Sleep Disorders and Quality of Life in Patients With Cancer: Prospective Observational Study of the Rafael Institute.

BACKGROUND: Sleep disorders are a common occurrence in the general population. Yet today, it is clearly agreed that sleep disorders represent both a cancer risk factor and a biological consequence of the of the activation of the immuno-inflammatory system induced by cancer itself. OBJECTIVE: The aim of this study was to assess the impact of sleep disorders on quality of life and identify the type of disorder and its causes in order to offer an adapted and personalized care plan. METHODS: In a survey completed during the COVID-19 lockdown, 2000 hours of interviews were collected by remote consultations. During these calls, we administered a sleep questionnaire. This questionnaire was inspired by the STOP-BANG questionnaire and enquired about 6 items. The demographic details of each patient (eg, age and sex), the nature of the pathology, their past treatments, the ongoing cancer treatment, the mood, whether or not the patient is anxious or depressed, and the use of sleeping drug pills were analyzed. A univariate analysis was performed according to the presence or absence of fatigue. Chi-square test was applied to assess possible differences of variables' link to sleep disturbance between patients complaining of fatigue and those without fatigue. The same test was then used to analyze patients on hormone therapy and those with no hormone therapy for 2 types of cancer-breast cancer and prostate cancer. RESULTS: A total of 905 patients were prospectively included in this study. The average age was 66.7 (5 SD) years, and 606 (67%) patients were women; 142 patients declared being overweight. Breast cancer was the most frequently reported cancer. Nocturnal awakening was reported by 70% (n=633), fatigue by 50% (n=452), difficulty falling asleep by 38% (n=343), snoring reported by an independent observer in 38% (n=343), and apnea reported by an independent observer in 9% (n=81) of the patients. The univariate analysis showed that the feeling of tiredness was significantly greater in patients reporting difficulty falling asleep (P≥.99), pain (P<.001), and frequent awakening (P<.001), as well as in patients who were not receiving cancer treatment (P<.001). The univariate analysis showed that patients who were receiving breast cancer treatment and were under hormone therapy reported difficulty falling asleep (P=.04) and pain (P=.05). In a univariate analysis of patients treated for prostate cancer, being overweight was the only factor reported that had a statistically significant value. CONCLUSIONS: Our preliminary data support and are consistent with data in the literature regarding the importance of sleep disorders in oncology. This justifies the usefulness of a diagnosis and early treatment of sleep disorders in patients with cancer. The Rafael Institute sleep observatory will enable patients to be identified and treated.

French-style genetics v. 2.0: The "e-CohortE" project.

In the digital age, a genetics cohort has become much more than a simple means of determining the cause of a disease. Two-sided markets, of which 23andMe, Ancestry DNA and MyHeritage are the best known, have showed this perfectly over the last few years: a cohort has become a means of producing massive amounts of data for medical, scientific and commercial exploitation, and for genetic use in particular. French law does not currently allow these foreign private companies to develop on French national territory and also forbids the creation of similar entities in France. However, at least in theory, this same law does not preclude the creation of new types of cohorts in France inspired by the success of two-sided markets but retaining features specific to the French healthcare management system. We propose an optimal solution for France, for genomic studies associated with multi-subject questionnaires, still purely theoretical for the moment: the development, with no need for any change in the law, of France's own version of "Genetics v.2.0": "e-CohortE."

Parameter identification of a model for prostate cancer treated by intermittent therapy.

Adenocarcinoma is the most frequent cancer affecting the prostate walnut-size gland in the male reproductive system. Such cancer may have a very slow progression or may be associated with a "dark prognosis" when tumor cells are spreading very quickly. Prostate cancers have the particular properties to be marked by the level of prostate specific antigen (PSA) in blood which allows to follow its evolution. At least in its first phase, prostate adenocarcinoma is most often hormone-dependent and, consequently, hormone therapy is a possible treatment. Since few years, hormone therapy started to be provided intermittently for improving patient's quality of life. Today, durations of on- and off-treatment periods are still chosen empirically, most likely explaining why there is no clear benefit from the survival point of view. We therefore developed a model for describing the interaction between the tumor environment, the PSA produced by hormone-dependent and hormone-independent tumor cells, respectively, and the level of androgens. Model parameters were identified using a genetic algorithm applied to the PSA time series measured in a few patients who initially received prostatectomy and were then treated by intermittent hormone therapy (LHRH analogs and anti-androgen). The measured PSA time series is quite correctly reproduced by free runs over the whole follow-up. Model parameter values allow for distinguishing different types of patient (age and Gleason score) meaning that the model can be individualized. We thus showed that the long-term evolution of the cancer can be affected by durations of on- and off-treatment periods.

How the growth rate of host cells affects cancer risk in a deterministic way.

It is well known that cancers are significantly more often encountered in some tissues than in other ones. In this paper, by using a deterministic model describing the interactions between host, effector immune and tumor cells at the tissue level, we show that this can be explained by the dependency of tumor growth on parameter values characterizing the type as well as the state of the tissue considered due to the "way of life" (environmental factors, food consumption, drinking or smoking habits, etc.). Our approach is purely deterministic and, consequently, the strong correlation (r = 0.99) between the number of detectable growing tumors and the growth rate of cells from the nesting tissue can be explained without evoking random mutation arising during DNA replications in nonmalignant cells or "bad luck". Strategies to limit the mortality induced by cancer could therefore be well based on improving the way of life, that is, by better preserving the tissue where mutant cells randomly arise.

Spatial avascular growth of tumor in a homogeneous environment.

Describing tumor growth is a key issue in oncology for correctly understanding the underlying mechanisms leading to deleterious cancers. In order to take into account the micro-environment in tumor growth, we used a model describing - at the tissue level - the interactions between host (non malignant), effector immune and tumor cells to simulate the evolution of cancer. The spatial growth is described by a Laplacian operator for the diffusion of tumor cells. We investigated how the evolution of the tumor diameter is related to the dynamics (periodic or chaotic oscillations, stable singular points) underlying the interactions between the different populations of cells in proliferation sites. The sensitivity of this evolution to the key parameter responsible for the immuno-evasion, namely the growth rate of effector immune cells and their inhibition rate by tumor cells, is also investigated.