Identifying the Association Rules between Clinicopathologic Factors and Higher Survival Performance in Operation-Centric Oral Cancer Patients Using the Apriori Algorithm

Tang, Jen‐Yang; Chuang, Li‐Yeh; Hsi, Edward; Lin, Yu‐Da; Yang, Cheng‐Hong; Chang, Hsueh-Wei

doi:10.1155/2013/359634

Cited by 25 publications

(17 citation statements)

References 21 publications

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“…The statistical analyses were reported to have the difficulty to identify the complex multifactor association [ 42 ]. Accordingly, several studies proposed comprehensive approaches to identify the association model with disease related factors [ 27 , 30 , 43 , 44 ]; these approaches have adequate power to explore the potential association models. The SNP combination generated by PSO can detect the association relationship in terms of selecting several important genotypes of SNPs.…”

Section: Discussionmentioning

confidence: 99%

The Combinational Polymorphisms ofORAI1Gene Are Associated with Preventive Models of Breast Cancer in the Taiwanese

Ouyang

Lin

Chuang

et al. 2015

BioMed Research International

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The ORAI calcium release-activated calcium modulator 1 (ORAI1) has been proven to be an important gene for breast cancer progression and metastasis. However, the protective association model between the single nucleotide polymorphisms (SNPs) of ORAI1 gene was not investigated. Based on a published data set of 345 female breast cancer patients and 290 female controls, we used a particle swarm optimization (PSO) algorithm to identify the possible protective models of breast cancer association in terms of the SNPs of ORAI1 gene. Results showed that the PSO-generated models of 2-SNP (rs12320939-TT/rs12313273-CC), 3-SNP (rs12320939-TT/rs12313273-CC/rs712853-(TT/TC)), 4-SNP (rs12320939-TT/rs12313273-CC/rs7135617-(GG/GT)/rs712853-(TT/TC)), and 5-SNP (rs12320939-TT/rs12313273-CC/rs7135617-(GG/GT)/rs6486795-CC/rs712853-(TT/TC)) displayed low values of odds ratios (0.409–0.425) for breast cancer association. Taken together, these results suggested that our proposed PSO strategy is powerful to identify the combinational SNPs of rs12320939, rs12313273, rs7135617, rs6486795, and rs712853 of ORAI1 gene with a strongly protective association in breast cancer.

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Section: Discussionmentioning

confidence: 99%

The Combinational Polymorphisms ofORAI1Gene Are Associated with Preventive Models of Breast Cancer in the Taiwanese

Ouyang

Lin

Chuang

et al. 2015

BioMed Research International

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“…Let D be a set of transactions. Step 1 contains 4 algorithms of conventional Apriori algorithms [ 8 ]. Algorithm 1 is the whole pseudocode of Apriori algorithm for screening large itemsets without introducing the mechanism of χ 2 .…”

Section: Methodsmentioning

confidence: 99%

“…The use of association algorithms, such as Apriori algorithm, has shown their feasibility and effectiveness in detecting adverse drug events (ADE) [ 6 ]. Apriori algorithm was first presented in 1994 [ 7 ] and has been widely used for frequent itemset mining and association rule learning [ 8 ]. Data mining techniques like Apriori algorithm typically focus on positive association rules based on frequently occurring itemsets to extract association rules from big data.…”

Section: Introductionmentioning

confidence: 99%

Discovering Associations of Adverse Events with Pharmacotherapy in Patients with Non-Small Cell Lung Cancer Using Modified Apriori Algorithm

