Reliability and validity of a quality of life measure for lung and colon cancer patients

Reliability and validity of a quality of life measure for lung and colon cancer patients

258 Abstracts blastic or undifferentiated leukemia in adults with respect to the German Multicentre ALL/AULStudy. The main questions were: Are the st...

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Abstracts blastic or undifferentiated leukemia in adults with respect to the German Multicentre ALL/AULStudy. The main questions were: Are the study, the treatment, and its results known, accepted, and transferred to medical care? Can the data necessary to answer this question be collected by a telephone or a mail survey? A regional telephone survey including all hospitals known to treat ALL/AUL-patients was done. The response rate was 100%. About 80% of the patients admitted to these hospitals (n = 55) are already treated according to the study protocol. At present a mail survey with all medical hospitals (n = 258) in one state is done.

R e l i a b i l i t y a n d V a l i d i t y of a Quality of Life Measure for Lung and Colon Cancer

Patients LuciUe S. Ryan, T h o m a s E. Moritz, a n d Leo R. Zacharski

Newington Veterans Administration Medical Center, Newington, Connecticut (P-35T) The development of a multidimensional instrument to measure the quality of life of lung and colon cancer patients participating in a VA cooperative study assessing anticoagulation therapy is the focus of this paper. Quality of Life is measured with 40 linear analog scale self-assessment items concerning the side effects of treatment, physical and emotional symptoms, social factors, perceived family support, and global quality of life. Since June 1982, 350 patients from 11 hospitals have been accrued to this longitudinal study, which measures quality of life before treatment and on subsequent clinic visits. Test-retest, parallel form interrater, and internal consistency reliability plus concurrent validity have been evaluated. Comparisons between the patients, the nurses, and the physicians' ratings of the patients quality of life have been done. The data to be reported describe the reliability and validity of the quality of life assessment (QOLA) instru fment. The results show that the QOLA is reliable, has concurrent validity, and measures change over time.

A Standardized Approach to the Tabulation and Statistical Evaluation of

Laboratory Data J o s e p h B. Q u i n n , C h e r y l L. Harris, a n d Linda M. Kudrick Mead Johnson Pharmaceutical Group, Evansville, Indiana (P-36T) The evaluation and presentation of laboratory data is one of the most important aspects of a clinical trial. The volume of information can make the process a difficult one unless handled in a standardized, multilevel fashion. Our approach includes listings by patient and by laboratory test, and categorical summaries of prestudy to poststudy changes within each treatment group. Statistical tests include Fisher's Sign test, Stuart Maxwell's test or McNemar's test and a between treatment group chi-square test. Our system is SAS-based using macros to generate each desired report. This provides medical and statistical personnel the flexibility to view the data from a clinical and statistical perspective.

Some Issues in the Analysis of Changes in Lipid Variables During Chronic D r u g Therapy J. H o r t o n , D. J o r d a n a n d H. G l a s s m a n

Abbott Laboratories, North Chicago, Illinois (P-37T) The evaluation of the effect of any new chronic drug therapy on lipid values is essential, due to the current understanding of the potential correlation between a patient's lipid profile and arteriosclerotic disease. In the development of a new antihypertensive compound, where lipid changes are evaluated, the analysis of lipid data is complicated by several factors. An adequate washout period at baseline, sufficient exposure to the drug, control of diet during therapy, and adequate techniques for handling blood samples must be considered in study design. The extreme values in lipids that are sometimes seen, due to a patient's underlying disease state or other unknown causes, can have a major effect on the results of the statistical analysis. Ways to minimize the effect such outliers can have on statistical conclusions are demonstrated with several statistical methods, including analysis of variance techniques, analysis of ranks, and Cochran-Mantel-Haenszel methodology.