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BACKGROUND: The-Optimal-Lymph-Flow (TOLF) is a patient-centered, web- and mobile-based mHealth system that delivers safe, easy, and feasible digital therapy of lymphatic exercises and limb mobility exercises. OBJECTIVE: The purpose of this randomized clinical trial (RCT) was to evaluate the effectiveness of the web- and mobile-based TOLF system for managing chronic pain and symptoms related to lymphedema. The primary outcome includes pain reduction, and the secondary outcomes focus on symptom relief, limb volume difference measured by infrared perometer, BMI, and quality of life (QOL) related to pain. We hypothesized that participants in the intervention group would have improved pain and symptom experiences, limb volume difference, BMI, and QOL. METHODS: A parallel RCT with a control-experimental, pre- and posttest, and repeated-measures design were used. A total of 120 patients were recruited face-to-face at the point of care during clinical visits. Patients were randomized according to pain in a 1:1 ratio into either the arm precaution (AP) control group to improve limb mobility and arm protection or The-Optimal-Lymph flow (TOLF) intervention group to promote lymph flow and limb mobility. Trial outcomes were evaluated at baseline and at week 12 after the intervention. Descriptive statistics, Fisher exact tests, Wilcoxon rank-sum tests, t test, and generalized linear mixed effects models were performed for data analysis. RESULTS: At the study endpoint of 12 weeks, significantly fewer patients in the TOLF intervention group compared with the AP control group reported chronic pain (45% [27/60] vs 70% [42/60]; odds ratio [OR] 0.39, 95% CI 0.17-0.90; P=.02). Patients who received the TOLF intervention were significantly more likely to achieve a complete reduction in pain (50% [23/46] vs 22% [11/51]; OR 3.56, 95% CI 1.39-9.76; P=.005) and soreness (43% [21/49] vs 22% [11/51]; OR 2.60, 95% CI 1.03-6.81; P=.03). Significantly lower median severity scores were found in the TOLF group for chronic pain (MedTOLF=0, IQR 0-1 vs MedAP=1, IQR 0-2; P=.02) and general bodily pain (MedTOLF=1, IQR=0-1.5 vs MedAP=1, IQR 1-3; P=.04). Compared with the AP control group, significantly fewer patients in the TOLF group reported arm/hand swelling (P=.04), heaviness (P=.03), redness (P=.03), and limited movement in shoulder (P=.02) and arm (P=.03). No significant differences between the TOLF and AP groups were found in complete reduction of aching (P=.12) and tenderness (P=.65), mean numbers of lymphedema symptom reported (P=.11), ≥5% limb volume differences (P=.48), and BMI (P=.12). CONCLUSIONS: The TOLF intervention had significant benefits for breast cancer survivors to manage chronic pain, soreness, general bodily pain, arm/hand swelling, heaviness, and impaired limb mobility. The intervention resulted in a 13% reduction (from 40% [24/60] to 27% [16/60]) in proportions of patients who took pain medications compared with the AP control group, which had a 5% increase (from 40% [24/60] to 45% [27/60]). A 12% reduction (from 27% [16/60] to 15% [9/60]) in proportions of patients with ≥5% limb volume differences was found in the TOLF intervention, while a 5% increase in the AP control group (from 40% [24/60] to 45% [27/60]) was found. In conclusion, the TOLF intervention can be a better choice for breast cancer survivors to reduce chronic pain and limb volume. TRIAL REGISTRATION: Clinicaltrials.gov NCT02462226; https://clinicaltrials.gov/ct2/show/NCT02462226. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/resprot.5104.
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Lymphatic pain and swelling due to lymph fluid accumulation are the most common and debilitating long-term adverse effects of cancer treatment. This study aimed to quantify the effects of obesity on lymphatic pain, arm, and truncal swelling. Methods: A sample of 554 breast cancer patients were enrolled in the study. Body mass index (BMI), body fat percentage, and body fat mass were measured using a bioimpedance device. Obesity was defined as a BMI ≥ 30 kg/m2. The Breast Cancer and Lymphedema Symptom Experience Index was used to measure lymphatic pain, arm, and truncal swelling. Multivariable logistic regression models were used to estimate the odds ratio (OR) with 95% confidence interval (CI) to quantify the effects of obesity. Results: Controlling for clinical and demographic characteristics as well as body fat percentage, obesity had the greatest effects on lymphatic pain (OR 3.49, 95% CI 1.87-6.50; p < 0.001) and arm swelling (OR 3.98, 95% CI 1.82-4.43; p < 0.001). Conclusions: Obesity is a significant risk factor for lymphatic pain and arm swelling in breast cancer patients. Obesity, lymphatic pain, and swelling are inflammatory conditions. Future study should explore the inflammatory pathways and understand the molecular mechanisms to find a cure.
