL were correlated with improvements in 6MWD.
Comment: The disease-specific and general QOL measures used in the NETT were correlated. Analyses suggested that these measures improved significantly following the rehabilitation phase of the NETT.
The National Emphysema Treatment Trial (NETT) is a multicenter randomized clinical trial that is designed to compare lung volume reduction surgery (LVRS) to medical therapy.1 Subjects with moderate-to-severe emphysema were randomly assigned to usual medical therapy alone or to usual medical therapy plus LVRS. All patients in the trial participated in pulmonary rehabilitation prior to randomization.
Although the primary outcome measures in the NETT are survival and maximum exercise capacity, quality of life (QOL) was chosen as an important secondary outcome. QOL measures have become common in major clinical trials. A recent PUBMED review identified > 140 articles under the headings “Quality of Life” and “COPD,” and > 20 articles under the headings “Quality of Life” and “LVRS.” Several studies2–7 have suggested that there are improvements in patient QOL following LVRS. Despite the interest in QOL as an outcome in COPD clinical studies, there is still uncertainty about the optimum methods of measurement. The NETT used both disease-specific and general QOL measures. The disease-specific measures were chosen because of their direct relevance to patients with lung disease. Many authors think that these measures are necessary because they are sensitive to the effects of interventions such as pulmonary rehabilitation.8General measures were included because they can capture unanticipated side effects and benefits of treatment,9and because they are necessary for cost/utility analysis.10However, general measures may be less responsive to the lung disease-specific effects of interventions and may be less meaningful to clinicians.11 Few studies have evaluated the properties of general and disease-specific measures for patients with advanced lung disease.
The purpose of this report is to evaluate four different measures of health-related QOL used in the NETT. The measures are the self-administered version of the quality-of-well-being scale (QWB-SA),12the medical outcomes study 36-item short form (SF-36),13–14 the St. George Respiratory Questionnaire (SGRQ),15and the University of California, San Diego, shortness-of-breath questionnaire (SOBQ).16 The NETT offers a unique opportunity to evaluate the functioning of these questionnaires, because patients with emphysema were evaluated using a large number of physiologic and clinical measures close to the time when the QOL measures were obtained. The results reported here were obtained prior to randomization.
The subjects were 746 men and 472 women who volunteered for the NETT. The average age of the participants was 67 years. Nearly 95% of the participants were white, and 3.4% were African-American. Participants came from all 17 NETT sites. The inclusion criteria included the following: (1) radiographic evidence of bilateral emphysema; (2) studies demonstrating severe airflow obstruction and hyperinflation; and (3) completion of a prerandomization pulmonary rehabilitation program. Exclusion criteria were formulated with the goal of excluding emphysema patients with certain characteristics, as follows: (1) characteristics that placed patients at high risk for perioperative morbidity and/or mortality; (2) emphysema that was thought to be unsuitable for LVRS; and (3) medical conditions or other circumstances that made it likely that the patient would be unable to complete the trial. The exclusionary criteria relating to cardiologic issues were based on the work of Goldman et al.17 A more detailed description of the NETT methodology is available elsewhere.1
In selecting measures for the NETT, it was decided to rely on questionnaires that could be self-administered by patients in a relatively short period of time. This was done for the following reasons: (1) to maximize data collection on the greatest number of patients, including those who were unable or unwilling to return for scheduled follow-up visits; (2) to minimize the time and effort required for questionnaire administration during follow-up visits, given the complexity and overall time required for the assessments; and (3) to allow for multiple questionnaires to be used.
For the general measures, the SF-36 and QWB-SA were selected. These have been widely used in health services research and can be self-completed by patients. For the disease-specific measures, the SGRQ15was selected because it can be completed easily by patients, and does not require structured and supervised administration. The SGRQ had been used successfully by several NETT centers. The SOBQ also was chosen because it can be completed easily by the patients, and because it provides information about breathlessness with various ADLs that can be helpful in the clinical evaluation and management of the rehabilitation program. It has been used successfully in research studies in pulmonary rehabilitation. In a study16 comparing several strategies for measuring dyspnea in patients with COPD, it proved to be as valid and reliable as the baseline dyspnea index or the transition dyspnea index.
In a pilot test prior to their use with NETT patients, the four questionnaires (ie, SF-36, QWB-SA, SGRQ, and SOBQ) were self-administered to a group of patients who were similar to those eligible for the NETT. All four questionnaires were completed in an average time of < 30 min (maximum, 40 min) on the first administration with minimal instructions.
The SF-36 is a 36-item general health status assessment questionnaire.13 The SF-36 has nine separate scales, including the following: (1) physical functioning; (2) social functioning; (3) role limitations (physical); (4) role limitations (emotional); (5) emotional well-being; (6) energy/fatigue; (7) pain; (8) general health perceptions; and (9) current general health perceptions compared to 1 year ago. Data from the ninth scale are typically not reported and were excluded from these analyses. There are substantial reliability and validity data for the SF-36,13–14,18–19 and the measure is perhaps the most common outcome-assessment instrument in use in contemporary health services research. SF-36 scores are reported as either raw scores or standardized T-scores. In this article, we report raw scores. Higher scores indicate better health status. The SF-36 has been factor-analyzed and reduced to two summary scores.18 The physical component score (PCS) represents the four physical health scales (ie, physical functioning, role physical, bodily pain, and general health perceptions), while the mental component score (MCS) reflects the four mental health scales (ie, mental health, role emotional, vitality, and social functioning). We used both summary scores (PCS and MCS) and individual scale scores in our analysis.
