Differences in limb volume trajectories after breast cancer treatment

Identification Of A Higher Risk Lymphedema Phenotype And Associations With Cytokine Gene Polymorphisms

CONTEXT

Breast cancer-related lymphedema (BCRL) is chronic condition that occurs in 5% to 75% of women following treatment for breast cancer. However, little is known about the risk factors and mechanisms associated with a worse BCRL profile.

OBJECTIVES

Identify distinct BCRL profiles in women with the condition (i.e., lower vs. higher risk phenotype) and evaluate for associations with pro- and anti-inflammatory genes.

METHODS

Latent class profile analysis (LCPA) was used to identify the BCRL profiles using phenotypic characteristics evaluated prior to surgery. Candidate gene analyses were done to identify cytokine genes associated with the two BCRL profiles.

RESULTS

Of the 155 patients evaluated, 35.5% (n = 55) were in the Lower and 64.5% (n = 100) were in the Higher Risk classes. Risk factors for membership in the Higher class included: lower functional status, having sentinel lymph node biopsy, axillary lymph node dissection, mastectomy, higher number of positive lymph nodes, and receipt of chemotherapy. Polymorphisms for interleukin (IL)1-beta and IL6 were associated with membership in the Higher Risk class.

CONCLUSION

The readily available and clinically relevant phenotypic characteristics associated with a worse BCRL profile can be used by clinicians to identify higher risk patients. If confirmed, these characteristics can be tested in predictive risk models. In addition, the candidate gene findings may guide the development of mechanistically-based interventions to decrease the risk of BCRL.

Assessment of Arm Volume Using a Tape Measure Versus a 3D Optical Scanner in Survivors with Breast Cancer-Related Lymphedema

Background: Lymphedema (LE) is a significant clinical problem for breast cancer survivors. While the water displacement test and circumferential assessment using a tape measure (TM) are common methods to assess differences in arm volumes, faster and more reliable methods are needed. Study purposes, in breast cancer survivors (n = 294), were to compare the average total arm volumes and interlimb volume ratios for women with and without a history of LE, using a TM and three-dimensional (3D), whole-body surface scanner (3D scan); compare the level of agreement between arm volumes and interlimb volume ratios obtained using the two devices; and evaluate the percent agreement between the two measures in classifying cases of LE using three accepted thresholds. Methods and Results: Measurements were done using a spring-loaded TM and Fit3D ProScanner. Paired t-tests and Bland-Altman analyses were used to achieve the study aims. For circumference and volume comparisons, compared with the 3D scan, values obtained using the TM were consistently smaller. In terms of level of agreement, the Bland-Altman analyses demonstrated large biases and wide limits of agreement for the calculated arm volumes and volume ratios. In terms of the classification of caseness, using the 200-mL interlimb volume difference criterion resulted in 81.6% overall agreement; using the >10% volume difference between the affected and unaffected arms resulted in 78.5% overall agreement; and using the volume ratio ≥1.04 criterion resulted in 62.5% overall agreement. For all three accepted threshold criteria, the percentage of cases was significantly different between the TM and 3D scan techniques. Conclusions: The 3D technology evaluated in this study has the potential to be used for self-initiated surveillance for LE. With improvements in landmark identification and software modifications, it is possible that accurate and reliable total arm volumes can be calculated and used for early detection.

A Comparison of Supine Versus Stand-on Bioimpedance Devices to Assess Breast Cancer-Related Lymphedema

Background: While supine bioimpedance devices are used to evaluate for lymphedema (LE), stand-on devices are gaining popularity. Because research on differences in bioimpedance values between the two devices is limited, this study's purposes were to: (1) determine the average upper limb impedance values and inter-limb ratios for women who self-reported having (n = 34) or not having (n = 61) a history of LE, using a single-frequency supine device and a multifrequency stand-on device; (2) compare the level of agreement in inter-limb impedance ratios between the two devices; evaluate the percent agreement between the two devices in classifying cases of LE using established supine thresholds; and evaluate the percent agreement in classifying cases of LE between the supine device using previously established supine thresholds and the stand-on device using two published standing thresholds. Methods and Results: Bioimpedance measures were done using the two devices. For the entire sample, absolute impedance values for both the affected and unaffected limbs were significantly higher for the stand-on device in women with and without LE. Impedance values for the two methods were highly correlated. Bland-Altman analysis determined that for the entire range of impedance ratios the values for the two devices could not be used interchangeably. Conclusions: Findings suggest that the stand-on device can be a useful and valid tool to assess for LE. However, because agreement is not perfect, values obtained from the two devices should not be used interchangeably to evaluate for changes in impedance ratios, particularly for ratios of >1.20.

