The COVID-19 pandemic continues to spread globally at a rapid pace, and its rapid detection remains a challenge due to its rapid infectivity and limited testing availability. One of the simply ...available imaging modalities in clinical routine involves chest X-ray (CXR), which is often used for diagnostic purposes. Here, we proposed a computer-aided detection of COVID-19 in CXR imaging using deep and conventional radiomic features. First, we used a 2D U-Net model to segment the lung lobes. Then, we extracted deep latent space radiomics by applying deep convolutional autoencoder (ConvAE) with internal dense layers to extract low-dimensional deep radiomics. We used Johnson-Lindenstrauss (JL) lemma, Laplacian scoring (LS), and principal component analysis (PCA) to reduce dimensionality in conventional radiomics. The generated low-dimensional deep and conventional radiomics were integrated to classify COVID-19 from pneumonia and healthy patients. We used 704 CXR images for training the entire model (i.e., U-Net, ConvAE, and feature selection in conventional radiomics). Afterward, we independently validated the whole system using a study cohort of 1597 cases. We trained and tested a random forest model for detecting COVID-19 cases through multivariate binary-class and multiclass classification. The maximal (full multivariate) model using a combination of the two radiomic groups yields performance in classification cross-validated accuracy of 72.6% (69.4-74.4%) for multiclass and 89.6% (88.4-90.7%) for binary-class classification.
Chemotherapy-induced autophagy is a proposed mechanism of chemoresistance and potential therapeutic target in osteosarcoma. We evaluated heat shock protein 27 (HSP27) and autophagy-related proteins ...as predictors of pathologic treatment response and prognostic markers among osteosarcoma patients who received standard chemotherapy. We analyzed 394 tumor specimens (pre-treatment, post-treatment, and metastases) from 260 osteosarcoma patients by immunohistochemistry for cytoplasmic light chain 3B (LC3B)-positive puncta, sequestosome 1 (SQSTM1), high mobility group box 1 (HMGB1), and HSP27 expression. The staining percentage and intensity for each marker were scored and the extent to which marker expression was correlated with pathologic response, relapse-free survival (RFS), and overall survival (OS) was assessed. LCB3
puncta in post-treatment primary tumors (50%) and metastases (67%) was significantly higher than in pre-treatment biopsy specimens (30%;
= 0.023 and <0.001). Among 215 patients with localized osteosarcoma, both pre-treatment multivariate hazard ratio (HR), 26.7; 95% confidence interval (CI), 1.47-484;
= 0.026 and post-treatment HSP27 expression (multivariate HR, 1.85; 95% CI, 1.03-3.33;
= 0.039) were associated with worse OS. Lack of LC3B
puncta at resection was an independent poor prognostic marker in both univariate (HR, 1.78; 95% CI, 1.05-3.03;
= 0.034) and multivariate models (HR, 1.75; 95% CI, 1.01-3.04;
= 0.045). Patients with LC3B
/HSP27
tumors at resection had the best 10-year OS (75%) whereas patients with LC3B
/HSP27
tumors had the worst 10-year survival (25%). Neither HSP27 expression nor the presence of LCB3
puncta was correlated with pathologic treatment response. Our findings establish HSP27 expression and LC3B
puncta as independent prognostic markers in osteosarcoma patients receiving standard chemotherapy and support further investigation into strategies targeting HSP27 or modulating autophagy in osteosarcoma treatment.
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Metastatic colorectal cancer (mCRC) continues to show poor outcomes, with many patients exhausting effective standard‐of‐care therapy. To explore the current landscape of clinical trials for mCRC, we ...reviewed over 600 clinical trials that are currently ongoing for mCRC patients. Immunotherapeutic agents form approximately 39% (includes monoclonal antibodies, viruses, vaccines, and immunomodulators) of all agents and targeted therapy forms 45% (tyrosine kinase inhibitors, epigenetic modulators, and others) of all agents being investigated for mCRC.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Cancer patients are particularly vulnerable to COVID-19, partially owing to their compromised immune systems and curbed or cut cancer healthcare services caused by the pandemic. As a result, cancer ...caregivers may have to shoulder triple crises: the COVID-19 pandemic, pronounced healthcare needs from the patient, and elevated need for care from within. While technology-based health interventions have the potential to address unique challenges cancer caregivers face amid COVID-19, limited insights are available. Thus, to bridge this gap, we aim to identify technology-based interventions designed for cancer caregivers and report the characteristics and effects of these interventions concerning cancer caregivers' distinctive challenges amid COVID-19.
