腫瘤生存數(shù)據(jù)中比例風(fēng)險假定失效時的統(tǒng)計分析策略
發(fā)布時間：2018-07-25 12:24
【摘要】：背景子宮內(nèi)膜癌、宮頸癌、卵巢癌是嚴(yán)重危害婦女生命健康的三大婦科腫瘤,即使在醫(yī)學(xué)技術(shù)發(fā)達(dá)的今天,其病死率和死亡率仍然高居不下。子宮內(nèi)膜癌是女性生殖系統(tǒng)的三大惡性腫瘤之首,占女性生殖系統(tǒng)腫瘤的20%-30%,在歐美國家,子宮內(nèi)膜癌發(fā)病率已占據(jù)婦科惡性腫瘤第一位,2016年美國新增的子宮內(nèi)膜癌病例即超過了宮頸癌和卵巢癌的總和,而近些年來發(fā)展中國家的發(fā)病率也明顯上升。劇WHO統(tǒng)計,2012年全球新發(fā)宮頸癌患者為527,624(占女性癌癥7.9%),死人數(shù)為265,672(占所有女性癌癥7.5%),位居世界婦女發(fā)病率的第四位,雖然近年來,在發(fā)達(dá)國家的發(fā)病率正在下降,但在一些發(fā)展中國家位居首位,在2015年,300,000例死者中,約90%的病例來自于中低等收入國家,因此宮頸癌的預(yù)后也是我們不容忽視的問題。卵巢癌在婦科惡性腫瘤中的發(fā)病率位居第二,病死率位居第一,全球每年約有19萬新發(fā)病例,流行病學(xué)研究顯示,婦女一生患卵巢癌的風(fēng)險為1.4%,由于卵巢癌深居盆腔,缺乏早期癥狀及有效的篩查手段,被確診時多數(shù)已達(dá)晚期,總的5年生存率僅有45%,在婦科惡性腫瘤中最難早期診斷,最難治愈,預(yù)后最差,所以構(gòu)建恰當(dāng)?shù)念A(yù)后模型探索其影響因素和預(yù)測患者的生存率將變得尤為重要。Cox比例風(fēng)險模型是腫瘤數(shù)據(jù)分析中最常見的回歸模型。然而,當(dāng)比例風(fēng)險假定失效時,Cox比例風(fēng)險模型違背其前提條件,這種情況下使用Cox比例風(fēng)險模型得到的結(jié)果不可靠。而加速失效模型中的Buckley-James模型應(yīng)用線性回歸思想處理生存時間與影響因素之間的關(guān)系不需要滿足該假定。Trinquart等人提倡用限制性平均生存時間(RMST)作為另一個概括型統(tǒng)計量來評價組間效應(yīng),然而,Buckley-James模型和RMST模型得到的指標(biāo)均為概括型指標(biāo),不能展現(xiàn)不同時間點的變化的趨勢,Cox提出可以用時間函數(shù)和時間相依協(xié)變量的交互項來構(gòu)造擴展Cox模型探索不同時間點的相對風(fēng)險比。在實際的臨床治療中,病人可能更為關(guān)心的是其自身在不同治療期間的生存率,動態(tài)預(yù)測中的比例基線界標(biāo)超級模型(PBLS模型)是一個條件模型,可以探索不同時間點的相對風(fēng)險比,更可以預(yù)測w年的動態(tài)生存率。目的本研究選取來自美國監(jiān)測、流行病和最終結(jié)果數(shù)據(jù)庫中在2004年1月1日到2013年12月31日10年間三大婦科惡性腫瘤患者的生存數(shù)據(jù),采用Cox比例風(fēng)險模型、半?yún)?shù)加速失效模型(AFT模型)、以RMST為指標(biāo)的廣義線性模型(RMST模型)、Cox時間相依模型(擴展Cox模型)和動態(tài)預(yù)測分析中的PBLS模型探索宮頸癌、子宮內(nèi)膜癌、卵巢癌患者預(yù)后的影響因素,并進(jìn)行不同時間點的5年生存率的預(yù)測分析,為三大婦科惡性腫瘤患者的預(yù)后提供基本臨床資料依據(jù),幫助臨床研究者針對不同患者而制定最佳治療方案。方法本研究將子宮內(nèi)膜癌患者、宮頸癌患者、卵巢癌患者的死亡原因(或終點事件)為全因死亡,將患者失訪或存活等作為刪失。單因素分析采用Kaplan-Meier方法來估計不同癌癥病人(宮頸癌、子宮內(nèi)膜癌、卵巢癌)各個協(xié)變量的生存率,并用Log-rank檢驗生存曲線之間的差異是否有統(tǒng)計學(xué)意義。用Cox比例風(fēng)險模型探索協(xié)因素的相對風(fēng)險比,用AFT模型探索各個因素的加速失效因子、用RMST模型探索協(xié)變量對限制性平均生存時間的影響,用擴展Cox模型探索各個因素在不同時間點對相對風(fēng)險比的影響,用PBLS模型預(yù)測不同時間點的5年生存率。評價模型的指數(shù)采用C-index、AIC、AUC。分析使用R軟件(3.3.4版本)進(jìn)行,檢驗均為雙側(cè)檢驗,檢驗水準(zhǔn)α = 0.05。結(jié)果三大婦科惡性腫瘤主要以已婚為主,白人為主,子宮內(nèi)膜癌和卵巢癌的診斷年齡較大、宮頸癌的診斷年齡較小,不同診斷年份沒有差異,子宮內(nèi)膜癌和宮頸癌的FIGO以一期為主、卵巢癌以三期為主,發(fā)生淋巴結(jié)轉(zhuǎn)移較少,子宮內(nèi)膜癌接受放療人數(shù)較少、宮頸癌人數(shù)較多、卵巢癌本研究中沒有納入放療的患者,子宮內(nèi)膜癌和卵巢癌的手術(shù)率高達(dá)90%,而宮頸癌低于70%,分化程度由高到低為,惡性度由低到高為:子宮內(nèi)膜癌、宮頸癌、卵巢癌,子宮內(nèi)膜癌、卵巢癌主要以腺癌為主、宮頸癌主要以鱗癌為主,注冊地點東西部相當(dāng),宮頸癌好發(fā)于子宮頸,卵巢癌好發(fā)于雙邊。對于婚姻狀態(tài),已婚分離(離異、分居、喪偶)相對于已婚的死亡風(fēng)險高,生存率低,未婚女性較為復(fù)雜,子宮內(nèi)膜癌的未婚女性與已婚女性的生存率沒有統(tǒng)計學(xué)差異,在宮頸癌中,未婚女性的生存率顯著高于已婚女性,在卵巢癌中,相對風(fēng)險比隨著時間發(fā)生變化;診斷年齡越大,生存率越低,在宮頸癌中,年齡間的相對風(fēng)險具有時間效應(yīng);不同種族的子宮內(nèi)膜癌患者的生存率不同,宮頸癌也是,但是白人的卵巢癌患者和其他人種的生存率沒有統(tǒng)計學(xué)差異;FIGO分期越高,生存率越低,其中子宮內(nèi)膜癌的FIGO分期的相對風(fēng)險比呈下降趨勢;淋巴結(jié)轉(zhuǎn)移的病人的生存率均低于沒有淋巴結(jié)轉(zhuǎn)移的病人,其相對風(fēng)險比在子宮內(nèi)膜癌先增大后減少,宮頸癌呈下降趨勢、而卵巢癌不變;手術(shù)對于三大婦科惡性腫瘤是一個保護(hù)因素。應(yīng)用動態(tài)預(yù)測分析發(fā)現(xiàn),PBLS模型能體現(xiàn)不同時間點的5年生存率,而Cox比例風(fēng)險模型不能體現(xiàn)不同時間點的變化過程。在三大婦科惡性腫瘤的5個模型分析中,無論從C-index還是從AIC,都是擴展Cox模型表現(xiàn)最好,同樣30次的重抽樣結(jié)果也顯示擴展Cox模型最好,在子宮內(nèi)膜癌和卵巢癌中,AFT模型的C-index較大,而在宮頸癌中,RMST模型的C-index較大,發(fā)現(xiàn)在AUC值和Slope指數(shù)中,PBLS模型顯著高于Cox比例風(fēng)險模型,動態(tài)預(yù)測不但能探索癌癥患者的預(yù)后因素,最重要的是預(yù)測不同時間點的w年生存率。結(jié)論婚姻狀態(tài)、診斷年齡、種族、FIGO分期、淋巴結(jié)轉(zhuǎn)移、放療等都是影響女性生殖器三大惡性腫瘤的影響因素,且部分因素相對風(fēng)險并不是永恒不變的。首次使用動態(tài)預(yù)測分析中的PBLS模型預(yù)測美國女性的婦科三大女惡性腫瘤的不同時間點的5年生存率,臨床研究者制定患者的個體治療方案,指導(dǎo)病人持續(xù)治療、增加依從性、最終提高生存率。
