Grutsch et al. BMC Cancer 2011, 11:193 http://www.biomedcentral.com/1471-2407/11/193 0.0187) and shortness of breath (p < 0.001), achieved statistical significance between our two patient groups, indicating the profound leveling effect of advanced non- small cell lung cancer vis a vis their most common and devastating symptoms. Our patients’ mean score of 16.23 in the Ferrans/ Powers QLI health/functioning domain is nearly eight points lower (worse) than the population-based mean score. This is some two standard deviations below mean scores from a general population survey. Patients were very dissatisfied with their health. Interestingly, however, the other three QLI domains (social/eco- nomic, psychological/spiritual well being, and family) did not differ at all from the population-based scores (Table 3). Actigraphy Actigraphic parameters of lung cancer patients were found to be grossly abnormal when compared to the healthy control population. Healthy individuals show a more robust 24-hour activity rhythm while lung cancer patients show a flatter curve (Figure 1). Cancer patients were 30% less active and napped at least three times longer than the controls during the putative wake/activ- ity period (Table 4). During the nightly sleep span, lung cancer patients had significantly more and longer wak- ing episodes than controls (Table 4). No gender differ- ences were found. Actigraphy characterizing the putative daily wake span and the overall circadian organization differed by site (Table 4, Figure 1). Outpatients were more active during the day and consolidated activity and sleep better com- pared to hospitalized inpatients. The sleep phase actigra- phy parameters at both sites, however, were indistinguishable. These prominent site specific differ- ences in actigraphy collection protocol required that all such data be analyzed by site. The most obvious ubiqui- tous and severe differences across the groups of normal controls and lung cancer patients include uniformly poor sleep among all lung cancer patients and decreas- ing daytime activity which is most severe, as might be expected, among hospitalized patients. Page 5 of 13 Correlation of Quality of Life and Actigraphy among Inpatients Among inpatients we only found several statistically sig- nificant associations with actigraphy parameters. We found that the QLI Health/Functioning domain scores correlate with the 24-hour activity autocorrelation, which measures day to day stability of the peak and trough timings of the daily activity/sleep pattern (r = 0.34, p = 0.05). Inpatients with the most stable circadian time structures of the daily activity pattern express the highest level of satisfaction with their health. Those who are most disrupted have much worse satisfaction with their health. Two EORTC symptom items correlated strongly with activity circadian rhythm parameters; insomnia severity correlates negatively with 24-hour autocorrelation, the day-to-day reproducibility of peak and trough activity (r = -0.48, p = 0.003), and loss of appetite correlates with decreased peak daily activity (r = -0.41, p = 0.005) and Circadian Quotient, a measure of the strength of the circadian rhythm compared to noise or other high frequency rhythms (r = 0.4, p = 0.015). Circadian activity/sleep rhythm disruption is reflected in or caused by nocturnal insomnia and those patients with most decreased daily activity (ie. greatest daytime fatigue) have the poorest appetite, even in the hospital setting. Relationships between QLI and Actigraphy among Outpatients Among ambulatory outpatients with advanced lung can- cer in their own homes, higher levels of daytime activity, as measured by the parameter “peak activity,” is signifi- cantly associated with each of the five Power and Ferrans QLI domains: health/functioning(r = 0.51, p < 0.01), social/economic (r = 0.38, p = 0.048), psychological/spiri- tual (r = 0.45, p = 0.02), family (r = 0.45, p = 0.02), and overall QLI (r = 0.57, p < 0.01), see Figure 2 and Table 5. Robustness (largest peak to trough difference in daily activity or amplitude) of objectively measured daytime activity is reflective of all measured aspects of quality of life in the face of advanced lung cancer. The health/func- tioning domain also demonstrates a statistically Table 3 Distribution of Powers and Ferrans QLI domain scores by site Domain Health & Functioninga Social/Economica Psychological/Spirituala Familya Overall Quality of Lifea All Patients 16.23 ± 0.72* 21.15 ± 0.46 21.57 ± 0.71 23.22 ± 0.60 19.61 ± 0.48 Study Population (mean ± se) Inpatients 15.13 ± 1.14 21.21 ± 0.58 21.04 ± 0.88 24.50 ± 0.75 19.28 ± 0.69 Outpatients 17.55 ± 0.0.73 21.08 ± 0.74 22.21 ± 1.16 21.68 ± 0.89 20.02 ± 0.66 General Populationb [mean (SD)] 23.19 (4.47)* 21.83 (4.11) 22.95 (5.21) 25.60 (4.49) 23.00 (4.04) aHigher scores indicate greater satisfaction with life. bPowers and Ferrans QLI General Population is taken from a database of 339 randomly selected subjects ages 18 and above (C. Ferrans, Feb 2009). *Study Population scores are markedly lower than General Population scores.