scholarly journals Parametric and Non-Parametric Survival Analysis of Patients with Acute Myeloid Leukemia (AML)

2021 ◽  
Vol 11 (01) ◽  
pp. 126-148
Author(s):  
Aditya Chakraborty ◽  
Chris P. Tsokos
Keyword(s):  
Acute Myeloid Leukemia ◽  
Survival Analysis ◽  
Myeloid Leukemia ◽  
Parametric Survival ◽  
Parametric Survival Analysis ◽  
Acute Myeloid ◽  
Non Parametric

scholarly journals Pitfalls and perils of survival analysis under incorrect assumptions: the case of Covid-19 data

Biomédica ◽  
2021 ◽  
Vol 41 (Sp. 2) ◽  
Author(s):  
Daniele Piovani ◽  
Georgios K. Nikolopoulos ◽  
Stefanos Bonovas
Keyword(s):  
Decision Making ◽  
Survival Analysis ◽  
Preventive Measures ◽  
Clinical Course ◽  
Virus Disease ◽  
Current Medical Research ◽  
Basic Assumptions ◽  
Parametric Survival ◽  
Parametric Survival Analysis ◽  
Non Parametric

Non-parametric survival analysis has become a very popular statistical method in current medical research. Employing, however, survival methodology when its fundamental assumptions are not fulfilled can severely bias the results. Currently, hundreds of clinical studies are using survival methods to investigate factors potentially associated with the prognosis of Corona Virus Disease 2019 (Covid-19), and test new preventive and therapeutic strategies. In the pandemic era, it is more critical than ever that decision-making is evidence-based and relies on solid statistical methods. However, this is not always the case. Serious methodologic errors have been identified in recent seminal studies about Covid-19: one reporting outcomes of patients treated with remdesivir, and another one on the epidemiology, clinical course and outcomes of critically-ill patients. High-quality evidence is essential to inform clinicians about optimal Covid-19 therapies, and policymakers about the true effect of preventive measures aiming to tackle the pandemic. Though timely evidence is needed, we should encourage the appropriate application of survival analysis methods and careful peer-review to avoid publishing flawed results, which could affect decision-making. In this paper, we recapitulate the basic assumptions underlying non-parametric survival analysis and frequent errors in its application, and discuss how to handle data of Covid-19.

Outcome Of Patients With Acute Myeloid Leukemia/High Risk MDS According To The Kidney Function

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 5007-5007
Author(s):  
Ahmed Malkawi ◽  
Ankit Anand ◽  
Ali Al-Ameri ◽  
Mohamed Abdelfatah ◽  
Zeyad Kanaan ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Survival Analysis ◽  
Glomerular Filtration Rate ◽  
High Risk ◽  
Glomerular Filtration ◽  
Myeloid Leukemia ◽  
Filtration Rate ◽  
Myelogenous Leukemia ◽  
Number Of Patients ◽  
Acute Myeloid

Abstract Background Acute renal failure or injury is a common complication of treatment of patients with acute myelogenous leukemia (AML) or high risk MDS, but the effect of renal function of patients who have acute myeloid leukemia/high risk MDS is not clearly highlighted as a predictor of survival, to the best of our knowledge this issue has not been studied in depth before. Aim study the effect of chronic kidney disease on the survival of patient with acute myeloid leukemia/High Risk MDS. Methods A retrospective study of all AML & high risk MDS patients treated at AGMC, Ohio, USA during 2001-2010. After IRB approval of the project, patients’ charts were reviewed to gather information on demographics, diagnosis types/subtypes, glomerular filtration rate (GFR), treatment, and cytogenetics. Patients were classified as low-intermediate risk or high risk according to cytogenetic background using WHO criteria. Also according to GFR patients were classified to GFR <30, 30 - 60 and > 60. Overall survival (OS) rates were determined by Kaplan-Meier Survival Analysis. Prognostic factors were evaluated by Log Rank analysis. Result Out of 130 patients we were able to classify 99 patients (75%). Patient were grouped into 59 Pts with GFR>60, 37 Pts with GFR 30-60 and 3 Pts with GFR<30. Time to event survival analysis was done. Conclusion Glomerular filtration rate GFR is a major identified factor in patients survival who have acute myeloid leukemia AML/High Risk MDS, those patients with GFR 30-60 do better in term of survival, we don’t have any explanation for that, more data with high number of patients needed to elaborate on this issue. Disclosures: No relevant conflicts of interest to declare.

scholarly journals Identification of Prognostic Signature Based on the Copy Number Variation (CNV) and Expression in Acute Myeloid Leukemia

2020 ◽  
Author(s):  
Changchun Niu ◽  
Di Wu ◽  
Alexander J. Li ◽  
Kevin H. Qin ◽  
Daniel A. Hu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Acute Myeloid Leukemia ◽  
Survival Analysis ◽  
Copy Number Variation ◽  
Copy Number ◽  
Myeloid Leukemia ◽  
Risk Groups ◽  
Number Variation ◽  
Acute Myeloid ◽  
Cancer Panel

Abstract Purpose Acute myeloid leukemia (AML) is caused by multiple genetic alterations in the hematopoietic progenitors, and molecular genetic analysis has provided useful information for AML diagnosis and prognosis. However, an integrative understanding about the prognosis value of specific copy number variation (CNV) and CNV-modulated gene expression has been limited. Methods We conducted an integrative analysis of CNV profiling and gene expression using data from the TARGET and TCGA AML cohorts. The CNV data from TCGA were analyzed using the GISTIC. CNV survival analysis and mRNA survival analysis were conducted with the Multivariate Cox proportional hazards regression model using R software with “survminer” and “survival” packages. KEGG cancer panel genes were extracted from the cancer related pathways from Kyoto Encyclopedia of Genes and Genomes (KEGG). The R package “circlize” was used for mapping the CNV genes to chromosomes. Results From this investigation, we observed distinct CNV patterns in the AML risk groups as well as the expression of 251 genes significantly modulated by CNV in both cohorts. There were 102 CNV genes (located at 7q31-34, 16q24) associated with clinical outcomes in AML, which were identified in the TARGET cohort and validated in the TCGA cohort, three of which being miRNA genes (MIR29A, MIR183, MIR335) that overlapped with a KEGG cancer panel. Five genes were identified whose expressions were modulated by CNV and significantly associated with clinical outcomes, and among them, the deletion of SEMA4D and CBFB were found to potentially have protective effects against AML. Moreover, the distribution of CNV in these five CNV-modulated genes was independent of the risk groups, which suggests that they are independent prognosis factors. Conclusion Overall, this study identified 102 CNV genes and five CNV-modulated gene expressions that are crucial for developing new modes of prognosis evaluation and target therapy for AML.

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