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目的 利用SEER数据库分析局限期可手术食管癌术前放化疗患者的预后及其相关因素,并建立生存预测列线图,为筛选术前放化疗患者提供一定参考。方法 选取SEER数据库2010-2015年食管癌接受术前放化疗且分期为T1b-4aN0-3M0(2010年AJCC第7版分期)的病例;生存率采用Kaplan-Meier法,单因素分析采用Logrank检验,多因素分析采用Cox模型检验;通过R软件建立预测模型列线图;一致性指数(C-index)及校准曲线用来评价模型准确度。结果 共1697例患者符合条件并可纳入分析。单因素分析显示性别、T分期、N分期、分化程度与总生存(OS)及癌症特异生存(CSS)均相关(P均<0.001),年龄与OS相关(P=0.027)。多因素分析显示年龄、性别、分化程度、N分期与OS相关;性别、分化程度、T分期、N分期与CSS相关(P均<0.05)。将预后相关因素纳入Nomogram预后模型,5年OS、CSS的C-index值分别为0.60、0.61。同样方法建立食管鳞癌亚组患者预后模型,OS及CSS的C-index值为0.62、0.64。结论 性别、临床分期、分化程度为局限期可手术食管癌行术前放化疗者CSS预后因素,根据以上数据建立的列线图可为是否采用术前放化疗联合手术治疗这一模式提供一定参考。 相似文献
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目的:探讨治疗前预后营养指数(prognostic nutritional index,PNI)对宫颈癌同步放化疗患者疗效及预后的预测价值。方法:收集2015年1月至2016年11月在四川省肿瘤医院接受根治性同步放化疗的324名宫颈癌患者。利用受试者工作特征曲线(ROC)及约登(Youden)指数获取PNI最佳切点(cut-off point),将患者分为高PNI组及低PNI组,比较2组宫颈癌患者的客观缓解率(objective response rate,ORR)、无进展生存期(progression-free survival,PFS)及总生存期(overall survival,OS)。结果:末次随访时间为2019年11月,平均随访时间(39.18±13.15)月。PNI的最佳切点为49.55,约登指数为0.410,敏感度71.83%,特异度69.17%,曲线下面积(AUC)为0.717。高PNI组(PNI>49.55)与低PNI组(PNI≤49.55)之间 ORR、3年OS及PFS之比分别为为93.85% vs 77.52%,90.3% vs 62.8%、79.9% vs 48.1%,差异均具有统计学意义(P<0.05)。单因素及多因素COX回归分析提示治疗前低PNI值(<49.55)、病理类型、淋巴结转移是影像宫颈癌OS及PFS的独立危险因素。结论:治疗前PNI值可作为宫颈癌患者简单可行的临床疗效及预后指标。 相似文献
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目的 探讨小野寺预后营养指数(PNI)与根治性放化疗或放疗的食管鳞癌患者的预后关系,为评估疗后长期生存提供方便、有效、准确的预测指标。方法 回顾分析2013—2015年在河北医科大学第四医院行根治性放化疗或放疗并符合入组条件的食管鳞癌患者共 231例,统计分析每例患者不同放疗阶段的PNI值并运用ROC曲线确定放疗前PNI的最佳临界值,将231患者分为营养良好组(86例)和营养不良组(145例)。应用Kaplan-Meier法生存分析,Cox模型分析不同营养状况与预后关系。比较两组患者近期疗效及不良反应。结果 全组患者放疗前、第3周、第6周及结束后1月时的PNI均值分别为 48.68±5.08、39.68±4.87、43.74±4.89、48.31±4.92。运用ROC曲线确认的患者疗前PNI最佳临界值为49.25,曲线下面积为0.655,敏感性为68.6%,特异性为60.9%。营养良好组(PNI≥49.25)的 5年总生存率和无进展生存率分别为36.0%和31.3%,均优于营养不良组(PNI<49.25)的19.3%和18.6%(P=0.001、0.039)。多因素分析显示疗前PNI为总生存的独立预后因素(P=0.021)。进一步分层分析发现临床分期为Ⅰ、Ⅱ期以及同期化疗者营养良好组的总生存优于营养不良组(P=0.007、0.004)。另外,营养良好组放疗后缓解率高于营养不良组(P=0.047),而≥3级急性放射性食管炎发生率有低于营养不良组趋势(P=0.060)。结论 疗前患者的PNI作为方便、可靠的指标可预测食管鳞癌根治性放化疗或放疗后的生存状况,PNI较高者具有较好的预后和放疗耐受性,尤其是在分期偏早或同期化疗患者中PNI的预测价值更大。 相似文献
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《Current problems in cancer》2022,46(6):100899
Unlike cervical squamous cell carcinoma (CSCC), no uniform standard has been implemented to identify serum biomarkers for adenocarcinoma of the cervix (ADC). In the present study, we aimed to determine whether pretreatment serum tumor markers were of prognostic value in patients with ADC and constructed and validated the novel accurate nomogram for stratifying the risk groups. Patients with ADC who underwent curative hysterectomy or definitive radiotherapy from January 2011 to December 2016 were included. Significant factors independently predicting prognosis were selected by univariate multivariate Cox proportional hazard regression models and adopted for constructing the overall survival (OS) and progression-free survival (PFS) prediction nomograms. The receiver operating characteristic (ROC) curve and concordance index (C-index) with calibration curve was used to determine the accuracy of the nomogram in the prediction and determination of performance. We enrolled a total of 295 samples and randomized them as the training set (n = 207) or validation set (n = 88). Federation of Gynecology and Obstetrics Staging Guidelines (FIGO) stage, para-aortic lymph node (PALN), carcinoembryonic antigen (CEA), neuron-specific enolase (NSE), and HCG-β were assessed as the common factors independently