[Abstract]:Background endometrial cancer, cervical cancer, and ovarian cancer are the three major gynecologic tumors that seriously harm the life and health of women. Even in the advanced medical technology, the mortality and mortality rate still remain high. Endometrial cancer is the first of the three major female reproductive system tumors, which accounts for the 20%-30% of female reproductive system tumors, in European and American countries. The incidence of endometrial cancer has taken the first place in gynecologic malignancies. In 2016, the new cases of endometrial cancer in the United States were more than the total of cervical and ovarian cancer. In recent years, the incidence of the developing countries was also significantly increased. The WHO statistics showed that in 2012, the number of new cervical cancer patients in the world was 527624 (7.9% of female cancer) and the number of dead people was 265,67 2 (7.5% of all women's cancer), ranking fourth in the world's incidence of women, although the incidence of the disease in the developed countries is declining in recent years, but in some developing countries, in 2015, about 90% of the 300000 cases of the deceased are from the middle and lower income countries, so the prognosis of cervical cancer is also a problem we can not ignore. The incidence of ovarian cancer in gynecologic malignancies is second, the mortality rate is the first, and there are about 19 million new cases in the world every year. The epidemiological study shows that the risk of women's ovarian cancer is 1.4%. Because of the deep pelvic cavity, the lack of early symptoms and effective screening methods, most of the ovarian cancer has reached the late period and the total of 5 years. The survival rate is only 45%. It is the most difficult to diagnose in the malignant tumor of Gynecology, the most difficult to cure, and the worst prognosis. Therefore, it is particularly important to construct an appropriate prognostic model to explore its influencing factors and predict the patient's survival rate. The.Cox proportion risk model is the most common regression model in the analysis of tumor data. However, when the proportional risk is assumed to be invalid, Cox The proportional risk model is contrary to its precondition, and the results obtained by using the Cox proportional hazard model in this case are not reliable. While the Buckley-James model in the accelerated failure model applies the linear regression idea to deal with the relationship between the survival time and the influencing factors, it does not need to satisfy the assumption that.Trinquart and others advocate using the restrictive average survival time. RMST is another generalized statistic to evaluate inter group effects. However, the Buckley-James model and the RMST model are all generalized indexes, which can