Grutsch et al. BMC Cancer 2011, 11:193 http://www.biomedcentral.com/1471-2407/11/193 practices and the VA setting of one of our groups, per- fect age- and gender-matched comparisons to clearly evaluate the extent of the affects of sex and age upon circadian function of our cancer inpatients vs. outpati- ents. We did, however, obtain relevant actigraphy data upon 35 healthy controls aged 20 to 30 for comparison. While not a perfect control, this population provides reasonable comparison data. The most significant limita- tion may be that our statistical models are less than optimally sensitive to linking the degree of disorder in the patient’s circadian system and advanced lung cancer symptoms [51]. Despite these very real limitations, our data and those of others indicate that among cancer patients, circadian organization is an integrative pathway involved in a vari- ety of important pathophysiologic processes that promi- nently and quantitatively affect a variety of quality of life outcomes. The next step in this program is to determine whether restoring the robustness of circadian organiza- tion among advanced cancer patients is possible and whether doing so will reduce symptom intensity, improve function and overall satisfaction with their phy- sical/emotional/psychological health, improve perfor- mance status and well being, and ultimately determine whether survival duration can be prolonged by improv- ing the circadian organization of patients with advanced cancer. Conclusions These data suggest the testable possibility that beha- vioral, hormonal and/or light-based strategies to improve circadian organization may help patients suffer- ing from advanced lung cancer to feel and function better. Appendix 1. Circadian Parameters Used The following parameters described the activity phase of the daily circadian cycle: mean daily activity, mean duration of activity during wakefulness, mean duration of sleep during wakefulness, proportion of wakefulness spent sleeping, number of sleep episodes during wake- fulness, and frequency of long naps. During the pre- sumed sleep phase of the circadian cycle, the following parameters were evaluated: mean duration of wakeful- ness, number of sleep interruptions, proportion of sleep episode spent actually sleeping, and frequency of long duration of sleep. The number of accelerations per minute for a continuous 4-7 days was recorded through the actigraphy watch and was translated into sleep/activity parameters through the Act Millennium and Action W2 software (Ambulatory Monitoring, Inc.). Rhythmometric analysis (using Chronolab v2) was car- ried out on these sleep/activity patterns in order to Page 11 of 13 assess disruption and consolidation of sleep in lung can- cer patients. Rhythmometric analysis fits a cosine curve to the circadian activity providing three standard para- meters: mesor - the average activity over the 24-h per- iod, amplitude-peak to nadir difference and acrophase - the time of peak activity. In addition to these para- meters, peak activity (mesor+amplitude) to measure activity levels, the circadian quotient (amplitude/mesor) to characterize the strength of the circadian rhythm, and the rhythm quotient (A24 h/(A4 h+A8 h+A12 h)) were computed. A4 h, A8 h, and A12 h are the amplitudes of 4-hr, 8-hr and 12-hr cosine fits, respectively. Higher amplitudes indicate more robust rhythms but people who move vigorously would have higher amplitude, thus, the circadian quotient provides normalized values that would allow comparison between individuals [54,55]. We also looked at the dichotomy index (I < O), com- paring amounts of activity when in bed and out of bed, which is significantly associated with colorectal cancer patients’ quality of life and survival 14. I < O is the per- centage of minutes or epochs during the putative sleep span with activity score that are less than the median activity during the putative wakefulness. Thus, high I < O reflects a marked rest/activity rhythm 15 Further, cir- cadian rhythms were assessed through spectral density analysis where 24-hour autocorrelations (r24) were com- puted. Autocorrelations theoretically can range from 0 to1. If a circadian variation is present, autocorrelations will increase around 24-hour and a more pronounced and stable day-to-day circadian rhythm will result in a higher autocorrelation at 24-hour. Acknowledgements The study was funded by a peer-review grant provided by the Gateway for Cancer ResearchSM with support from the National Cancer Institute (1982- 2000 R01CA031635, WJMH) and by VA grants (1989-2006 Merit Award, WJMH; 1989-2001 Merit Award, PAW). Author details 1Cancer Treatment Centers of America®® at Midwestern Regional Medical Center, 2520 Elisha Ave. Zion, IL 60099, USA. 2School of Medicine University of South Carolina, 6311 Garners Ferry Road, Columbia, SC 29209, USA. 3School of Public Health, University of South Carolina, 800 Sumter Street, Columbia, SC 29208, USA. 4University of Illinois, School of Nursing, 845 South Damen Avenue, Chicago, IL 60612 USA. 5University of Illinois, School of Public Health, 1603 W. Taylor Street, Chicago, IL 60612, USA. Authors’ contributions JFG, CF, PAW, MAD, RDL, CGL and WJMH participated in the concept, design and data interpretation. JFG, JDQ, JLR, DPB, and WJMH were involved in the statistical analysis. JFG, JDQ, DG and WJMH were involved in the writing. DFTQ, JLR, CMA, EYO, MAD and RDL were involved in patient recruitment and data management. All authors read and approved the final manuscript. Competing interests The authors declare that they have no competing interests. Received: 22 March 2010 Accepted: 23 May 2011 Published: 23 May 2011