预测年轻乳腺癌患者生存率列线图的建立和验证

目的:构建预测年轻乳腺癌患者生存情况的列线图，以期帮助临床诊疗。方法:收集SEER数据库中5 525例年轻乳腺癌患者的临床信息，通过单因素Log-rank检验和多因素Cox生存分析筛选出独立预后因素,用于构建预测患者3、5年总生存率(overall survival,OS)和癌症特异性生存率（cancer special survival,CSS)的列线图，将我院就诊的147例年轻乳腺癌患者作为验证集进行外部验证。结果:单因素和多因素分析结果显示，种族、病理类型、组织学分级、T分期、N分期、M分期、ER状态、HER-2状态、手术方式是与患者OS和CSS相关的独立危险因素，将这些因素纳入并建立预测患者OS和CSS的列线图模型。内部和外部验证结果显示模型具有良好的预测性能。基于建立的OS和CSS列线图模型对患者进行了风险分层，能够准确地将年轻乳腺癌患者分成预后有显著差异的三个风险亚组。结论:本研究构建的预测模型能较为准确的预测年轻乳腺癌患者的预后情况，为临床的诊疗提供科学依据。     

宫颈癌术后患者列线图预测模型及危险分层系统构建

目的 构建宫颈癌术后患者列线图预测模型,基于列线图个体得分建立危险分层系统。方法 通过搜索美国SEER （Surveillance,Epidemiology,and End Results）数据库中1973—2015年的6 835例宫颈癌术后患者数据构建预测模型,同时选取120例于苏州大学附属第二医院接受宫颈癌手术的患者作为外部验证队列。通过单因素和多因素的Cox回归筛选预后因子并构建列线图,基于列线图模型建立危险分层系统。结果 Cox回归分析显示诊断年龄、人种、组织学分级、T分期、N分期、淋巴结清扫状况、肿瘤大小、肿瘤浸润深度是宫颈癌术后患者的独立预后指标。由此构建的列线图模型的一致性指数在建模队列、内部验证队列和外部验证队列分别为0.824、0.814、0.730,校准曲线显示模型预测效果与实际生存情况基本相符,危险分层系统能区分不同FIGO分期患者的生存情况（均P<0.05）。结论 本研究所建立的列线图模型能有效预测宫颈癌术后患者预后,基于该列线图预测模型的危险分层系统对区分高危患者具有一定临床价值。     

基于TXNs家族的肺腺癌预后模型的建立及应用

目的:探索TXNs家族与肺腺癌（LUAD）预后的相关性并建立预后预测模型。方法:利用癌症基因组图谱（TCGA）数据，采用Cox单因素及多因素分析筛选TXNs家族中LUAD的独立预后因素，计算基于TXNs家族的风险评分RS，并分析RS与临床病理学参数的关系，最终构建包含RS的预后预测列线图模型。结果:TMX4是独立预后保护因素，TXNRD1是独立预后危险因素；基于TMX4与TXNRD1的风险评分RS高危患者预后差（P=0.005），且与较晚的T分期呈正相关（P<0.05）；利用独立预后因素RS、T分期、年龄构建的列线图能够直观个体化地预测LUAD患者的预后。结论:基于TXNs家族构建的LUAD预后预测列线图模型有望成为LUAD预后判断的有效指标。     

基于术前FAR和SⅡ的预后模型与TNM分期系统在评估胰腺癌根治术患者预后中的比较

目的 探讨胰腺导管腺癌患者术前纤维蛋白原/白蛋白比值（FAR）和系统免疫炎症指数（SⅡ）对预后的预测价值。方法 受试者工作特征（ROC）曲线确定FAR、SⅡ的最佳截断值,并进行分组。Cox风险比例模型分析胰腺癌根治术的预后影响因素,依此建立列线图（Nomogram）预后模型。C-index、AUC和校准曲线评估列线图的辨别和校准能力。DCA曲线评估列线图的临床有效性。结果 术前FAR及SⅡ的最佳截断值分别为0.095和532.945。Cox比例风险回归模型显示：FAR≥0.095、SⅡ≥532.945、CA199≥450.9U/ml、肿瘤最大径≥4cm、术后未进行化疗是影响胰腺癌预后不佳的独立危险因素（P<0.05）。C-index、AUC、校准曲线和DCA曲线表明,列线图预后模型的辨别能力、校准能力和临床有效性均优于TNM分期系统预后模型。结论 构建的Nomogram预后模型较TNM分期预后模型具有更高的准确性、区分度及临床获益。     

