本文選題：艾滋病　切入點(diǎn)：高效抗逆轉(zhuǎn)錄病毒治療　出處：《首都醫(yī)科大學(xué)》2017年碩士論文

【摘要】：目的:艾滋病是危害嚴(yán)重的一種傳染性疾病�；颊呤状谓邮芨咝Э鼓孓D(zhuǎn)錄病毒治療(highly active antiretroviral therapy,HAART)時的藥物配伍方案是否合理是治療成功與否的關(guān)鍵。由于艾滋病患者的個人身體素質(zhì)不同、基線情況復(fù)雜、患病后病情進(jìn)程不一、患者耐藥性不同,選用某一藥物配伍方案對這些患者進(jìn)行治療后,效果可能完全不同。本研究探討利用數(shù)據(jù)挖掘方法分析艾滋病患者的多項(xiàng)指標(biāo)與藥物配伍方案之間的關(guān)系,制定艾滋病患者個性化治療方案,從而避免治療過程中的多次換藥以及由此產(chǎn)生的耐藥性、減輕藥物治療的毒副反應(yīng)、提高患者生存質(zhì)量、延長壽命。方法:收集721例首次接受HAART治療的艾滋病患者治療前以及治療后多次隨訪時的年齡、身高、體重以及CD4+T淋巴細(xì)胞計數(shù)、CD8+T淋巴細(xì)胞計數(shù)、HIV病毒載量、白細(xì)胞計數(shù)、總淋巴細(xì)胞計數(shù)、血小板計數(shù)、血紅蛋白、血肌酐、血尿素氮、血糖、谷草轉(zhuǎn)氨酶、谷丙轉(zhuǎn)氨酶、總膽紅素數(shù)據(jù),并對各種治療方案中抗病毒藥物的使用情況進(jìn)行整理。對治療后免疫重建良好患者的數(shù)據(jù),分別通過基于患者相似性的聚類分析、基于案例推理和關(guān)聯(lián)規(guī)則挖掘方法,確定患者的最佳治療方案。最后對由三種方法得出的個性化治療方案的準(zhǔn)確性進(jìn)行驗(yàn)證和比較。結(jié)果:(1)計算基于歐氏距離的患者相似性。利用聚類分析方法確定每一聚類中多數(shù)患者的用藥方案為該類患者的最佳用藥方案,由此推薦的患者用藥方案與實(shí)際患者用藥方案的一致率為67.3%。利用基于案例推理方法確定與某患者最相似的前10%患者的治療方案作為該患者的推薦方案,分別以全部16項(xiàng)指標(biāo)和7項(xiàng)核心指標(biāo)計算相似性時,推薦方案與實(shí)際患者治療方案的一致率分別為83.3%和86.0%。(2)經(jīng)關(guān)聯(lián)規(guī)則挖掘分析,得到用藥情況與患者7個核心指標(biāo)的相關(guān)關(guān)系,以及藥物配伍情況之間對應(yīng)關(guān)聯(lián)。用藥方案中包含依非韋倫的患者的最高支持度為0.02835,均高于用藥方案中包含奈韋拉平的患者的最高支持度0.00622和包含洛匹那韋利托那韋的患者的最高支持度0.00138。留一法驗(yàn)證后的推薦一致率為71.4%。結(jié)論:利用數(shù)據(jù)挖掘技術(shù)中的聚類分析、基于案例推理和關(guān)聯(lián)規(guī)則分析方法,能夠針對艾滋病患者的人口學(xué)和實(shí)驗(yàn)室指標(biāo)進(jìn)行個性化用藥方案推薦,其中基于案例推理方法的推薦準(zhǔn)確性最高。研究證實(shí)了利用數(shù)據(jù)挖掘方法制定艾滋病患者個性化治療方案的可行性和有效性,為患者個性化治療方案的制定提供客觀、科學(xué)的建議。
[Abstract]:Objective: AIDS is a serious infectious disease hazards. For the first time in patients receiving highly active antiretroviral therapy (highly active antiretroviral therapy, HAART) when the drug compatibility program is reasonable is the key to the success of treatment of AIDS patients. Due to personal physical fitness, the baseline situation is complex, the prevalence of disease after process, patients the resistance of these patients, treatment selection of a drug formula, the effect may be completely different. This study explores the use of data mining methods to analyze the relationship between a number of indicators of AIDS patients and drug combinations for patients, develop individualized treatment programs for AIDS, so as to avoid the repeated dressing treatment process and resulting resistance, reduce the side-effects of the drug treatment, improve the quality of survival, prolong the life of patients. Methods: collecting 721 cases of the first. By AIDS patients treated with HAART before and after treatment follow-up times of age, height, weight and CD4+T lymphocyte count, CD8+T lymphocyte count and HIV viral load, leukocyte count, total lymphocyte count, platelet count, hemoglobin, serum creatinine, blood urea nitrogen, blood glucose, aspartate aminotransferase, alanine aminotransferase, the total bilirubin data, and use of antiviral drugs in the treatment of a variety of sorting out. After the treatment of immune reconstitution in patients with good data, through the analysis of clustering similar patients based on case based reasoning and association rules mining method based on the best treatment plan were determined. Finally, verify and compare the accuracy of the individualized treatment plan obtained by the three methods. Results: (1) calculate the Euclidean distance similarity. Based on patients by using cluster analysis method to identify each cluster in the majority The medication regimen in patients with the best regimen for the patients, consistent rate of patients with medication and thus recommend medication for patients with the actual treatment of patients before 10% patients with the most similar as recommended the patient's case to determine the case based reasoning method using 67.3%., respectively, with all 16 indicators and 7 the core index of similarity calculation, consistency rate recommendation and treatment of actual patients were 83.3% and 86.0%. (2) by association rules analysis, get the correlation between the 7 core indicators and medication of patients, as well as the corresponding relationship between drug compatibility. Medication regimen included in the highest support of efavirenz with the degree of 0.02835, were higher than the highest support patients included nevirapine regimen in the highest support 0.00622 and contains the Tonave Wiley Los horse with a degree of 0.00138. After the verification of the method recommended the concordance rate was 71.4%. conclusion: using the technology of data mining and clustering analysis method, case based reasoning and association rules based on demographic and laboratory indicators for AIDS patients to recommend personalized medicine program, which recommended accuracy of case-based reasoning method based on maximum. Research has confirmed the use of data mining methods to develop the feasibility patients with personalized treatment of AIDS and effectiveness for patients with individualized treatment plan to provide objective and scientific advice.

【學(xué)位授予單位】：首都醫(yī)科大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：R512.91;TP311.13

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