Effect of exercise on body composition among women with ovarian cancer

Pre-Operative Malnutrition in Patients with Ovarian Cancer: What Are the Clinical Implications? Results of a Prospective Study

BACKGROUND

Malnutrition was associated with worse survival outcomes, impaired quality of life, and deteriorated performance status across various cancer types. We aimed to identify risk factors for malnutrition in patients with epithelial ovarian cancer (EOC) and impact on survival.

METHODS

In our prospective observational monocentric study, we included the patients with primary and recurrent EOC, tubal or peritoneal cancer conducted. We assessed serum laboratory parameters, body mass index, nutritional risk index, nutritional risk screening score (NRS-2002), and bio-electrical impedance analysis.

RESULTS

We recruited a total of 152 patients. Patients > 65 years-old, with ascites of >500 mL, or with platinum-resistant EOC showed statistically significant increased risk of malnutrition when evaluated using NRS-2002 (p-values= 0.014, 0.001, and 0.007, respectively). NRS-2002 < 3 was an independent predictive factor for complete tumor resectability (p = 0.009). The patients with NRS-2002 ≥ 3 had a median overall survival (OS) of seven months (95% CI = 0-24 months), as compared to the patients with NRS-2002 < 3, where median OS was forty-six months (p = 0.001). A phase angle (PhAα) ≤ 4.5 was the strongest predictor of OS.

CONCLUSIONS

In our study, we found malnutrition to be an independent predictor of incomplete cytoreduction and independent prognostic factor for poor OS. Preoperative nutritional assessment is an effective tool in the identification of high-risk EOC groups characterized by poor clinical outcome.

Explainable machine learning model for predicting skeletal muscle loss during surgery and adjuvant chemotherapy in ovarian cancer

BACKGROUND

Skeletal muscle loss during treatment is associated with poor survival outcomes in patients with ovarian cancer. Although changes in muscle mass can be assessed on computed tomography (CT) scans, this labour-intensive process can impair its utility in clinical practice. This study aimed to develop a machine learning (ML) model to predict muscle loss based on clinical data and to interpret the ML model by applying SHapley Additive exPlanations (SHAP) method.

METHODS

This study included the data of 617 patients with ovarian cancer who underwent primary debulking surgery and platinum-based chemotherapy at a tertiary centre between 2010 and 2019. The cohort data were split into training and test sets based on the treatment time. External validation was performed using 140 patients from a different tertiary centre. The skeletal muscle index (SMI) was measured from pre- and post-treatment CT scans, and a decrease in SMI ≥ 5% was defined as muscle loss. We evaluated five ML models to predict muscle loss, and their performance was determined using the area under the receiver operating characteristic curve (AUC) and F1 score. The features for analysis included demographic and disease-specific characteristics and relative changes in body mass index (BMI), albumin, neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR). The SHAP method was applied to determine the importance of the features and interpret the ML models.

RESULTS

The median (inter-quartile range) age of the cohort was 52 (46-59) years. After treatment, 204 patients (33.1%) experienced muscle loss in the training and test datasets, while 44 (31.4%) patients experienced muscle loss in the external validation dataset. Among the five evaluated ML models, the random forest model achieved the highest AUC (0.856, 95% confidence interval: 0.854-0.859) and F1 score (0.726, 95% confidence interval: 0.722-0.730). In the external validation, the random forest model outperformed all ML models with an AUC of 0.874 and an F1 score of 0.741. The results of the SHAP method showed that the albumin change, BMI change, malignant ascites, NLR change, and PLR change were the most important factors in muscle loss. At the patient level, SHAP force plots demonstrated insightful interpretation of our random forest model to predict muscle loss.

CONCLUSIONS

Explainable ML model was developed using clinical data to identify patients experiencing muscle loss after treatment and provide information of feature contribution. Using the SHAP method, clinicians may better understand the contributors to muscle loss and target interventions to counteract muscle loss.

Effect of Exercise on Chemotherapy-Induced Peripheral Neuropathy Among Patients Treated for Ovarian Cancer: A Secondary Analysis of a Randomized Clinical Trial

Importance

Chemotherapy-induced peripheral neuropathy (CIPN), one of the most common and severe adverse effects of chemotherapy, is associated with worse quality of life among survivors of ovarian cancer. Currently, there is no effective treatment for CIPN.