早发型非转移性结直肠癌患者预后预测模型的构建及外部验证

目的:探讨影响早发型非转移性结直肠癌（early-onset non-metastatic colorectal cancer,EONCRC）患者预后的相关独立危险因素,并构建列线图预测EONCRC患者预后。方法:从美国监测、流行病学和结果数据库SEER数据库中收集了9 097例EONCRC患者的数据,患者按照7∶3比例随机分配到训练集(6 369例)和验证集(2 728例)。通过单变量、多变量COX比例风险回归分析确定独立的预后因素,并构建列线图。 使用C指数、ROC曲线和校准曲线评价列线图的区分度、预测效能和校准度。使用新疆军区总医院收治的EONCRC患者临床资料(n=171)对列线图进行了外部验证并对其预后影响因素进行了分析。结果:多因素分析确定了与总生存期有关的8个独立风险因素,分别是组织学分化程度、组织学类型、神经浸润、分期、T分期、手术、化疗和放疗,并将它们纳入列线图。SEER训练集、SEER验证集、外部验证集的C指数值分别为0.765(95%置信区间,0.749~0.781)、0.785(95%置信区间,0.763~0.807)、0.766(95%置信区间,0.713~0.819),校准曲线表明了列线图预测总生存率与实际总生存率具有良好的一致性。ROC曲线显示,列线图可以准确预测EONCRC患者1年(AUC=0.834 9)、3年(AUC=0.794 7)和5年(AUC=0.771 2)的生存率。根据列线图的风险评分将患者分为高风险、中风险和低风险组,在SEER训练集、SEER验证集、外部验证集中,低风险组的5年生存率均最高,其次是中风险组和高危组。结论:本研究确定了EONCRC患者预后相关的8个独立危险因素,列线图能准确预测中国及美国EONCRC患者1年、3年、5年总生存率,对EONCRC患者进行个体化的分层及预后评估,为临床的诊疗提供科学依据。     

横纹肌肉瘤患者列线图预后模型的构建

  目的  构建列线图预测横纹肌肉瘤患者的1、3、5年生存率。  方法  从美国国立癌症研究所的监测、流行病学、结果数据库（SEER）数据库中收集1975年至2016年间诊断的横纹肌肉瘤患者,经筛选后最终获得861例符合条件的患者,采用单因素Kaplan-Meier法及多因素Cox模型分析确定横纹肌肉瘤患者独立的预后影响因素,然后将这些因素纳入并构建预测横纹肌肉瘤患者1、3、5年生存率的列线图。通过一致性指数（C-index）对所得列线图进行内部验证,检查其预测精度;同时,列线图预后模型的校正曲线一致性良好。  结果  年龄、病理类型、病理分级、总分期、手术、放疗及化疗均是横纹肌肉瘤患者的独立预后影响因素（P < 0.05）,将这些因素纳入并成功构建了列线图。列线图的内部验证所得C指数为0.776。  结论  本次研究构建的横纹肌肉瘤患者生存风险的列线图具有良好的预测精度,有助于临床医师对横纹肌肉瘤患者预后作出较为准确的评估,也有利于对横纹肌肉瘤患者实施个体化诊疗。      