not show the trend of change at different time points. Cox proposes to use the time function and time dependent covariate to construct extended Cox model to explore different time points. Relative risk ratio. In practical clinical treatment, patients may be more concerned about their own survival rate during different treatments. The proportional baseline supermodel (PBLS model) in dynamic prediction is a conditional model, which can explore the relative risk ratio at different time points, and can predict the dynamic survival rate of W years. The survival data of three major gynecologic cancer patients from January 1, 2004 to December 31, 2013 were selected from the US monitoring, epidemic and final result database, using the Cox proportional hazard model, the semi parametric accelerated failure model (AFT model), the generalized linear model (RMST model) with RMST as the index, and the Cox time dependent model (expansion). The Cox model) and the PBLS model in dynamic prediction analysis are used to explore the factors affecting the prognosis of cervical cancer, endometrial cancer and ovarian cancer, and to predict the 5 year survival rate at different time points, providing basic clinical data for the prognosis of three major gynecologic malignancies, and helping clinical researchers to make the most for different patients. Methods the cause of death (or endpoint event) of endometrial cancer patients, cervical cancer patients and ovarian cancer patients was all caused by death, and the patients were lost or survived. The Kaplan-Meier method was used to estimate the survival of different cancer patients (cervical, endometrial and ovarian cancer). We use the Cox proportional hazard model to explore the relative risk ratio of the co factors, explore the accelerated failure factors of each factor with the AFT model, explore the influence of the covariate on the restrictive average survival time with the AFT model, and explore the factors with the extended Cox model, and explore the different factors by using the extended Cox model. The impact of time point on relative risk ratio, PBLS model was used to predict the 5 year survival rate at different time points. The index of the evaluation model was C-index, AIC, and AUC. analysis used R software (3.3.4 version). The test was both bilateral test. The test level was alpha = 0.05. results and the three major gynecologic malignancies were mainly married, white predominantly, endometrium. The diagnosis of cancer and ovarian cancer is older, the age of the diagnosis of cervical cancer is smaller, there is no difference in different diagnostic years, the FIGO of endometrial and cervical cancer is mainly in the first stage, the ovarian cancer is mainly in the three stage, the lymph node metastases are less, the number of endometrium cancer is less, the number of cervical cancer is more, the ovarian cancer is not included in this study. The operation rate of endometrial and ovarian cancer in patients with radiotherapy is up to 90%, while cervical cancer is less than 70%, the degree of differentiation is from high to low, and the