The QWB-SA is a comprehensive measure of health-related QOL that includes the following five sections: acute symptoms; chronic symptoms; self-care; mobility; and social activity.9,20–22 The observed level of function and the subjective symptomatic complaints are weighted by preference, or the utility for the state, on a scale ranging from 0 (for dead) to 1.0 (for optimum function). The QWB-SA has been used in a wide variety of clinical and population studies21–24 to evaluate therapeutic interventions in patients with a range of medical and surgical conditions. The average total daily score was analyzed in this report.
The SGRQ is a self-administered, standardized, 50-item instrument with three separate scales (ie, symptoms, activity, and impacts on daily life). A total score also can be calculated from the three component scores and is analyzed here. Specific questions carry varying weights. Lower scores on the SGRQ indicate wellness, while higher scores suggest greater disability. The questionnaire has been evaluated for reliability and validity in several studies of patients with chronic lung disease of varying severity, particularly COPD and asthma.15
The SOBQ is self-administered and asks subjects to rate their breathlessness for 21 various daily activities (plus 3 overall items) on a 6-point scale from none at all (0) to severe (4) to maximal or unable to do because of breathlessness (5).16 The 21 activities of daily living (ADLs) can be grouped according to factor analysis into the following four categories: rest and light ADLs (factor 1), eight questions; moderate ADLs (factor 2), five questions; walking (factor 3), four questions; and strenuous ADLs (factor 4), four questions. In this analysis, we focus on the total score.
Pulmonary function and gas exchange were assessed with spirometry, plethysmographic determination of the functional residual capacity, the single-breath diffusing capacity of the lung for carbon monoxide (Dlco) [only at the prerehabilitation evaluation], room air arterial blood gas levels measured with the patient at rest, and the maximal inspiratory and expiratory mouth pressures.1
All subjects participated in the prerandomization program, consisting of a pulmonary rehabilitation program composed of at least 16 to 20 sessions over > 6 to 10 weeks that was supervised by a NETT clinical center. Portions of the program could be carried out at a NETT-certified rehabilitation facility closer to the participant’s home. Over 400 satellite centers participated in the study.
Components of the pulmonary rehabilitation program included the following: (1) a comprehensive evaluation of medical, psychosocial, and nutritional needs; (2) the setting of goals for education and exercise training; (3) exercise training (ie, lower extremity, flexibility, strengthening, and upper extremity); (4) education about emphysema, medical treatments, and the NETT; (5) psychosocial counseling; and (6) nutritional counseling.
The data were analyzed using standard descriptive methods to estimate means and SDs and Pearson product moment correlations. The t test was used to compare the QOL measures for participants who had not been hospitalized in the 3 months prior to the assessment (1,039 patients) with those who had been in the hospital for ≥ 1 day (179 patients). To compare the relative performance of QOL measures in relation to the physiologic criteria, we compared the strength of the correlations. Because there were so many correlations for which pairwise comparisons of significance could be done, we used the Fisher r-to-Z transformation to calculate a range of values that would reach significance for the differences between any two correlations, given the minimum sample size. Using 1,218 patients as the sample size for the Fisher r-to-Z transformation to be conservative, we found a confidence interval of ± 0.06 for correlations in a range of differences between correlations of 0.20 to 0.40. More specifically, a correlation of 0.30 between a QOL and a physiologic measure for this sample size would be significantly different from a correlation measurement of < 0.24 or > 0.36. In addition, QOL scores obtained prior to and following rehabilitation were compared by t tests. Effect size for the prerehabilitation-to-postrehabilitation change was estimated by dividing the mean change by the SD of the change. A statistical software package (SPSS, version 10.0 for Macintosh; SPSS; Chicago, IL) was used to complete the calculations.
summarizes the characteristics of the patients prior to completion of the NETT prerandomization rehabilitation program. Following these evaluations, all participants completed 6 to 10 weeks of comprehensive pulmonary rehabilitation. A second assessment was completed within 3 weeks prior to randomization. QOL measures were completed during the clinic visit prior to the initiation of rehabilitation, but could be completed at home following the completion of rehabilitation and returned to the clinic by mail for the second assessment.
The correlations among the QOL measures are shown in Table 2
. The SF-36 MCS and PCS scores were originally derived from factor analysis, and were expected to be uncorrelated. With this exception, all other correlations in Table 2 are statistically significant, with values ranging from −0.31 to 0.70. Some of the correlations in Table 2 are negative. This occurs because good health on the SOBQ and SGRQ is associated with lower scores, while better health is associated with higher scores for the SF-36 and QWB-SA. Figure 1
places the means for the general QOL measures in context by showing the mean scores in relation to normative populations matched for age and gender. QWB-SA scores were multiplied by 100 to place them on approximately the same scale as the SF-36. For the QWB-SA and the SF-36 scales, the normative sample was older adults selected from the general population in Beaver Dam, WI.25 Patients in the Beaver Dam sample had a mean age of 64.1 years. Since the Beaver Dam sample did not include PCS and MCS scores, we compared the NETT participants against general population norms for the US population in the age category 55 to 64 years, as reported by Ware.13 These summary measures suggest that the participants in the NETT were quite ill. With the exception of SF-36 scores for bodily pain, all other measures show NETT participants to be well below the population norms. Considering the SF-36 summary scores, NETT patients had significant deficits as evaluated by Z tests (in relation to population norms26) on the PCS (p < 0.01) but were comparable to those of the normative population.
Correlations between the QOL measures and physiologic parameters are shown in Table 3
. Maximum work was significantly correlated (p < 0.001) with each QOL measure. FEV1 was correlated with each QOL measure using at least a p < 0.05 criterion. In every case evaluated, the SOBQ was more highly correlated with the physiologic measures than with the other health-related QOL measures. Although statistically significant, the correlations among pulmonary function measures (ie, FEV1 and FVC) and QOL measures (ie, MCS and QWB-SA) tended to be low. The relationships were slightly stronger among FEV1, FVC, and the disease-specific SOBQ. For example, the correlation between SOBQ and FVC was −0.18, and the correlation between SOBQ and FEV1 was −0.23. Using confidence intervals from the Fisher r-to-Z transformation, the correlations between disease-specific QOL measures and physiologic parameters were determined to be significantly higher than those between general QOL measures and physiologic parameters. The only nonsignificant relationships shown in Table 3 are between PCS with FVC and PCS with Dlco. The disease-specific and generic QOL measures were moderately correlated with one another (Table 2).
