Building a biopsychosocial model of cancer-related fatigue: the BIOCARE FActory cohort study protocol.

BACKGROUND: Cancer-related fatigue (CRF) is the most common side effect of cancer and cancer treatment. CRF prevalence is up to 50% in breast cancer patients and can continue several years after cancer remission. This persistent subjective sense of exhaustion is multifactorial. Numerous parameters have been evidenced to be related to CRF across biological, physical, psychological, social and/or behavioral dimensions. Although CRF has been studied for many years, the majority of previous studies focused on only one dimension, i.e., physical function. Moreover, few studies investigated CRF longitudinally with repeated measures. These are the two main obstacles that limit the understanding of CRF mechanisms. The purpose of this study is to create a biopsychosocial model of CRF with simultaneous and longitudinal anthropometric, clinical, biological, physical, psychological and sociological parameters. METHODS: BIOCARE FActory is a multicentric prospective study that will consist of an 18-month follow-up of 200 women diagnosed with breast cancer. Four visits will be scheduled at diagnosis, after treatments, and 12 and 18 months after diagnosis. The same procedure will be followed for each visit. Each session will be composed of anthropometric data collection, a semi-structured interview, cognitive tests, postural control tests, neuromuscular fatigability tests and a cardiorespiratory fitness test. Clinical and biological data will be collected during medical follow-ups. Participants will also complete questionnaires to assess psychological aspects and quality of life and wear an actigraphy device. Using a structural equation modeling analysis (SEM), collected data will build a biopsychosocial model of CRF, including the physiological, biological, psychological, behavioral and social dimensions of CRF. DISCUSSION: This study aims to highlight the dynamics of CRF and its correlates from diagnosis to post treatment. SEM analysis could examine some relations between potential mechanisms and CRF. Thus, the biopsychosocial model will contribute to a better understanding of CRF and its underlying mechanisms from diagnosis to the aftermaths of cancer and its treatments. TRIAL REGISTRATION: This study is registered at ClinicalTrials.gov ( NCT04391543 ), May 2020.

Handgrip fatiguing exercise can provide objective assessment of cancer-related fatigue: a pilot study.

PURPOSE: As a subjective symptom, cancer-related fatigue is assessed via patient-reported outcomes. Due to the inherent bias of such evaluation, screening and treatment for cancer-related fatigue remains suboptimal. The purpose is to evaluate whether objective cancer patients' hand muscle mechanical parameters (maximal force, critical force, force variability) extracted from a fatiguing handgrip exercise may be correlated to the different dimensions (physical, emotional, and cognitive) of cancer-related fatigue. METHODS: Fourteen women with advanced breast cancer, still under or having previously received chemotherapy within the preceding 3 months, and 11 healthy women participated to the present study. Cancer-related fatigue was first assessed through the EORTC QLQ-30 and its fatigue module. Fatigability was then measured during 60 maximal repeated handgrip contractions. The maximum force, critical force (asymptote of the force-time evolution), and force variability (root mean square of the successive differences) were extracted. Multiple regression models were performed to investigate the influence of the force parameters on cancer-related fatigue's dimensions. RESULTS: The multiple linear regression analysis evidenced that physical fatigue was best explained by maximum force and critical force (r = 0.81; p = 0.029). The emotional fatigue was best explained by maximum force, critical force, and force variability (r = 0.83; p = 0.008). The cognitive fatigue was best explained by critical force and force variability (r = 0.62; p = 0.035). CONCLUSION: The handgrip maximal force, critical force, and force variability may offer objective measures of the different dimensions of cancer-related fatigue and could provide a complementary approach to the patient reported outcomes.

Neuromuscular fatigue in healthy muscle: underlying factors and adaptation mechanisms.

OBJECTIVES: This review aims to define the concept of neuromuscular fatigue and to present the current knowledge of the central and peripheral factors at the origin of this phenomenon. This review also addresses the literature that focuses on the mechanisms responsible for the adaption to neuromuscular fatigue. METHOD: One hundred and eighty-two articles indexed in PubMed (1954-2010) have been considered. RESULTS: Neuromuscular fatigue has central and peripheral origins. Central fatigue, preponderant during long-duration, low-intensity exercises, may involve a drop in the central command (motor, cortex, motoneurons) elicited by the activity of cerebral neurotransmitters and muscular afferent fibers. Peripheral fatigue, associated with an impairment of the mechanisms from excitation to muscle contraction, may be induced by a perturbation of the calcium ion movements, an accumulation of phosphate, and/or a decrease of the adenosine triphosphate stores. To compensate for the consequent drop in force production, the organism develops several adaptation mechanisms notably implicating motor units. CONCLUSION: Fatigue onset is associated with an alteration of the mechanisms involved in force production. Then, the interaction between central and peripheral mechanisms leads to a series of events that ultimately contribute to the observed decrease in force production.

Thigh muscle activities in elite rowers during on-water rowing.

