Quality of Life Studies from the Perspective of an FDA Reviewing Statistician

Smith, Nancy D.

doi:10.1177/009286159302700306

Cited by 24 publications

(14 citation statements)

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“…The large attrition rate for the combined dataset precluded further evaluation of trends according to sociodemographic variables at day 29 and day 71. Several solutions to this problem of measurement bias have been presented previously by the developers of the LCSS [15] and by others [17][18][19][20][21][22].…”

Section: Discussionmentioning

confidence: 99%

Normative data and trends in quality of life from the Lung Cancer Symptom Scale (LCSS)

Hollen

Gralla

Kris

et al. 1999

Supportive Care in Cancer

104

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Normative data and trends for a disease- and site-specific quality of life (QL) instrument for individuals with lung cancer, the Lung Cancer Symptom Scale (LCSS), are presented to facilitate the user's interpretation of test scores. Data for patients enrolled in two large, identical, randomized trials of a new combination chemotherapy regimen for patients with stages III and IV non-small-cell lung cancer (NSCLC) were combined into one dataset (n = 673). For these patients with a Karnofsky performance status (KPS) of 60-100%, QL had been prospectively measured at baseline, day 29 and every 6 weeks thereafter. Descriptive statistics for the LCSS are presented for three time points (baseline, day 29 and day 71) and for specific demographic and disease-related characteristics (age, gender, race, performance status and stage of disease) to provide expected values and their variability during chemotherapy. Data from a small dataset of 63 NSCLC inpatients with KPS scores of 20-50% are also presented for a comparison sample of supportive care for inpatients and hospice patients. For the 673 NSCLC patients at baseline there were no significant differences in QL by age, gender, or race. Major presenting lung cancer symptoms at baseline for this combined sample were dyspnea 87%, cough 86%, pain 81%, loss of appetite 75%, and hemoptysis 41%. Of these patients, 81% had three or more presenting symptoms at baseline (2% had no symptoms; 5%, one symptom; 12%, two symptoms; 18%, three symptoms; 27%, four symptoms; and 36%, five symptoms). The mean LCSS baseline score (best = 0; worst = 100) was 26.56 (SD 16.10). The mean scores for day 29 and day 71 were 25.46 (SD 16.52) and 25.30 (SD 16.93), respectively, but follow-up assessments on progressers were not obtained. Stage III patients had a mean LCSS score of 23.7 (SD 15.1), whereas stage IV patients reported a mean LCSS score of 27.3 (SD 16.3). The mean LCSS score for the group with KPS 60-70% was 34.8 (SD 15.5), and that for the group with KPS 80-100% was 23.3 (SD 15.1). The mean LCSS score for the lower performance group, with KPS scores of 20-50% at baseline, was 46.85 (SD 17.65).

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Section: Discussionmentioning

confidence: 99%

Normative data and trends in quality of life from the Lung Cancer Symptom Scale (LCSS)

Hollen

Gralla

Kris

et al. 1999

Supportive Care in Cancer

104

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“…The clinical, biochemical, and physiological benefits and adverse effects of treatment can have a positive or a negative impact on HRQL, making this an important outcome of treatment. The evaluation of HRQL is taking on greater significance in the development and evaluation of new pharmaceutical agents and devices for several reasons [1]:…”

Section: Rationalementioning

confidence: 99%

Recommendations for Evaluating the Validity of Quality of Life Claims for Labeling and Promotion

Leidy¹,

Revicki²,

Geneste³

1999

Value in Health

345

306

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The pharmaceutical industry, the medical device industry, and national regulatory agencies such as the United States Food and Drug Administration (FDA) are faced with a number of difficult issues related to the development and evaluation of health-related quality of life (HRQL) claims for product labeling and promotion. This paper outlines some of the unique challenges of HRQL research and makes recommendations for assuring that claims are based on the results of rigorous studies designed and conducted according to accepted scientific principles and practices. Standards of evidence for HRQL are discussed in terms of research design and methodology, instrumentation, statistical analysis, and interpretation. Examples are provided to highlight important points. The paper concludes with a brief discussion of future trends in HRQL outcomes evaluation.

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“…Progression of disease or death were the main reasons for patient dropout from this QOL evaluation. Missing data is a serious problem for QOL evaluation, because the reason for loss is not generally independent of the condition of interest producing a measurement bias [1,17,29,33 ]. Internal validity is compromised if attrition is different among the comparison groups due to the effect of the treatment [2].…”

mentioning

confidence: 99%

“…Suggested parameters for the repeating of QOL assessment have included frequency sufficient to represent the natural history of the disease, timing of treatment, and to detect changes of interest [33,24,28,19,27,17,4]. The 1995 American Society of Clinical Oncology (ASCO) cancer treatment guidelines only advise using validated patient report QOL measures and ones that capture clinically meaningful changes produced by treatment [25].…”

mentioning

confidence: 99%

Quality of life as a clinical trial endpoint: determining the appropriate interval for repeated assessments in patients with advanced lung cancer

Hollen

Gralla²,

Rittenberg³

2004

Support Care Cancer

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One of the unresolved design issues for clinical trials with quality of life (QOL) as an endpoint is the frequency of measurement in patients with stage III and IV lung cancer. In a retrospective review of clinical trials, the QOL interval varied widely from 1 to 12 weeks during treatment. During follow-up, the interval was generally 2 to 3 months or not at all. The purpose of this methodological study was to determine an appropriate interval for QOL serial measurement based on prospectively collected data. The 20 patients for this study were part of a phase I/I study using combination chemotherapy in patients with advanced non-small cell lung cancer (NSCLC). They were typical of patients in lung cancer clinical trials, with a median age of 67 (interquartile range: 58, 72) years, the majority were male (13, 65%), and a baseline median Karnofsky performance status was 80 (interquartile range: 70%, 90%). The primary instrument, developed in 1985, was the Lung Cancer Symptom Scale (LCSS) patient form, a 9-item self-report and site-specific QOL measure. The method, outcome, and implication of these findings to research are presented for establishing a method for obtaining an appropriate serial measurement interval for QOL during therapy in clinical trials. Based on the findings of this study, an every 3-week QOL assessment for patients with advanced NSCLC provides data similar to more frequent evaluation (94% of data preserved compared to twice-weekly assessment, 95% confidence interval, 86-98%, p=0.05). Less frequent assessment (every 4 or every 6 weeks) retained less than 85% of the data, which is the recommended minimum adequacy rate. Retaining a high percentage of QOL information may lessen the effect of measurement bias due to patient attrition and may give more validity to QOL studies.

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Quality of Life Studies from the Perspective of an FDA Reviewing Statistician

Cited by 24 publications

References 0 publications

Normative data and trends in quality of life from the Lung Cancer Symptom Scale (LCSS)

Normative data and trends in quality of life from the Lung Cancer Symptom Scale (LCSS)

Recommendations for Evaluating the Validity of Quality of Life Claims for Labeling and Promotion

Quality of life as a clinical trial endpoint: determining the appropriate interval for repeated assessments in patients with advanced lung cancer

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