Although the range of hospital days for the 3 months prior to study enrollment was 0 through 44, most participants (1,039 patients) had not been hospitalized. The t tests comparing QOL for those who had been hospitalized and for those who had not showed a significant difference for the PCS and MCS components of the SF-36, the QWB-SA, the disease-specific SGRQ total score, and the SOBQ. For all comparisons, differences were statistically significant at the 0.001 level (Table 4
). Effect size was calculated by dividing the difference between those who had been hospitalized and those who had not been in the hospital by the SD of those who had been hospitalized. The observed effect size ranged from 0.28 (for the SF-36 PCS) to 0.46 (for the SGRQ). In detecting the effect of hospitalization, the disease-specific measures performed only slightly better than the generic measures.
The prerehabilitation-to-postrehabilitation changes showed significant improvements on all QOL measures (Table 5
). The largest effect size was observed for the SGRQ followed by the generic QWB-SA. Overall, the effect sizes were comparable across the measures. The correlations among the changes in QOL measures and the change in the 6-min walk distance (6MWD) from baseline to the completion of rehabilitation are shown in Table 6
. Although the magnitude of the correlations is small, all relationships were statistically significant. The correlations were slightly, but nonsignificantly, higher for the disease-specific measures. Prior to rehabilitation, the mean FEV1 value obtained before bronchodilator therapy was 0.68 ± 0.22 L. FEV1 improved slightly (1,215 codes in the analysis) following rehabilitation (mean, 0.69 ± 0.22 L; p = 0.04). Although this difference was statistically significant, it was very small (ie, < 0.007 L).
There are very few published studies that have evaluated QOL measures for patients with advanced lung disease. Similarly, there are limited data on the impact of interventions on various lung-related QOL parameters. The NETT has provided the opportunity to study a large number of emphysema patients in a detailed manner. Disease-specific and general measures were included to elucidate any possible effect of surgery and pulmonary rehabilitation.
The disease-specific and general QOL measures used in the NETT are modestly correlated. These findings confirm those of previous reports27identifying relationships among QOL measures. Preliminary evidence from the NETT has suggested that QOL measures improve following pulmonary rehabilitation. Although the QOL changes following rehabilitation were small, they may be clinically meaningful. A change in the QWB-SA of 0.04 U, for example, if maintained for 1 year, would produce the equivalent of about 1 year of life for every 25 patients treated. Although some studies28have failed to find changes in QOL measures following rehabilitation, other studies29–30 have confirmed improvements in QOL measures following pulmonary rehabilitation. The generic measures used in this study had low, but statistically significant, correlations with physiologic and functional measures. Other studies31 have shown that disease-specific measures are more highly correlated with FEV1. In terms of responsiveness to clinical change, the disease-specific measures performed only slightly better than the generic measures.
This analysis confirms the findings of previous studies32 suggesting that there are QOL benefits for pulmonary rehabilitation. In the NETT study, FEV1 changed only very slightly during the rehabilitation phase (about 0.01 L). The results are also consistent with studies that have failed to show changes in pulmonary function measures following rehabilitation,28 and with studies that have found low, but statistically significant, correlations between QOL and physiologic measures.33
Although the QOL measures in the NETT were modestly correlated with one another, each has a specific purpose. Disease-specific measures, such as the SOBQ and SGRQ, may be more sensitive to clinical improvement following pulmonary rehabilitation. However, evidence from the NETT indicates that general measures also detect significant clinical change following rehabilitation. Thus, we did not find clear evidence that disease-specific measures were significantly more responsive to clinical change. General measures have some advantages because they allow comparisons with other benchmarks. For example, the impact of COPD can be compared with the impact of other chronic diseases. Patients in the NETT, for example, had lower QWB scores than patients in other clinical trials of rehabilitation. NETT patients were comparable to patients with macular degeneration in terms of QOL.34 Their QOL was higher than patients with Alzheimer disease.21 These comparisons cannot be made with disease-specific measures. Further, utility-based QOL measures are required for analyzing the cost-effectiveness of complex treatments.35 Because a utility-based measure was used in the NETT, it was possible to show that LVRS produces a quality-adjusted life-year for $190,000, when considered at 3 years, and $98,000 for a subgroup with predominantly upper lobe emphysema and lower exercise capacity at baseline.10,36 These results contributed to the Centers for Medicare and Medicaid Services decision to reimburse selected centers for LVRS. Finally, generic measures may capture unanticipated negative consequences of treatment.
In summary, the NETT offers an unusual opportunity to evaluate outcomes for patients with COPD. Evidence from the prerandomization phase of the trial suggests that the measurement of QOL is feasible, and that generic and disease-specific measures are associated with each other and with clinical changes following pulmonary rehabilitation. Furthermore, there are modest associations among QOL measures and measures of disease severity such as FEV1 and 6MWD. We concluded that QOL measures are meaningful indicators of outcome in clinical trials for patients with COPD. Disease-specific measures may be slightly more sensitive to clinical change, although the responsiveness of the generic measures was comparable in these analyses. On the basis of these evaluations, we recommend either the SGRQ or the SOBQ as COPD-specific outcome measures. The SF-36 is the preferred generic measure for studies requiring a profile of health outcomes, while the QWB-SA is recommended for studies considering companion cost-effectiveness.