degree of malignancy is from low to high: endometrial cancer, cervical cancer, ovarian cancer, endometrial cancer, ovarian cancer mainly adenocarcinoma, cervix cancer mainly based on squamous cell carcinoma, the location of registered location is equal, cervical cancer is good hair. In the sub cervix, ovarian cancer is more bilateral. For marital status, marriage separation (divorce, separation, widowhood) is higher than married death, low survival rate, unmarried women more complex, the survival rate of unmarried women with endometrial cancer and married women is not statistically different. In cervical cancer, the survival rate of unmarried women is significantly higher than that of the already married women. Married women, in ovarian cancer, the relative risk is changed over time; the greater the diagnostic age, the lower the survival rate, the relative risk of age in the cervical cancer, the time effect; the survival rate of the endometrium cancer patients of different races, the cervical cancer is also, but the survival rate of the white ovarian cancer patients and other ethnic groups is not unified. The higher the FIGO stage, the lower the survival rate, the relative risk ratio of the FIGO staging of endometrial carcinoma decreased, the survival rate of the patients with lymph node metastasis was lower than that of the patients without lymph node metastasis, and the relative risk was decreased after the endometrial cancer, and the cervical cancer was declining, and the ovarian cancer was unchanged; the operation was not constant. The three major gynecologic malignant tumor is a protective factor. The application of dynamic prediction analysis shows that the PBLS model can reflect the 5 year survival rate at different time points, while the Cox proportional hazard model can not reflect the change process at different time points. In the 5 model analysis of three major gynecologic malignant tumors, both from C-index or from AIC, the Cox model is extended. Best performance, the same 30 resampling results also showed that the extended Cox model was best. In endometrial and ovarian cancer, the C-index of the AFT model was larger. In the cervical cancer, the C-index of the RMST model was larger. It was found that the PBLS model was significantly higher than the Cox ratio risk model in the AUC value and the Slope index, and the dynamic prediction could not only explore the cancer patients. The most important factor in prognosis is to predict the w year survival rate at different time points. Conclusion marriage status, age, race, FIGO stage, lymph node metastasis, radiotherapy are all influencing factors of three major female genital cancers, and the relative risk of some factors is not permanent. For the first time, the PBLS model in dynamic prediction analysis is used. The model predicts the 5 year survival rate at different time points of three major female gynecologic malignancies in American women. The clinical researchers formulate individual treatment programs for patients, guide patients to continue treatment, increase compliance, and ultimately improve survival.
