Purpose
Previous research showed the benefits of mindfulness meditation on the mental health and quality of life of breast cancer patients. Traditionally, these programs relied on in-person interactions, but the COVID-19 pandemic necessitated alternative delivery methods. This study evaluated the effectiveness and feasibility of a mindfulness-based self-help (MBSH) program via Netflix for breast cancer patients undergoing radiotherapy.
Materials and Methods
This prospective non-randomized controlled study assigned patients to a control or MBSH group based on age and preference. The MBSH group watched episodes of "Headspace Guide to Meditation" on Netflix and practiced guided meditation at least twice per week for four weeks. Participants completed questionnaires assessing depression, anxiety, stress, insomnia, mindfulness, mental adjustment to cancer, and quality of life at weeks 0 and 8. Data were analyzed using a two-way repeated measures ANOVA.
Results
Ninety-six patients participated, with 84 eligible for final analysis (44 control, 40 MBSH). Intention-to-treat analysis revealed a significant improvement in depression (f=4.306, p=0.041). Half of the experimental group (n = 20) adhered to the study protocol. At week 8, the experimental group showed significant improvement compared to the control group in cognitive avoidance (f=8.530, p=0.005) and positive attitude (f=5.585, p=0.021), both indicative of adaptive coping strategies.
Conclusion
This study firstly investigated the effect and feasibility of a Netflix-based MBSH program for breast cancer patients undergoing radiotherapy. Findings suggest MBSH on Netflix can improve mental health and adaptive mental adjustment, highlighting the potential of self-help mindfulness interventions to enhance the well-being of cancer patients and need for further research.
Purpose We investigated the effects of economic status (classified based on insurance type and residential area) on oncological outcomes of prostate cancer using a nationwide database. We additionally investigated oncological outcomes based on economic status and residential area in patients who underwent surgical treatment.
Materials and Methods The study included 75,518 men with newly diagnosed prostate cancer between 2009 and 2018 in whom oncological outcomes were investigated based on economic status and residential area. Among the 75,518 men with prostate cancer, the data of 29,973 men who underwent radical prostatectomy were further analyzed. Multivariate analysis was performed to determine the effects of economic status and residential area on postoperative oncological outcomes.
Results Among the 75,518 patients with prostate cancer, 3,254 (4.31%) were medical aid beneficiaries. The 5-year overall survival rates were 81.2% and 64.8% in the health insurance and medical aid groups, respectively. Radical prostatectomy was more common in the health insurance group, and surgical intervention was significantly affected by the residential area. Among patients who underwent surgery, 5-year androgen deprivation therapy–free and overall survival were better in the health insurance group. Multivariate analysis showed that insurance type and residential area were significantly associated with the androgen deprivation therapy–free and overall survival after adjustment for other variables.
Conclusion Economic status and residential area were shown to affect not only treatment patterns but also post-diagnosis and postoperative oncological outcomes. Political support for early diagnosis and appropriate treatment of prostate cancer is warranted for medically vulnerable populations.
Young-Gon Kim, In Hye Song, Hyunna Lee, Sungchul Kim, Dong Hyun Yang, Namkug Kim, Dongho Shin, Yeonsoo Yoo, Kyowoon Lee, Dahye Kim, Hwejin Jung, Hyunbin Cho, Hyungyu Lee, Taeu Kim, Jong Hyun Choi, Changwon Seo, Seong il Han, Young Je Lee, Young Seo Lee, Hyung-Ryun Yoo, Yongju Lee, Jeong Hwan Park, Sohee Oh, Gyungyub Gong
Cancer Res Treat. 2020;52(4):1103-1111. Published online June 30, 2020
Purpose
Assessing the status of metastasis in sentinel lymph nodes (SLNs) by pathologists is an essential task for the accurate staging of breast cancer. However, histopathological evaluation of sentinel lymph nodes by a pathologist is not easy and is a tedious and time-consuming task. The purpose of this study is to review a challenge competition (HeLP 2018) to develop automated solutions for the classification of metastases in hematoxylin and eosin–stained frozen tissue sections of SLNs in breast cancer patients.
Materials and Methods
A total of 297 digital slides were obtained from frozen SLN sections, which include post–neoadjuvant cases (n = 144, 48.5%) in Asan Medical Center, South Korea. The slides were divided into training, development, and validation sets. All of the imaging datasets have been manually segmented by expert pathologists. A total of 10 participants were allowed to use the Kakao challenge platform for six weeks with two P40 GPUs. The algorithms were assessed in terms of the AUC (area under receiver operating characteristic curve).