Members of the NETT Research Group
Office of the Chair of the Steering Committee, University of Pennsylvania, Philadelphia, PA
Alfred P. Fishman, MD (Chair); Betsy Ann Bozzarello; and Ameena Al-Amin.
Baylor College of Medicine, Houston, TX:
Marcia Katz, MD (Principal Investigator); Carolyn Wheeler, RN, BSN (Principal Clinical Coordinator); Elaine Baker, RRT, RPFT; Peter Barnard, PhD, RPFT; James Carter, MD; Sophia Chatziioannou, MD; Karla Conejo-Gonzales; John Haddad, MD; David Hicks, RRT, RPFT; Neal Kleiman, MD; Mary Milburn-Barnes, CRTT; Chinh Nguyen, RPFT; Michael Reardon, MD; Joseph Reeves-Viets, MD; Steven Sax, MD; Amir Sharafkhaneh, MD; Christine Young PT; Rafael Espada, MD (Principal Investigator from 1996 to 2002); Rose Butanda (from 1999 to 2001); Kimberly Dubose, RRT (from 1998 to 2001); Minnie Ellisor (2002); Pamela Fox, MD (from 1999 to 2001); Katherine Hale, MD (from 1998 to 2000); Everett Hood, RPFT (1998 - 2000); Amy Jahn (from 1998 to 2000); Satish Jhingran, MD (from 1998 to 2001); Karen King, RPFT (from 1998 to 1999); Charles Miller III, PhD (from 1996 to 1999); Imran Nizami, MD (Co-Principal Investigator, from 2000 to 2001); Todd Officer (from 1998 to 2000); Jeannie Ricketts (1998 −2000); Joe Rodarte, MD (Co-Principal Investigator from 1996 to 2000); Robert Teague, MD (Co-Principal Investigator from 1999 to 2000); and Kedren Williams (from 1998 to 1999).
Brigham and Women’s Hospital, Boston, MA:
John Reilly, MD (Principal Investigator); David Sugarbaker, MD (Co-Principal Investigator); Carol Fanning, RRT (Principal Clinic Coordinator); Simon Body, MD; Sabine Duffy, MD; Vladmir Formanek, MD; Anne Fuhlbrigge, MD; Philip Hartigan, MD; Sarah Hooper, EP; Andetta Hunsaker, MD; Francine Jacobson, MD; Marilyn Moy, MD; Susan Peterson, RRT; Roger Russell, MD; Diane Saunders; and Scott Swanson, MD (Co-Principal Investigator, from 1996 to 2001).
Cedars-Sinai Medical Center, Los Angeles, CA:
Rob McKenna, MD (Principal Investigator); Zab Mohsenifar, MD (Co-Principal Investigator); Carol Geaga, RN (Principal Clinic Coordinator); Manmohan Biring, MD; Susan Clark, RN, MN; Robert Frantz, MD; Peter Julien, MD; Michael Lewis, MD; Jennifer Minkoff-Rau, MSW; Valentina Yegyan, BS, CPFT; and Milton Joyner, BA (from 1996 to 2002).
Cleveland Clinic Foundation, Cleveland, OH:
Malcolm DeCamp, MD (Principal Investigator); James Stoller, MD (Co-Principal Investigator); Yvonne Meli, RN,C (Principal Clinic Coordinator); John Apostolakis, MD; Darryl Atwell, MD; Jeffrey Chapman, MD; Pierre DeVilliers, MD; Raed Dweik, MD; Erik Kraenzler, MD; Rosemary Lann, LISW; Nancy Kurokawa, RRT, CPFT; Scott Marlow, RRT; Kevin McCarthy, RCPT; Pricilla McCreight, RRT, CPFT; Atul Mehta, MD; Moulay Meziane, MD; Omar Minai, MD; Peter O’Donovan, MD; Mindi Steiger, RRT; Kenneth White, RPFT; Janet Maurer, MD (Principal Investigator, from 1996 to 2001); Charles Hearn, DO (from 1998 to 2001); Susan Lubell, PA-C (from 1999 to 2000); Robert Schilz, DO (from 1998 to 2002); and Terri Durr, RN (from 2000 to 2001).
Columbia University, New York, NY, in consortium with Long Island Jewish Medical Center, New Hyde Park, NY:
Mark Ginsburg, MD (Principal Investigator); Byron Thomashow, MD (Co-Principal Investigator); Patricia Jellen, MSN, RN (Principal Clinic Coordinator); John Austin, MD; Matthew Bartels, MD; Yahya Berkmen, MD; Patricia Berkoski, MS, RRT (Site Coordinator, Long Island Jewish Medical Center); Frances Brogan, MSN, RN; Amy Chong, BS, CRT; Glenda DeMercado, BSN; Angela DiMango, MD; Sandy Do, MS, PT; Bessie Kachulis, MD; Arfa Khan, MD; Berend Mets, MD; Mitchell O’Shea, BS, RT, CPFT; Gregory Pearson, MD; Leonard Rossoff, MD; Steven Scharf, MD, PhD (Co-Principal Investigator, from 1998 to 2002); Maria Shiau, MD; Paul Simonelli, MD; Kim Stavrolakes, MS, PT; Donna Tsang, BS; Denise Vilotijevic, MS, PT; Chun Yip, MD; Mike Mantinaos, MD (from 1998 to 2001); Kerri McKeon, BS, RRT, RN (from 1998 to 1999); and Jacqueline Pfeffer, MPH, PT (from 1997 to 2002).
