Postgraduate Students’ Experience of Using a Learning Management System to Support Their Learning: A Qualitative Descriptive Study

Introduction Educational institutions worldwide have implemented learning management systems (LMSs) to centralise and manage learning resources, educational services, learning activities and institutional information. LMS has mainly been used by teachers as storage and transfer of course material. To effectively utilise digital technologies in education, there is a need for more knowledge of student experiences with digital technology, such as LMSs and especially regarding how LMSs can contribute to student engagement and learning. Objective This study aimed to gain knowledge about postgraduate nursing students’ experiences with the use of LMS in a subject in an advanced practice nursing master's programme. Methods A qualitative method with a descriptive design was employed. Two focus group interviews were performed with eight postgraduate nursing students from an advanced practice nursing programme at a university college in Norway. Data were analysed using qualitative content analysis. Results Three themes emerged from the data material: 1) A course structure that supports learning; 2) LMS tools facilitate preparation, repetition and flexibility; and 3) own responsibility for using the LMS for preparation before on-campus activities. Conclusion The course structure within the LMS seemed to be important to enhance postgraduate students’ ability to prepare before on-campus activities. Implementation and use of LMS tools can facilitate preparation, repetition and flexibility, especially when postgraduate students study difficult topics. Postgraduate students seem to have different views regarding their own responsibility for using the LMS to prepare before on-campus activities.publishedVersio

Postgraduate Students’ Experience of Using a Learning Management System to Support Their Learning: A Qualitative Descriptive Study

Introduction Educational institutions worldwide have implemented learning management systems (LMSs) to centralise and manage learning resources, educational services, learning activities and institutional information. LMS has mainly been used by teachers as storage and transfer of course material. To effectively utilise digital technologies in education, there is a need for more knowledge of student experiences with digital technology, such as LMSs and especially regarding how LMSs can contribute to student engagement and learning. Objective This study aimed to gain knowledge about postgraduate nursing students’ experiences with the use of LMS in a subject in an advanced practice nursing master's programme. Methods A qualitative method with a descriptive design was employed. Two focus group interviews were performed with eight postgraduate nursing students from an advanced practice nursing programme at a university college in Norway. Data were analysed using qualitative content analysis. Results Three themes emerged from the data material: 1) A course structure that supports learning; 2) LMS tools facilitate preparation, repetition and flexibility; and 3) own responsibility for using the LMS for preparation before on-campus activities. Conclusion The course structure within the LMS seemed to be important to enhance postgraduate students’ ability to prepare before on-campus activities. Implementation and use of LMS tools can facilitate preparation, repetition and flexibility, especially when postgraduate students study difficult topics. Postgraduate students seem to have different views regarding their own responsibility for using the LMS to prepare before on-campus activities

Sample preparation approach influences pam50 risk of recurrence score in early breast cancer

The PAM50 gene expression subtypes and the associated risk of recurrence (ROR) score are used to predict the risk of recurrence and the benefits of adjuvant therapy in early-stage breast cancer. The Prosigna assay includes the PAM50 subtypes along with their clinicopathological features, and is approved for treatment recommendations for adjuvant hormonal therapy and chemotherapy in hormone-receptor-positive early breast cancer. The Prosigna test utilizes RNA extracted from macrodissected tumor cells obtained from formalin-fixed, paraffin-embedded (FFPE) tissue sections. However, RNA extracted from fresh-frozen (FF) bulk tissue without macrodissection is widely used for research purposes, and yields high-quality RNA for downstream analyses. To investigate the impact of the sample preparation approach on ROR scores, we analyzed 94 breast carcinomas included in an observational study that had available gene expression data from macrodissected FFPE tissue and FF bulk tumor tissue, along with the clinically approved Prosigna scores for the node-negative, hormone-receptor-positive, HER2-negative cases (n = 54). ROR scores were calculated in R; the resulting two sets of scores from FFPE and FF samples were compared, and treatment recommendations were evaluated. Overall, ROR scores calculated based on the macrodissected FFPE tissue were consistent with the Prosigna scores. However, analyses from bulk tissue yielded a higher proportion of cases classified as normal-like; these were samples with relatively low tumor cellularity, leading to lower ROR scores. When comparing ROR scores (low, intermediate, and high), discordant cases between the two preparation approaches were revealed among the luminal tumors; the recommended treatment would have changed in a minority of cases

An independent poor-prognosis subtype of breast cancer defined by a distinct tumor immune microenvironment

