Grutsch et al. BMC Cancer 2011, 11:193 http://www.biomedcentral.com/1471-2407/11/193 range from 0 to 100. Higher scores in the global and functional domains indicate better Quality of Life and lower scores in the symptom items indicate better Qual- ity of Life. Ferrans and Powers Quality of Life Index (QLI) Cancer Version III The Ferrans and Powers Quality of Life Index (QLI) dif- fers from the EORTC QLQ-C30 in that it elicits infor- mation quantifying each patient’s satisfaction or dissatisfaction with various aspects of life and thus assesses the individual’s feelings of emotional well-being and capacity to enjoy life. Consequently, this instrument evaluates how cancer has affected, both positively and negatively, the patient’s well being in terms of their own personal values [22]. The QLI Cancer Version III con- sists of two parts. Part one requires the patient to describe satisfaction levels with 33 aspects of life. Part two requires the patient to rate the importance of the same 33 aspects of his or her life. The QLI produces an overall quality of life score and subscale scores on four specific domains: health and functioning, social and eco- nomic, psychological and spiritual, and family. The scores range from 0 to 30, with higher scores indicating greater satisfaction with life. Thus, the EORTC-QLQ C30 and the QLI provide distinct, unique, and comple- mentary insights into different aspects of each patient’s quality of life [34]. Actigraphy Measurements of Rest-Activity Cycles A watch-like wrist actigraph, worn on the non-dominant wrist, was used to record a patient’s movement patterns continuously over a four to seven day span (Ambulatory Monitoring, Inc, AMI, Ardsley, NY USA). Internal motion sensors (accelerometers) capture patient move- ment data, measured as the number of accelerations per minute. These data are transferred to a computer for analysis to produce a report containing parameters of activity during each sleep and wake period, detailing their extent, timing, duration and other characteristics [35]. Actigraphy data were recorded in the hospital set- ting at MRMC in the four to seven days immediately prior to and during the first treatment, while these data were obtained in the patient’s home for VAMC patients during the week prior to the first treatment. Determination of Presence and severity of Chronic Obstructive Pulmonary Disease (COPD) Chronic Obstructive Pulmonary Disease (COPD) is common among lung cancer patients and, thereby, a potential confounding variable for this investigation of quality of life outcomes and circadian time structure. All VA patients were assessed clinically and with pulmonary functions for the presence of COPD. Its severity was Page 3 of 13 graded according to the Spirometric Classification of COPD severity, by reference to percent of predicted forced expiratory volume in one second (FEV1). Thirty to fifty percent of predicted FEV1 is considered severe; moderate is 50 to 80%; and mild COPD is greater than 80% of predicted FEV1. No such data were available for inpatients. Statistical Analysis Descriptive statistics such as mean and standard error were computed for continuous variables and actigraphy endpoints to describe the average and variability of values across the population. Frequency and percentages were computed for qualitative factors such as sex and quality of life outcomes. Both parametric (Analysis of Variance) and non-parametric analyses were used to determine time of day differences among factor levels (SAS v 9.1, Cary, NC) and their shapes across (circa- dian) time of day. For four to seven days, an actigraphy watch recorded the number of accelerations per minute. These data were translated into polysomnographically- validated sleep/activity parameters through the Act Mil- lenium and Action W2 software (Ambulatory Monitor- ing, Inc). Cosinor analysis was done on these sleep/ activity patterns in order to assess the circadian charac- teristics of sleep and activity among these lung cancer patients. Cosinor analysis provides three standard para- meters: mesor - the average activity over the 24-hr per- iod, amplitude - peak to nadir difference and acrophase - the time of daily peak activity. We also computed measures of circadian rhythm robustness and day-to-day stability (circadian quotient = amplitude/mesor), peak activity (mesor + amplitude) and 24 hour autocorrela- tion for each patient. We further measured circadian indices of the daily timing of sleep and activity, such as the ratio of amount of activity during the day to night- time activity, night/day sleep balance that is the amount of nighttime sleep relative to daytime sleep. Inpatient and outpatient differences were tested using t-test for quantitative characteristics while chi-square was used for categorical factors. The relationships between quality of life domain values and actigraphy measurements were measured using the Spearman rank correlation test. Results Patient Characteristics 84 patients were enrolled and consented at two sites. One site studied patients only in the outpatient home environ- ment while the second site studied them only as inpati- ents. There were differences in demographic and clinical status in participants by site. All 42 outpatients were males while 19 of 42 inpatients were female. Outpatients were older on average with a mean age of 66 compared to the inpatients’ mean age of 57 years (Table 1). More