Duke University Medical Center, Durham, NC:
Neil MacIntyre, MD (Principal Investigator); R. Duane Davis, MD (Co-Principal Investigator); John Howe, RN (Principal Clinic Coordinator); R. Edward Coleman, MD; Rebecca Crouch, RPT; Dora Greene; Katherine Grichnik, MD; David Harpole, Jr, MD; Abby Krichman, RRT; Brian Lawlor, RRT; Holman McAdams, MD; John Plankeel, MD; Susan Rinaldo-Gallo, MED; Jeanne Smith, ACSW; Mark Stafford-Smith, MD; Victor Tapson, MD; Mark Steele, MD (from 1998 to 1999); and Jennifer Norten, MD (from 1998 to 1999).
Mayo Foundation, Rochester, MN:
James Utz, MD (Principal Investigator); Claude Deschamps, MD (Co-Principal Investigator); Kathy Mieras, CCRP (Principal Clinic Coordinator); Martin Abel, MD; Mark Allen, MD; Deb Andrist, RN; Gregory Aughenbaugh, MD; Sharon Bendel, RN; Eric Edell, MD; Marlene Edgar; Bonnie Edwards; Beth Elliot, MD; James Garrett, RRT; Delmar Gillespie, MD; Judd Gurney, MD; Boleyn Hammel; Karen Hanson, RRT; Lori Hanson, RRT; Gordon Harms, MD; June Hart; Thomas Hartman, MD; Robert Hyatt, MD; Eric Jensen, MD; Nicole Jenson, RRT; Sanjay Kalra, MD; Philip Karsell, MD; David Midthun, MD; Carl Mottram, RRT; Stephen Swensen, MD; Anne-Marie Sykes, MD; Karen Taylor; Norman Torres, MD; Rolf Hubmayr, MD (from 1998 to 2000); Daniel Miller, MD (from 1999 to 2002); Sara Bartling, RN (from 1998 to 2000); and Kris Bradt (from 1998 to 2002).
National Jewish Medical and Research Center, Denver, CO:
Barry Make, MD (Principal Investigator); Marvin Pomerantz, MD (Co-Principal Investigator); Mary Gilmartin, RN, RRT (Principal Clinic Coordinator); Joyce Canterbury; Martin Carlos; Phyllis Dibbern, PT; Enrique Fernandez, MD; Lisa Geyman, MSPT; Connie Hudson; David Lynch, MD; John Newell, MD; Robert Quaife, MD; Jennifer Propst, RN; Cynthia Raymond, MS; Jane Whalen-Price, PT; Kathy Winner, OTR; Martin Zamora, MD; and Reuben Cherniack, MD (Principal Investigator, from 1997 to 2000).
Ohio State University, Columbus, OH:
Philip Diaz, MD (Principal Investigator); Patrick Ross, MD (Co-Principal Investigator); Tina Bees (Principal Clinic Coordinator); Hamdy Awad, MD; Jan Drake; Charles Emery, PhD; Mark Gerhardt, MD, PhD; Mark King, MD; David Rittinger; and Mahasti Rittinger.
Saint Louis University, St. Louis, MO:
Keith Naunheim, MD (Principal Investigator); Francisco Alvarez, MD (Co-Principal Investigator); Joan Osterloh, RN, MSN (Principal Clinic Coordinator); Susan Borosh; Willard Chamberlain, DO; Sally Frese; Alan Hibbit; Mary Ellen Kleinhenz, MD; Gregg Ruppel; Cary Stolar, MD; Janice Willey; and Cesar Keller, MD (Co-Principal Investigator, from 1996 to 2000).
Temple University, Philadelphia, PA:
Gerard Criner, MD (Principal Investigator); Satoshi Furukawa, MD (Co-Principal Investigator); Anne Marie Kuzma, RN, MSN (Principal Clinic Coordinator); Roger Barnette, MD; Neil Brister, MD; Kevin Carney, RN, CCTC; Wissam Chatila, MD; Francis Cordova, MD; Gilbert D’Alonzo, DO; Michael Keresztury, MD; Karen Kirsch; Chul Kwak, MD; Kathy Lautensack, RN, BSN; Madelina Lorenzon, CPFT; Ubaldo Martin, MD; Peter Rising, MS; Scott Schartel, MD; John Travaline, MD; Gwendolyn Vance, RN, CCTC; Phillip Boiselle, MD (from 1997 to 2000); and Gerald O’Brien, MD (from 1997 to 2000).
University of California, San Diego, San Diego, CA:
Andrew Ries, MD, MPH (Principal Investigator); Robert Kaplan, PhD (Co-Principal Investigator); Catherine Ramirez, BS, RCP (Principal Clinic Coordinator); David Frankville, MD; Paul Friedman, MD; James Harrell, MD; Jeffery Johnson; David Kapelanski, MD; David Kupferberg, MD, MPH; Catherine Larsen, MPH; Trina Limberg, RRT; Michael Magliocca, RN, CNP; Frank J. Papatheofanis, MD, PhD; Dawn Sassi-Dambron, RN; and Melissa Weeks.
University of Maryland at Baltimore, Baltimore, MD in consortium with Johns Hopkins Hospital, Baltimore, MD:
Mark Krasna, MD (Principal Investigator); Henry Fessler, MD (Co-Principal Investigator); Iris Moskowitz (Principal Clinic Coordinator); Timothy Gilbert, MD; Jonathan Orens, MD; Steven Scharf, MD, PhD; David Shade; Stanley Siegelman, MD; Kenneth Silver, MD; Clarence Weir; and Charles White, MD.
University of Michigan, Ann Arbor, MI:
Fernando Martinez, MD (Principal Investigator); Mark Iannettoni, MD (Co-Principal Investigator); Catherine Meldrum, BSN, RN, CCRN (Principal Clinic Coordinator); William Bria, MD; Kelly Campbell; Paul Christensen, MD; Kevin Flaherty, MD; Steven Gay, MD; Paramjit Gill, RN; Paul Kazanjian, MD; Ella Kazerooni, MD; Vivian Knieper; Tammy Ojo, MD; Lewis Poole; Leslie Quint, MD; Paul Rysso; Thomas Sisson, MD; Mercedes True; Brian Woodcock, MD; and Lori Zaremba, RN.