APRI评分对HBV相关肝细胞癌切除术患者预后的预测价值

目的:评估天冬氨酸转氨酶与血小板计数比值指数（APRI）对HBV相关肝细胞癌（HCC）切除术患者术后总生存率（OS）的预测价值。方法:采用回顾性队列研究方法,收集2012年1月至2016年12月期间在广西医科大学附属肿瘤医院行切除术治疗的1 031例HBV相关HCC患者的术前临床资料。通过Kaplan-Meier生存曲线确定APRI评分的cutoff值。采用Kaplan-Meier法绘制不同APRI组患者的生存曲线,并通过Log-rank检验评估两组人群的生存差异。运用逐步多因素Cox回归筛选患者OS独立影响因素。采用限制性立方条图（RCS)评价患者APRI与死亡风险的相关性。建立列线图模型评估APRI对OS的预测能力并内部验证。结果:RCS显示APRI与死亡风险呈非线性关联（非线性P＜0.001）。多因素Cox回归结果显示:APRI、BCLC分期、AFP、性别和肿瘤大小是OS独立影响因素,高APRI组死亡风险是低APRI组2.1倍。患者OS的列线图显示APRI对OS的预测能力仅次于BCLC分期。在建模组和验证组中预测OS列线图的C-index分别为0.71（95%CI:0.68~0.74）、0.69（95%CI:0.64~0.75）;1和5年OS校正曲线显示列线图具有良好的校准度;临床决策曲线（DCA）显示模型具有良好的临床应用价值。结论:APRI是HBV相关HCC切除术患者OS独立影响因素,基于APRI对患者预后进行分层,有利于进行个体化治疗和随访。     

术前炎症指标对肝细胞癌肝切除术患者的预后预测价值

目的  探讨术前炎症指标中性粒细胞与淋巴细胞比值（NLR）、血小板与淋巴细胞比值（PLR）和预后营养指数（PNI）在肝细胞癌（HCC）肝切除术后患者预后中的预测价值。方法 本研究为回顾性队列研究。选择2015年6月—2018年3月于本院行肝切除术的HCC患者为研究对象,随访截至2021年1月。主要研究指标为总生存期（OS）。采用限制性立方样条、Cox比例风险回归模型、时间依赖的受试者工作特征（ROC）曲线以及列线图评估术前NLR、PLR及PNI的预后预测价值。结果 共77例患者符合标准纳入分析,其中男性59例;中位年龄51岁。限制性立方样条分析结果显示,NLR、PLR、PNI与HCC患者的死亡风险均呈线性关系（非线性P>0.05）,Cox比例风险回归模型结果显示,NLR、PLR、PNI、肿瘤分化程度及肿瘤包膜是否完整是影响HCC患者OS的因素。NLR、PLR、PNI等炎症指标构建的列线图模型预测1年、3年总生存率的AUC均大于NLR、PLR、PNI（均P<0.05）,且联合预后影响因素肿瘤分化程度和肿瘤包膜是否完整后AUC进一步提高（均P<0.05）。结论 术前炎症指标NLR、PLR、PNI在预测肝细胞癌肝切除术患者预后中具有良好效能,联合临床因素可进一步提高预测效能。     

胰头癌根治性胰十二指肠切除术后早期复发预测模型的建立与应用

目的 构建可预测胰头癌根治性胰十二指肠切除术后早期复发的列线图模型,并评估其应用价值。方法 本研究为一项回顾性队列研究,选择2017年6月—2019年7月在本院行胰头癌根治性胰十二指肠切除术的患者为研究对象。研究结局为术后早期复发,采用单因素和多因素logistic回归分析早期复发的影响因素,并基于影响因素构建列线图模型。采用受试者工作特征（ROC）曲线下面积（AUC）评估列线图模型的区分度,校准曲线和Hosmer-Lemeshow检验评估校准度,决策曲线评估临床应用价值。结果 共137例患者符合标准纳入最终分析,术后早期复发58例（42.3%）。多因素logistic回归显示,肿瘤大小≥3 cm、术前CA19-9水平>37 U/mL、肿瘤分化程度低分化和淋巴结转移数目>3枚是影响患者术后早期复发的危险因素（均P<0.05）,基于这些因素成功构建了列线图模型,AUC为0.807 （95%CI：0.729~0.885）,校准曲线Hosmer-Lemeshow检验表明模型具有良好的校准度（P=0.569）。决策曲线显示,列线图具有良好的临床应用价值,即预测早期复发概率达到22%时,可采取干预。结论 本研究成功构建可预测胰头癌根治性胰十二指肠切除术后早期复发的列线图模型,有助于临床早期筛选并识别风险患者。     