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BACKGROUND: Lymphedema is a progressive and chronic illness. Early detection and treatment often lead to better clinical outcomes and improvement of patients' quality of life. Lymphedema symptoms can assist in detecting lymphedema. However, the use of patient-reported symptom evaluation is still limited in clinical practice. To address this gap in clinical practice, a metropolitan cancer center implemented an electronic patient evaluation of lymphedema symptoms (EPE-LE) to enable patients' real-time symptom report during patients' routine clinical visit while waiting to see their doctors in a waiting room. The purpose of this clinical project was to evaluate the usefulness of EPE-LE during patients' routine clinical visit. METHODS: A cross-sectional design was used. Participants were outpatient post-surgical breast cancer patients and clinicians who were involved in the EPE-LE implementation at a metropolitan cancer center of US. Data were collected during the three-month EPE-LE implementation, including patients' report of lymphedema symptoms, patient and clinician satisfaction, and referral to lymphedema specialists. Descriptive statistics were used for data analysis. RESULTS: During the three-month implementation, a total of 334 patients utilized the EPE-LE to report their lymphedema symptoms and 24 referrals to lymphedema specialists. Nearly all of the patients found that the EPE-LE was easy to use (91%) and that they were satisfied with the EPE-LE for reporting lymphedema symptoms (89%). The majority (70%) of patients reported that the EPE-LE helped them to learn about symptoms related to lymphedema and encouraged them to monitor their symptoms. All clinicians (100%) agreed that the use of the EPE-LE improved their lymphedema symptom assessment in post-surgical breast cancer patients; 75% reported that the EPE-LE increased their communication with patients related to lymphedema symptoms, 75% agreed they would recommend the EPE-LE for use at other cancer centers, and 75% reported that the information retrieved from the EPE-LE was helpful in evaluation of lymphedema. CONCLUSIONS: The use of EPE-LE enhanced patients' real-time report of lymphedema symptoms, improved patient education on lymphedema symptoms, and helped clinicians for evaluation of lymphedema. The use of EPE-LE is an example how to implement evidence-based research into clinical practice that provides benefits for both patients and clinicians.
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BACKGROUND: In the digital era when mHealth has emerged as an important venue for health care, the application of computer science, such as machine learning, has proven to be a powerful tool for health care in detecting or predicting various medical conditions by providing improved accuracy over conventional statistical or expert-based systems. Symptoms are often indicators for abnormal changes in body functioning due to illness or side effects from medical treatment. Real-time symptom report refers to the report of symptoms that patients are experiencing at the time of reporting. The use of machine learning integrating real-time patient-centered symptom report and real-time clinical analytics to develop real-time precision prediction may improve early detection of lymphedema and long term clinical decision support for breast cancer survivors who face lifelong risk of lymphedema. Lymphedema, which is associated with more than 20 distressing symptoms, is one of the most distressing and dreaded late adverse effects from breast cancer treatment. Currently there is no cure for lymphedema, but early detection can help patients to receive timely intervention to effectively manage lymphedema. Because lymphedema can occur immediately after cancer surgery or as late as 20 years after surgery, real-time detection of lymphedema using machine learning is paramount to achieve timely detection that can reduce the risk of lymphedema progression to chronic or severe stages. This study appraised the accuracy, sensitivity, and specificity to detect lymphedema status using machine learning algorithms based on real-time symptom report. METHODS: A web-based study was conducted to collect patients' real-time report of symptoms using a mHealth system. Data regarding demographic and clinical information, lymphedema status, and symptom features were collected. A total of 355 patients from 45 states in the US completed the study. Statistical and machine learning procedures were performed for data analysis. The performance of five renowned classification algorithms of machine learning were compared: Decision Tree of C4.5, Decision Tree of C5.0, gradient boosting model (GBM), artificial neural network (ANN), and support vector machine (SVM). Each classification algorithm has certain user-definable hyper parameters. Five-fold cross validation was used to optimize these hyper parameters and to choose the parameters that led to the highest average cross validation accuracy. RESULTS: Using machine leaning procedures comparing different algorithms is feasible. The ANN achieved the best performance for detecting lymphedema with accuracy of 93.75%, sensitivity of 95.65%, and specificity of 91.03%. CONCLUSIONS: A well-trained ANN classifier using real-time symptom report can provide highly accurate detection of lymphedema. Such detection accuracy is significantly higher than that achievable by current and often used clinical methods such as bio-impedance analysis. Use of a well-trained classification algorithm to detect lymphedema based on symptom features is a highly promising tool that may improve lymphedema outcomes.