【學(xué)位授予單位】：南方醫(yī)科大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：R73-31
本文編號：2143810
[Abstract]:Background endometrial cancer, cervical cancer, and ovarian cancer are the three major gynecologic tumors that seriously harm the life and health of women. Even in the advanced medical technology, the mortality and mortality rate still remain high. Endometrial cancer is the first of the three major female reproductive system tumors, which accounts for the 20%-30% of female reproductive system tumors, in European and American countries. The incidence of endometrial cancer has taken the first place in gynecologic malignancies. In 2016, the new cases of endometrial cancer in the United States were more than the total of cervical and ovarian cancer. In recent years, the incidence of the developing countries was also significantly increased. The WHO statistics showed that in 2012, the number of new cervical cancer patients in the world was 527624 (7.9% of female cancer) and the number of dead people was 265,67 2 (7.5% of all women's cancer), ranking fourth in the world's incidence of women, although the incidence of the disease in the developed countries is declining in recent years, but in some developing countries, in 2015, about 90% of the 300000 cases of the deceased are from the middle and lower income countries, so the prognosis of cervical cancer is also a problem we can not ignore. The incidence of ovarian cancer in gynecologic malignancies is second, the mortality rate is the first, and there are about 19 million new cases in the world every year. The epidemiological study shows that the risk of women's ovarian cancer is 1.4%. Because of the deep pelvic cavity, the lack of early symptoms and effective screening methods, most of the ovarian cancer has reached the late period and the total of 5 years. The survival rate is only 45%. It is the most difficult to diagnose in the malignant tumor of Gynecology, the most difficult to cure, and the worst prognosis. Therefore, it is particularly important to construct an appropriate prognostic model to explore its influencing factors and predict the patient's survival rate. The.Cox proportion risk model is the most common regression model in the analysis of tumor data. However, when the proportional risk is assumed to be invalid, Cox The proportional risk model is contrary to its precondition, and the results obtained by using the Cox proportional hazard model in this case are not reliable. While the Buckley-James model in the accelerated failure model applies the linear regression idea to deal with the relationship between the survival time and the influencing factors, it does not need to satisfy the assumption that.Trinquart and others advocate using the restrictive average survival time. RMST is another generalized statistic to evaluate inter group effects. However, the Buckley-James model and the RMST model are all generalized indexes, which can not show the trend of change at different time points. Cox proposes to use the time function and time dependent covariate to construct extended Cox model to explore different time points. Relative risk ratio. In practical clinical treatment, patients may be more concerned about their own survival rate during different treatments. The proportional baseline supermodel (PBLS model) in dynamic prediction is a conditional model, which can explore the relative risk ratio at different time points, and can predict the dynamic survival rate of W years. The survival data of three major gynecologic cancer patients from January 1, 2004 to December 31, 2013 were selected from the US monitoring, epidemic and final result database, using the Cox proportional hazard model, the semi parametric accelerated failure model (AFT model), the generalized linear model (RMST model) with RMST as the index, and the Cox time dependent model (expansion). The Cox model) and the PBLS model in dynamic prediction analysis are used to explore the factors affecting the prognosis of cervical cancer, endometrial cancer and ovarian cancer, and to predict the 5 year survival rate at different time points, providing basic clinical data for the prognosis of three major gynecologic malignancies, and helping clinical researchers to make the most for different patients. Methods the cause of death (or endpoint event) of endometrial cancer patients, cervical cancer patients and ovarian cancer patients was all caused by death, and the patients were lost or survived. The Kaplan-Meier method was used to estimate the survival of different cancer patients (cervical, endometrial and ovarian cancer). We use the Cox proportional hazard model