基于SEER数据库肺腺癌脑转移预测模型的构建及分析

目的 构建可视化预测肺腺癌（LUAD）脑转移风险概率的列线图模型,提高患者生存率。方法 研究纳入监测、流行病学和最终结果（SEER）数据库中58 928例LUAD患者,并按7∶3比例随机分为训练集和验证集。在训练集中采用Lasso回归与多因素Logistic回归分析筛选最有意义的预测变量,构建预测LUAD脑转移的列线图模型。采用受试者工作特征（ROC）曲线的曲线下面积（AUC）,Boostrap绘制校正曲线,Brier评分验证模型区分度及校准度,决策曲线分析（DCA）评价预测模型的临床效能。结果 最终筛选出7个独立影响因素构建列线图预测模型。训练集和验证集列线图预测LUAD患者发生脑转移概率的AUC分别为0.853(95%CI:0.849～0.858)和0.851(95%CI:0.844～0.857),校准曲线显示模型预测概率与实际观察概率具有较高的一致性,Brier评分均为0.092,DCA显示净收益率较高,模型临床效能较好。结论 本研究成功建立了预测LUAD脑转移的列线图模型,该模型能够准确区分脑转移高风险患者,可以有效指导临床医师制订个体化治疗方案。     

Socioeconomic factors and survival in patients with non‐metastatic head and neck squamous cell carcinoma

The effect of socioeconomic factors on receipt of definitive treatment and survival outcomes in non‐metastatic head and neck squamous cell carcinoma (HNSCC) remains unclear. Eligible patients (n = 37 995) were identified from the United States Surveillance, Epidemiology and End Results (SEER) database between 2007 and 2012. Socioeconomic factors (i.e., median household income, education level, unemployment rate, insurance status, marital status and residence) were included in univariate/multivariate Cox regression analysis; validated factors were used to generate nomograms for cause‐specific survival (CSS) and overall survival (OS), and a prognostic score model for risk stratification. Low‐ and high‐risk groups were compared for all cancer subsites. Impact of race/ethnicity on survival was investigated in each risk group. Marital status, median household income and insurance status were included in the nomograms for CSS and OS, which had higher c‐indexes than the 6th edition TNM staging system (all P < 0.001). Based on three disadvantageous socioeconomic factors (i.e., unmarried status, uninsured status, median household income <US $65 394), the prognostic score model generated four risk subgroups with scores of 0, 1, 2 or 3, which had significantly separated CSS/OS curves (all P < 0.001). Low‐risk patients (score 0–1) were more likely to receive definitive treatment and obtain better CSS/OS than high‐risk patients (score 2–3). Chinese and non‐Hispanic black patients with high‐risk socioeconomic status had best and poorest CSS/OS, respectively. Therefore, marital status, median household income and insurance status have significance for predicting survival outcomes. Low‐risk socioeconomic status and Chinese race/ethnicity confer protective effects in HNSCC.     