A systematic search of the literature will be conducted in PubMed, PsycINFO, CINAHL, and Scopus from the database inception to the end of March 2021. Articles that center on technology-based interventions for cancer caregivers will be included in the review. The search strategy will be developed in consultation with an academic librarian who is experienced in systematic review studies. Titles, abstracts, and full-text articles will be screened against eligibility criteria developed a priori. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses procedures will be followed for the reporting process.
COVID-19 has upended cancer care as we know it. Findings of this study can shed light on evidence-based and practical solutions cancer caregivers can utilize to mitigate the unique challenges they face amid COVID-19. Furthermore, results of this study will also offer valuable insights for researchers who aim to develop interventions for cancer caregivers in the context of COVID-19. In addition, we also expect to be able to identify areas for improvement that need to be addressed in order for health experts to more adequately help cancer caregivers weather the storm of global health crises like COVID-19 and beyond. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42020196301.
Evidence regarding the association between body mass index (BMI) and immune-related adverse events (irAEs) among cancer patients receiving immune checkpoint inhibitors (ICIs) is limited. Here, we use ...cross-sectional hospital-based data to explore their relationship. Pre-treatment BMI was treated as an ordinal variable (<25, 25 to ≤30, ≥30 kg/m
). The outcome of interest was irAEs after ICI initiation. A multivariable logistic regression model estimated the adjusted odds ratio (aOR) and 95% confidence interval (CI) of BMI. A total of 684 patients with stage III or IV cancer were included in the study (lung: 269, melanoma: 204, other: 211). The mean age at the first dose of ICI was 64.1 years (SD = 13.5), 394 patients (57.6%) were male, and over one-third (
= 260, 38.0%) were non-White. Overall, 52.9% of patients had BMI ≥ 25 kg/m
(25 to ≤30: 217, ≥30: 145) and 288 (42.1%) had irAEs after ICI treatment. Patients with higher BMI tended to have a higher rate of irAEs (<25: 35.7%, 25 to ≤30: 47.0%, ≥30: 49.0%). The multivariable logistic regression yielded consistent results (BMI ≥ 30 vs. BMI < 25: aOR = 1.47, 95% CI = 0.96-2.23; 25 ≤ BMI < 30 vs. BMI < 25: aOR = 1.46, 95% CI = 1.02-2.11,
-trend = 0.04). In conclusion, among patients with advanced cancer receiving ICIs, the rate of irAEs appears to be higher among those with higher BMI.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Few treatment decision support interventions (DSIs) are available to engage patients diagnosed with late-stage non-small cell lung cancer (NSCLC) in treatment shared decision making (SDM). We ...designed a novel DSI that includes care plan cards and a companion patient preference clarification tool to assist in shared decision making. The cards answer common patient questions about treatment options (chemotherapy, chemotherapy plus immunotherapy, targeted therapy, immunotherapy, clinical trial participation, and supportive care). The form elicits patient treatment preference. We then conducted interviews with clinicians and patients to obtain feedback on the DSI. We also trained oncology nurse educators to implement the prototype. Finally, we pilot tested the DSI among five patients with NSCLC at the beginning of an office visit scheduled to discuss treatment with an oncologist. Analyses of pilot study baseline and exit survey data showed that DSI use was associated with increased patient awareness of the alternatives’ treatment options and benefits/risks. In contrast, patient concern about treatment costs and uncertainty in treatment decision making decreased. All patients expressed a treatment preference. Future randomized controlled trials are needed to assess DSI implementation feasibility and efficacy in clinical care.
Breast density is associated with breast cancer risk in women aged 40 to 65 years, but there is limited evidence of its association with risk of breast cancer among women aged 65 years or older.
To ...compare the association between breast density and risk of invasive breast cancer among women aged 65 to 74 years vs women aged 75 years or older and to evaluate whether the association is modified by body mass index (BMI).