Objective

To evaluate the effect of a 6-month aerobic exercise intervention vs attention-control on CIPN among women treated for ovarian cancer in the Women's Activity and Lifestyle Study in Connecticut (WALC) to provide evidence to inform the guidelines and recommendations for prevention or treatment of CIPN.

Design, Setting, and Participants

This prespecified secondary analysis evaluated the Women's Activity and Lifestyle Study in Connecticut (WALC), a multicentered, open-label, population-based, phase 3 randomized clinical trial of an aerobic exercise intervention vs attention control for CIPN in patients who were diagnosed with ovarian cancer. Only WALC participants who received chemotherapy were included in this analysis. Participants were randomized 1:1 to either a 6-month aerobic exercise intervention or to attention control. All analyses were conducted between September 2022 and January 2023.

Interventions

The exercise intervention consisted of home-based moderate-intensity aerobic exercise facilitated by weekly telephone counseling from an American College of Sports Medicine/American Cancer Society-certified cancer exercise trainer. Attention control involved weekly health education telephone calls from a WALC staff member.

Main Outcomes and Measure

Change in CIPN was the primary outcome in this secondary analysis. This outcome was represented by CIPN severity, which was self-measured by participants at baseline and 6 months using the Functional Assessment of Cancer Therapy/Gynecologic Oncology Group-Neurotoxicity scale, with a score range of 0 to 44. A mixed-effects model was used to assess the 6-month change in CIPN between the exercise intervention and attention control arms.

Results

Of the 134 participants (all females; mean [SD] age, 57.5 [8.3] years) included in the analysis, 69 were in the exercise intervention arm and 65 were in the attention control arm. The mean (SD) time since diagnosis was 1.7 (1.0) years. The mean (SD) baseline CIPN scores were 8.1 (5.6) in the exercise intervention arm and 8.8 (7.9) in the attention control arm (P = .56). At 6 months, the self-reported CIPN score was reduced by 1.3 (95% CI, -2.3 to -0.2) points in the exercise intervention arm compared with an increase of 0.4 (95% CI, -0.8 to 1.5) points in the attention control arm. The between-group difference was -1.6 (95% CI, -3.1 to -0.2) points. The point estimate was larger among the 127 patients with CIPN symptoms at enrollment (-2.0; 95% CI, -3.6 to -0.5 points).

Conclusions and Relevance

Findings of this secondary analysis of the WALC trial indicate that a 6-month aerobic exercise intervention vs attention control significantly improved self-reported CIPN among patients who were treated for ovarian cancer. While replication of the findings in other studies is warranted, incorporating referrals to exercise programs into standard oncology care could reduce CIPN symptoms and increase quality of life in patients with ovarian cancer.

Trial Registration

ClinicalTrials.gov Identifier: NCT02107066.

Whole-Body Composition Features by Computed Tomography in Ovarian Cancer: Pilot Data on Survival Correlations

BACKGROUND

The primary objective of this study was to assess the associations of computed tomography (CT)-based whole-body composition values with overall survival (OS) and progression-free survival (PFS) in epithelial ovarian cancer (EOC) patients. The secondary objective was the association of body composition with chemotherapy-related toxicity.

METHODS

Thirty-four patients (median age 64.9 years; interquartile range 55.4-75.4) with EOC and thorax and abdomen CT scans were included. Clinical data recorded: age; weight; height; stage; chemotherapy-related toxicity; and date of last contact, progression and death. Automatic extraction of body composition values was performed by dedicated software. Sarcopenia was defined according to predefined cutoffs. Statistical analysis included univariate tests to investigate associations of sarcopenia and body composition with chemotoxicity. Association of body composition parameters and OS/PFS was evaluated by log-rank test and Cox proportional hazard model. Multivariate models were adjusted for FIGO stage and/or age at diagnosis.

RESULTS

We found significant associations of skeletal muscle volume with OS (p = 0.04) and PFS (p = 0.04); intramuscular fat volume with PFS (p = 0.03); and visceral adipose tissue, epicardial and paracardial fat with PFS (p = 0.04, 0.01 and 0.02, respectively). We found no significant associations between body composition parameters and chemotherapy-related toxicity.

