Wearable computing devices allow collection of densely sampled real-time information on movement enabling researchers and medical experts to obtain objective and non-obtrusive records of actual activity of a subject in the real world over many days. Our interest here is motivated by the use of activity data for evaluating and monitoring the circadian rhythmicity of subjects for research in chronobiology and chronotherapeutic healthcare. In order to translate the information from such high-volume data arising we propose the use of a Markov modelling approach which (i) naturally captures the notable square wave form observed in activity data along with heterogeneous ultradian variances over the circadian cycle of human activity, (ii) thresholds activity into different states in a probabilistic way while respecting time dependence and (iii) gives rise to circadian rhythm parameter estimates, based on probabilities of transitions between rest and activity, that are interpretable and of interest to circadian research.

BackgroundPsychosocial symptoms often cluster together, are refractory to treatment, and impair health‐related quality of life (HR‐QoL) in cancer patients. The contribution of circadian rhythm alterations to systemic symptoms has been overlooked in cancer, despite a causal link shown under jet lag and shift work conditions. We investigated whether the circadian rest‐activity rhythm provides a reliable and objective estimate of the most frequent patient‐reported outcome measures (PROMs).MethodsTwo datasets were used, each involving concomitant 3‐day time series of wrist actigraphy and HR‐QoL questionnaires: EORTC QLQ‐C30 was completed once by 237 patients with metastatic colorectal cancer; MD Anderson Symptom Inventory (MDASI) was completed daily by 31 patients with advanced cancer on continuous actigraphy monitoring, providing 1015 paired data points. Circadian function was assessed using the clinically validated dichotomy index I < O. Nonparametric tests compared PROMs and I < O. Effect sizes were computed. Sensitivity subgroup and temporal dynamics analyses were also performed.Results I < O values were significantly lower with increasing symptom severity and worsening HR‐QoL domains. Fatigue and anorexia were worse in patients with circadian disruption. The differences were both statistically and clinically significant (P < 0.001; d ≥ 0.33). Physical and social functioning, and global quality/enjoyment of life were significantly better in patients with robust circadian rhythm (P < 0.001; d ≥ 0.26). Sensitivity analyses validated these findings.ConclusionObjectively determined circadian disruption was consistently and robustly associated with clinically meaningfully severe fatigue, anorexia, and interference with physical and social functioning. This supports an important role of the circadian system in the determination of cancer patients’ HR‐QoL and symptoms that deserves therapeutic exploitation.

BackgroundTelehealth solutions can improve the safety of ambulatory chemotherapy, contributing to the maintenance of patients at their home, hence improving their well-being, all the while reducing health care costs. There is, however, need for a practicable multilevel monitoring solution, encompassing relevant outputs involved in the pathophysiology of chemotherapy-induced toxicity. Domomedicine embraces the delivery of complex care and medical procedures at the patient’s home based on modern technologies, and thus it offers an integrated approach for increasing the safety of cancer patients on chemotherapy.ObjectiveThe objective was to evaluate patient compliance and clinical relevance of a novel integrated multiparametric telemonitoring domomedicine platform in cancer patients receiving multidrug chemotherapy at home.MethodsSelf-measured body weight, self-rated symptoms using the 19-item MD Anderson Symptom Inventory (MDASI), and circadian rest-activity rhythm recording with a wrist accelerometer (actigraph) were transmitted daily by patients to a server via the Internet, using a dedicated platform installed at home. Daily body weight changes, individual MDASI scores, and relative percentage of activity in-bed versus out-of-bed (I

