Meaningful Patient Engagement in Adolescent and Young Adult (AYA) Cancer Research: A Framework for Qualitative Studies.

Over the last two decades, patient engagement in cancer research has evolved significantly, especially in addressing the unique challenges faced by adolescent and young adult (AYA) cancer populations. This paper introduces a framework for meaningful engagement with AYA cancer patient research partners, drawing insights from the "FUTURE" Study, a qualitative study that utilizes focus groups to explore the impact of cancer diagnosis and treatment on the sexual and reproductive health of AYA cancer patients in Canada. The framework's development integrates insights from prior works and addresses challenges with patient engagement in research specific to AYA cancer populations. The framework is guided by overarching principles (safety, flexibility, and sensitivity) and includes considerations that apply across all phases of a research study (collaboration; iteration; communication; and equity, diversity, and inclusion) and tasks that apply to specific phases of a research study (developing, conducting, and translating the study). The proposed framework seeks to increase patient engagement in AYA cancer research beyond a supplementary aspect to an integral component for conducting research with impact on patients.

Sexual health outcomes among adolescent and young adult cancer patients: a systematic review and meta-analysis.

BACKGROUND: Sexual health outcomes (SHO), which entail the physical, emotional, mental, and social impacts, are an important consideration for adolescent and young adults (AYA, ages 15-39) affected by cancer. The objective of this systematic review and meta-analysis is to summarize the current literature and evaluate AYA cancer impact on SHO. METHODS: EMBASE and MEDLINE were searched from January 1, 2000 to September 28, 2022 to identify epidemiologic studies that used an analytic observational design, included individuals with AYA cancer and non-cancer control participants, and evaluated SHO. Odds ratios and prevalence ratios were calculated; random effects models were used to obtain pooled measures where possible. RESULTS: Of 2621 articles, 8 were included that investigated 23 SHO in 9038 AYA cancer patients. Based on the sexual response cycle, outcomes were categorized as those occurring among males (desire = 1, arousal = 1, orgasm = 4, other = 3) and females (desire = 2, arousal = 1, orgasm = 2, pain = 6, other = 3). It was feasible to conduct meta-analysis for 3 female SHO and 5 male SHO. There were associations between AYA cancer and 3 SHO: vaginal dryness (pooled odds ratio = 3.94; 95% confidence interval (CI) = 2.02 to 7.70), ejaculatory dysfunction (pooled odds ratio = 3.66; 95% CI = 2.20 to 6.08), and testosterone level (pooled mean difference = -2.56 nmol/liter; 95% CI = -3.46 to -1.66; P = .00001). CONCLUSION: This study found increased ejaculatory dysfunction and reduced testosterone levels in male AYA cancer patients and increased vaginal dryness in female AYA cancer patients, highlighting the need for sexual health resources in this population.

A qualitative study of sexual health and function of females with pelvic cancer.

Background: Pelvic cancers are among the most common cancers, impacting millions of individuals worldwide annually. However, little is known about the impact of more rare pelvic cancers on the sexual health of females. Aim: In this study we explored sexual health experiences of female pelvic cancer survivors (FPCS) and their healthcare providers (HCP) in order to identify the most salient impacts of pelvic cancer on sexual function. Methods: In this qualitative study, semi-structured online interviews were conducted with 15 female patients with vulvar, vaginal, uterine, ovarian, endometrial, cervical, bladder, and/or colorectal cancers. Additionally, semi-structured online interviews were conducted with HCPs who treat pelvic cancers (n = 9). For data analysis, qualitative framework analysis was used. Outcomes: We used the collected data and analysis of findings to establish recommendations including ways to improve sexual health and function in female survivors of pelvic cancer. Results: Most FPCS experienced negative impacts on their sexual health and function through increased pain and dryness, bleeding due to atrophy, decreased libido, and psychosocial issues such as body dysmorphia. Females with the rarer vulvar and vaginal cancers faced additional challenges to their sexual health such as shortening of vaginal canals, high levels of neuropathy, lack of sexual activity with their partners, and suicidal ideation. FPCS had unmet sexual health needs, which can be attributed to lack of appropriate training by HCPs and lack of resources and availability of services. Although HCPs recognized the importance of providing sexual healthcare, they lacked confidence in their ability to facilitate a conversation on sexual health with their patients, and often avoided this topic. Clinical implications: The sexual health outcomes of FPCS can be improved by providing targeted training for HCPs, developing standard resources for sexual health, and integrating tiers of support, including group interventions and counseling. Strengths and limitations: The main strength of this study is that data were collected from HCPs as well as FPCS, thus providing a more in-depth overall picture of the current strengths and weaknesses of the resources for sexual health support available for this patient population. A limitation of this study is that the experiences of transgender men were not captured. Conclusions: Sexual difficulties are very common in all FPCS, particularly survivors of vulvar and vaginal cancers. Improvement of sexual health outcomes is needed in this patient population, which can be achieved by providing more training for HCPs, developing robust resources for FPCS and their sexual health, and providing more opportunities for tiered support.

