Unveiling the Burden of Interactions Among Clinical Risk Factors for 1-Year Mortality in Hospitalized Older Patients

Background: Hospitalized older patients are particularly exposed to adverse health outcomes.Objective: In this study, we aimed at investigating the prognostic interactions between disability in basic activities of daily living (BADL), cognitive impairment, low handgrip strength, anticholinergic cognitive burden (ACB), and depression on 1-year mortality.Setting and Subjects: Our series consisted of 503 older patients discharged from acute care hospitals.Methods: Disability in at least one BADL, ACB, depression, cognitive impairment, and low handgrip strength was considered in the analysis. One-year mortality was investigated by Cox regression analysis and prognostic interactions among study variables were assessed by survival tree analysis.Results: Basic activities of daily living disability, ACB, cognitive impairment, and low handgrip strength were significantly associated with 1-year mortality. Survival tree analysis showed that patients with BADL disability and high ACB carried the highest risk of poor survival [hazard ratio (HR): 16.48 (2.63–74.72)], followed by patients with BADL disability and low ACB (HR: 8.43, 95% CI: 1.85–38.87). Patients with cognitive impairment and no BADL disability were characterized by a lower but still significant risk of mortality (HR: 6.61, 95% CI: 1.51–28.97) and those with high ACB scores and good cognitive and functional performance (HR: 5.28, 95% CI: 1.13–24.55).Conclusion: Basic activities of daily living dependency, cognitive impairment, and ACB score were the three main predictors of 1-year mortality among patients discharged from acute care hospitals; the interaction between BADL dependency and ACB score wasfound to significantly affect survival. Early identification of such high-risk patients may help tailor targeted interventions to counteract their detrimental effects on prognosis.

Application of ensemble clustering and survival tree analysis for identifying prognostic clinicogenomic features in patients with colorectal cancer from the 100,000 Genomes Project

Objective The objective of this study was to employ ensemble clustering and tree-based risk model approaches to identify interactions between clinicogenomic features for colorectal cancer using the 100,000 Genomes Project. Results Among the 2211 patients with colorectal cancer (mean age of diagnosis: 67.7; 59.7% male), 16.3%, 36.3%, 39.0% and 8.4% had stage 1, 2, 3 and 4 cancers, respectively. Almost every patient had surgery (99.7%), 47.4% had chemotherapy, 7.6% had radiotherapy and 1.4% had immunotherapy. On average, tumour mutational burden (TMB) was 18 mutations/Mb and 34.4%, 31.3% and 25.7% of patients had structural or copy number mutations in KRAS, BRAF and NRAS, respectively. In the fully adjusted Cox model, patients with advanced cancer [stage 3 hazard ratio (HR) = 3.2; p < 0.001; stage 4 HR = 10.2; p < 0.001] and those who had immunotherapy (HR = 1.8; p < 0.04) or radiotherapy (HR = 1.5; p < 0.02) treatment had a higher risk of dying. The ensemble clustering approach generated four distinct clusters where patients in cluster 2 had the best survival outcomes (1-year: 98.7%; 2-year: 96.7%; 3-year: 93.0%) while patients in cluster 3 (1-year: 87.9; 2-year: 70.0%; 3-year: 53.1%) had the worst outcomes. Kaplan–Meier analysis and log rank test revealed that the clusters were separated into distinct prognostic groups (p < 0.0001). Survival tree or recursive partitioning analyses were performed to further explore risk groups within each cluster. Among patients in cluster 2, for example, interactions between cancer stage, grade, radiotherapy, TMB, BRAF mutation status were identified. Patients with stage 4 cancer and TMB ≥ 1.6 mutations/Mb had 4 times higher risk of dying relative to the baseline hazard in that cluster.