to explore the relative risk ratio of the co factors, explore the accelerated failure factors of each factor with the AFT model, explore the influence of the covariate on the restrictive average survival time with the AFT model, and explore the factors with the extended Cox model, and explore the different factors by using the extended Cox model. The impact of time point on relative risk ratio, PBLS model was used to predict the 5 year survival rate at different time points. The index of the evaluation model was C-index, AIC, and AUC. analysis used R software (3.3.4 version). The test was both bilateral test. The test level was alpha = 0.05. results and the three major gynecologic malignancies were mainly married, white predominantly, endometrium. The diagnosis of cancer and ovarian cancer is older, the age of the diagnosis of cervical cancer is smaller, there is no difference in different diagnostic years, the FIGO of endometrial and cervical cancer is mainly in the first stage, the ovarian cancer is mainly in the three stage, the lymph node metastases are less, the number of endometrium cancer is less, the number of cervical cancer is more, the ovarian cancer is not included in this study. The operation rate of endometrial and ovarian cancer in patients with radiotherapy is up to 90%, while cervical cancer is less than 70%, the degree of differentiation is from high to low, and the degree of malignancy is from low to high: endometrial cancer, cervical cancer, ovarian cancer, endometrial cancer, ovarian cancer mainly adenocarcinoma, cervix cancer mainly based on squamous cell carcinoma, the location of registered location is equal, cervical cancer is good hair. In the sub cervix, ovarian cancer is more bilateral. For marital status, marriage separation (divorce, separation, widowhood) is higher than married death, low survival rate, unmarried women more complex, the survival rate of unmarried women with endometrial cancer and married women is not statistically different. In cervical cancer, the survival rate of unmarried women is significantly higher than that of the already married women. Married women, in ovarian cancer, the relative risk is changed over time; the greater the diagnostic age, the lower the survival rate, the relative risk of age in the cervical cancer, the time effect; the survival rate of the endometrium cancer patients of different races, the cervical cancer is also, but the survival rate of the white ovarian cancer patients and other ethnic groups is not unified. The higher the FIGO stage, the lower the survival rate, the relative risk ratio of the FIGO staging of endometrial carcinoma decreased, the survival rate of the patients with lymph node metastasis was lower than that of the patients without lymph node metastasis, and the relative risk was decreased after the endometrial cancer, and the cervical cancer was declining, and the ovarian cancer was unchanged; the operation was not constant. The three major gynecologic malignant tumor is a protective factor. The application of dynamic prediction analysis shows that the PBLS model can reflect the 5 year survival rate at different time points, while the Cox proportional hazard model can not reflect the change process at different time points. In the 5 model analysis of three major gynecologic malignant tumors, both from C-index or from AIC, the Cox model is extended. Best performance, the same 30 resampling results also showed that the extended Cox model was best. In endometrial and ovarian cancer, the C-index of the AFT model was larger. In the cervical cancer, the C-index of the RMST model was larger. It was found that the PBLS model was significantly higher than the Cox ratio risk model in the AUC value and the Slope index, and the dynamic prediction could not only explore the cancer patients. The most important factor in prognosis is to predict the w year survival rate at different time points. Conclusion marriage status, age, race, FIGO stage, lymph node metastasis, radiotherapy are all influencing factors of three major female genital cancers, and the relative risk of some factors is not permanent. For the first time, the PBLS model in dynamic prediction analysis is used. The model predicts the 5 year survival rate at different time points of three major female gynecologic malignancies in American women. The clinical researchers formulate individual treatment programs for patients, guide patients to continue treatment, increase compliance, and ultimately improve survival.
【學(xué)位授予單位】：南方醫(yī)科大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：R73-31
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