RESUMO
Background: Currently, surgical resection is the mainstay for colorectal liver metastases (CRLM) management and the only potentially curative treatment modality. Prognostication tools can support patient selection for surgical resection to maximize therapeutic benefit. This study aimed to develop a survival prediction model using machine learning based on a multicenter patient sample in Hong Kong. Methods: Patients who underwent hepatectomy for CRLM between 1 January 2009 and 31 December 2018 in four hospitals in Hong Kong were included in the study. Survival analysis was performed using Cox proportional hazards (CPH). A stepwise selection on Cox multivariable models with Least Absolute Shrinkage and Selection Operator (LASSO) regression was applied to a multiply-imputed dataset to build a prediction model. The model was validated in the validation set, and its performance was compared with that of Fong Clinical Risk Score (CRS) using concordance index. Results: A total of 572 patients were included with a median follow-up of 3.6 years. The full models for overall survival (OS) and recurrence-free survival (RFS) consist of the same 8 established and novel variables, namely colorectal cancer nodal stage, CRLM neoadjuvant treatment, Charlson Comorbidity Score, pre-hepatectomy bilirubin and carcinoembryonic antigen (CEA) levels, CRLM largest tumor diameter, extrahepatic metastasis detected on positron emission-tomography (PET)-scan as well as KRAS status. Our CRLM Machine-learning Algorithm Prognostication model (CMAP) demonstrated better ability to predict OS (C-index =0.651), compared with the Fong CRS for 1-year (C-index =0.571) and 5-year OS (C-index =0.574). It also achieved a C-index of 0.651 for RFS. Conclusions: We present a promising machine learning algorithm to individualize prognostications for patients following resection of CRLM with good discriminative ability.
RESUMO
BACKGROUND: Near-peer teaching (NPT) is becoming an increasingly popular pedagogical tool in health professions education. Despite the shift in formal medical education from face-to-face teaching toward encompassing web-based learning activities, NPT has not experienced a similar transition. Apart from the few reports on NPT programs hastily converted to web-based learning in light of the COVID-19 pandemic, no studies to date have explored web-based learning in the specific context of NPT. OBJECTIVE: This qualitative study examined the nature of interactions among peer learners (PLs), peer teachers (PTs), and the learning content in a student-led, web-based NPT program for medical students. METHODS: A 5-month-long voluntary NPT program to support first- and second-year medical students' biomedical science learning in the undergraduate medical curriculum was designed by 2 senior-year medical students and delivered by 25 PTs with 84 PLs participating. In total, 9 PLs and 3 PTs underwent individual semistructured interviews at the end of the program to explore general NPT experience, reasons for joining NPT, the effectiveness of NPT, the demand and importance of NPT, and the feasibility of incorporating NPT in the formal curriculum. Interview transcripts were analyzed using a thematic analysis approach. RESULTS: The first general theme focused on the nature of student-student, student-teacher, and student-content interactions. Although PLs were engaged in web-based NPT, there was minimal interaction between students, as most PLs preferred to learn passively and remain anonymous. PLs believed the web-based NPT learning process to be a unidirectional transmission of knowledge from teacher to learner, with the teacher responsible for driving the interactions. This was in sharp contrast to PTs' expectation that both parties shared responsibility for learning in a collaborative effort. The second general theme identified the advantages and disadvantages of delivering NPT on a web platform, which were mainly convenience and teaching skills development and poor interactivity, respectively. CONCLUSIONS: Student-led, web-based NPT offers a flexible and comfortable means of delivering academic and nonacademic guidance to medical students. However, the web-based mode of delivery presents unique challenges in facilitating meaningful interactions among PLs, PTs, and subject content. A blended learning approach may be best suited for this form of student-led NPT program to optimize its efficacy.