University of Pennsylvania, Philadelphia, PA:
Larry Kaiser, MD (Principal Investigator); John Hansen-Flaschen, MD (Co-Principal Investigator); Mary Louise Dempsey, BSN, RN (Principal Clinic Coordinator); Abass Alavi, MD; Theresa Alcorn Selim Arcasoy, MD; Judith Aronchick, MD; Stanley Aukberg, MD; Bryan Benedict, RRT; Susan Craemer, BS, RRT, CPFT; Ron Daniele, MD; Jeffrey Edelman, MD; Warren Gefter, MD; Laura Kotler-Klein, MSS; Robert Kotloff, MD; David Lipson, MD; Wallace Miller, Jr, MD; Richard O’Connell, RPFT; Staci Opelman, MSW; Harold Palevsky, MD; William Russell, RPFT; Heather Sheaffer, MSW; Rodney Simcox, BSRT, RRT; Susanne Snedeker, RRT, CPFT; Jennifer Stone-Wynne, MSW; Gregory Tino, MD; Peter Wahl; James Walter, RPFT; Patricia Ward; David Zisman, MD; James Mendez, MSN, CRNP (from 1997 to 2001); and Angela Wurster, MSN, CRNP (from 1997 to 1999).
University of Pittsburgh, Pittsburgh, PA:
Frank Sciurba, MD (Principal Investigator); James Luketich, MD (Co-Principal Investigator); Colleen Witt, MS (Principal Clinic Coordinator); Gerald Ayres; Michael Donahoe, MD; Carl Fuhrman, MD; Robert Hoffman, MD; Joan Lacomis, MD; Joan Sexton; William Slivka; Diane Strollo, MD; Erin Sullivan, MD; Tomeka Simon; Catherine Wrona, RN, BSN; Gerene Bauldoff, RN, MSN (from 1997 to 2000); Manuel Brown, MD (from 1997 to 2002); Elisabeth George, RN, MSN (Principal Clinic Coordinator from 1997 to 2001); Robert Keenan, MD (Co-Principal Investigator from 1997 to 2000); Theodore Kopp, MS (from 1997 to 1999); and Laurie Silfies (from 1997 to 2001).
University of Washington, Seattle, WA:
Joshua Benditt, MD (Principal Investigator), Douglas Wood, MD (Co-Principal Investigator); Margaret Snyder, MN (Principal Clinic Coordinator); Kymberley Anable; Nancy Battaglia; Louie Boitano; Andrew Bowdle, MD; Leighton Chan, MD; Cindy Chwalik; Bruce Culver, MD; Thurman Gillespy, MD; David Godwin, MD; Jeanne Hoffman; Andra Ibrahim, MD; Diane Lockhart; Stephen Marglin, MD; Kenneth Martay, MD; Patricia McDowell; Donald Oxorn, MD; Liz Roessler; Michelle Toshima; and Susan Golden (from 1998 to 2000).
Agency for Healthcare Research and Quality, Rockville, MD:
Lynn Bosco, MD, MPH; Yen-Pin Chiang, PhD; Carolyn Clancy, MD; and Harry Handelsman, DO.
Centers for Medicare and Medicaid Services, Baltimore, MD:
Steven Sheingold, PhD; Tanisha Carino, PhD; Joe Chin, MD; JoAnna Farrell; Karen McVearry; Anthony Norris; Sarah Shirey; and Claudette Sikora.
Coordinating Center, The Johns Hopkins University, Baltimore, MD:
Steven Piantadosi, MD, PhD (Principal Investigator); James Tonascia, PhD (Co-Principal Investigator); Patricia Belt; Karen Collins; Betty Collison; John Dodge; Michele Donithan, MHS; Vera Edmonds; Julie Fuller; Judith Harle; Rosetta Jackson; Heather Koppelman; Shing Lee, ScM; Charlene Levine; Hope Livingston; Jill Meinert; Jennifer Meyers; Deborah Nowakowski; Kapreena Owens; Shangqian Qi, MD; Michael Smith; Brett Simon, MD; Paul Smith; Alice Sternberg, ScM; Mark Van Natta, MHS; Laura Wilson, ScM; and Robert Wise, MD.
Cost Effectiveness Subcommittee:
Robert M. Kaplan, PhD (Chair); J. Sanford Schwartz, MD (Co-Chair); Yen-Pin Chiang, PhD; Marianne C. Fahs, PhD; A. Mark Fendrick, MD; Alan J. Moskowitz, MD; Dev Pathak, PhD; Scott Ramsey, MD, PhD; Steven Sheingold, PhD; A. Laurie Shroyer, PhD; Judith Wagner, PhD; and Roger Yusen, MD.
Cost Effectiveness Data Center, Fred Hutchinson Cancer Research Center, Seattle, WA:
Scott Ramsey, MD, PhD (Principal Investigator); Ruth Etzioni, PhD; Sean Sullivan, PhD; Douglas Wood, MD; Thomas Schroeder, MA; Robert Smith, MS; Kristin Berry, MS; and Nancy Myers.
CT Scan Image Storage and Analysis Center, University of Iowa, Iowa City, IA:
Eric Hoffman, PhD (Principal Investigator); Janice Cook-Granroth, BS; Angela Delsing, RT; Junfeng Guo, PhD; Geoffrey McLennan, MD; Brian Mullan, MD; Chris Piker, BS; Joseph Reinhardt, PhD; Jered Sieren, RTR; and William Stanford, MD.
Data and Safety Monitoring Board:
John A. Waldhausen, MD (Chair); Gordon Bernard, MD; David DeMets, PhD; Mark Ferguson, MD; Eddie Hoover, MD; Robert Levine, MD; Donald Mahler, MD; A. John McSweeny, PhD; Jeanine Wiener-Kronish, MD; O. Dale Williams, PhD; and Magdy Younes, MD.
