Background and Purpose: Tumor recurrence, a characteristic of malignant tumors, is the biggest concern for rectal cancer survivors. The epidemiology of the disease calls for a pressing need to... Show moreBackground and Purpose: Tumor recurrence, a characteristic of malignant tumors, is the biggest concern for rectal cancer survivors. The epidemiology of the disease calls for a pressing need to improve healthcare quality and patient outcomes. Prediction models such as Bayesian networks, which can probabilistically reason under uncertainty, could assist caregivers with patient management. However, some concerns are associated with the standard approaches to developing these structures in medicine. Therefore, this study aims to compare Bayesian network structures that stem from these two techniques. Materials and Methods: A retrospective analysis was performed on 6754 locally advanced rectal cancer (LARC) patients enrolled in 14 international clinical trials. Local tumor recurrence at 2, 3, and 5-years was defined as the endpoints of interest. Five rectal cancer treating physicians from three countries elicited the expert structure. The algorithmic structure was inferred from the data with the hill-climbing algorithm. Structural performance was assessed with calibration plots and area under the curve values. Results: The area under the curve for the expert structure on the training and validation data was above 0.9 and 0.8, respectively, for all the time points. However, the algorithmic structure had superior predictive performance over the expert structure for all time points of interest. Conclusion: We have developed and internally validated a Bayesian networks structure from experts' opinions, which can predict the risk of a LARC patient developing a tumor recurrence at 2, 3, and 5 years. Our result shows that the algorithmic-based structures are more performant and less interpretable than expert based structures. Show less
Aim This study aimed to determine predictive factors for the circumferential resection margin (CRM) within two northern European countries with supposed similarity in providing rectal cancer care.... Show moreAim This study aimed to determine predictive factors for the circumferential resection margin (CRM) within two northern European countries with supposed similarity in providing rectal cancer care. Method Data for all patients undergoing rectal resection for clinical tumour node metastasis (TNM) stage I-III rectal cancer were extracted from the Swedish ColoRectal Cancer Registry and the Dutch ColoRectal Audit (2011-2015). Separate analyses were performed for cT1-3 and cT4 stage. Predictive factors for the CRM were determined using univariable and multivariable logistic regression analyses. Results A total of 6444 Swedish and 12 089 Dutch patients were analysed. Over time the number of hospitals treating rectal cancer decreased from 52 to 42 in Sweden, and 82 to 79 in the Netherlands. In the Swedish population, proportions of cT4 stage (17% vs 8%), multivisceral resection (14% vs 7%) and abdominoperineal excision (APR) (37% vs 31%) were higher. The overall proportion of patients with a positive CRM (CRM+) was 7.8% in Sweden and 5.4% in the Netherlands. In both populations with cT1-3 stage disease, common independent risk factors for CRM+ were cT3, APR and multivisceral resection. No common risk factors for CRM+ in cT4 stage disease were found. An independent impact of hospital volume on CRM+ could be demonstrated for the cT1-3 Dutch population. Conclusion Within two northern European countries with implemented clinical auditing, rectal cancer care might potentially be improved by further optimizing the treatment of distal and locally advanced rectal cancer. Show less