This study analysed the muscle activity levels and patterns of the major thigh muscle activation during training sections at different intensities of on-water rowing. 9 experienced rowers performed 2 imposed-pace sections (B1 and B2) and 2 maximal-speed sections (start, 500 m) of on-water rowing. The knee angle, power output, mean torque and stroke rate were measured using specific instrumentation and were synchronised with surface electromyography signals of 5 superficial quadriceps and hamstring muscles. B1 and B2 sections were not significantly different regarding mechanical parameters and EMG activities, while the start phase induced large differences. The EMG patterns for B1, B2 were similar (cross-correlation coefficients (CC) ranged between 0.972-0.984) and the moderate CC found between both B1 and start (0.605-0.720) and B2 and start (0.629-0.720). Our results suggest that the hamstring muscles have a motor action and contribute to the power production during the leg drive. During an all-out 500 m section, a decrease in power and stroke rate was found (up to 20%). However, EMG patterns were not time shifted for all muscles. During the leg drive, the muscle activity levels of the quadriceps muscles were unchanged, while the activity of the hamstring muscles decreased.

Changes in sEMG parameters among trunk and thigh muscles during a fatiguing bilateral isometric multi-joint task in trained and untrained subjects.

This study aimed to explore changes in the electrical activity distribution among synergist muscles involved in the maintenance of this bilateral multi-joint task. It also tested relations between changes in surface electromyographic (sEMG) parameters with endurance time. Eighteen subjects, trained and untrained in hiking, performed a submaximal (50% of maximal contraction) isometric hiking test until exhaustion. The electrical activity of main superficial muscles implicated in this posture was recorded bilaterally. Trained subjects sustained the hiking position for 315+/-82 s, versus 225+/-68 s for untrained subjects. Patterns of electrical activity and mean power frequency (MPF) were different between populations. MPF shift in abdominal muscles was higher than in other synergists for both groups. Although typical changes in sEMG parameters were observed, few relations with endurance time were found, and for untrained subjects only. Changes in the relative contribution among synergists were observed, mainly for trained subjects. It is hypothesized that the task (a complex multi-joint posture involving numerous joints and muscles) may allow some variability in the contribution of synergist muscles during fatigue especially for the trained group. This probably explains the absence of relationship between endurance time and sEMG changes for trained subjects.

Specific neuromuscular responses of high skilled laser sailors during a multi-joint posture sustained until exhaustion.

The aim of this study was to examine the myoelectric manifestations of neuromuscular fatigue induced by a sustained bout of hiking with regard to training status, laterality and muscle. Nineteen subjects, separated into three different groups according to their training status in hiking, volunteered to take part in this study. Subjects performed a sustained hiking test until exhaustion at 50 % of the maximal hiking torque on a specially developed hiking ergometer. The electrical activity of two bilateral (left and right sides) muscular chains involved in hiking including the rectus abdominis (RA), rectus femoris (RF), vastus lateralis (VL), and tibialis anterior (TA) muscles was explored using surface electromyography. Results indicated a higher endurance time (Tlim) for the highly trained group in hiking (45 %, p < 0.05). The mean electrical activity of the muscles studied reached a medium level at the end of the sustained hiking period (51 % of maximal values, p < 0.001), regardless of the training status. However, the increase in activation level was delayed in hikers (50 % Tlim) compared to non-hikers (25 % Tlim), especially for rectus abdominis and rectus femoris muscles. Furthermore, activation patterns of synergistic muscles differed among the groups so that electrical activity of knee extensors was higher than that of trunk flexors of hikers at the end of hiking task (e.g., left RA: 32 % vs. left VL: 54 % of maximal values, p < 0.001). Shifts in mean power frequency were more pronounced in rectus abdominis muscles (- 24 %, p < 0.001) than in rectus femoris (- 7 %, p < 0.001) and vastus lateralis (unchanged), regardless of the group. Hikers exhibited a lower and more delayed spectral compression (left side: - 1.3 %, right side: - 9.8 %) compared to non-hikers (left and right sides: - 15.1 %). These findings suggest that hikers prolonged endurance time by adjusting neural distribution of activity among synergists, thereby minimizing the contribution of the most fatigable muscles, such as the trunk flexors.

Power responses of a rowing ergometer: mechanical sensors vs. Concept2 measurement system.

The aim of this study was to compare the power provided by a recent ergometer with the power developed by the rower determined using mechanical sensors set on the same apparatus. Six rowers and six non-rowers performed a power graded test and an all-out start on an instrumented ergometer (Concept2 system, model D, Morrisville, VT, USA). Power values displayed by the ergometer were recorded with a specific software. A strain gauge placed near the handle and a position sensor installed on the chain allowed the calculation of the power developed by the rower. Power values provided by the ergometer were strongly correlated to those determined with a direct measurement and calculation of power. However, power values given by the Concept2 system were lower (- 17.4 to - 72.4 W) than those calculated using mechanical sensors. This difference in power measurements was lower at a steady pace and for rowers. The Concept2 system underestimates the power produced by the rower by approximately 25 W. This difference in power seems to be independent of the level of power developed but increases with variations in intensity and pace. The deletion of the first strokes following changes in power production allows to limit this phenomenon. According to the use of the power parameter in the experimental design, it could be appropriate to correct values provided by the Concept2 ergometer.