Development and Validation of a Novel Nomogram for Individualized Prediction of Survival in Cancer of Unknown Primary.
Development and Validation of a Novel Nomogram for Individualized Prediction of Survival in Cancer of Unknown Primary.
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在未知主要癌症中的个性化预测生存的个性化预测的新型诺明图的开发和验证。
DOI：
10.1158/1078-0432.ccr-20-4117
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发表时间：
2021-06-15
期刊：
影响因子：
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通讯作者：
Varadhachary GR
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文献类型：
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作者：
Raghav K;Hwang H;Jácome AA;Bhang E;Willett A;Huey RW;Dhillon NP;Modha J;Smaglo B;Matamoros A Jr;Estrella JS;Jao J;Overman MJ;Wang X;Greco FA;Loree JM;Varadhachary GR
预后不确定性是未知原发癌（CUP）的主要挑战。目前的模式限制了有意义的医患对话。我们的目的是建立一个基于可靠的临床病理预后因素的预测CUP总生存期（OS）的nomogram。我们评估了MDACC （MD Anderson Cancer Center, Houston， USA）的521例CUP患者（2012-2016）。基线变量使用cox回归分析，并使用显著预测因子开发nomogram。通过校准曲线、一致性概率估计（CPE）（±标准误差[SE]）和一致性统计量（C-index）评估预测准确性和判别性能。该模型使用两个独立的CUP队列进行了启动和多机构外部验证：V1 （MDACC [2017]， N=103）和V2（加拿大温哥华BC癌症中心和美国Sarah Cannon癌症中心/田纳西肿瘤中心，N=302）。整个队列（N=926）的基线特征包括：中位年龄（63岁），女性（51%），ECOG-PS 0-1(64%)，腺癌（52%），≥3个转移部位（30%），中位随访时间和OS分别为40.1和14.7个月。确定了五个独立的预后因素：性别，ECOG-PS，组织学，转移部位数量和中性粒细胞淋巴细胞比例。该模型预测OS的CPE为0.69 (SE：±0.01)[C-index: 0.71 (95%CI: 0.68-0.74)]，优于Culine/Seve预后模型（CPE: 0.59±0.01）。外部验证队列V1和V2的CPE分别为0.67（±0.02）和0.70（±0.01）。在所有队列中，1年OS的校准曲线显示nomogram预测值与实际观测值之间有很强的一致性。我们用户友好的CUP图整合了常用的基线因素，提供了强大的个性化预测，可以帮助临床决策和临床试验的选择/分层。
Prognostic uncertainty is a major challenge for cancer of unknown primary (CUP). Current models limit a meaningful patient-provider dialogue. We aimed to establish a nomogram for predicting overall survival (OS) in CUP based on robust clinicopathological prognostic factors. We evaluated 521 patients with CUP at MDACC [MD Anderson Cancer Center, Houston, USA] (2012–2016). Baseline variables were analyzed using Cox-regression and nomogram developed using significant predictors. Predictive accuracy and discriminatory performance were assessed by calibration curves, concordance probability estimate (CPE) (±standard error [SE]) and concordance statistic (C-index). The model was subjected to bootstrapping and multi-institutional external validations using two independent CUP cohorts: V1 (MDACC [2017], N=103) and V2 (BC Cancer, Vancouver, Canada and Sarah Cannon Cancer Center/Tennessee Oncology, USA, N=302). Baseline characteristics of entire cohort (N=926) included: median age (63 years), women (51%), ECOG-PS 0–1 (64%), adenocarcinomas (52%), ≥3 sites of metastases (30%), median follow-up duration and OS of 40.1 and 14.7 months, respectively. Five independent prognostic factors were identified: gender, ECOG-PS, histology, number of metastatic sites and neutrophil-lymphocyte ratio. The resulting model predicted OS with CPE of 0.69 (SE: ±0.01) [C-index: 0.71 (95%CI:0.68–0.74)] outperforming Culine/Seve prognostic models (CPE: 0.59±0.01). CPE for external validation cohorts V1 and V2 were 0.67 (±0.02) and 0.70 (±0.01), respectively. Calibration curves for 1-year OS showed strong agreement between nomogram prediction and actual observations in all cohorts. Our user-friendly CUP nomogram integrating commonly available baseline factors provides robust personalized prognostication which can aid clinical decision making and selection/stratification for clinical trials.