基于列线图探索脑内皮黏附分子表达水平在结肠癌预后预测中的作用

目的：探索脑内皮细胞黏附分子（CERCAM）与结肠癌患者预后的关系，利用Cox模型建立具有良好预后判断价值的列线图并予以验证。方法：下载TCGA及GTEx数据库中结肠癌及正常组织中CERCAM表达及患者临床特征数据，收集2013年2月至2019年6月南京市第一医院收治的4例结肠癌患者的癌及癌旁组织样本进行验证，通过差异分析、通路富集分析以及生存分析等方法探索CERCAM的组织定位、功能及预后价值。通过Cox回归筛选出结肠癌的预后危险因素，基于CERCAM及各危险因素构建列线图，分别使用一致性指数、校准曲线、时间依赖性受试者工作特征（ROC）曲线进行验证与评价，根据危险分层绘制生存曲线。结果：结肠肿瘤组织中CERCAM基因的表达水平显著低于正常组织（P<0.001），在结肠癌患者中，CERCAM高表达人群OS（P=0.034）及存活状态（P=0.002）显著劣于低表达组，且CERCAM与癌症信号通路以及PI3K-Akt信号通路的活化有关联。Cox分析显示，CERCAM表达水平（HR=2.23，P=0.015）、T分期（HR=5.64，P=0.015）、M分期（HR=2.62，P=0.022）是结肠癌预后的独立危险因素，血管浸润（HR=2.30，P=0.089）是危险因素，利用上述因素建立列线图，一致性指数提示其区分度好，且训练集与测试集一致；校准曲线、ROC曲线同样显示该列线图的预测能力较好。通过危险分层绘制生存曲线，结果提示高风险组有更低的生存率（P<0.000 1）。结论：CERCAM高表达与结肠癌患者不良预后密切相关，且可能与癌症中蛋白聚糖及PI3K-Akt信号通路有关联，基于CERCAM建立的列线图优于传统预测模型，对结肠癌患者生存预后的评估具有一定临床价值，这种实用的模型有助于患者风险分层及治疗方案的优化。     

Geriatric Early-Stage Triple-Negative Breast Cancer Patients in Low-risk Population: Omitting Chemotherapy Based on Nomogram

BackgroundConsidering old age and comorbidities, the actual benefit of chemotherapy in older patients with early triple-negative breast cancer (TNBC) remains uncertain. We aimed to select appropriate patients who could avoid chemotherapy in this population.MethodsA total of 6482 patients more than 65 years old with T1-2N0-1M0 TNBC in 2010-2015 were extracted from SEER program. Multivariate logistic regression was performed to identify independent factors associated with chemotherapy usage. Survival analysis was performed using Kaplan-Meier plots and log-rank tests. Independent prognostic factors were identified by multivariate Cox analysis. A nomogram predicting breast cancer-specific survival (BCSS) and a risk stratification model were constructed.ResultsA total of 3379 (52.13%) patients received chemotherapy while 3103 (47.87%) did not. Age, married status, grade, T-stage, N-stage, radiation and breast-conserving surgery (BCS) were significantly associated with chemotherapy usage (all P < .05). Chemotherapy significantly improved OS (HR = 0.606, P < .001) and BCSS (HR = 0.763, P = .006) in the entire population. A nomogram was built by incorporating independent risk factors (age, T-stage, N-stage, grade and radiation). Based on the score of the nomogram, the risk stratification model demonstrated that chemotherapy improved OS (P < .001) and BCSS (P < .001) of patients in the high-risk group (score >180), but not in the low-risk group (score ≤75).ConclusionChemotherapy is beneficial for geriatric patients with T1-2N0-1M0 TNBC in this study, and the risk stratification model indicates the feasibility of sparing chemotherapy in low-risk subgroup without sacrificing survival, providing clinicians tools to weigh the risk–benefit of chemotherapy and customize the individualized treatment accordingly.     

A new nomogram for recurrence-free survival prediction of gastrointestinal stromal tumors: Comparison with current risk classification methods

BackgroundThis study aimed to build a new risk stratification nomogram for gastrointestinal stromal tumors (GISTs) focused on a popular factor Ki-67 to enable individualized and precise predictions of the most suitable candidates for imatinib therapy.MethodsWe retrospectively collected clinicopathologic data of the patients diagnosed with GISTs from January 1998 to December 2015 at Southern Medical University Nanfang Hospital as the experiment group. And patients with GISTs at the Sun Yat-sen University Cancer Center from January 2007 to December 2012 were included as the validation group. The nomogram was built using Kaplan-Meier method and the Cox proportional hazards regression model. The receiver operating characteristic (ROC) curves were established to compare the discriminative ability of the new nomogram with other risk stratification systems, including the modified National Institute of Health (modified NIH) criteria, Armed Forces Institute of Pathology (AFIP) criteria, Memorial Sloan Kettering Cancer Center (MSKCC) prognostic nomogram, and contour maps.ResultsIn univariate analysis, the tumor size, site, mitotic count, tumor rupture and Ki-67 labeling index were significant factors (all P < 0.05) and included in the Cox model to build our nomogram. According to the ROC curve, our new nomogram showed the largest AUC value (0.778) compared with that of the other classification methods (contour maps, AUC = 0.743; AFIP, AUC = 0.719; MSKCC, AUC = 0.712; and modified NIH, AUC = 0.719).ConclusionOur new nomogram exhibits an excellent performance and might become a potential risk stratification to support therapeutic decision-making for GISTs.     