How mixtures of immune cells associate with cancer cell phenotype and affect pathogenesis is still unclear. In 15 breast cancer gene expression datasets, we invariably identify three clusters of patients with gradual levels of immune infiltration. The intermediate immune infiltration cluster (Cluster B) is associated with a worse prognosis independently of known clinicopathological features. Furthermore, immune clusters are associated with response to neoadjuvant chemotherapy. In silico dissection of the immune contexture of the clusters identified Cluster A as immune cold, Cluster C as immune hot while Cluster B has a pro-tumorigenic immune infiltration. Through phenotypical analysis, we find epithelial mesenchymal transition and proliferation associated with the immune clusters and mutually exclusive in breast cancers. Here, we describe immune clusters which improve the prognostic accuracy of immune contexture in breast cancer. Our discovery of a novel independent prognostic factor in breast cancer highlights a correlation between tumor phenotype and immune contexture

Optima: Optimal personalised treatment of early breast cancer using multi-parameter analysis, an international randomized trial of tumor gene expression test-directed chemotherapy treatment in a largely node-positive population

Background: Multi-parameter tumor gene expression assays (MPAs) are validated tools to assist adjuvant chemotherapy decisions for post-menopausal women with luminal-type node-negative breast cancer. Currently there is less certainty for women with 1-3 involved axillary lymph nodes and no information on MPA use for patients with higher level nodal involvement. Three RCTs with available data report chemotherapy benefit for premenopausal women; with limited use of ovarian function suppression (OFS) for non-chemotherapy treated participants, chemotherapy-induced menopause may explain these results. Methods: OPTIMA is an international academic, partially-blinded RCT of test-directed chemotherapy treatment with an adaptive design. Women and men aged 40 or older with resected luminal-type breast cancer may participate if they fulfil one of the following stage criteria: pN1-2; pN1mi with pT ≥20mm; pN0 with pT ≥30mm. Consenting patients are randomized between standard treatment with chemotherapy followed by endocrine therapy or to undergo Prosigna testing; those with high-Prosigna Score ( &gt; 60) tumors receive standard treatment whilst those with low-score tumors are treated with endocrine therapy alone. Patients are informed only of their treatment; test details, and randomization for chemotherapy-treated patients are masked. Clinical choice of chemotherapy is declared at randomization from a menu of standard regimens. Endocrine therapy must be for at least 5 years. Women postmenopausal at trial entry should receive an AI; men, tamoxifen; and premenopausal women, either an AI or tamoxifen, and OFS for 3 or more years; OFS initiation may be deferred because of post-chemotherapy amenorrhea. OPTIMA aims to randomize 2250 patients in each arm to demonstrate non-inferiority of test directed treatment, defined as not more than 3% below the estimated 85% 5-year IDFS for the control arm with a one sided 5% significance level. Power is 81% assuming recruitment over 96-months from January 2017 and 12 months minimum follow-up. OPTIMA also has at least 80% power to demonstrate 3.5% non-inferiority of IDFS for patients with low Prosigna Score tumors (estimated 65% of participants). Cox proportional hazards models will be used to explore important prognostic factors including menopausal status. Additional secondary endpoints include DRFI. A cost-effectiveness analysis of protocol specified MPA driven treatment against standard clinical practice will be conducted. At 31/01/2021, 2004 patients had been randomized. The DMC reviewed the trial in December 2020 with knowledge of related trial results and suggested that the trial continues as planned.<br/

An independent poor-prognosis subtype of breast cancer defined by a distinct tumor immune microenvironment

How mixtures of immune cells associate with cancer cell phenotype and affect pathogenesis is still unclear. In 15 breast cancer gene expression datasets, we invariably identify three clusters of patients with gradual levels of immune infiltration. The intermediate immune infiltration cluster (Cluster B) is associated with a worse prognosis independently of known clinicopathological features. Furthermore, immune clusters are associated with response to neoadjuvant chemotherapy. In silico dissection of the immune contexture of the clusters identified Cluster A as immune cold, Cluster C as immune hot while Cluster B has a pro-tumorigenic immune infiltration. Through phenotypical analysis, we find epithelial mesenchymal transition and proliferation associated with the immune clusters and mutually exclusive in breast cancers. Here, we describe immune clusters which improve the prognostic accuracy of immune contexture in breast cancer. Our discovery of a novel independent prognostic factor in breast cancer highlights a correlation between tumor phenotype and immune contexture