Results
The top three teams showed 0.986, 0.985, and 0.945 AUCs for the development set and 0.805, 0.776, and 0.765 AUCs for the validation set. Micrometastatic tumors, neoadjuvant systemic therapy, invasive lobular carcinoma, and histologic grade 3 were associated with lower diagnostic accuracy.
Conclusion
In a challenge competition, accurate deep learning algorithms have been developed, which can be helpful in making frozen diagnosis of intraoperative sentinel lymph node biopsy. Whether this approach has clinical utility will require evaluation in a clinical setting
Citations
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Diagnostic Assessment of Deep Learning Algorithms for Frozen Tissue Section Analysis in Women with Breast Cancer Young-Gon Kim, In Hye Song, Seung Yeon Cho, Sungchul Kim, Milim Kim, Soomin Ahn, Hyunna Lee, Dong Hyun Yang, Namkug Kim, Sungwan Kim, Taewoo Kim, Daeyoung Kim, Jonghyeon Choi, Ki-Sun Lee, Minuk Ma, Minki Jo, So Yeon Park, Gyungyub Gong Cancer Research and Treatment.2023; 55(2): 513. CrossRef
Artificial intelligence and frozen section histopathology: A systematic review Benjamin G. Gorman, Mark A. Lifson, Nahid Y. Vidal Journal of Cutaneous Pathology.2023; 50(9): 852. CrossRef
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Purpose
We investigated B-cell lymphoma 2 (BCL2) regulation across DNA, RNA, protein, and methylation status according to molecular subtype of breast cancer using The Cancer Genome Atlas (TCGA) database.
Materials and Methods
We analyzed clinical and biological data on 1,096 breast cancers from the TCGA database. Biological data included reverse phase protein array (RPPA), mRNA sequencing (mRNA-seq), mRNA microarray, methylation, copy number alteration linear, copy number alteration nonlinear, and mutation data.
Results
The luminal A and luminal B subtypes showed upregulated expression of RPPA and mRNAseq and hypomethylation compared to the human epidermal growth factor receptor 2 (HER2) and triple-negative subtypes (all p < 0.001). No mutations were found in any subjects. High mRNA-seq and high RPPA were strongly associated with positive estrogen receptor, positive progesterone receptor (all p < 0.001), and negative HER2 (p < 0.001 and p=0.002, respectively). Correlation analysis revealed a strong positive correlation between protein and mRNA levels and a strong negative correlation between methylation and protein and mRNA levels (all p < 0.001). The high BCL2 group showed superior overall survival compared to the low BCL2 group (p=0.006).
Conclusion
The regulation of BCL2 was mainly associated with methylation across the molecular subtypes of breast cancer, and luminal A and luminal B subtypes showed upregulated expression of BCL2 protein, mRNA, and hypomethylation. Although copy number alteration may have played a minor role, mutation status was not related to BCL2 regulation. Upregulation of BCL2 was associated with superior prognosis than downregulation of BCL2.
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Cancer Res Treat. 2017;49(4):1114-1126. Published online February 2, 2017
Purpose
This study investigated the role of the education level (EL) as a prognostic factor for breast cancer and analyzed the relationship between the EL and various confounding factors.
Materials and Methods
The data for 64,129 primary breast cancer patients from the Korean Breast Cancer Registry were analyzed. The EL was classified into two groups according to the education period; the high EL group (≥ 12 years) and low EL group (< 12 years). Survival analyses were performed with respect to the overall survival between the two groups.
Results
A high EL conferred a superior prognosis compared to a low EL in the subgroup aged > 50 years (hazard ratio, 0.626; 95% confidence interval [CI], 0.577 to 0.678) but not in the subgroup aged ≤ 50 years (hazard ratio, 0.941; 95% CI, 0.865 to 1.024). The EL was a significant independent factor in the subgroup aged > 50 years according to multivariate analyses. The high EL group showed more favorable clinicopathologic features and a higher proportion of patients in this group received lumpectomy, radiation therapy, and endocrine therapy. In the high EL group, a higher proportion of patients received chemotherapy in the subgroups with unfavorable clinicopathologic features. The EL was a significant prognosticator across all molecular subtypes of breast cancer.
Conclusion
The EL is a strong independent prognostic factor for breast cancer in the subgroup aged > 50 years regardless of the molecular subtype, but not in the subgroup aged ≤ 50 years. Favorable clinicopathologic features and active treatments can explain the main causality of the superior prognosis in the high EL group.
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