BackgroundExperimental and epidemiologic studies have shown that circadian clocks’ disruption can play an important role in the development of cancer and metabolic diseases. The cellular clocks outside the brain are effectively coordinated by the body temperature rhythm. We hypothesized that concurrent measurements of body temperature and rest-activity rhythms would assess circadian clocks coordination in individual patients, thus enabling the integration of biological rhythms into precision medicine.ObjectiveThe objective was to evaluate the circadian clocks’ coordination in healthy subjects and patients through simultaneous measurements of rest-activity and body temperature rhythms.MethodsNoninvasive real-time measurements of rest-activity and chest temperature rhythms were recorded during the subject’s daily life, using a dedicated new mobile electronic health platform (PiCADo). It involved a chest sensor that jointly measured accelerations, 3D orientation, and skin surface temperature every 1-5 min and relayed them out to a mobile gateway via Bluetooth Low Energy. The gateway tele-transmitted all stored data to a server via General Packet Radio Service every 24 hours. The technical capabilities of PiCADo were validated in 55 healthy subjects and 12 cancer patients, whose rhythms were e-monitored during their daily routine for 3-30 days. Spectral analyses enabled to compute rhythm parameters values, with their 90% confidence limits, and their dynamics in each subject.ResultsAll the individuals displayed a dominant circadian rhythm in activity with maxima occurring from 12:09 to 20:25. This was not the case for the dominant temperature period, which clustered around 24 hours for 51 out of 67 subjects (76%), and around 12 hours for 13 others (19%). Statistically significant sex- and age-related differences in circadian coordination were identified in the noncancerous subjects, based upon the range of variations in temperature rhythm amplitudes, maxima (acrophases), and phase relations with rest-activity. The circadian acrophase of chest temperature was located at night for the majority of people, but it occurred at daytime for 26% (14/55) of the noncancerous people and 33% (4/12) of the cancer patients, thus supporting important intersubject differences in circadian coordination. Sex, age, and cancer significantly impacted the circadian coordination of both rhythms, based on their phase relationships.ConclusionsComplementing rest-activity with chest temperature circadian e-monitoring revealed striking intersubject differences regarding human circadian clocks’ coordination and timing during daily routine. To further delineate the clinical importance of such finding, the PiCADo platform is currently applied for both the assessment of health effects resulting from atypical work schedules and the identification of the key determinants of circadian disruption in cancer patients.

The dichotomy index (I < O), a quantitative estimate of the circadian regulation of daytime activity and sleep, predicted overall cancer survival and emergency hospitalization, supporting its integration in a mHealth platform. Modifiable causes of I < O deterioration below 97.5%—(I < O)low—were sought in 25 gastrointestinal cancer patients and 33 age- and sex-stratified controls. Rest-activity and temperature were tele-monitored with a wireless chest sensor, while daily activities, meals, and sleep were self-reported for one week. Salivary cortisol rhythm and dim light melatonin onset (DLMO) were determined. Circadian parameters were estimated using Hidden Markov modelling, and spectral analysis. Actionable predictors of (I < O)low were identified through correlation and regression analyses. Median compliance with protocol exceeded 95%. Circadian disruption—(I < O)low—was identified in 13 (52%) patients and four (12%) controls (p = 0.002). Cancer patients with (I < O)low had lower median activity counts, worse fragmented sleep, and an abnormal or no circadian temperature rhythm compared to patients with I < O exceeding 97.5%—(I < O)high—(p < 0.012). Six (I < O)low patients had newly-diagnosed sleep conditions. Altered circadian coordination of rest-activity and chest surface temperature, physical inactivity, and irregular sleep were identified as modifiable determinants of (I < O)low. Circadian rhythm and sleep tele-monitoring results support the design of specific interventions to improve outcomes within a patient-centered systems approach to health care.

Purpose To assess the impact of chronomodulated irinotecan fluorouracil-leucovorin and oxaliplatin (chronoIFLO4) delivered at home on the daily life of patients with cancer in real time using a home-based e-Health multifunction and multiuser platform. This involved multidimensional telemonitoring of circadian rest-activity rhythm (CircAct), sleep, patient-reported outcome measures, and body weight changes (BWCs). Patients and Methods Patients received chronoIFLO4 fortnightly at home. Patients completed the 19-item MD Anderson Symptom Inventory on an interactive electronic screen, weighed themselves on a dedicated scale, and continuously wore a wrist accelerometer for CircAct and sleep monitoring. Daily data were securely teletransmitted to a specific server accessible by the hospital team. The clinically relevant CircAct parameter dichotomy index I < O and sleep efficiency (SE) were calculated. The dynamic patterns over time of patient-reported outcome measures, BWC, I < O, and SE informed the oncology team on tolerance in real time. Results The platform was installed in the home of 11 patients (48 to 72 years of age; 45% men; 27% with performance status = 0), who were instructed on its use on site. They received 26 cycles and provided 5,891 data points of 8,736 expected (67.4%). The most severe MD Anderson Symptom Inventory scores were: interference with work (mean: 5.1 of 10) or general activity (4.9), fatigue (4.9), distress (4.2), and appetite loss (3.6). Mean BWC was −0.9%, and mean SE remained > 82%. CircAct disruption (I < O ≤ 97.5%) was observed in four (15%) cycles before chronoIFLO4 start and in five (19%) cycles at day 14. Conclusion The patient-centered multidimensional telemonitoring solution implemented here was well accepted by patients receiving multidrug chemotherapy at home. Moreover, it demonstrated that chronoIFLO4 was a safe therapeutic option. Such integrated technology allows the design of innovative management approaches, ultimately improving patients’ experience with chemotherapy, wellbeing, and outcomes.

