Protocol for a 4-arm randomized controlled trial testing remotely delivered exercise-only, diet-only, and exercise + diet interventions among men with prostate cancer treated with radical prostatectomy (Prostate 8-II)

Nutrition and Exercise Knowledge, Attitude, and Practice: A Scoping Review of Assessment Questionnaires in Cancer Survivorship

Cancer survivors are encouraged to maintain a healthy diet and engage in regular exercise to improve overall physical and psychosocial health, and to reduce the likelihood of cancer recurrence and related mortality. Consequently, nutrition and exercise (the structured component of physical activity) knowledge, attitude, and practice (NE-KAP) are frequently evaluated in research studies involving cancer survivors and are associated with various health outcomes. The aims of this scoping review were to (1) systematically map the types of NE-KAP assessment questionnaires used in cancer survivorship research (i.e., trend or use over the past five years), (2) provide a directory of questionnaires, and (3) identify the most frequently reported health outcomes that have been associated with them. A systematic search was conducted across four databases-Medline, Emcare, CINAHL, and Scopus-from 1 January 2019 to 9 May 2024, for studies addressing one or more aspects of NE-KAP (e.g., food frequency questionnaire for nutrition practice, attitude towards exercise scale for exercise attitude). Eligible studies were extracted, assessed, and reviewed by two independent authors, and data were summarized descriptively. Of the initial 5452 records screened, 1122 articles were screened for full text, and 852 were deemed eligible, with 262 studies included. There was an overall increasing trend in NE-KAP research in cancer survivorship research from 2019 to 2023. Of the 200 unique questionnaires aligning with at least one NE-KAP domain, 45 were untitled and created/adapted specifically for their respective studies, with limited information about their psychometric properties. Out of the 262 included studies, the most utilized questionnaires were those measuring nutrition or physical activity practices, such as study-specific food frequency questionnaires (n = 26, 10%) and the Godin-Shephard Leisure-Time Physical Activity questionnaire (n = 52, 20%). Out of studies that had reported health outcomes (nutrition, n = 23; exercise, n = 40), health-related quality of life was most commonly associated with nutrition (n = 12, 53%) and exercise (n = 9, 23%), and from cross-sectional studies (nutrition, n = 13; exercise, n = 23). An emphasis was placed on assessing nutrition and exercise practices, with limited attention towards the knowledge and attitude domains. Psychometric evaluation of questionnaires was also lacking.

Race and Ethnicity, Lifestyle, Diet, and Survival in Patients With Prostate Cancer

Importance

Prostate cancer (PCa) remains a leading cause of cancer-related death among men in the US.

Objective

To evaluate the association of healthy lifestyle and dietary behaviors with survival after a nonmetastatic PCa diagnosis in a multiethnic population.

Design, Setting, and Participants

This prospective cohort study was conducted among men aged 45 to 75 years enrolled between 1993 and 1996 in the Multiethnic Cohort study. Participants with nonmetastatic PCa completed a questionnaire after diagnosis (2003-2008) and were followed up until death or loss to follow-up. Data were analyzed from January 10, 2023, to May 20, 2024.

Exposures

Lifestyle and dietary patterns were assessed after diagnosis using 3 PCa behavior scores and 13 dietary indices (4 prioritized scores: the Healthy Eating Index-2015, Healthful Plant-Based Diet Index, Dietary Inflammatory Index, and Empirical Dietary Index for Hyperinsulinemia).

Main Outcomes and Measures

Cox proportional hazards models were used to evaluate multivariable-adjusted associations of each PCa behavior score with all-cause, cardiovascular disease (CVD), and PCa-specific mortality.

Results

A total of 2603 men with nonmetastatic PCa (mean [SD] age, 69.6 [7.1] years) were followed up, and 1346 deaths were documented, including 356 (24.6%) from CVD and 197 (14.6%) from PCa. The median (IQR) follow-up was 10.9 (IQR, 6.8-12.7) years from questionnaire return and 14.5 (IQR, 11.8-18.0) years from diagnosis. The 2021 PCa Behavior Score was associated with reduced risks of all-cause (hazard ratio [HR] per point, 0.69; 95% CI, 0.63-0.77) and CVD-related (HR, 0.67; 95% CI, 0.56-0.79) mortality. This score was also associated with a lower risk of PCa-specific mortality among African American men (HR, 0.46; 95% CI, 0.24-0.88) but not in the other racial and ethnic groups. Comparing quintile 5 (highest score) with 1 (lowest score), the Empirical Dietary Index for Hyperinsulinemia was positively associated with all-cause (HR, 1.37; 95% CI, 1.02-1.84) and CVD-related (HR, 1.96; 95% CI, 1.15-3.33) mortality, whereas the Healthful Plant-Based Diet Index was associated with a reduced risk of all-cause (HR, 0.75; 95% CI, 0.58-0.97); findings for CVD-related mortality were not statistically significant (HR, 0.67; 95% CI, 0.44-1.03). No associations were found between lifestyle or dietary patterns and PCa mortality.

Conclusions and Relevance

In this multiethnic cohort of patients with nonmetastatic PCa, healthier lifestyles were associated with improved overall survival but not with PCa-specific survival. Given the predominance of non-PCa-specific deaths, these findings support the need for health behavior counseling to treat comorbidities in men with PCa.

Development of Machine Learning Algorithm to Predict the Risk of Incontinence After Robot-Assisted Radical Prostatectomy

Introduction: Predicting postoperative incontinence beforehand is crucial for intensified and personalized rehabilitation after robot-assisted radical prostatectomy. Although nomograms exist, their retrospective limitations highlight artificial intelligence (AI)'s potential. This study seeks to develop a machine learning algorithm using robot-assisted radical prostatectomy (RARP) data to predict postoperative incontinence, advancing personalized care. Materials and Methods: In this propsective observational study, patients with localized prostate cancer undergoing RARP between April 2022 and January 2023 were assessed. Preoperative variables included age, body mass index, prostate-specific antigen (PSA) levels, digital rectal examination (DRE) results, Gleason score, International Society of Urological Pathology grade, and continence and potency questionnaires responses. Intraoperative factors, postoperative outcomes, and pathological variables were recorded. Urinary continence was evaluated using the Expanded Prostate cancer Index Composite questionnaire, and machine learning models (XGBoost, Random Forest, Logistic Regression) were explored to predict incontinence risk. The chosen model's SHAP values elucidated variables impacting predictions. Results: A dataset of 227 patients undergoing RARP was considered for the study. Post-RARP complications were predominantly low grade, and urinary continence rates were 74.2%, 80.7%, and 91.4% at 7, 13, and 90 days after catheter removal, respectively. Employing machine learning, XGBoost proved the most effective in predicting postoperative incontinence risk. Significant variables identified by the algorithm included nerve-sparing approach, age, DRE, and total PSA. The model's threshold of 0.67 categorized patients into high or low risk, offering personalized predictions about the risk of incontinence after surgery. Conclusions: Predicting postoperative incontinence is crucial for tailoring rehabilitation after RARP. Machine learning algorithm, particularly XGBoost, can effectively identify those variables more heavily, impacting the outcome of postoperative continence, allowing to build an AI-driven model addressing the current challenges in post-RARP rehabilitation.