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BACKGROUND: Many women suffer from daily distressing symptoms related to lymphedema following breast cancer treatment. Lymphedema, an abnormal accumulation of lymph fluid in the ipsilateral body area or upper limb, remains an ongoing major health problem affecting more than 40% of 3.1 million breast cancer survivors in the United States. Patient-centered care related to lymphedema symptom management is often inadequately addressed in clinical research and practice. mHealth plays a significant role in improving self-care, patient-clinician communication, and access to health information. The-Optimal-Lymph-Flow health IT system (TOLF) is a patient-centered, web-and-mobile-based educational and behavioral mHealth interventions focusing on safe, innovative, and pragmatic electronic assessment and self-care strategies for lymphedema symptom management. The purpose of this paper is to describe the development and test of TOLF system. METHODS: The development of TOLF was guided by the Model of Self-Care for Lymphedema Symptom Management and designed based on principles fostering accessibility, convenience, and efficiency of mHealth system to enhance training and motivating assessment of and self-care for lymphedema symptoms. Test of TOLF was accomplished by conducting a psychometric study to evaluate reliability, validity, and efficiency of the electronic version of Breast Cancer and Lymphedema Symptom Experience Index (BCLE-SEI), a usability testing and a pilot feasibility testing of mHealth self-care interventions. RESULTS: Findings from the psychometric study with 355 breast cancer survivors demonstrated high internal consistency of the electronic version of the instrument: a Cronbach's alpha coefficient of 0.959 for the total scale, 0.919 for symptom occurrence, and 0.946 for symptom distress. Discriminant validity of the instrument was supported by a significant difference in symptom occurrence (z=-6.938, P<0.000), symptom distress (z=-5.894, P<0.000), and total scale (z=-6.547, P<0.000) between breast cancer survivors with lymphedema and those without it. Findings of usability testing showed that breast cancer survivors were very satisfied with the mHealth self-care interventions: 90% rated the system having no usability problems; 10% noted minor cosmetic problems: spelling errors or text font size. The majority of participants 96.6% strongly agreed that the system was easy to use and effective in helping to learn about lymphedema, symptoms and self-care strategies. Feasibility testing demonstrated that a 12-week one group intervention using TOLF had significantly positive effects on less pain (P=0.031), less soreness (P=0.021), less aching (P=0.024), less tenderness (P=0.039), fewer numbers of lymphedema symptoms (P=0.003), and improved symptom distress (P=0.000) at 12 weeks after intervention. Themes from the qualitative data included empowerment, high quality information, loving avatar simulation videos, easy accessibility, and user-friendliness. CONCLUSIONS: TOLF system using the electronic version of the instrument is able to assess patients' lymphedema symptoms with high reliability and validity. TOLF system is also able to deliver self-care interventions to enhance self-care strategies for lymphedema symptom management.
