Data Analysis of Epidemiological Studies

Ressing, Meike; Blettner, Maria; Klug, Stefanie J.

doi:10.3238/arztebl.2010.0187

Cited by 39 publications

(25 citation statements)

References 17 publications

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“…Inclusion criteria for quantitative meta-analysis were studies that reported an SIR or SMR or data on expected and observed cases of melanoma or confirmed melanoma that could be used to calculate an SIR or SMR. 5 We excluded articles that presented no data, such as review articles and editorials. If duplicate data were present in separate publications, we included the publication with the larger amount of data, obtained either through a longer follow-up period or greater number of participants.…”

Section: Methodsmentioning

confidence: 99%

The Risk of Melanoma in Airline Pilots and Cabin Crew

et al. 2015

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Importance Airline pilots and cabin crew are occupationally exposed to higher levels of cosmic and UV radiation than the general population, but their risk of developing melanoma is not yet established. Objective To assess the risk of melanoma in pilots and airline crew. Data Sources PubMed (1966 to October 30, 2013), Web of Science (1898 to January 27, 2014), and Scopus (1823 to January 27, 2014). Study Selection All studies were included that reported a standardized incidence ratio (SIR), standardized mortality ratio (SMR), or data on expected and observed cases of melanoma or death caused by melanoma that could be used to calculate an SIR or SMR in any flight-based occupation. Data Extraction and Synthesis Primary random-effect meta-analyses were used to summarize SIR and SMR for melanoma in any flight-based occupation. Heterogeneity was assessed using the χ2 test and I2 statistic. To assess the potential bias of small studies, we used funnel plots, the Begg rank correlation test, and the Egger weighted linear regression test. Main Outcomes and Measures Summary SIR and SMR of melanoma in pilots and cabin crew. Results Of the 3527 citations retrieved, 19 studies were included, with more than 266 431 participants. The overall summary SIR of participants in any flight-based occupation was 2.21 (95% CI, 1.76-2.77; P < .001; 14 records). The summary SIR for pilots was 2.22 (95% CI, 1.67-2.93; P = .001; 12 records). The summary SIR for cabin crew was 2.09 (95% CI, 1.67-2.62; P = .45; 2 records). The overall summary SMR of participants in any flight-based occupation was 1.42 (95% CI, 0.89-2.26; P = .002; 6 records). The summary SMR for pilots was 1.83 (95% CI, 1.27-2.63, P = .33; 4 records). The summary SMR for cabin crew was 0.90 (95% CI, 0.80-1.01; P = .97; 2 records). Conclusions and Relevance Pilots and cabin crew have approximately twice the incidence of melanoma compared with the general population. Further research on mechanisms and optimal occupational protection is needed.

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Section: Methodsmentioning

confidence: 99%

The Risk of Melanoma in Airline Pilots and Cabin Crew

et al. 2015

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“…relatives Risiko (RR), die den Zusammenhang zwischen dem Vorliegen einer pathogenen Mutation und dem Auftreten der jeweiligen Krebserkrankung beschreiben (▶ Tab. 1), [7]. Nach der Evidenzklassifikation werden diese Studien in Level Im Folgenden wird für jedes der o. g. "Core"-Gene des TruRisk ® -Panels eine Risikobewertung und die daraus resultierende klinische Konsequenz angegeben.…”

Section: Neue Risikogene: Herausforderung Für Risikokalkulation Und Kunclassified

“…▶ Tab. 1 Definition relatives Risiko (RR), Odds Ratio (OR) und Hazard Ratio (HR) (basiert auf Daten aus [7]). Keimbahnmutationen im E-Cadherin(CDH1)-Gen sind ursächlich für das hereditäre diffuse Magenkarzinom.…”

Section: Mutationen In Palb2 Atm Und Chek2 Erhöhen Das Risiko Für Brunclassified

Konsensusempfehlung des Deutschen Konsortiums Familiärer Brust- und Eierstockkrebs zum Umgang mit Ergebnissen der Multigenanalyse

et al. 2018

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ZusammenfassungDas Deutsche Konsortium Familiärer Brust- und Eierstockkrebs (GC-HBOC) hat für die Analyse von Risikogenen für das familiäre Mamma- und Ovarialkarzinom ein Multigen-Panel (TruRisk®) etabliert, das derzeit die Kerngene („core genes“) ATM, BRCA1, BRCA2, CDH1, CHEK2, NBN, PALB2, RAD51C, RAD51 D und TP53 enthält, sowie weitere Gene, die aus aktuellen Forschungsarbeiten hervorgegangen sind und noch validiert werden müssen. Das syndromassoziierte Gen PTEN befindet sich hinsichtlich seiner Bedeutung in Familien mit prädominantem Brust- und Eierstockkrebs-Phänotyp derzeit ebenfalls in der Evaluation. Ein interdisziplinäres Expertenteam des GC-HBOC hat die verfügbaren Daten zur Risikomodifikation bei Vorliegen einer pathogenen (krankheitsverursachenden) Mutation in diesen Genen basierend auf einer strukturierten Literaturrecherche (Abb. 1S) und im Rahmen eines formalen Konsensusprozesses bewertet. Ziel dieser Arbeit ist es, das individuelle Erkrankungsrisiko besser einschätzen und auf dieser Basis klinische Empfehlungen ableiten zu können. Auf der Grundlage dieser evidenzbasierten Bewertung werden die Ratsuchenden in den Zentren des Deutschen Konsortiums vom Erstgespräch vor Gentest bis zur Inanspruchnahme individueller risikoadaptierter präventiver/therapeutischer Maßnahmen beraten und betreut. Dieser Artikel fasst die konsentierten Inhalte zusammen.