Application of Survival Tree Model in Determining Affecting Factors in Breastfeeding Duration

Background and Purpose: Survival tree model is a nonparametric method which can be used to identify the affecting factors from a specific time to the onset of an event. In this method, the categories are selected according to the most important factors. The purpose of this study was to determine the factors affecting the duration of breastfeeding in mothers and introduce the homogeneous subgroups using a survival tree model. Materials and Methods: It was a historical cohort study analyzing the survival data of mothers with healthy single childbirths referring to the rural and urban health centers of Agh-Ghala County since 2011 until 2014. Data analyses and groupings of breastfeeding survival were performed using survival tree model with conditional inference algorithm in R Software. A separation criterion (SEP) confirmed the relevance of the model. Results: Survival tree model results revealed that the type of consumed milk with the complementary nutrition, ethnicity and the time interval between current childbirth and the previous delivery were the most important factors affecting the duration of breastfeeding. The SEP's criterion was 2.082. Thus, due to the significant difference between the subgroups and the value of more than 1 for SEP criterion, the efficiency of the model was confirmed. Conclusion: Survival tree model could be introduced as a suitable and powerful method for ranking the duration of breastfeeding rate which presents four homogeneous subgroups for analysis in addition to identifying the predictive variables.

Real-world prognostic model for malignant pleural mesothelioma.

e20562 Background: Two mesothelioma prognostic models have been suggested: European Organisation for Research and Treatment of Cancer (EORTC) and Cancer and Leukaemia Group B (CALGB) models. Both were based on clinical trial patients enrolled in the mid-1980s to early-1990s. Several changes to mesothelioma management have been adopted since publication of these models, including improved surgical and palliative interventions and changes to systemic therapy. Methods: With ethics approval, we collected and analyzed the health data of malignant pleural mesothelioma (MPM) patients with histologically confirmed diagnosis treated at our institution between January 1991 and March 2019. The primary endpoint was overall survival (OS). Univariate analysis was used to identify significant predictors of survival, which were then used to construct a multivariate survival tree with complete case-analysis and bootstrapping. Patients were then stratified into three prognostic groups based on their median OS. Results: 337 patients were included in the study; 309 (91.7%) were dead at last follow-up. The median OS was 9.4 (8.1-11.5) months for the entire population. Eastern Cooperative Oncology Group (ECOG) performance status (PS), histology, white blood count, platelets, International Mesothelioma Interest Group stage, age and hemoglobin were independent predictors of survival. The final pruned survival tree was based on 285 patients and incorporated the first five predictors. Good, intermediate and poor prognostic groups had median OS of > 12 months, 6-12 months, and < 6 months, respectively. Factors associated with the prognostic groups were: good prognosis: ECOG 0-1, normal platelets, stage 1, 2 and epithelioid histology; intermediate prognosis: ECOG 0-1 with either stage 3, 4 and/or sarcomatoid or biphasic histology; poor prognosis: ECOG 2-4 regardless of other factors. Conclusions: In contrast to EORTC/CALGB, real world evidence generates these prognostic groups with face validity but will need independent validation. Our data does not account for recent advances including immunotherapy, and thus patients with non-epithelioid histology may have better survival than predicted.[Table: see text]

Evaluation of select cider apple (Malus domestica Borkh.) cultivars grown in Ontario. I. Horticultural attributes

Twenty-eight apple cultivars were selected for their potential for hard cider production in Ontario. An experiment was conducted to evaluate their horticultural potential in the province. After being planted in spring 2015, the trees were evaluated annually for their survival, tree height and spread, trunk growth, flowering dates, flower counts, fruit per tree, pre-harvest drop, crop load, fruit weight, fruit firmness, juicing extraction efficiency, and harvest dates. These horticultural attributes were sufficient to discriminate between cultivars. Additional exploratory analyses indicated a relationship between horticultural attributes and a cultivar’s origin, with British cider cultivars blooming the latest, American cider apples producing the most juice, and French cider cultivars having the highest pre-harvest fruit drop. Cultivars in this study that show promise for continued research in Ontario include Binet Rouge, Bramley’s Seedling, Breakwell, Bulmers Norman, Calville Blanc d’Hiver, Cline Russet, Cox Orange Pippin, Crimson Crisp®, Dabinett, Enterprise, Esopus Spitzenberg, Golden Russet, GoldRush, Medaille d’Or, Porter’s Perfection, and Stoke Red.