Trend Of Leukemia Research Articles

Acute Leukemia Diagnosis Based on Images of Lymphocytes and Monocytes Using Type-II Fuzzy Deep Network

A cancer diagnosis is one of the most difficult medical challenges. Leukemia is a type of cancer that affects the bone marrow and/or blood and accounts for approximately 8% of all cancers. Understanding the epidemiology and trends of leukemia is critical for planning. Specialists diagnose leukemia using morphological analysis, but there is a possibility of error in diagnosis. Since leukemia is so difficult to diagnose, intelligent methods of diagnosis are required. The primary goal of this study is to develop a novel method for extracting features hierarchically and accurately, in order to diagnose various types of acute leukemia. This method distinguishes between acute leukemia types, namely Acute Lymphocytic Leukemia (ALL) and Acute Myeloid Leukemia (AML), by distinguishing lymphocytes from monocytes. The images used in this study are obtained from the Shahid Ghazi Tabatabai Oncology Center in Tabriz. A type-II fuzzy deep network is designed for this purpose. The proposed model has an accuracy of 98.8% and an F1-score of 98.9%, respectively. The results show that the proposed method has a high diagnostic performance. Furthermore, the proposed method has the ability to generalize more satisfactorily and has a stronger learning performance than other methods.

Epidemiologic features and trends of leukemia in Shenzhen during 2001-2015

Objective To describe the incidence trend of leukemia in Shenzhen during 2001 to 2015, and to provide base data for designing prevention and treatment strategies on leukemia. Methods The leukemia incidence data and population data collected by Shenzhen Cancer Registry from 2001 to 2015 were used in our analysis. The crude incidence, age-standardized incidence rate by Chinese standard population (ASR China) and age-standardized incidence rate by world standard population (ASR world) were calculated. The annual percentage change (APC) of the incidence was analyzed by Joinpoint regression. Results Shenzhen Cancer Registry registered 2 106 new cases of leukemia from 2001 to 2015. The crude incidence was 6.31 per 100 000, with 6.75 per 100 000 ASR China and 7.15 per 100 000 ASR world. Cumulative rate (0-74 years) was 0.63%, and truncated rate (35-64 years) was 7.03 per 100 000. From the perspective of gender distribution, the incidence of male was significantly higher than female, with a sex ratio of 1.38∶1. In terms of time trend, the incidence of leukemia was stable, and the Joinpoint regression showed that APC=-0.09%(95%CI: -1.60%-1.41%, P=0.92). In terms of subtypes, acute myelocytic leukemia (AML) accounted for 17.66% of the total cases, and the incidence of AML has increased during 2001 to 2015 (APC=13.34%, 95%CI: 5.71%-21.51%, P<0.01). The median age of leukemia patients was 36 years old, and the mean age was 37.29 years old. The two peaks of the incidence were 1-4 and 80-84 age groups, and the ASR incidences were 9.13 per 100 000 and 39.40 per 100 000 respectively. Conclusion The incidence of leukemia is very high in Shenzhen. Children and the elderly are at high risk of leukemia. Government needs to guide institutions to carry out research to reduce the incidence of leukemia. Key words: Leukemia; Incidence; Time trend; Cancer register

A JOINPOINT REGRESSION ANALYSIS OF LONG-TERM TRENDS IN LEUKEMIA INCIDENCE AND MORTALITY IN CENTRAL SERBIA AND NIŠAVA DISTRICT (1999-2014)

Leukemia contributes 2.3% to the overall cancer incidence in Serbia and 2.9% in the total mortality, while the estimated incidence and mortality rate for males and females were 8.7 and 6.3 ‰, respectively and occupies 13th place among both sexes in Central Serbia. The objective of our study was to examine the time trends of leukemia in Central Serbia, with a focus on Nisava district, from 1999-2014, using a Joinpoint regression analysis and compare them with the trend in other populations, and identify possible changes. The standardised incidence and mortality were obtained from the Serbian Cancer Registry of Central Serbia. Time trends for incidence and mortality of leukemia were assessed using the annual percent change, estimated through Joinpoint regression analysis (age period cohort models - APC) using the Joinpoint Regression Software. Our results demonstrate a stable trend of the age-adjusted leukemia incidence rate both in males and females in Central Serbia during the observed 1999-2014 period. However, statistically significant decreasing trend of leukemia incidence rate was found in men from Nisava district, while non-significant slightly increasing pattern was present in women. Joinpoint analysis in our research demonstrated favorable mortality declines until the 2002, and than stabile trend in Central Serbia in both sexes to the end of the observed period. Conversely, mortality among males in Nisava district shows a positive trend, but not statistically significant. The results of the study suggest that leukemia profile in Central Serbia was stabile during the study period. It is particularly interesting that incidence is decreasing among male population from Nisava district.

Trend of leukemia in Ninawa/Iraq

Trend of leukemia in Ninawa/Iraq

Infrared parameters in the characterization of the neoplastic cell transformation

In this paper we report the results on the characterization of neoplastic cells by means of FT-IR spectroscopy. Spectral differences have been found in examining normal and leukemic lymphocytes. Through analyzing also nuclei extracted from normal and leukemic lymphocytes an increase of DNA with respect to proteic components was observed in the order: normal lymphocytes, leukemic lymphocytes, normal nuclei, and leukemic nuclei. Spectral differences were observed between lipids extracted from normal and leukemic cells. Recently the infrared spectra of single normal and leukemic cells have been obtained. The later opens new possibilities for revealing the early phase of the disease, in following the trends of leukemia in patients who are under treatment with drugs, and in evaluating the residual neoplastic disease. This research has extended to the study of human tumor lung cells. Spectral differences were also observed analyzing normal and neoplastic cells. Spectroscopic parameters distinguishing normal from tumoral cells have been suggested.