PURPOSE Early identification of patients who may be at high risk of significant weight loss (SWL) is important for timely clinical intervention in lung cancer radiotherapy (RT). A clinical decision support system (CDSS) for SWL prediction was implemented within the routine clinical workflow and assessed on a prospective cohort of patients. MATERIALS AND METHODS CDSS incorporated a machine learning prediction model on the basis of radiomics and dosiomics image features and was connected to a web-based dashboard for streamlined patient enrollment, feature extraction, SWL prediction, and physicians' evaluation processes. Patients with lung cancer (N = 37) treated with definitive RT without prior RT were prospectively enrolled in the study. Radiomics and dosiomics features were extracted from CT and 3D dose volume, and SWL probability (≥ 0.5 considered as SWL) was predicted. Two physicians predicted whether the patient would have SWL before and after reviewing the CDSS prediction. The physician's prediction performance without and with CDSS and prediction changes before and after using CDSS were compared. RESULTS CDSS showed significantly better prediction accuracy than physicians (0.73 v 0.54) with higher specificity (0.81 v 0.50) but with lower sensitivity (0.55 v 0.64). Physicians changed their original prediction after reviewing CDSS prediction for four cases (three correctly and one incorrectly), for all of which CDSS prediction was correct. Physicians' prediction was improved with CDSS in accuracy (0.54-0.59), sensitivity (0.64-0.73), specificity (0.50-0.54), positive predictive value (0.35-0.40), and negative predictive value (0.76-0.82). CONCLUSION Machine learning–based CDSS showed the potential to improve SWL prediction in lung cancer RT. More investigation on a larger patient cohort is needed to properly interpret CDSS prediction performance and its benefit in clinical decision making.
This article analyzes transformations in Brazilian agriculture in the light of the relations between the rural sector and the Brazilian model of economic development during the last 50 years. The article aims to distinguish the period prior to the crisis of the 1980s with that prevailing in the last two decades, focusing on the State's intervention in the rural context. Particular attention is given to the way in which the Brazilian State incorporated specific interests from different rural segments, both in the developmentalist phase and the subsequent period marked by fiscal crisis.
Background: Here, we investigated the relationship between clinical parameters, including the site of surgical anastomosis and radiation dose to the anastomotic region, and anastomotic complications in esophageal cancer patients treated with trimodality therapy. Methods: Between 2007 and 2016, esophageal cancer patients treated with trimodality therapy at a tertiary academic cancer center were identified. Patient, treatment, and outcome parameters were collected. Radiation dose to the gastric regions were extracted. Anastomotic complication was defined as leak and/or stricture. We used Fisher's exact and Wilcoxon rank-sum tests to compare the association between clinical parameters and anastomotic complications. Results: Of 89 patients identified, the median age was 63 years, 82% (n = 73) were male, and 82% had distal (n = 47) or gastroesophageal junction (n = 26) tumors. Median follow-up was 25.8 months. Esophagectomies were performed with cervical (65%, n = 58) or thoracic anastomoses (35%, n = 31). Anastomotic complications developed in 60% (n = 53). Cervical anastomosis was associated with anastomotic complications (83%, n = 44/53, p < 0.01). Radiation to any gastric substructure was not associated with anastomotic complications (p > 0.05). In the subset of patients with distal/gastroesophageal junction tumors undergoing esophagectomy with cervical anastomosis where radiation was delivered to the future neoesophagus, 80% (n = 35/ 44) developed anastomotic complications. In this high-risk subgroup, radiation was not associated with anastomotic complications (p > 0.05). Conclusions: Our analysis did not demonstrate an association between radiation dose to gastric substructures and anastomotic complications. However, it showed an association between esophagectomy with cervical anastomosis and anastomotic complications. Patients with distal/gastroesophageal junction tumors who undergo esophagectomy with cervical anastomosis have higher rates of anastomotic complications unrelated to radiation to gastric substructures.
ratio for the effect of treatment group on OS. Using only patients in the matched dataset, the distribution of OS was estimated with the Kaplan-Meier method by treatment group. Results: Starting with an unmatched dataset of 978 patients, 582 patients were selected into the matched dataset: 388 in the CRT group and 194 in the chemotherapy alone group. The HR for the group effect was 0.751 (95% CI 0.613-0.920), two-sided p-value of 0.006. Median OS in the CRT group was 21.1 months (95% CI: 17.4-24.0) versus 14.6 months in the CT group (95% CI: 12.2-18.4). Corresponding 5-year OS rates were 23% (95% CI: 18-28%) and 14% (95% CI: 7-21%), respectively. Additionally, male patients (p<0.001) and patients with visceral metastasis (versus nodal metastasis) (pZ0.005) had worse outcomes. Conclusion: In this largest series to date analyzing outcomes in stage IV patients, CRT was associated with improved OS versus CT alone. In view of lack of prospective data in this setting, this evidence will help guide treatment approaches in this uncommon group of patients.
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