Identification and Characterization of Long Term Survival Population In Non-Small-Cell Lung Cancer Patients Treated With Immunotherapies
Patricia Lorenzo LuacesL. SánchezCarmen ViadaP.C. RodríguezMarco Polo Peralta ÁlvarezCarla FonteLeacky MucheneS. ShkedyA. Lage
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Les recentes modifications de la politique d'immigration en Australie ont accru la selection des immigrants (criteres d'utilite economique et sociale). Pres de 20 % de la population australienne ne parle pas aujourd'hui l'anglais comme premiere langue. Dans la milieu scolaire, cette proportion passe de 30 a 90 %. L'A. evalue les consequences a court terme et a long terme des modifications de la politique de l'immigration sur le systeme scolaire
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<p>Figure S8. Kaplan-Meier survival analysis the relationship between survival time of multiple tumors and Twist1 expression. (A) Kaplan-Meier survival analysis of Kaplan-Meier plotter for the relationship between survival time of breast, gastric, ovarian and lung cancer and their expression of Twist1. (B) The relationship between survival time of 75 cases HCC and the Twist1 expression.</p>
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Objective To analyze survival condition of patients with digestive cancer and explore the influence of various factors to patients' survival time.The results will provide powerful evidence to prevent and recover from digestive cancer,prolong survival time and improve survival rate of patients.Methods 278 patients with digestive cancer received service of hospice from 2007 to 2009 were taken part in following up investigation and retrospective analysis.The median survival time and survival rate were calculated and the relationships among various factors were explored.Results The median survival time of all the patients died of cancer was 11 months and the average survival time was 20.4 months.The accumulated survival rate of 1 year was 0.478±0.031 and the accumulated survival rate of 5 year was 0.079±0.018.The gender,age,doing or not doing operation and the time of pain appearing influenced survival time statistically.Conclusion The most important measures of prolonging survival time of patients with digestive cancer were early found,early diagnosed,efficient operation and positive multiple intervention.
Cancer Survival
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Survival in multiple myeloma (MM) has developed favorably over the past decades for reasons that have been ascribed to new medications and treatment. However, development of survival over a long period and comparison to other hematopoietic neoplasms (HN) is less well known. Here we used Swedish cancer data from the Nordcan database, spanning a 50-year period from 1967 to 2016, and analyzed 1- and 5-year survival data. As a novel type of analysis we calculate the difference in survival between year 1 and 5 which indicates how well survival was maintained in the 4-year period following year 1 after diagnosis. The relative 1- and 5- year survival increased constantly; the 5-year survival graph for women was almost linear. The difference between 1- and 5-year survival revealed that the 5-year survival gain was entirely due to the improvement in 1-year survival, except for the last period. Survival improvement in all HNs exceeded that in MM. The linear 5-year survival increase for female MM patients suggests a contribution by many small improvements in the first year care rather than single major events. The future challenges are to push the gains past year 1 and to extend them to old patients.
Hematologic Neoplasms
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Stressor
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Data from 10418 ostrich chicks hatched in the period from 2000 to 2008 were analyzed to determine the influence of fixed effects upon age specific survival. Age-specific survival was divided into the following intervals: 0 to 1 week survival, 0 to 3 week survival, 0 to 12 week survival, 0 to 24 week survival, 2 to 3 week survival, 4 to 12 week survival and 13 to 24 week survival. ASREML software was used to formulate a fixed effects model for each trait. Storage time only affected 0 to 3 week survival (P = 0.03), while incubator type had a significant effect on 0 to 3 week survival (P = 0.03), 0 to 12 week survival (P < 0.001), 0 to 24 week survival (P < 0.001), and 4 to 12 week survival (P < 0.001). At older ages (i.e. 0 to 24 weeks, 0 to 12 weeks, 4 to 12 weeks, and 13 to 24 weeks) females exhibited higher survival than males (P < 0.001; P = 0.010; P < 0.001; P < 0.001). Hen age was found to have a significant influence on almost all traits (i.e. 0 to 3 week survival, 0 to 12 week survival, 0 to 24 week survival, 2 to 3 week survival and 4 to 12 week survival) except for survival during the first week, and survival from 13 to 24 weeks post-hatch (P = 0.020; P = 0.002; P = 0.036; P = 0.017; P = 0.014). Exhibiting a significant environmental component, ostrich chick survival to 6 months post-hatch can be optimized by manipulating certain environmental factors like the age of the breeding female as well as the type of incubator used.
Child survival
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Background/Aim: The aim of this study was to analyze the survival predictions obtained from a web platform allowing for computation of the so-called Bone Metastases Ensemble Trees for Survival (BMETS). This prediction model is based on a machine learning approach and considers 27 prognostic covariates. Patients and Methods: This was a retrospective single-institution analysis of 326 patients, managed with palliative radiotherapy for bone metastases. Deviations between model-predicted survival and observed survival were assessed. Results: The median actuarial survival was 7.5 months. In total, 59% of patients survived for a period shorter than predicted. Twenty percent of the predictions of the median survival deviated from the observed survival by at least 6 months. Regarding actual survival <3 months (99 of 326 patients), the BMETS-predicted median survival was <3 months, i.e. correct in 67 of 99 cases (68%), whereas the model predicted a median of 4-6 months in 16 (16%) and of >6 months in another 16 cases. Conclusion: The model predicted survival with high accuracy in a large number of patients. Nevertheless, if the model predicts a low likelihood of 3-month survival, actual survival may be very poor (often 1 month or less). Also, in patients who died within 3 months from the start of radiotherapy, the model often predicted longer survival (16% had >6 months predicted median survival). It would, therefore, be interesting to feed the U.S. database utilized to develop the BMETS with additional poor-prognosis patients to optimize the predictions.
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