CONCLUSIONS

In this exploratory study, we found significant associations of whole-body composition parameters with OS and PFS. These results open a window to the possibility to perform body composition profiling without approximate estimations.

Supervised resistance exercise for women with ovarian cancer who have completed first-line treatment: a pragmatic study

OBJECTIVES

In ovarian cancer (OC), suboptimal muscle morphology (i.e., low muscle mass and density) is associated with poor clinical outcomes, yet little is known about the effect of interventions aimed at improving these measures. We investigated the effect of resistance exercise after first-line treatment on muscle mass and density, muscle strength and physical function, health-related quality of life (QoL), and pelvic-floor function in advanced-stage OC survivors.

METHODS

Fifteen OC survivors participated in supervised resistance exercise twice weekly for 12 weeks (in-clinic or by telehealth). Assessments included muscle mass and density (dual-energy X-ray absorptiometry, peripheral quantitative computed tomography), muscle strength (1-repetition maximum [1RM] chest press, 5RM leg press, handgrip strength), physical function (400-m walk, timed up-and-go [TUG]), QoL (QLQ-C30 questionnaire), and self-reported pelvic floor function (Australian Pelvic Floor Questionnaire).

RESULTS

The median age was 64 (range 33-72) years, 10 women underwent neoadjuvant chemotherapy and five underwent adjuvant chemotherapy. All participants completed the intervention (median attendance = 92%; range 79-100%). Post-intervention improvements were observed for whole-body lean mass (1.0 ± 1.4 kg, p = 0.015), appendicular lean mass (0.6 ± 0.9 kg, p = 0.013), muscle density (p = 0.011), upper and lower body strength (p ≤ 0.001), 400-m walk (p = 0.001), TUG (p = 0.005), and social and cognitive QoL domains (p = 0.002 and 0.007), with no change to pelvic floor symptoms (p > 0.05).

CONCLUSION

In this study, supervised resistance exercise effectively improved muscle mass and density, muscle strength, and physical functioning without deleterious effects on the pelvic floor. Considering the prognostic value of these outcomes, larger studies are needed to confirm the benefits of resistance exercise in OC supportive care.

Exercise adherence in a randomized controlled trial of exercise on quality of life in ovarian cancer survivors

PURPOSE

Factors associated with improving exercise in ovarian cancer survivors remain unknown. We explored characteristics associated with exercise adherence among women treated for ovarian cancer in the Women's Activity and Lifestyle Study in Connecticut (WALC) randomized controlled trial.

METHODS

We evaluated adherence among women randomized to the WALC exercise intervention (N = 74). Women had to be exercising ≤ 90 min/week and post-treatment. The intervention included 25 telephone-based exercise counseling sessions over 6 months. Adherence was defined as 150 min/week of moderate/vigorous-intensity exercise. We evaluated factors associated with exercise adherence and duration using multivariate logistic and linear regression. The number of sessions sufficient to achieve 150 min/week was modeled with an unadjusted receiver operating characteristic (ROC) curve.

RESULTS

Women were 57.3 ± 8.8 years old and 1.7 ± 1.0 years since diagnosis. The mean exercise time over 6 months was 166.0 ± 66.1 min/week, and 64.9% of women met the 150 min/week goal. Women attended 22.8 ± 3.6 (92%) counseling sessions. No cancer recurrence during the study (OR = 9.15, 95% CI: 1.09-44.02) and greater session attendance (OR = 1.21, 95% CI: 1.02-1.43) were related to meeting the exercise goal. Greater session attendance (P < 0.01) and higher baseline activity level (P = 0.02) were associated with greater average weekly exercise duration. The ROC curve suggested attending 18 counseling sessions was optimal to meet the exercise goal.

CONCLUSIONS

Women attending more counseling sessions or with no cancer recurrence during the study were more likely to meet the exercise goal. More research is needed to understand ideal counseling intensity for ovarian cancer survivors.

IMPLICATIONS FOR CANCER SURVIVORS

Eighteen counseling sessions are sufficient for ovarian cancer survivors to achieve 150 min/week exercise.