Development and Validation of a Novel Nomogram for Individualized Prediction of Survival in Cancer of Unknown Primary
| Autor: | Ryan W. Huey, Anneleis Willett, Eric Bhang, Jonathan M. Loree, Brandon G. Smaglo, Aurelio Matamoros, Gauri R. Varadhachary, Alexandre A. Jácome, Kanwal Pratap Singh Raghav, N. Dhillon, Jignesh Modha, Michael J. Overman, Xuemei Wang, Hyunsoo Hwang, Justin Jao, Jeannelyn S. Estrella, F. Anthony Greco |
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| Rok vydání: | 2020 |
| Předmět: |
Oncology
Cancer Research medicine.medical_specialty Lung Neoplasms Concordance Article Cohort Studies 03 medical and health sciences 0302 clinical medicine Internal medicine medicine Humans 030212 general & internal medicine Bootstrapping (statistics) Proportional hazards model business.industry Cancer Nomogram Middle Aged medicine.disease Prognosis Confidence interval Clinical trial Nomograms 030220 oncology & carcinogenesis Cohort Neoplasms Unknown Primary Female business |
| Zdroj: | Clin Cancer Res |
| ISSN: | 1557-3265 |
| Popis: | Purpose: 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 clinicopathologic prognostic factors. Experimental Design: We evaluated 521 patients with CUP at MD Anderson Cancer Center (MDACC; Houston, TX; 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 ± 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, Nashville, TN; N = 302). Results: Baseline characteristics of entire cohort (N = 926) included: median age (63 years), women (51%), Eastern Cooperative Oncology Group performance status (ECOG PS) 0–1 (64%), adenocarcinomas (52%), ≥3 sites of metastases (30%), and 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% confidence interval: 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. Conclusions: 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. |
| Databáze: | OpenAIRE |
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