Sexual dysfunction in female patients with anal cancer treated with curative intent: A systematic review of the literature.

BACKGROUND AND PURPOSE: Patients with anal squamous cell carcinoma (SCC) are treated with sphincter-preserving radiation therapy and concurrent chemotherapy, achieving excellent oncologic outcomes. Patients, however, may experience treatment-related morbidity including sexual dysfunction. The objective of this systematic review was to review the literature on sexual dysfunction in female patients treated for anal cancer and to identify knowledge gaps. MATERIALS AND METHODS: This systematic review was registered in PROSPERO prior to initiation. Databases searched included MEDLINE, Embase, PubMed, Cochrane, and Google Scholar. There were no restrictions on the study time period. Studies were limited to English. All study designs were included except review articles, letters to the editor, and case reports with less than ten patients. RESULTS: In total, 1801 studies were retrieved and 19 met the inclusion criteria, including: 13 cross-sectional surveys, 3 prospective studies, 1 longitudinal intervention study, 1 retrospective chart review, 1 case control study. Sexual function was assessed using the female sexual functioning index (FSFI), EORTC-QLQ-CR30 and -CR38; response rates were low (<50 % in most studies). Sexual dysfunction was reported by up to 85 % of women; the most common symptoms being dyspareunia (17-65 %), vaginal dryness (22-88 %), and loss of libido (38-95 %). Gastrointestinal issues, such as bowel problems, and body image concerns additionally affected sexual function and quality of life. CONCLUSION: Sexual dysfunction is a common issue affecting most female patients treated for anal cancer and there is a paucity of evidence on the management of this important survivorship issue. There is additionally a lack of ethnic, economic, and educational diversity and there are no studies addressing the unique needs of LGBTQ individuals - future studies should make a concerted effort to include a diverse patient population.

Quantitative ultrasound radiomics for therapy response monitoring in patients with locally advanced breast cancer: Multi-institutional study results.

BACKGROUND: Neoadjuvant chemotherapy (NAC) is the standard of care for patients with locally advanced breast cancer (LABC). The study was conducted to investigate the utility of quantitative ultrasound (QUS) carried out during NAC to predict the final tumour response in a multi-institutional setting. METHODS: Fifty-nine patients with LABC were enrolled from three institutions in North America (Sunnybrook Health Sciences Centre (Toronto, Canada), MD Anderson Cancer Centre (Texas, USA), and Princess Margaret Cancer Centre (Toronto, Canada)). QUS data were collected before starting NAC and subsequently at weeks 1 and 4 during chemotherapy. Spectral tumour parametric maps were generated, and textural features determined using grey-level co-occurrence matrices. Patients were divided into two groups based on their pathological outcomes following surgery: responders and non-responders. Machine learning algorithms using Fisher's linear discriminant (FLD), K-nearest neighbour (K-NN), and support vector machine (SVM-RBF) were used to generate response classification models. RESULTS: Thirty-six patients were classified as responders and twenty-three as non-responders. Among all the models, SVM-RBF had the highest accuracy of 81% at both weeks 1 and week 4 with area under curve (AUC) values of 0.87 each. The inclusion of week 1 and 4 features led to an improvement of the classifier models, with the accuracy and AUC from baseline features only being 76% and 0.68, respectively. CONCLUSION: QUS data obtained during NAC reflect the ongoing treatment-related changes during chemotherapy and can lead to better classifier performances in predicting the ultimate pathologic response to treatment compared to baseline features alone.

Quantitative ultrasound radiomics in predicting response to neoadjuvant chemotherapy in patients with locally advanced breast cancer: Results from multi-institutional study.

BACKGROUND: This study was conducted in order to develop a model for predicting response to neoadjuvant chemotherapy (NAC) in patients with locally advanced breast cancer (LABC) using pretreatment quantitative ultrasound (QUS) radiomics. METHODS: This was a multicenter study involving four sites across North America, and appropriate approval was obtained from the individual ethics committees. Eighty-two patients with LABC were included for final analysis. Primary tumors were scanned using a clinical ultrasound system before NAC was started. The tumors were contoured, and radiofrequency data were acquired and processed from whole tumor regions of interest. QUS spectral parameters were derived from the normalized power spectrum, and texture analysis was performed based on six QUS features using a gray level co-occurrence matrix. Patients were divided into responder or nonresponder classes based on their clinical-pathological response. Classification analysis was performed using machine learning algorithms, which were trained to optimize classification accuracy. Cross-validation was performed using a leave-one-out cross-validation method. RESULTS: Based on the clinical outcomes of NAC treatment, there were 48 responders and 34 nonresponders. A K-nearest neighbors (K-NN) approach resulted in the best classifier performance, with a sensitivity of 91%, a specificity of 83%, and an accuracy of 87%. CONCLUSION: QUS-based radiomics can predict response to NAC based on pretreatment features with acceptable accuracy.