Reproductive Health Outcomes among Adolescent and Young Adult Cancer Patients: A Systematic Review and Meta-Analysis.

BACKGROUND: This systematic review and meta-analysis (SRMA) aimed to synthesize the current literature on the impacts of adolescent and young adult (AYA, ages 15-39 years) cancer on reproductive health outcomes. METHODS: EMBASE and Medline were searched from 1 January 2000 to 26 January 2022 for observational studies that included individuals with AYA cancer and controls which evaluated reproductive health outcomes. We used random effects models and 95% confidence intervals to obtain pooled measures of associations between AYA cancer, cancer treatment, and reproductive health outcomes. RESULTS: The search identified 8625 articles; 21 were included. 62 reproductive outcomes were assessed and classified according to a sex-based framework as fetal/neonatal (n = 26), maternal (n = 11), fetal/neonatal-maternal (n = 23), and maternal-paternal (n = 2). Meta-analyses of crude estimates showed significant associations between AYA cancer and outcomes including preterm birth (pooled odds ratio [pOR] 1.31; 95% CI: 1.22, 1.42), gestational diabetes (pOR 1.43; 95% CI: 1.03, 1.99), and fertility treatment (pOR 2.66; 95% CI 1.71, 4.11). We also found higher odds of preterm birth (pOR 1.65; 95% CI: 1.21, 2.26) and low APGAR score at birth (pOR 2.03; 95% CI: 1.32, 3.13) among AYA cancer patients who received radiation compared to controls. CONCLUSIONS: Our SRMA quantified impacts of AYA cancers and treatments on several reproductive health outcomes.

Double distress: women healthcare providers and moral distress during COVID-19.

Background: COVID-19 pandemic has led to heightened moral distress among healthcare providers. Despite evidence of gendered differences in experiences, there is limited feminist analysis of moral distress.Objectives: To identify types of moral distress among women healthcare providers during the COVID-19 pandemic; to explore how feminist political economy might be integrated into the study of moral distress.Research Design: This research draws on interviews and focus groups, the transcripts of which were analyzed using framework analysis.Research Participants and Context: 88 healthcare providers, based in British Columbia Canada, participated virtually.Ethical Considerations: The study received ethical approval from Simon Fraser University.Findings: Healthcare providers experienced moral dilemmas related to ability to provide quality and compassionate care while maintaining COVID-19 protocols. Moral constraints were exacerbated by staffing shortages and lack of access to PPE. Moral conflicts emerged when women tried to engage decision-makers to improve care, and moral uncertainty resulted from lack of clear and consistent information. At home, women experienced moral constraints related to inability to support children's education and wellbeing. Moral conflicts related to lack of flexible work environments and moral dilemmas developed between unpaid care responsibilities and COVID-19 risks. Women healthcare providers resisted moral residue and structural constraints by organizing for better working conditions, childcare, and access to PPE, engaging mental health support and drawing on professional pride.Discussion: COVID-19 has led to new and heightened experiences of moral distress among HCP in response to both paid and unpaid care work. While many of the experiences of moral distress at work were not explicitly gendered, implicit gender norms structured moral events. Women HCP had to take it upon themselves to organize, seek out resources, and resist moral residue.Conclusion: A feminist political economy lens illuminates how women healthcare providers faced and resisted a double layering of moral distress during the pandemic.

Colorectal Cancer and Onset of Anxiety and Depression: A Systematic Review and Meta-Analysis.