BACKGROUNDCircadian timing of treatments can largely improve tolerability and efficacy in patients. Thus, drug metabolism and cell cycle are controlled by molecular clocks in each cell and coordinated by the core body temperature 24-hour rhythm, which is generated by the hypothalamic pacemaker. Individual circadian phase is currently estimated with questionnaire-based chronotype, center-of-rest time, dim light melatonin onset (DLMO), or timing of core body temperature (CBT) maximum (acrophase) or minimum (bathyphase).METHODSWe aimed at circadian phase determination and readout during daily routines in volunteers stratified by sex and age. We measured (a) chronotype, (b) every minute (q1min) CBT using 2 electronic pills swallowed 24 hours apart, (c) DLMO through hourly salivary samples from 1800 hours to bedtime, and (d) q1min accelerations and surface temperature at anterior chest level for 7 days, using a teletransmitting sensor. Circadian phases were computed using cosinor and hidden Markov modeling. Multivariate regression identified the combination of biomarkers that best predicted core temperature circadian bathyphase.RESULTSAmong the 33 participants, individual circadian phases were spread over 5 hours, 10 minutes (DLMO); 7 hours (CBT bathyphase); and 9 hours, 10 minutes (surface temperature acrophase). CBT bathyphase was accurately predicted, i.e., with an error less than 1 hour for 78.8% of the subjects, using a new digital health algorithm (INTime), combining time-invariant sex and chronotype score with computed center-of-rest time and surface temperature bathyphase (adjusted R2 = 0.637).CONCLUSIONINTime provided a continuous and reliable circadian phase estimate in real time. This model helps integrate circadian clocks into precision medicine and will enable treatment timing personalization following further validation.FUNDINGMedical Research Council, United Kingdom; AP-HP Foundation; and INSERM.

Subjective sleep assessment in cancer patients poorly correlates with actigraphy parameters that usually encompass multiple nights. We aimed to determine the objective actigraphy measures that best correlated with subjective sleep ratings on a night-by-night basis in cancer patients. Thirty-one cancer patients daily self-rated sleep disturbances using the single dedicated item of the MD Anderson Symptom Inventory (0–10 scale) with 18 other items, and continuously wore a wrist actigraph for 30 days. Objective sleep parameters were computed from the actigraphy nighttime series, and correlated with subjective sleep disturbances reported on the following day, using repeated measures correlations. Multilevel Poisson regression analysis was performed to identify the objective and subjective parameters that affected subjective sleep rating. Poor subjective sleep score was correlated with poor sleep efficiency (rrm = −0.13, p = 0.002) and large number of wake episodes (rrm = 0.12, p = 0.005) on the rated night. Multilevel analysis demonstrated that the expected sleep disturbance score was affected by the joint contribution of the wake episodes (exp(β) = 1.01, 95% confidence interval = 1.00 to 1.02, p = 0.016), fatigue (exp(β) = 1.35, 95% confidence interval = 1.15 to 1.55, p < 0.001) and drowsiness (exp(β) = 1.70, 95% confidence interval = 1.19 to 2.62, p = 0.018), self-rated the following evening, and sleep disturbance experienced one night before (exp(β) = 1.77, 95% confidence interval = 1.41 to 2.22, p < 0.001). The night-by-night approach within a multidimensional home tele-monitoring framework mainly identified the objective number of wake episodes computed from actigraphy records as the main determinant of the severity of sleep complaint in cancer patients on chemotherapy. This quantitative information remotely obtained in real time from cancer patients provides a novel framework for streamlining and evaluating interventions toward sleep improvement in cancer patients.