Chen

Yang

Wang

et al. 2018

BioMed Research International

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Aim To explore the associations between adverse events and pharmacotherapy in patients with non-small cell lung cancer. Methods 16,527 patients with non-small cell lung cancer admitted to the Cancer Hospital, Chinese Academy of Medical Sciences, between January 1, 2010, and December 31, 2016, were included in the study. Their medication and laboratory examinations data were extracted from the medical records. Common Terminology Criteria for Adverse Events Version 4.03 were utilized for adverse events reporting. A new association algorithm was developed based on Apriori algorithm and used to investigate the associations between drugs and adverse events. In addition, a statistical comparison was conducted to compare the modified Apriori algorithm with the conventional Apriori algorithm. Results Different types and levels of adverse events were identified from the abnormal laboratory findings. The three most common adverse events were hypocalcemia, elevated creatine phosphokinase, and hypertriglyceridemia. In addition, using the modified Apriori algorithm, 380 association rules were found between adverse events and chemotherapy. Moreover, the statistical comparison of the two methods demonstrated that the modified Apriori algorithm was more advantageous in analyzing the correlation between drugs and adverse events than the conventional Apriori algorithm. Conclusions The modified Apriori algorithm can be used to more efficiently associate pharmacotherapy with adverse events. Based on the modified Apriori algorithm, meaningful association rules between drugs and adverse events were found, demonstrating a promising way to reveal the risk factors of adverse events during cancer treatment.

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“…The measures effectively quantify the correlation between the antecedents and the consequent. Subjective techniques incorporate the subjective knowledge of the user into the assessment strategy [33,34]. In this study, apart from confidence measure, the interestingness of resulting rules was evaluated according to three objective measures: confidence, lift and conviction (▶Figure 4).…”

Section: Selection Of Meaningful Association Rulesmentioning

confidence: 99%

Association Patterns in Open Data to Explore Ciprofloxacin Adverse Events

Yıldırım¹

2015

Appl Clin Inform

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SummaryBackground: Ciprofloxacin is one of the main drugs to treat bacterial infections. Bacterial infections can lead to high morbidity, mortality, and costs of treatment in the world. In this study, an analysis was conducted using the U.S. Food and Drug Administration (FDA) Adverse Event Reporting System (AERS) database on the adverse events of ciprofloxacin. Objectives: The aim of this study was to explore unknown associations among the adverse events of ciprofloxacin, patient demographics and adverse event outcomes. Methods: A search of FDA AERS reports was performed and some statistics was highlighted. The most frequent adverse events and event outcomes of ciprofloxacin were listed, age and gender specific distribution of adverse events are reported, then the apriori algorithm was applied to the dataset to obtain some association rules and objective measures were used to select interesting ones. Furthermore, the results were compared against classical data mining algorithms and discussed. Results: The search resulted in 6 531 reports. The reports included within the dataset consist of 3 585 (55.8%) female and 2 884 (44.1%) male patients. The mean age of patients is 54.59 years. Preschool child, middle aged and aged groups have most adverse events reports in all groups. Pyrexia has the highest frequency with ciprofloxacin, followed by pain, diarrhoea, and anxiety in this order and the most frequent adverse event outcome is hospitalization. Age and gender based differences in the events in patients were found. In addition, some of the interesting associations obtained from the Apriori algorithm include not only psychiatric disorders but specifically their manifestation in specific gender groups. Conclusions: The FDA AERS offers an important data resource to identify new or unknown adverse events of drugs in the biomedical domain. The results that were obtained in this study can provide valuable information for medical researchers and decision makers at the pharmaceutical research field.

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Identifying the Association Rules between Clinicopathologic Factors and Higher Survival Performance in Operation-Centric Oral Cancer Patients Using the Apriori Algorithm

Cited by 25 publications

References 21 publications

The Combinational Polymorphisms ofORAI1Gene Are Associated with Preventive Models of Breast Cancer in the Taiwanese

The Combinational Polymorphisms ofORAI1Gene Are Associated with Preventive Models of Breast Cancer in the Taiwanese

Discovering Associations of Adverse Events with Pharmacotherapy in Patients with Non-Small Cell Lung Cancer Using Modified Apriori Algorithm

Association Patterns in Open Data to Explore Ciprofloxacin Adverse Events

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