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BACKGROUND: Despite current advances in cancer treatment, many breast cancer survivors still face long-term post-operative challenges as a result of suffering from daily pain and other distressing symptoms related to lymphedema, ie, abnormal accumulation of lymph fluid in the ipsilateral upper limb or body. Grounded in research-driven behavioral strategies, The-Optimal-Lymph-Flow is a unique Web- and mobile-based system focusing on self-care strategies to empower, rather than inhibit, how breast cancer survivors manage daily pain and symptoms. It features a set of safe, feasible, and easily-integrated-into-daily-routine exercises to promote lymph flow and drainage, as well as guidance to maintain an optimal body mass index (BMI). OBJECTIVE: To conduct a randomized clinical trial (RCT) to evaluate the efficacy of the Web- and mobile-based The-Optimal-Lymph-Flow system for managing chronic pain and symptoms related to lymphedema. The primary outcome includes pain reduction, and the secondary outcomes focus on symptom relief, limb volume difference by infra-red perometer, BMI, and quality of life (QOL) related to pain. We hypothesize that participants in the intervention group will have improved pain and symptom experiences, limb volume difference, body mass index, and QOL. METHODS: A parallel RCT with a control-experimental, pre- and post-test, repeated-measures design is used in this study. A total of 120 patients will be randomized according to the occurrence of pain. Participants will be recruited face-to-face at the point of care during clinical visits. Participants in the intervention group will receive the Web- and mobile-based The-Optimal-Lymph-Flow intervention and will have access to and learn about the program during the first in-person research visit. Participants in the control group will receive the Web- and mobile-based Arm Precaution program and will have access to and learn about the program during the first in-person research visit. Participants will be encouraged to enhance their learning by accessing the program and following the daily exercises during the study period. Participants will have monthly online self-report of pain and symptoms at 4 and 8 weeks post-intervention. During the two in-person research visits prior to and 12 weeks post-intervention, participants will be measured for limb volume difference, BMI, and complete self-report of pain, symptoms, self-care behaviors, and QOL. RESULTS: This trial is currently open for recruitment. The anticipated completion date for the study is July 2017. The primary endpoint for the study is absence or reduction of pain reported by the participants at week 12 post-intervention. CONCLUSIONS: The-Optimal-Lymph-Flow is a unique Web- and mobile-based self-care and patient-reported outcome system designed to effectively help women treated for breast cancer manage daily pain and symptoms related to lymphedema. Patients learn self-care strategies from a Web- and mobile-based program and track their symptoms. The RCT will directly benefit all women treated for breast cancer who suffer from or at risk for pain and symptoms related to lymph fluid accumulation. TRIAL REGISTRATION: Clinicaltrials.gov NCT02462226; https://clinicaltrials.gov/ct2/show/NCT02462226 (Archived by WebCite at http://www.webcitation.org/6du4IupG5).
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PURPOSE: The-Optimal-Lymph-Flow health IT system (TOLF) is a patient-centered, web-and-mobile-based educational and behavioral health IT system focusing on safe, innovative, and pragmatic self-care strategies for lymphedema symptom management. The purpose of this study was to evaluate usability, feasibility, and acceptability of TOLF among the end-user of breast cancer survivors. METHODS: Two types of usability testing were completed with 30 breast cancer survivors: heuristic evaluation and end-user testing. Each participant was asked to think aloud while completing a set of specified tasks designed to explicate and freely explore the system features. A heuristic evaluation checklist, the Perceived Ease of Use and Usefulness Questionnaire, and The Post Study System Usability Questionnaire were used to evaluate usability of the system. Open-ended questions were used to gather qualitative data. Quantitative data were analyzed using descriptive statistics and qualitative data were summarized thematically. RESULTS: Breast cancer survivors were very satisfied with the system: 90% (n = 27) rated the system having no usability problems; 10% (n = 3) noted minor cosmetic problems: spelling errors or text font size. The majority of participants 96.6% (n = 29) strongly agreed that the system was easy to use and effective in helping to learn about lymphedema, symptoms and self-care strategies. Themes from the qualitative data included empowerment, high quality information, loving avatar simulation videos, easy accessibility, and user-friendliness. CONCLUSIONS: This usability study provided evidence on breast cancer survivor's acceptance and highly positive evaluation of TOLF's usability as well as feasibility of using technologically-driven delivery model to enhance self-care strategies for lymphedema symptom management.
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Breast cancer-related lymphedema is a syndrome of abnormal swelling coupled with multiple symptoms resulting from obstruction or disruption of the lymphatic system associated with cancer treatment. Research has demonstrated that with increased number of symptoms reported, breast cancer survivors' limb volume increased. Lymphedema symptoms in the affected limb may indicate a latent stage of lymphedema in which changes cannot be detected by objective measures. The latent stage of lymphedema may exist months or years before overt swelling occurs. Symptom report may play an important role in detecting lymphedema in clinical practice. The purposes of this study were to: 1) examine the validity, sensitivity, and specificity of symptoms for detecting breast cancer-related lymphedema and 2) determine the best clinical cutoff point for the count of symptoms that maximized the sum of sensitivity and specificity. Data were collected from 250 women, including healthy female adults, breast cancer survivors with lymphedema, and those at risk for lymphedema. Lymphedema symptoms were assessed using a reliable and valid instrument. Validity, sensitivity, and specificity were evaluated using logistic regression, analysis of variance, and areas under receiver operating characteristic curves. Count of lymphedema symptoms was able to differentiate healthy adults from breast cancer survivors with lymphedema and those at risk for lymphedema. A diagnostic cutoff of three symptoms discriminated breast cancer survivors with lymphedema from healthy women with a sensitivity of 94% and a specificity of 97% (area under the curve =0.98). A diagnostic cutoff of nine symptoms discriminated at-risk survivors from survivors with lymphedema with a sensitivity of 64% and a specificity of 80% (area under the curve =0.72). In the absence of objective measurements capable of detecting latent stages of lymphedema, count of symptoms may be a cost-effective initial screening tool for detecting lymphedema.