中国肝癌分期Ⅲ期肝细胞癌放疗后预后因素分析及列线图构建

目的 探讨影响接受调强放疗（intensity-modulated radiotherapy,IMRT）的中国肝癌分期（China liver cancer staging,CNLC）Ⅲ期肝细胞癌（hepatocellular carcinoma,HCC）患者预后的危险因素,并建立预后列线图模型。方法 收集2012年1月到2021年3月在广西医科大学附属肿瘤医院接受IMRT治疗的CNLCⅢ期HCC患者的临床资料进行回顾性分析。采用单因素和多因素Cox回归分析影响患者预后的独立危险因素。构建列线图模型预测患者1年、2年、3年的总生存率,并采用受试者工作特征（receiver operating characteristic,ROC）曲线和校准曲线评估模型效能。根据Cox模型风险评分的中位数将患者分为高、低风险组,使用Kaplan-Meier法绘制生存曲线图,log-rank检验分析两组的生存差异。结果 本研究共纳入250 HCC例患者。多因素Cox回归分析结果显示,肿瘤数目、甲胎蛋白（alpha-fetoprotein,AFP）、血清碱性磷酸酶(alkaline phosphatase,...     

Black patients with multiple myeloma have better survival than white patients when treated equally: a matched cohort study

We assessed differences in survival between non-Hispanic black (NHB) and non-Hispanic white (NHW) patients with multiple myeloma (MM), and the sequential effects of patient characteristics, and diagnosis and treatment-related factors on the survival disparity using data from 3319 NHB and 20,831 NHW MM patients in the SEER-Medicare (1999–2017) database. Four sets of 3319 NHWs were matched sequentially to the same set of 3319 NHBs, based on demographics (age, sex, year of diagnosis, marital status, and SEER site), socioeconomic status (SES, demographics plus SES), presentation factors (SES variables plus comorbidity), and treatment factors (presentation variables plus antimyeloma therapies). We found NHBs were less likely to receive treatment than NHWs even among patients matched for demographics, SES, and comorbidities. The absolute difference in 5-year survival between NHBs and NHWs was not significant in the demographics match (0.6%; P = 0.30) and remained non-significant after matching for SES (1.4%, P = 0.17). When matching for presentation, NHBs had significantly longer 5-year survival than NHWs (absolute difference = 3.8%, P = 0.003). Additional matching on treatment-related factors further enlarged the racial difference in 5-year survival to 4.6% (P < 0.001). Our findings reinforce the importance of equitable access to effective treatment modalities to further improve the survival of NHB patients with MM.Subject terms: Risk factors, Epidemiology     

Socioeconomic Status Is an Independent Prognostic Factor for Overall Survival in Patients With Multiple Myeloma: Real-World Data From a Cohort of 223 Patients