Research suggests that colorectal cancer (CRC) is associated with mental health disorders, primarily anxiety and depression. To synthesize this evidence, we conducted a systematic review and meta-analysis of studies evaluating the onset of anxiety and depression among patients with CRC. We searched EMBASE and Medline from inception to June 2022. We included original, peer-reviewed studies that: used an epidemiologic design; included patients with CRC and a comparator group of individuals without cancer; and evaluated anxiety and depression as outcomes. We used random effects models to obtain pooled measures of associations. Quality assessment was completed using the Newcastle-Ottawa scale. Of 7326 articles identified, 8 were eligible; of which 6 assessed anxiety and depression and 2 assessed depression only. Meta-analyses showed a non-significant association between CRC and anxiety (pooled HR 1.67; 95% CI 0.88 to 3.17) and a significant association between CRC and depression (pooled HR 1.78; 95% CI 1.23 to 2.57). Predictors of anxiety and depression among patients with CRC included clinical characteristics (e.g., comorbidities, cancer stage, cancer site), cancer treatment (e.g., radiotherapy, chemotherapy, colostomy), and sociodemographic characteristics (e.g., age, sex). The impacts of anxiety and depression in patients with CRC included increased mortality and decreased quality of life. Altogether, our systematic review and meta-analysis quantified the risks and impacts of CRC on anxiety and depression, particularly an increased risk of depression after CRC diagnosis. Findings provide support for oncologic care that encompasses mental health supports for patients with CRC.

'Forgotten as first line providers': The experiences of midwives during the COVID-19 pandemic in British Columbia, Canada.

OBJECTIVE: To explore midwives' experiences working on the frontlines of the COVID-19 pandemic in British Columbia, Canada. DESIGN: Qualitative study involving three semi-structured focus groups and four in-depth interviews with midwives. SETTING: The COVID-19 pandemic in British Columbia, Canada from 2020-2021. PARTICIPANTS: 13 midwives working during the first year of the COVID-19 pandemic in British Columbia. FINDINGS: Qualitative analysis surfaced four key themes. First, midwives faced a substantial lack of support during the pandemic. Second, insufficient support was compounded by a lack of recognition. Third, participants felt a strong duty to continue providing high-quality care despite COVID-19 related restrictions and challenges. Lastly, lack of support, increased workloads, and moral distress exacerbated burnout among midwives and raised concerns around the sustainability of their profession. KEY CONCLUSIONS AND IMPLICATIONS FOR PRACTICE: Lack of effective support for midwives during the initial months of the COVID-19 pandemic exacerbated staffing shortages that existed prior to the pandemic, creating detrimental gaps in essential care for pregnant people, especially with increasing demands for homebirths. Measures to support midwives should combat inequities in the healthcare system, mitigating the risks of disease exposure, burnout, and professional and financial impacts that may have long-lasting implications on the profession. Given the crucial role of midwives in women- and people-centred care and advocacy, protecting midwives and the communities they serve should be prioritized and integrated into pandemic preparedness and response planning to preserve women's health and rights around the world.

Risk of Anxiety and Depression after Diagnosis of Young-Onset Colorectal Cancer: A Population-Based Cohort Study.

Given the increasing incidence of young-onset colorectal cancer (yCRC; <50 years), we aimed to evaluate the risk of depression and anxiety in individuals with yCRC in comparison to average-age-onset CRC (aCRC; ≥50 years) and to cancer-free controls, with stratification by sex. Our cohort study identified individuals (≥18 years) with CRC and cancer-free controls (10:1) matched on age and sex using population-based linked administrative health databases in British Columbia, Canada. We assessed depression and anxiety using validated algorithms. We evaluated the risk of depression and anxiety using multivariable Cox proportional hazard models. The cohort included 54,634 individuals with CRC (46.5% female, mean age 67.9 years) and 546,340 controls (46.5% female, mean age 67.9 years). Those with yCRC as compared to aCRC had an increased risk for depression (adjusted hazard ratio [aHR] 1.41; 95% confidence interval [CI] 1.25 to 1.60), and when stratified by sex, the risk was only significant among males (aHR 1.76; 95% CI 1.48 to 2.10). When comparing individuals with yCRC to cancer-free controls, the overall risk of depression (aHR 1.00; 95% CI 0.92 to 1.10) and anxiety (aHR 1.10; 95% CI 0.95 to 1.27) was non-significant; however, males had a significantly higher risk for mental health disorders, specifically depression (aHR 1.17; 95% CI 1.03 to 1.33). Altogether, our findings that individuals with yCRC experience higher risk of depression compared to those with aCRC as well as cancer-free controls, particularly among males, suggest effects of age and sex on mental health outcomes.

Women healthcare workers' experiences during COVID-19 and other crises: A scoping review.