predicting OS and PFS. For our constructed nomograms, its C-index values in OS and PFS prediction were 0.896 (95% CI, 0.879-0.913) and 0.895 (95% CI, 0.878-0.912) in training set, whereas 0.845 (95% CI:0.796-0.894) and 0.846 (95% CI:0.797-0.895) in validation set. ROC and calibration curves for our constructed nomograms predicted the excellent consistency of nomogram-predicted values with real measurements of 1-, 3-, and 5-year OS. We explored novel prognostic serum tumor markers of ADC and constructed effective nomograms comprising NSE, HCG-β, FIGO stage, PALN, and CEA, which could estimate OS and PFS for patients with ADC. These nomograms performed well in predicting patient prognosis, which was a potentially useful approach for stratifying ADC risk, thus contributing to clinical decision-making and individualized follow-up planning. 相似文献
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《European journal of surgical oncology》2021,47(6):1473-1480
IntroductionSurvival of patients with the same clinical stage varies widely and effective tools to evaluate the prognosis utilizing clinical staging information is lacking. This study aimed to develop a clinical nomogram for predicting survival of patients with Esophageal Squamous Cell Carcinoma (ESCC).Materials and methodsOn the basis of data extracted from the SEER database (training cohort, n = 3375), we identified and integrated significant prognostic factors for nomogram development and internal validation. The model was then subjected to external validation with a separate dataset obtained from Jinling Hospital of Nanjing Medical University (validation cohort, n = 1187). The predictive accuracy and discriminative ability of the nomogram were determined by concordance index (C-index), Akaike information criterion (AIC) and calibration curves. And risk group stratification was performed basing on the nomogram scores.ResultsOn multivariable analysis of the training cohort, seven independent prognostic factors were identified and included into the nomogram. Calibration curves presented good consistency between the nomogram prediction and actual observation for 1-, 3-, and 5-year OS. The AIC value of the nomogram was lower than that of the 8th edition American Joint Committee on Cancer TNM (AJCC) staging system, whereas the C-index of the nomogram was significantly higher than that of the AJCC staging system. The risk groups stratified by CART allowed significant distinction between survival curves within respective clinical TNM categories.ConclusionsThe risk stratification system presented better discriminative ability for survival prediction than current clinical staging system and might help clinicians in decision making. 相似文献
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目的 探讨围手术期预后营养指数(PNI)对结直肠癌患者3年无进展生存(PFS)期和总生存(OS)期评估的价值.方法 选取2012年12月至2020年1月中国人民解放军总医院海南医院经术后病理确诊的结直肠癌患者153例,根据围手术期PNI并将患者分为不同亚组,通过Kaplan-Meier分析不同亚组患者预后差异,通过多因... 相似文献
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目的:开发和验证一种新型列线图模型预测进展期胃腺癌患者远期预后。方法:回顾性分析2010年1月至2018年12月在福建医科大学附属协和医院132例及青海大学附属医院45例接受新辅助化疗后行根治性切除术的胃腺癌患者临床资料。基于新辅助化疗前CT影像组学评分(CT-RS)构建列线图模型(RS-CN),并通过ROC曲线下面积(AUC),Time-ROC曲线,Cindex评估RS-CN的预测能力。结果:训练队列中,RS-CN预测胃腺癌患者总体生存率的C-Index为0.72,AUC显著优于TRG分级(P=0.019),且与ypTNM分期相当(P=0.786)。Time-ROC曲线显示在各个时间段RS-CN预测总体生存能力始终优于TRG分级及ypTNM分期。外部验证队列中得到相同的结果。进一步分析,低风险组(RS-CN<288.4)患者3年总生存(overall survival,OS)及无病生存(disease-free survival,DFS)均显著优于高风险组(RS-CN≥288.4),但高风险组进行术后辅助化疗3年DFS显著提高(P<0.05),3年OS (P=0.099)... 相似文献