This prospective cohort study used data from the Breast Cancer Surveillance Consortium from January 1, 1996, to December 31, 2012, for US women aged 65 years or older who underwent screening mammography. Data were analyzed from January 1, 2018, to December 31, 2020.
Breast Imaging Reporting and Data System breast density category, age, and BMI.
The 5-year cumulative incidence of invasive breast cancer by level of breast density (almost entirely fat, scattered fibroglandular densities, or heterogeneous or extreme density) and age (65-74 vs ≥75 years) was calculated using weighted means. Cox proportional hazards models were fit to estimate the association of breast density with invasive breast cancer risk. The likelihood ratio test was used to test the interaction between BMI and breast density.
A total of 221 714 screening mammograms from 193 787 women were included in the study; a total of 38% of the study population was aged 75 years or older. Of the mammograms, most were from women aged 65 to 74 years (64.6%) and non-Hispanic White individuals (81.4%). The 5-year cumulative incidence of invasive breast cancer increased in association with increasing breast density among women aged 65 to 74 years (almost entirely fatty breasts: 11.3 per 1000 women 95% CI, 10.4-12.5 per 1000 women; scattered fibroglandular densities: 17.2 per 1000 women 95% CI, 16.1-17.9 per 1000 women; extremely or heterogeneously dense breasts: 23.7 per 1000 women 95% CI, 22.4-25.3 per 1000 women) and among those aged 75 years or older (fatty breasts: 13.5 per 1000 women 95% CI, 11.6-15.5; scattered fibroglandular densities: 18.4 per 1000 women 95% CI, 17.0-19.5 per 1000 women; extremely or heterogeneously dense breasts: 22.5 per 1000 women 95% CI, 20.2-24.2 per 1000 women). Extreme or heterogeneous breast density was associated with increased risk of breast cancer compared with scattered fibroglandular breast density in both age categories (65-74 years: hazard ratio HR, 1.39 95% CI, 1.28-1.50; ≥75 years: HR, 1.23 95% CI, 1.10-1.37). Women with almost entirely fatty breasts had a decrease of approximately 30% (range, 27%-34%) in the risk of invasive breast cancer compared with women with scattered fibroglandular breast density (65-74 years: HR, 0.66 95% CI, 0.58-0.75; ≥75 years: HR, 0.73; 95% CI, 0.62-0.86). Associations between breast density and breast cancer risk were not significantly modified by BMI (for age 65-74 years: likelihood ratio test, 2.67; df, 2; P = .26; for age ≥75 years, 2.06; df, 2; P = .36).
The findings suggest that breast density is associated with increased risk of invasive breast cancer among women aged 65 years or older. Breast density and life expectancy should be considered together when discussing the potential benefits vs harms of continued screening mammography in this population.
IntroductionA growing number of technology-based interventions are used to support the health and quality of life of nursing home residents. The onset of COVID-19 and recommended social distancing ...policies that followed led to an increased interest in technology-based solutions to provide healthcare and promote health. Yet, there are no comprehensive resources on technology-based healthcare solutions that describe their efficacy for nursing home residents. This systematic review will identify technology-based interventions designed for nursing home residents and describe the characteristics and effects of these interventions concerning the distinctive traits of nursing home residents and nursing facilities. Additionally, this paper will present practical insights into the varying intervention approaches that can assist in the delivery of broad digital health solutions for nursing home residents amid and beyond the impact of COVID-19.Methods and analysisDatabases including the PubMed, PsycINFO, CINAHL and Scopus will be used to identify articles related to technology-based interventions for nursing home residents published between 1 January 2010 to 30 September 2021. Titles, abstracts and full-text papers will be reviewed against the eligibility criteria. The Cochrane Collaboration evaluation framework will be adopted to examine the risk of bias of the included study. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses procedures will be followed for the reporting process and implications for existing interventions and research evaluated by a multidisciplinary research team.Ethics and disseminationAs the study is a protocol for a systematic review, ethical approval is not required. The study findings will be disseminated via peer-reviewed publications and conference presentations.Trial registration numberCRD 42020191880.
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