BACKGROUND: Throughout the COVID-19 pandemic, as measures have been taken to both prevent the spread of COVID-19 and provide care to those who fall ill, healthcare workers have faced added risks to their health and wellbeing. These risks are disproportionately felt by women healthcare workers, yet health policies do not always take a gendered approach. OBJECTIVES: The objective of this review was to identify the gendered effects of crises on women healthcare workers' health and wellbeing, as well as to provide guidance for decision-makers on health systems policies and programs that could better support women healthcare workers. METHODS: A scoping review of published academic literature was conducted. PubMed, EMBASE, and CINAHL were searched using combinations of relevant medical subject headings and keywords. Data was extracted using a thematic coding framework. Seventy-six articles met the inclusion criteria. RESULTS: During disease outbreaks women healthcare workers were found to experience: a higher risk of exposure and infection; barriers to accessing personal protective equipment; increased workloads; decreased leadership and decision-making opportunities; increased caregiving responsibilities in the home when schools and childcare supports were restricted; and higher rates of mental ill-health, including depression, anxiety, and post-traumatic stress disorder. There was a lack of attention paid to gender and the health workforce during times of crisis prior to COVID-19, and there is a substantial gap in research around the experiences of women healthcare workers in low- and middle-income countries during times of crises. CONCLUSION: COVID-19 provides an opportunity to develop gender-responsive crisis preparedness plans within the health sector. Without consideration of gender, crises will continue to exacerbate existing gender disparities, resulting in disproportionate negative impacts on women healthcare workers. The findings point to several important recommendations to better support women healthcare workers, including: workplace mental health support, economic assistance to counteract widening pay gaps, strategies to support their personal caregiving duties, and interventions that support and advance women's careers and increase their representation in leadership roles.

Cardiac SPECT radiomic features repeatability and reproducibility: A multi-scanner phantom study.

BACKGROUND: The aim of this work was to assess the robustness of cardiac SPECT radiomic features against changes in imaging settings, including acquisition, and reconstruction parameters. METHODS: Four commercial SPECT and SPECT/CT cameras were used to acquire images of a static cardiac phantom mimicking typical myorcardial perfusion imaging using 185 MBq of 99mTc. The effects of different image acquisition and reconstruction parameters, including number of views, view matrix size, attenuation correction, as well as image reconstruction related parameters (algorithm, number of iterations, number of subsets, type of post-reconstruction filter, and its associated parameters, including filter order and cut-off frequency) were studied. In total, 5,063 transverse views were reconstructed by varying the aforementioned factors. Eighty-seven radiomic features including first-, second-, and high-order textures were extracted from these images. To assess reproducibility and repeatability, the coefficient of variation (COV), as a widely adopted metric, was measured for each of the radiomic features over the different imaging settings. RESULTS: The Inverse Difference Moment Normalized (IDMN) and Inverse Difference Normalized (IDN) features from the Gray Level Co-occurrence Matrix (GLCM), Run Percentage (RP) from the Gray Level Co-occurrence Matrix (GLRLM), Zone Entropy (ZE) from the Gray Level Size Zone Matrix (GLSZM), and Dependence Entropy (DE) from the Gray Level Dependence Matrix (GLDM) feature sets were the only features that exhibited high reproducibility (COV ≤ 5%) against changes in all imaging settings. In addition, Large Area Low Gray Level Emphasis (LALGLE), Small Area Low Gray Level Emphasis (SALGLE) and Low Gray Level Zone Emphasis (LGLZE) from GLSZM, and Small Dependence Low Gray Level Emphasis (SDLGLE) from GLDM feature sets turned out to be less reproducible (COV > 20%) against changes in imaging settings. The GLRLM (31.88%) and GLDM feature set (54.2%) had the highest (COV < 5%) and lowest (COV > 20%) number of the reproducible features, respectively. Matrix size had the largest impact on feature variability as most of the features were not repeatable when matrix size was modified with 82.8% of them having a COV > 20%. CONCLUSION: The repeatability and reproducibility of SPECT/CT cardiac radiomic features under different imaging settings is feature-dependent. Different image acquisition and reconstruction protocols have variable effects on radiomic features. The radiomic features exhibiting low COV are potential candidates for future clinical studies.

Noninvasive Fuhrman grading of clear cell renal cell carcinoma using computed tomography radiomic features and machine learning.

