Understanding the Challenges Facing Invest

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included in the published article.4 Based on other publications from the Chelsea and Westminister group, however, it is likely that a significant number of the individuals included in the current analysis were never treated with curative intent.5,6 Thus, the Chelsea-Westminister group recently recounted their data regarding leptomeningeal disease in patients with ARL, employing the same cohort.5 In that publication, which included a total of 176 patients comprising their full database of ARL at the time, the authors stated that a total of 84 (48% of the total group) with adverse prognostic features received therapy with palliative intent.5 One can assume, therefore, that many of the patients treated in the pre-HAART era as well as at least 10.8% diagnosed in the HAART era, did not, in fact, receive either optimal or specific therapy for their lymphomatous disease, yet were included in the analyses which sought to determine prognostic factors for survival. In our own study of 363 patients, we analyzed prognostic factors in patients treated in pre-HAART versus HAART eras, and specifically evaluated those patients who actually received chemotherapy with curative intent. We found that lack of receipt of a complete remission and CD4 cells less than 100/mm3 were statistically associated with decreased survival on multivariate analysis in the pre-HAART era, while lack of complete remission and BL histology were significant predictors of poor prognosis in the HAART era. We believe that the divergent results between our data and those of the Chelsea-Westminister group in terms of the importance of histologic type may have been lost by their inclusion of patients who received palliative chemotherapy or supportive therapy alone in their prognostic model. A further potential explanation for the divergent results between Stebbing’s current report and our own concerns the fact that patients diagnosed in both pre-HAART and HAART eras are included in their prognostic model. In addition, the authors defined the HAART era as commencing on January 1, 1996, but failed to provide full information on the proportion of patients who actually did receive HAART.4 Considering the impact of HAART in improving the survival of patients with AIDS,6 it is surprising that HAART use did not feature as an important prognostic factor in their study. Furthermore, since HAART is now employed routinely in patients with ARL, either concomitant or subsequent to chemotherapy, the clinical relevance of the proposed prognostic scoring system in Stebbing’s 215 patients, in whom approximately half did not receive HAART, is likely to be limited. The finding by Stebbing et al that a pathologic subtype of BL is an independent poor prognostic factor for survival for the entire cohort of patients as well as for patients in the pre-HAART but not the HAART era is difficult to understand, as they readily admit. It is certainly possible that this unexpected result could simply reflect the fact that the prognostic model employed included a proportion of patients who were never treated with curative intent, as well as those who did not receive HAART, leading to results that are divergent from other published data,2,3 including our

own.1 As we demonstrated, the survival of patients with HIV-diffuse large-cell lymphoma has improved substantially in the HAART era, along with CD4 cell count, while survival of similarly treated patients with HIV BL has remained poor. The current practice of using the same regimen for both groups of patients should be re-evaluated.1 Alexandra M. Levine Division of Hematology, University of Southern California/Norris Cancer Hospital, Los Angeles, CA

Soon-Thye Lim Department of Medical Oncology National Cancer Center, Singapore, Singapore ■ ■ ■

Authors’ Disclosures of Potential Conflicts of Interest The authors indicated no potential conflicts of interest. REFERENCES 1. Lim ST, Karim R, Nathwani BN, et al: AIDS-related Burkitt’s lymphoma versus diffuse large-cell lymphoma in the pre-highly active antiretroviral therapy (HAART) and HAART eras: Significant differences in survival with standard chemotherapy. J Clin Oncol 23:4430-4438, 2005 2. Spina M, Jaeger U, Sparano JA, et al: Rituximab plus infusional cyclophosphamide, doxorubicin, and etoposide in HIV-associated non-Hodgkin lymphoma: Pooled results from 3 phase 2 trials. Blood 105:1891-1897, 2005 3. Kaplan LD, Lee JY, Ambinder RF, et al: Rituximab does not improve clinical outcome in a randomized phase 3 trial of CHOP with or without rituximab in patients with HIV-associated non-Hodgkin lymphoma: AIDSMalignancies Consortium Trial 010. Blood 106:1538-1543, 2005 4. Bower M, Gazzard B, Mandalia S: A prognostic index for systemic AIDS-related non-Hodgkin lymphoma treated in the era of highly active antiretroviral therapy. Ann Intern Med 143:265-273, 2005 5. Sarker D, Thirlwell C, Nelson M: Leptomeningeal disease in AIDSrelated non-Hodgkin’s lymphoma. AIDS 17:861-865, 2003 6. Palella FJ Jr., Delaney KM, Moorman AC, et al: Declining morbidity and mortality among patients with advanced human immunodeficiency virus infection: HIV Outpatient Study Investigators. N Engl J Med 338:853-860, 1998

DOI: 10.1200/JCO.2005.03.0205

Variability and Sample Size Requirements for Health-Related Quality-of-Life Measures: Understanding the Challenges Facing Investigators TO THE EDITOR: We read with interest the recent article by Cheung et al1 which addressed the important issue of variability and discriminative ability of three commonly used cancer specific health-related quality of life (HRQOL) instruments: the Functional Assessment of Cancer Therapy-General (FACT-G), the Functional Living Index–Cancer (FLIC), and the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire-C30 (EORTC QLQC30). Such methodological research is important, and could 8541