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Obesity is one of the risk factors for developing lymphedema following breast cancer treatment. We prospectively enrolled 140 women and followed the participants for 12 months after surgery to investigate patterns of obesity and lymph fluid level in the first year of cancer treatment. Electrical bioimpedance devices were used to measure weight, BMI, and percent of body fat as well as lymph fluid level. General instructions were given to the participants on maintaining pre-surgery weight. Among the 140 participants, 136 completed the study with 2.9% attrition. More than 60% of the participants were obese (30.8%) or overweight (32.4%), while only two participants were underweight and about 35% had normal weight. This pattern of obesity and overweight was consistent at 4-8 weeks and 12 months post-surgery. At 12 months post-surgery, the majority of the women (72.1%) maintained pre-surgery weight and 15.4% had >5% weight loss; 12.5% of the women increase >5% of their weight. Significantly more patients in the obesity group had lymphedema defined by L-Dex ratio >7.1 than those in the normal/underweight and overweight group at pre-surgery and 4-8 weeks post-surgery. There was a trend of more patients in the obesity group had L-Dex ratio >7.1 at 12 months post-surgery. Obesity and overweight remain among women at the time of cancer diagnosis and the patterns of obesity and overweight continue during the first year of treatment. General instructions on having nutrition-balanced and portion-appropriate diet and physical activities daily or weekly can be effective to maintain pre-surgery weight.
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Many breast cancer survivors have coexistent chronic diseases or comorbidities at the time of their cancer diagnosis. The purpose of the study was to evaluate the association of comorbidities on breast cancer survivors' quality of life. A prospective design was used to recruit 140 women before cancer surgery, 134 women completed the study. Comorbidities were assessed using self-report and verified by medical record review and the Charlson Comorbidity Index (CCI) before and 12-month after cancer surgery. Quality of life was evaluated using Short-Form Health Survey (SF-36 v2). Descriptive statistics, chi-square tests, t-tests, Fisher's exact test, and correlations were performed for data analysis. A total of 28 comorbidities were identified. Among the 134 patients, 73.8% had at least one of the comorbidities, 54.7% had 2-4, and only 7.4% had 5-8. Comorbidities did not change at 12 months after surgery. Numbers of comorbidities by patients' self-report and weighted categorization of comorbidities by CCI had a similar negative correlation with overall quality of life scores as well as domains of general health, physical functioning, bodily pain, and vitality. Comorbidities, specifically hypertension, arthritis, and diabetes, were associated with poorer quality of life in multiple domains among breast cancer survivors. Future research should consider the combined influence of comorbidity and cancer on patients' quality of life.
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BACKGROUND: Advances in cancer treatments continue to reduce the incidence of lymphedema. Yet, many breast cancer survivors still face long-term postoperative challenges as a result of developing lymphedema. The purpose of this study was to preliminarily evaluate The Optimal Lymph Flow program, a patient-centered education and behavioral program focusing on self-care strategies to enhance lymphedema risk reduction by promoting lymph flow and optimize body mass index (BMI). METHODS: A prospective, longitudinal, quasi-experimental design with repeated-measures was used. The study outcomes included lymph volume changes by infrared perometer, and BMI by a bioimpedance device at pre-surgery baseline, 2-4 weeks after surgery, 6-month and 12-month follow-up. A total of 140 patients were recruited and participated in The Optimal Lymph Flow program; 134 patients completed the study with 4 % attrition rate. RESULTS: Fifty-eight percent of patients had axillary node dissection and 42 % had sentinel lymph node biopsy (SLNB). The majority (97 %) of patients maintained and improved their preoperative limb volume (LV) and BMI at the study endpoint of 12 months following cancer surgery. Cumulatively, two patients with SLNB and two patients with axillary lymph node dissection had measurable lymphedema (>10 % LV change). At the 12-month follow-up, among the four patients with measurable lymphedema, two patients' LV returned to preoperative level without compression therapy but by maintaining The Optimal Lymph Flow exercises to promote daily lymph flow. CONCLUSIONS: This educational and behavioral program is effective in enhancing lymphedema risk reduction. The study provided initial evidence for emerging change in lymphedema care from treatment-focus to proactive risk reduction.