TY - JOUR
T1 - Development and validation of a novel nomogram for individualized prediction of survival in cancer of unknown primary
AU - Raghav, A. C.Kanwal
AU - Hwang, Hyunsoo
AU - Jacome, Alexandre A.
AU - Bhang, Eric
AU - Willett, Anneleis
AU - Huey, Ryan W.
AU - Dhillon, Nishat P.
AU - Modha, Jignesh
AU - Smaglo, Brandon
AU - Matamoros, Aurelio
AU - Estrella, Jeannelyn S.
AU - Jao, Justin
AU - Overman, Michael J.
AU - Wang, Xuemei
AU - Greco, F. Anthony
AU - Loree, Jonathan M.
AU - Varadhachary, Gauri R.
N1 - Funding Information:
We thank our patients for entrusting us with their care and for giving us the opportunity to learn and understand their cancer and hopefully help others who may suffer from this orphan disease in the future. This work was supported in part by Painter Research Funds (to G.R. Varadhachary) and Cancer Center Support Grant (CCSG) - PA30 CA016672 (to K. Raghav and G.R. Varadhachary).
Publisher Copyright:
© 2021 American Association for Cancer Research.
PY - 2021/6
Y1 - 2021/6
N2 - 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 MDAnderson 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.
AB - 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 MDAnderson 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.
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U2 - 10.1158/1078-0432.CCR-20-4117
DO - 10.1158/1078-0432.CCR-20-4117
M3 - Article
C2 - 33858857
AN - SCOPUS:85107963734
SN - 1078-0432
VL - 27
SP - 3414
EP - 3421
JO - Clinical Cancer Research
JF - Clinical Cancer Research
IS - 12
ER -