IntroductionSocioeconomic status (SES) has been shown to be a prognostic factor for overall survival in a variety of hematologic malignancies, especially for patients who require continuous care such as those with multiple myeloma (MM).Patients and MethodsWe retrospectively collected data from 223 patients with symptomatic MM diagnosed and treated in our department from January 2005 to December 2019. The modified Kuppuswamy scale, slightly modified, was used for the SES assessment. The Kaplan-Meier estimator of survival and Cox regression analysis were used.ResultsIn our cohort of 223 patients with MM, low SES was an independent poor prognostic factor for overall survival (OS), in addition to higher International Staging System stage and high-risk cytogenetics (hazard ratio for low SES on Cox regression analysis, 2.092; 95% confidence interval [CI], 1.36-3.2; log-rank P = .000). Patients with low SES had inferior survival compared with the whole patient cohort (median OS: low SES, 28 months; 95% CI, 18-37.9; high SES, 68 months; 95% CI, 55.6-80.4; log-rank P = .000). The low SES effect on OS was more evident for the elderly patients who were not transplant eligible and in those with a diagnosis of MM International Staging System stage I. The effect of low SES on OS was attenuated by time, and ethnic origin had no effect on OS.ConclusionsThe results of the present study have shown that low SES is an independent poor prognostic factor for survival of patients with MM.     

Socioeconomic differences in survival among breast cancer patients in the Netherlands not explained by tumor size

There seem to be socioeconomically differences in survival for females with breast cancer, usually associated with a higher stage of disease. However, differences within tumor size have not been studied. Aim of this study is to assess differences in survival according to socioeconomic status (SES), stratified for tumor size and stage at diagnosis, for females with breast cancer in the Netherlands. All females diagnosed with breast cancer (1995–2005) were selected from the Netherlands Cancer Registry. Patients were linked to a SES database according to postal code. A multivariable logistic regression was used to assess factors associated with SES. Overall survival (OS) and relative survival (RS) were calculated. Overall, 127,599 patients were included. Higher SES was associated with lower T-stage (P < 0.0001). A decreased survival (OS and RS) was found for patients with a lower SES. Also within different size groups, RS was different. Overall, 10-year OS for the high SES group was 65 and 58% for the low SES group (hazard ratio 1.1, P < 0.001) and RS was 79 versus 74% (relative excess risk, RER 1.2; P < 0.001). The socioeconomic differences remained statistically significant (P < 0.001) after adjustment for age, year of diagnosis, grade, TNM stage, and treatment. For the lowest SES group 777 deaths could be avoided. Socioeconomic differences in survival of breast cancer patients were observed in the Netherlands. Higher stage at diagnosis of patients with a lower SES only partly explains the decreased survival. Policies aimed at the reduction of socioeconomic health inequalities might be important to improve survival of breast cancer.     

自体造血干细胞移植治疗多发性骨髓瘤的疗效及预后影响因素分析

目的:探讨自体造血干细胞移植治疗多发性骨髓瘤（MM）的疗效和影响MM患者预后的因素。方法:回顾性分析我院2012年01月至2019年12月37例接受自体造血干细胞移植的MM患者的临床资料,中位随访时间为55（1～91）个月。对37例患者的反应深度、无进展生存时间（PFS）、总生存时间（OS）和影响预后的相关因素进行分析。结果:移植后3月内疗效达到完全缓解率和深度缓解率均优于移植前（P＜0.01,P＜0.05）,移植前后总有效率（ORR）比较无统计学意义（P＞0.05）。患者3年、5年OS率为97.0%、81.4%;3年、5年PFS率为62.7%、51.0%;中位PFS和OS均未获得。单因素分析结果表明移植后3月内疗效获得深度缓解较未获得患者无论是OS 还是PFS均较优 (P均＜0.01);诱导化疗后获得深度缓解可明显延长OS（P＜0.05）;DS分期Ⅰ-Ⅱ期、mSMART3.0危险分层标危患者相比DS分期Ⅲ期、高危患者PFS均有明显优势(P＜0.05)。Cox 多因素回归分析显示,移植后3月内疗效达深度缓解是PFS和OS的独立预后因素,mSMART3.0危险分层也是PFS的独立预后因素。结论:自体造血干细胞移植可以提高 MM 患者的反应深度。移植前后疗效、DS分期和mSMART3.0危险分层均可影响MM患者生存率。移植后3月内疗效达深度缓解是PFS 和OS的独立预后因素,mSMART3.0危险分层也是PFS的独立预后因素。