Marketing Center, Temple University, Philadelphia, PA:
Gerard Criner, MD (Principal Investigator); and Charles Soltoff, MBA.
Project Office, National Heart, Lung, and Blood Institute, Bethesda, MD:
Gail Weinmann, MD (Project Officer); Joanne Deshler (Contracting Officer); Dean Follmann, PhD; James Kiley, PhD; and Margaret Wu, PhD (from 1996 to 2001).
Table 1. Minimum Scores, Maximum Scores, Means, and SDs of Variables Prior to Completion of Rehabilitation*
| Save Table
|Variables||Minimum Score||Maximum Score||Mean Score||SD|
| Pre-BD FEV1, L||0.29||1.58||0.68||0.22|
| Pre-BD FVC, L||0.71||5.19||2.14||0.72|
| Maximum work, W||0||111||36.0||21.07|
| Physical functioning||0||100||22.1||16.8|
| Role physical||0||100||20.9||30.8|
| Role emotional||0||100||68.5||41.0|
| Emotional well-being||0||100||74.6||17.5|
| Social functioning||0||100||61.8||27.7|
| Bodily pain||0||100||75.8||23.7|
| General health perceptions||0||100||37.6||20.2|
| Physical health summary index||8.3||55.5||28.3||7.4|
| Mental health summary index||11.7||72.9||53.2||10.9|
| SGRQ total score||19.6||100||56.5||13.0|
| SOBQ total score||8||120||65.6||19.0|
| QWB-SA average score||0.09||1.00||0.54||0.12|
Table 2. Pearson Correlations Between QOL Measures at Postrehabilitation Baseline*
| Save Table
Figure Jump LinkFigure 1. Comparison of QOL scores for NETT and normative samples. QWB-SA and SF-36 scale scores are from the 1-year normative sample of the Beaver Dam eye study for subjects with a mean age of 64 years.25 MCS and PCS norms from the US general population are for the age group 55 to 64 years, as reported by Ware.13 QWB-SA scores have been multiplied by 100 to place them in units similar to SF-36 scores.Grahic Jump Location
Table 3. Correlations Between Prerehabilitation Physiologic and QOL Measures*
| Save Table
|Variables||SF-36||SGRQ Total Score||SOBQ Total Score||QWB-SA Average Score|
|Maximum work, W||0.18†||0.14†||−0.23†||−0.34†||0.19†|
| FVC, L||0.05||0.11†||−0.10†||−0.18†||0.09†|
| FEV1, L||0.06‡||0.09†||−0.13†||−0.23†||0.07‡|
Table 4. Comparison of Postrehabilitation QOL Scores for Those Admitted and Not Admitted to a Hospital in the 3 Months Prior to NETT Initial Interview*
| Save Table
|Measure||Admitted to Hospital (n = 179)||Not Admitted to Hospital (n = 1,039)||p Value||Effect Size|
| PCS||27.8 (7.3)||30.0 (7.8)||0.001||0.28|
| MCS||52.9 (9.6)||55.7 (9.2)||0.001||0.30|
|SGRQ total score||57.9 (13.3)||52.2 (12.4)||0.001||0.46|
|SOBQ total score||68.4 (18.1)||61.5 (18.2)||0.001||0.38|
|QWB-SA average score||0.537 (0.132)||0.577 (0.111)||0.001||0.35|
Table 5. QOL Outcomes Before and After Pulmonary Rehabilitation (1,209 to 1,216 pairs)
| Save Table
|Variable||Pulmonary Rehabilitation||p Value||Effect Size|
| PCS||28.3||29.7||< 0.001||0.19|
| MCS||53.2||55.3||< 0.001||0.21|
Table 6. Correlations Between Changes in the 6MWD and Changes in QOL*
| Save Table
. The National Emphysema Treatment Trial Research Group (1999) Rationale and design of The National Emphysema Treatment Trial: a prospective randomized trial of lung volume reduction surgery.Chest116,1750-1761. [CrossRef] [PubMed]
Hamacher, J, Bloch, KE, Stammberger, U, et al Two years’ outcome of lung volume reduction surgery in different morphologic emphysema types.Ann Thorac Surg1999;68,1792-1798. [CrossRef] [PubMed]
Hamacher, J, Buchi, S, Georgescu, CL, et al Improved quality of life after lung volume reduction surgery.Eur Respir J2002;19,54-60. [CrossRef] [PubMed]
Malthaner, RA, Miller, JD Lung volume reduction surgery: results of a Canadian pilot study: Canadian Lung Volume Reduction Surgery Study Group.Can J Surg2000;43,377-383. [PubMed]
Moy, ML, Ingenito, EP, Mentzer, SJ, et al Health-related quality of life improves following pulmonary rehabilitation and lung volume reduction surgery.Chest1999;115,383-389. [CrossRef] [PubMed]
Tan, AL, Unruh, HW, Mink, SN Lung volume reduction surgery for the treatment of severe emphysema: a study in a single Canadian institution.Can J Surg2000;43,369-376. [PubMed]
Verpeut, AC, Verleden, GM, Van Raemdonck, D, et al Lung volume reduction surgery (LVRS) for emphysema: initial experience at the University Hospital Gasthuisberg; Leuven LVRS Group.Acta Clin Belg2000;55,154-162. [PubMed]
Curtis, JR, Martin, DP, Martin, TR Patient-assessed health outcomes in chronic lung disease: what are they, how do they help us, and where do we go from here?Am J Respir Crit Care Med1997;156,1032-1039. [PubMed]
Kaplan, RM, Atkins, CJ, Timms, R Validity of a quality of well-being scale as an outcome measure in chronic obstructive pulmonary disease.J Chronic Dis1984;37,85-95. [CrossRef] [PubMed]