L-Dex, arm volume, and symptom trajectories 24 months after breast cancer surgery

Purpose

Study objectives were to examine: (a) biomarker trajectories (change from presurgical baseline values of Lymphedema index (L‐Dex) units and arm volume difference) and symptom cluster scores 24 months after breast cancer surgery and (b) associations of these objective biomarkers and symptom cluster scores. Patient/treatment characteristics influencing trajectories were also evaluated.

Methods

A secondary analysis of data from the published interim analysis of a randomized parent study was undertaken using trajectory analysis. Five hundred and eight participants included in the prior analysis with 24 months of postsurgical follow‐up were initially measured with bioelectric impedance spectroscopy (BIS) and tape measure (TM) and completed self‐report measures. Patients were reassessed postsurgery for continuing eligibility and then randomized to either BIS or TM groups and measured along with self‐report data at regular and optional* visits 3, 6,12,15*,18, 21*, and 24‐months.

Results

Three subclinical trajectories were identified for each biomarker (decreasing, stable, increasing) and symptom cluster scores (stable, slight increase/decrease, increasing). Subclinical lymphedema was identified throughout the 24‐month period by each biomarker. An L‐Dex increase at 15 months in the BIS group was noted. The self‐report sets demonstrated contingency coefficients of 0.20 (LSIDS‐A soft tissue, P = .031) and 0.19 (FACTB+4, P = .044) with the L‐Dex unit change trajectories.

Conclusions

These data support the need for long‐term (24 months) prospective surveillance with frequent assessments (every 3 months) at least 15 months after surgery. Statistically significant convergence of symptom cluster scores with L‐Dex unit change supports BIS as beneficial in the early identification of subclinical lymphedema.

Early recovery trajectories after fast-track primary total hip arthroplasty: the role of patient characteristics

Background and purpose - Little is known about heterogeneity in early recovery after primary total hip arthroplasty (THA). Therefore, we characterized subgroups of patients according to their hip function trajectory during the first 6 weeks after THA in a fast-track setting. Patients and methods - 94 patients (median age 65 years [41-82], 56 women) from a single hospital participated in a diary study. Patients recorded their severity of hip problems (Oxford Hip Score, OHS) weekly for 6 weeks after THA. Latent class growth modelling (LCGM) was used to identify patients with the same hip function trajectory and to compare these subgroups on patient characteristics. Results - LCGM revealed a fast (n = 17), an average (n = 53), and a slow (n = 24) recovery subgroup. Subgroups differed on the estimated weekly growth rate during the first 2 weeks (fast: 9.5; average: 5.3; slow: 2.7), with fewer differences between groups in the last 4 weeks (fast: 0.90; average: 2.0; slow: 1.7). Patients in the slow recovery group could be characterized as women of older age (mean age =69) who rated their health as lower preoperatively, needed more assistance during recovery, and were less satisfied with the outcomes of the surgery. Interpretation - We identified distinct recovery trajectories in the first 6 weeks after fast-track primary THA which were associated with patient characteristics.

Prospective surveillance and targeted physiotherapy for arm morbidity after breast cancer surgery: a pilot randomized controlled trial

OBJECTIVE

To evaluate prospective surveillance and targeted physiotherapy (PSTP) compared to education (EDU) on the prevalence of arm morbidity and describe the associated program cost.

DESIGN

Pilot randomized single-blinded controlled trial.

SETTING

Urban with assessments and treatment delivered in hospitals.

PARTICIPANTS

Women scheduled for breast cancer surgery.

INTERVENTIONS

Participants were randomly assigned (1:1) to PSTP ( n = 21) or EDU ( n = 20) and assessed presurgery and 12 months postsurgery. All participants received usual care, namely, preoperative education and provision of an education booklet with postsurgical exercises. The PSTP group was monitored for arm morbidity every three months and referred for physiotherapy if arm morbidity was identified. The EDU group received three education sessions on nutrition, stress and fatigue management.

MAIN OUTCOME MEASURES

Arm morbidity was based on changes in the surgical arm(s) from presurgery in four domains: (1) shoulder range of motion, (2) strength, (3) volume, and (4) upper body function. Complex arm morbidity indicated ≥2 domains impaired. Second, the cost of the PSTP program was described.

RESULTS

At 12 months, 18 (49%) participants (10 PSTP and 8 EDU) had arm morbidity, with EDU participants presenting more complex arm morbidity compared to PSTP participants. PSTP participants attended 4.4 of 5 assessments with 90% retention. The PSTP program cost was $150 covered by the Health Care Provider and the Patient Out-of-Pocket Travel cost was CAN$40.

CONCLUSION

Our results suggest that PSTP is feasible among women with breast cancer for early identification of arm morbidity. A larger study is needed to determine the cost and effectiveness benefits.