PURPOSE: To identify optimal classification methods for computed tomography (CT) radiomics-based preoperative prediction of clear cell renal cell carcinoma (ccRCC) grade. MATERIALS AND METHODS: Seventy-one ccRCC patients (31 low grade and 40 high grade) were included in this study. Tumors were manually segmented on CT images followed by the application of three image preprocessing techniques (Laplacian of Gaussian, wavelet filter, and discretization of the intensity values) on delineated tumor volumes. Overall, 2530 radiomics features (tumor shape and size, intensity statistics, and texture) were extracted from each segmented tumor volume. Univariate analysis was performed to assess the association between each feature and the histological condition. Multivariate analysis involved the use of machine learning (ML) algorithms and the following three feature selection algorithms: the least absolute shrinkage and selection operator, Student's t test, and minimum Redundancy Maximum Relevance. These selected features were then used to construct three classification models (SVM, random forest, and logistic regression) to discriminate high from low-grade ccRCC at nephrectomy. Lastly, multivariate model performance was evaluated on the bootstrapped validation cohort using the area under the receiver operating characteristic curve (AUC) metric. RESULTS: The univariate analysis demonstrated that among the different image sets, 128 bin-discretized images have statistically significant different texture parameters with a mean AUC of 0.74 ± 3 (q value < 0.05). The three ML-based classifiers showed proficient discrimination between high and low-grade ccRCC. The AUC was 0.78 for logistic regression, 0.62 for random forest, and 0.83 for the SVM model, respectively. CONCLUSION: CT radiomic features can be considered as a useful and promising noninvasive methodology for preoperative evaluation of ccRCC Fuhrman grades.

MFP-Unet: A novel deep learning based approach for left ventricle segmentation in echocardiography.

Segmentation of the Left ventricle (LV) is a crucial step for quantitative measurements such as area, volume, and ejection fraction. However, the automatic LV segmentation in 2D echocardiographic images is a challenging task due to ill-defined borders, and operator dependence issues (insufficient reproducibility). U-net, which is a well-known architecture in medical image segmentation, addressed this problem through an encoder-decoder path. Despite outstanding overall performance, U-net ignores the contribution of all semantic strengths in the segmentation procedure. In the present study, we have proposed a novel architecture to tackle this drawback. Feature maps in all levels of the decoder path of U-net are concatenated, their depths are equalized, and up-sampled to a fixed dimension. This stack of feature maps would be the input of the semantic segmentation layer. The performance of the proposed model was evaluated using two sets of echocardiographic images: one public dataset and one prepared dataset. The proposed network yielded significantly improved results when comparing with results from U-net, dilated U-net, Unet++, ACNN, SHG, and deeplabv3. An average Dice Metric (DM) of 0.953, Hausdorff Distance (HD) of 3.49, and Mean Absolute Distance (MAD) of 1.12 are achieved in the public dataset. The correlation graph, bland-altman analysis, and box plot showed a great agreement between automatic and manually calculated volume, area, and length.

Noninvasive O6 Methylguanine-DNA Methyltransferase Status Prediction in Glioblastoma Multiforme Cancer Using Magnetic Resonance Imaging Radiomics Features: Univariate and Multivariate Radiogenomics Analysis.

BACKGROUND: This study aimed to predict methylation status of the O6 methylguanine-DNA methyltransferase (MGMT) gene promoter status by using magnetic resonance imaging radiomics features, as well as univariate and multivariate analysis. METHODS: Eighty-two patients who had an MGMT methylation status were included in this study. Tumors were manually segmented in the 4 regions of magnetic resonance images, 1) whole tumor, 2) active/enhanced region, 3) necrotic regions, and 4) edema regions. About 7000 radiomics features were extracted for each patient. Feature selection and classifier were used to predict MGMT status through different machine learning algorithms. The area under the curve (AUC) of the receiver operating characteristic curve was used for model evaluations. RESULTS: Regarding univariate analysis, the Inverse Variance feature From Gray Level Co-occurrence Matrix in whole tumor segment with 4.5 mm Sigma of Laplacian of Gaussian filter with AUC of 0.71 (P value = 0.002) was found to be the best predictor. For multivariate analysis, the Decision Tree classifier with Select from Model feature selector and LOG (Laplacian of Gaussian) filter in edema region had the highest performance (AUC, 0.78), followed by Ada-Boost classifier with Select from Model feature selector and LOG filter in edema region (AUC, 0.74). CONCLUSIONS: This study showed that radiomics using machine learning algorithms is a feasible noninvasive approach to predict MGMT methylation status in patients with glioblastoma multiforme cancer.