Multidisciplinary analysis of cancer-related fatigue at the time of diagnosis: preliminary results of the BIOCARE FActory cohort.

PURPOSE: Cancer-related fatigue (CRF) is a common side effect of cancer and cancer treatment that significantly impairs the quality of life and can persist for years after treatment completion. Although fatigue is often associated with cancer treatment, it is also a result of the disease itself, even before intervention. CRF at the time of diagnosis may affect treatment timing or completion and is a consistent predictor of post-treatment fatigue at any time. The mechanisms underlying CRF are multidimensional and not well understood, particularly at the time of diagnosis. METHODS: Sixty-five breast cancer patients at the time of diagnosis were included. The participants completed self-assessment questionnaires about CRF, sleep disturbances, and emotional symptoms and wore an accelerometer to assess levels of spontaneous physical activity and sleep quality. During the experimental session, the participants underwent cognitive, neuromuscular, and exercise metabolism evaluations. RESULTS: Using augmented backward elimination regression, this study found that emotional symptoms and perceived sleep disturbances were the strongest predictors of CRF (adjusted r2 = 0.51). Neuromuscular fatigability and sleep disturbance were also associated with physical dimensions, whereas cognitive performance was associated with cognitive dimensions. CONCLUSION: At the time of diagnosis, emotional and cognitive dimensions are over-represented compared to the general population, and specific subdimensions have specific predictors that support the idea of distinct mechanisms. Evaluating CRF subdimensions and their potential mechanisms at the time of diagnosis would be particularly relevant for identifying high-risk patients and offering them appropriate interventions. TRIAL REGISTRATION: This study was registered at ClinicalTrials.gov (NCT04391543) in May, 2020.

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.

Clinical validation of a prognostic tool in a population of outpatients treated for incurable cancer undergoing anticancer therapy: PRONOPALL study.

BACKGROUND: In 2008, a study of the characteristics of hospitalised patients led to the development of a prognostic tool that distinguished three populations with significantly different 2-month survival rates. The goal of our study aimed at validating prospectively this prognostic tool in outpatients treated for cancer in terminal stage, based on four factors: performance status (ECOG) (PS), number of metastatic sites, serum albumin and lactate dehydrogenase. PATIENTS AND METHODS: PRONOPALL is a multicentre study of current care. About 302 adult patients who met one or more of the following criteria: life expectancy under 6 months, performance status ≥ 2 and disease progression during the previous chemotherapy regimen were included across 16 institutions between October 2009 and October 2010. Afterwards, in order to validate the prognostic tool, the score was ciphered and correlated to patient survival. RESULTS: Totally 262 patients (87%) were evaluable (27 patients excluded and 13 unknown score). Median age was 66 years [37-88], and women accounted for 59%. ECOG PS 0-1 (46%), PS 2 (37%) and PS 3-4 (17%). The primary tumours were: breast (29%), colorectal (28%), lung (13%), pancreas (12%), ovary (11%) and other (8%). About 32% of patients presented one metastatic site, 35% had two and 31% had more than two. The median lactate dehydrogenase level was 398 IU/l [118-4314]; median serum albumin was 35 g/l [13-54]. According to the PRONOPALL prognostic tool, the 2-month survival rate was 92% and the median survival rate was 301 days [209-348] for the 130 patients in population C, 66% and 79 days [71-114] for the 111 patients in population B, and 24% and 35 days for [14-56] the 21 patients in population A. These three populations survival were statistically different (P <0.0001). CONCLUSION: PRONOPALL study confirms the three prognostic profiles defined by the combination of four factors. This PRONOPALL score is a useful decision-making tool in daily practice.