Introduction Around 25% of metastatic breast cancer (mBC) patients develop brain metastases, which vastly affects their overall survival and quality of life. According to the current clinical guidelines, regular magnetic resonance imaging screening is not recommended unless patients have recognized central nervous system-related symptoms. Patient Presentation The patient participated in the EFFECT study, a randomized controlled trial aimed to assess the effects of a 9-month structured, individualized and supervised exercise intervention on quality of life, fatigue and other cancer and treatment-related side effects in patients with mBC. She attended the training sessions regularly and was supervised by the same trainer throughout the exercise program. In month 7 of participation, her exercise trainer detected subtle symptoms (e.g., changes in movement pattern, eye movement or balance), which had not been noticed or reported by the patient herself or her family, and which were unlikely to have been detected by the oncologist or other health care providers at that point since symptoms were exercise related. When suspicion of brain metastases was brought to the attention of the oncologist by the exercise trainer, the response was immediate, and led to early detection and treatment of brain metastases. Conclusion and clinical implications The brain metastases of this patient were detected earlier due to the recognition of subtle symptoms detected by her exercise trainer and the trust and rapid action by the clinician. The implementation of physical exercise programs for cancer patients requires well-trained professionals who know how to recognize possible alterations in patients and also, good communication between trainers and the medical team to enable the necessary actions to be taken.
OBJECTIVE: To examine the use of a submaximal exercise test in detecting change in fitness level after a physical training program, and to investigate the correlation of outcomes as measured submaximally or maximally.DESIGN: A prospective study in which exercise testing was performed before and after training intervention.SETTING: Academic and general hospital and rehabilitation center.PARTICIPANTS: Cancer survivors (N=147) (all cancer types, medical treatment completed > or =3 mo ago) attended a 12-week supervised exercise program.INTERVENTIONS: A 12-week training program including aerobic training, strength training, and group sport.MAIN OUTCOME MEASURES: Outcome measures were changes in peak oxygen uptake (Vo(2)peak) and peak power output (both determined during exhaustive exercise testing) and submaximal heart rate (determined during submaximal testing at a fixed workload).RESULTS: The Vo(2)peak and peak power output increased and the submaximal heart rate decreased significantly from baseline to postintervention (P<.001). Changes in submaximal heart rate were only weakly correlated with changes in Vo(2)peak and peak power output. Comparing the participants performing submaximal testing with a heart rate less than 140 beats per minute (bpm) versus the participants achieving a heart rate of 140 bpm or higher showed that changes in submaximal heart rate in the group cycling with moderate to high intensity (ie, heart rate > or =140 bpm) were clearly related to changes in VO(2)peak and peak power output.CONCLUSIONS: For the monitoring of training progress in daily clinical practice, changes in heart rate at a fixed submaximal workload that requires a heart rate greater than 140 bpm may serve as an alternative to an exhaustive exercise test.
PURPOSE: In this study, we investigated factors associated with program adherence and patient satisfaction with a home-based physical activity program (Onco-Move, N = 77) and a supervised exercise program with a home-based component (OnTrack, N = 76).METHODS: We assessed adherence via self-report (home-based program) and attendance records (supervised program). We used logistic regression analysis to identify sociodemographic, clinical and behavioural variables associated with program adherence. Patient satisfaction was assessed with self-report and is reported descriptively.RESULTS: Fifty-one percent of Onco-Move and 62% of OnTrack participants were adherent to the home-based program, while 59% of OnTrack participants were adherent to the supervised sessions. Higher baseline physical fitness was associated with higher adherence to home-based components. Higher disease stage and having a partner were associated with adherence to OnTrack supervised sessions. Overall satisfaction with the exercise programs was high, but ratings of coaching provided by professionals for the home-based components were low. Patients offered suggestions for improving delivery of the programs.CONCLUSIONS: These findings point to factors relevant to program adherence and suggest ways in which such programs can be improved. Providing additional time and training for health care professionals could improve the quality and hopefully the effectiveness of the interventions. The use of online diaries and smartphone apps may provide additional encouragement to participants. Finally, allowing greater flexibility in the planning and availability of supervised exercise training in order to accommodate the variability in cancer treatment schedules and the (acute) side effects of the treatments could also enhance program adherence.TRIAL REGISTRATION: Netherlands Trial Register, NTR2159. http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=2159.
Low back pain is the leading cause of disability worldwide and a significant contributor to work incapacity. Although effective therapeutic options are scarce, exercises supervised by a physiotherapist have shown to be effective. However, the effects found in research studies tend to be small, likely due to the heterogeneous nature of patients' complaints and movement limitations. Personalized treatment is necessary as a 'one-size-fits-all' approach is not sufficient. High-tech solutions consisting of motions sensors supported by artificial intelligence will facilitate physiotherapists to achieve this goal. To date, physiotherapists use questionnaires and physical examinations, which provide subjective results and therefore limited support for treatment decisions. Objective measurement data obtained by motion sensors can help to determine abnormal movement patterns. This information may be crucial in evaluating the prognosis and designing the physiotherapy treatment plan. The proposed study is a small cohort study (n=30) that involves low back pain patients visiting a physiotherapist and performing simple movement tasks such as walking and repeated forward bending. The movements will be recorded using sensors that estimate orientation from accelerations, angular velocities and magnetometer data. Participants complete questionnaires about their pain and functioning before and after treatment. Artificial analysis techniques will be used to link the sensor and questionnaire data to identify clinically relevant subgroups based on movement patterns, and to determine if there are differences in prognosis between these subgroups that serve as a starting point of personalized treatments. This pilot study aims to investigate the potential benefits of using motion sensors to personalize the treatment of low back pain. It serves as a foundation for future research into the use of motion sensors in the treatment of low back pain and other musculoskeletal or neurological movement disorders.