Ramsey, SD, Sullivan, SD, Kaplan, RM, et al Economic analysis of lung volume reduction surgery as part of the National Emphysema Treatment Trial.Ann Thorac Surg2001;71,995-1002. [CrossRef] [PubMed]
Guyatt, GH, Townsend, M, Keller, J, et al Measuring functional status in chronic lung disease: conclusions from a randomized control trial.Respir Med1991;85,17-21
Kaplan, RM, Sieber, WJ, Ganiats, TG The quality of well-being scale: comparison of the interviewer-administered version with a self-administered questionnaire.Psychol Health1997;12,783-791. [CrossRef]
Ware, JE The SF-36 health survey. Spilker, B eds.Quality of life and pharmacoeconomics 2nd ed.1996,337-345 Lippincott-Raven. Philadelphia, PA:
Ware, JE, Jr, Gandek, B Overview of the SF-36 Health Survey and the International Quality of Life Assessment (IQOLA) Project.J Clin Epidemiol1998;51,903-912. [CrossRef] [PubMed]
Jones, PW, Quirk, FH, Baveystock, CM The St George’s respiratory questionnaire.Respir Med1991;85(suppl),25-31
Eakin, EG, Resnikoff, PM, Prewitt, LM, et al Validation of a new dyspnea measure: the UCSD shortness of breath questionnaire: University of California, San Diego.Chest1998;113,619-624. [CrossRef] [PubMed]
Goldman, L, Caldera, DL, Nussbaum, SR, et al Multifactorial index of cardiac risk in noncardiac surgical procedures.N Engl J Med1977;297,845-850. [CrossRef] [PubMed]
Ware, JE, Jr, Kosinski, M, Bayliss, MS, et al Comparison of methods for the scoring and statistical analysis of SF-36 health profile and summary measures: summary of results from the Medical Outcomes Study.Med Care1995;33,AS264-AS279. [PubMed]
Ware, JE, Jr The status of health assessment 1994.Annu Rev Public Health1995;16,327-354. [CrossRef] [PubMed]
Kaplan, RM, Schmidt, SM, Cronan, TA Quality of well being in patients with fibromyalgia.J Rheumatol2000;27,785-789. [PubMed]
Kerner, DN, Patterson, TL, Grant, I, et al Validity of the quality of well-being scale for patients with Alzheimer’s disease.J Aging Health1998;10,44-61. [CrossRef] [PubMed]
Rocco, MV, Gassman, JJ, Wang, SR, et al Cross-sectional study of quality of life and symptoms in chronic renal disease patients: the Modification of Diet in Renal Disease Study.Am J Kidney Dis1997;29,888-896. [CrossRef] [PubMed]
Kaplan, RM, Anderson, JP, Patterson, TL, et al Validity of the quality of well-being scale for persons with human immunodeficiency virus infection: HNRC Group; HIV Neurobehavioral Research Center.Psychosom Med1995;57,138-147. [PubMed]
Pyne, JM, Patterson, TL, Kaplan, RM, et al Assessment of the quality of life of patients with major depression.Psychiatr Serv1997;48,224-230. [PubMed]
Fryback, DG, Dasbach, EJ, Klein, R, et al The Beaver Dam Health Outcomes Study: initial catalog of health-state quality factors.Med Decis Making1993;13,89-102. [CrossRef] [PubMed]
Kosinski, M, Keller, SD, Hatoum, HT, et al The SF-36 Health Survey as a generic outcome measure in clinical trials of patients with osteoarthritis and rheumatoid arthritis: tests of data quality, scaling assumptions and score reliability.Med Care1999;37(suppl),MS10-MS22
Kaplan, RM, Ganiats, TG, Sieber, WJ, et al The quality of well-being scale: critical similarities and differences with SF-36.Int J Qual Health Care1998;10,509-520. [CrossRef] [PubMed]
Ries, AL, Kaplan, RM, Limberg, TM, et al Effects of pulmonary rehabilitation on physiologic and psychosocial outcomes in patients with chronic obstructive pulmonary disease.Ann Intern Med1995;122,823-832. [PubMed]
Ries, AL, Kaplan, RM, Myers, R, et al Maintenance after pulmonary rehabilitation in chronic lung disease: a randomized trial.Am J Respir Crit Care Med2003;167,880-888. [CrossRef] [PubMed]
Atkins, CJ, Kaplan, RM, Timms, RM, et al Behavioral exercise programs in the management of chronic obstructive pulmonary disease.J Consult Clin Psychol1984;52,591-603. [CrossRef] [PubMed]
Engstrom, CP, Persson, LO, Larsson, S, et al Health-related quality of life in COPD: why both disease-specific and generic measures should be used.Eur Respir J2001;18,69-76. [CrossRef] [PubMed]
Resnikoff, PM, Ries, AL Pulmonary rehabilitation for chronic lung disease.J Heart Lung Transplant1998;17,643-650. [PubMed]
Ries, AL, Kaplan, RM, Blumberg, E Use of factor analysis to consolidate multiple outcome measures in chronic obstructive pulmonary disease.J Clin Epidemiol1991;44,497-503. [CrossRef] [PubMed]
Williams, RA, Brody, BL, Thomas, RG, et al The psychosocial impact of macular degeneration.Arch Ophthalmol1998;116,514-520. [PubMed]
Gold, MR. Cost-effectiveness in health and medicine. 1996; Oxford University Press. New York, NY:.
Ramsey, SD, Berry, K, Etzioni, R, et al Cost effectiveness of lung-volume-reduction surgery for patients with severe emphysema.N Engl J Med2003;348,2092-2102. [CrossRef] [PubMed]