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well lead to better design and conduct of clinical trials where HRQOL is an important end point. Ultimately, Cheung et al concluded that “the global score of the EORTC QLQ-C30 performed less favorably than the FACT-G and FLIC in several aspects.” However, we believe that some caution should be used in interpreting these findings. The Cheung et al article focuses on the discriminative ability of the three HRQOL instruments in relation to Eastern Cooperative Oncology Group (ECOG) performance status. Toward this end, they employed the total scores of the FACT-G and the FLIC, and the global quality of life scale of the QLQ-C30. The total scores of the FACT-G and the FLIC represent a sum score of all items in those questionnaires (27 and 22 items, respectively), and include items assessing physical functioning (the HRQOL domain most closely related to the ECOG performance status measure). Conversely, the global scale of the QLQ-C30 includes only two items, one referring to overall health and the other to overall quality of life. In fact, given that the QLQ-C30 does not yield a total score, the scale that probably would be most appropriate for use in an analysis such as that performed by Cheung et al is the five-item physical functioning scale.2 As they have data for this scale as well, it would be of interest to know if it performed more efficiently in relation to the ECOG scale than the global QOL scale. As Cheung et al point out, the greater variability observed for the QLQ-C30 global QOL scale as compared to the FACT-G and FLIC total scores reflects, in large part, the simple fact that the former scale includes only two items, while the latter two scales include 10 fold that number of items. A scale composed of more items will invariably yield more precise results than a similar scale with fewer items. To date, the EORTC has not used of a total, summary score for the QLQ-C30, largely because of the inherent difficulty in interpreting such a score. Rather, it continues to advocate the use of questionnaire profiles that allow clinicians to identify those specific HRQL areas in which patients are improving or deteriorating over time. However, as noted by Cheung et al, some authors have generated such an overall summary score for the QLQ-C30.3 The EORTC is currently investigating whether such a total score, or more likely several summary scores (eg, physical and psychosocial health) can be empirically justified on the basis of structural equation models applied to large, international data sets. Ultimately, the choice of questionnaire to be used in assessing the HRQOL of patients with cancer should be based on a careful examination of the content, the specific wording, and the psychometric properties of candidate instruments. Contrary to what is suggested by Cheung et al, the FACT-G, the FLIC, and the QLQ-C30 generally have similar psychometric properties, but differ quite substantially in specific content and question phrasing. We would continue to encourage investigators to review carefully the content of questionnaires in order to select the instrument 8542

best suited to answering the specific research questions being posed. Corneel Coens, Andrew Bottomley, and Fabio Efficace European Organisation for Research and Treatment of Cancer Data Center, Brussels, Belgium

Henning Flechtner Clinic for Psychiatry and Psychotherapy of Children and Adolescents, University of Cologne, Cologne, Germany

Neil Aaronson Division of Psychosocial Research and Epidemiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands ■ ■ ■

Authors’ Disclosures of Potential Conflicts of Interest The authors indicated no potential conflicts of interest. REFERENCES 1. Cheung Y-B, Goh C, Thumboo J, et al: Variability and sample size requirements of quality-of-life measures: A randomized study of three major questionnaires. J Clin Oncol 23:4936-4944, 2005 2. Aaronson NK, Ahmedzai S, Bergman B, et al: The European Organization for Research and Treatment of Cancer QLQ-C30: A quality-of-life instrument for use in international clinical trials in oncology. J Natl Cancer Inst 85:365-376, 1993 3. Nordin K, Steel J, Hoffman K, et al: Alternative methods of interpreting quality of life data in advanced gastrointestinal cancer patients. Br J Cancer 85:1265-1272, 2001

DOI: 10.1200/JCO.2005.03.9776

IN REPLY: Coens et al rightly emphasize that the results of our recent article1 on the variability and sample size requirements for health-related quality-of-life questionnaires should be interpreted with some caution. In particular, the contents and wording of the three questionnaires, namely the Functional Assessment of Cancer TherapyGeneral (FACT-G), the Functional Living Index–Cancer (FLIC), and the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire-C30 (EORTC QLQ-C30), are not identical and researchers need to carefully examine them before making a choice of instrument. We have put forward this cautionary note in our article, but it is helpful to emphasize and reiterate this. Coens et al suggest that “given that the QLQ-C30 does not yield a total score, the scale that probably would be most appropriate for use in analysis such as that performed by Cheung et al is the 5-item physical functioning scale.” We have reservations about this view. The contents of the FACT-G and FLIC are clearly much more heterogeneous than that of the physical functioning scale (PFS) of the QLQ-C30. So a comparison between the PFS and the total scores of the FACT-G and FLIC are not useful. The FLIC only gives a total score. The FACT-G has a physical well-being and a functional well-being scale. However, careful examination of their contents would show that the concepts they measure are not comparable with that of PFS. So a scale-specific comparison is not appropriate either. We believe the most useful comparison of the three JOURNAL OF CLINICAL ONCOLOGY

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