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“…These fields contribute to health information to gain datum and health information analyzes these datum to create significant information and store to use in the future [5]. Healthcare data mining is based on the datum of clinical records and used to determine the risk factors and prevalence [6]. Accordingly, data mining needs both qualitative and quantitative datum to use in data mining algorithms.…”

Section: Introductionmentioning

confidence: 99%

Polyneuropathy disease forecast in the type 2 diabetes mellitus patients using data mining based approach

TORUN¹

2019

Ann Clin Anal Med

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Aim: The aim of this research was to predict the availability of polyneuropathy disease of the type 2 diabetes mellitus patient through data mining algorithms. Material and Method: The dataset was obtained from the Bilecik Public Hospital and the instance number is 2907. Models were created with two different classification data mining algorithms. The data set includes Gender, Glycated Haemoglobin (HbA1c), Creatinine, Total Cholesterol, Low-Density Lipoprotein (LDL) and High-Density Lipoprotein (HDL). Numerical data were transformed into interval forms and the percentiles were calculated for each interval. Results: Data analysis and performance evaluation were performed with R, RStudio. Random Forest Tree was found as the best algorithm for polyneuropathy disease prediction (the accuracy = 0,922547332185886). The accuracy of the C4.5 was found 0,920826161790017. The percentages of the normal levels HbA1c are 6%, the impaired fasting glucose levels are 22% and the diabetes mellitus type 2 levels are %72. The percentage of the low Creatinine is 2%, the normal Creatinine is %86 and the high Creatinine is 12%. The percentage of the desirable levels Total Cholesterol is 46%, the percentage of the borderline levels of Total Cholesterol is 31% and the the percentage of high levels of Total Cholesterol is 23%. The percentage of the optimal levels LDL is 30%, the percentage of the near optimal levels of LDL is 31%, the percentage of the borderline high levels of LDL is 23%, the percentage of the high levels of LDL is 12% and the percentage of the very high levels of LDL is 4%. The percentage of the bad levels of HDL is 43%, the percentage of the better levels of HDL is 42% and the percentage of the best levels HDL is 19%. This model indicated that Creatinine, LDL and HbA1c are the primary three determinative factors on polyneuropathy disease. Furthermore, the model created the following 5 rules. Rule 1: If Creatinine ≤0,6 mg/dL and HbA1c ≤5,7 mmol/L then polyneuropathy disease is available for male, if Creatinine ≤0,5 mg/dL and HbA1c ≤5,7 mmol/L then polyneuropathy disease is available for female. Rule 2: If Creatinine ≤0,5 mg/dL and HbA1c >5,7 mmol/L and 160 ≤ LDL ≤189 mg/dL and LDL ≤189 mg/dL then polyneuropathy disease is unavailable. Rule 3: If Creatinine ≤0,5 mg/dL and HbA1c >5,7 mmol/L and 160 ≤ LDL ≤ 189 mg/dL and LDL >189 mg/dL, then polyneuropathy disease is unavailable. Rule 4: If Creatinine ≤0,5 mg/dL and HbA1c >5,7 mmol/L and 160 ≤ LDL ≤ 189 mg/dL, then polyneuropathy disease is unavailable. Rule 5: If Creatinine >0,5 mg/dL then polyneuropathy disease is unavailable. Discussion: The results show that HDL, Gender and Total Cholesterol have no significant effect on the polyneuropathy disease in this model. To determine the availability of polyneuropathy disease through the given data mining algorithms, researchers may consider the Creatinine, LDL and HbA1c scores.

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Data Analysis of Epidemiological Studies

Abstract: The measures to be calculated and the analyses to be performed in an epidemiological study depend on the research questions being asked, the study type, and the available data.

Cited by 39 publications

References 17 publications

The Risk of Melanoma in Airline Pilots and Cabin Crew

The Risk of Melanoma in Airline Pilots and Cabin Crew

Konsensusempfehlung des Deutschen Konsortiums Familiärer Brust- und Eierstockkrebs zum Umgang mit Ergebnissen der Multigenanalyse

Polyneuropathy disease forecast in the type 2 diabetes mellitus patients using data mining based approach

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