Dataset Information

Development and Validation of Nomograms Predictive of Overall and Progression-Free Survival in Patients With Oropharyngeal Cancer.

ABSTRACT: Purpose Treatment of oropharyngeal squamous cell carcinoma (OPSCC) is evolving toward risk-based modification of therapeutic intensity, which requires patient-specific estimates of overall survival (OS) and progression-free survival (PFS). Methods To develop and validate nomograms for OS and PFS, we used a derivation cohort of 493 patients with OPSCC with known p16 tumor status (surrogate of human papillomavirus) and cigarette smoking history (pack-years) randomly assigned to clinical trials using platinum-based chemoradiotherapy (NRG Oncology Radiation Therapy Oncology Group [RTOG] 0129 and 0522). Nomograms were created from Cox models and internally validated by use of bootstrap and cross-validation. Model discrimination was measured by calibration plots and the concordance index. Nomograms were externally validated in a cohort of 153 patients with OPSCC randomly assigned to a third trial, NRG Oncology RTOG 9003. Results Both models included age, Zubrod performance status, pack-years, education, p16 status, and T and N stage; the OS model also included anemia and age × pack-years interaction; and the PFS model also included marital status, weight loss, and p16 × Zubrod interaction. Predictions correlated well with observed 2-year and 5-year outcomes. The uncorrected concordance index was 0.76 (95% CI, 0.72 to 0.80) for OS and 0.70 (95% CI, 0.66 to 0.74) for PFS, and bias-corrected indices were similar. In the validation set, OS and PFS models were well calibrated, and OS and PFS were significantly different across tertiles of nomogram scores (log-rank P = .003;< .001). Conclusion The validated nomograms provided useful prediction of OS and PFS for patients with OPSCC treated with primary radiation-based therapy.

SUBMITTER: Fakhry C

PROVIDER: S-EPMC5736236 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Development and Validation of Nomograms Predictive of Overall and Progression-Free Survival in Patients With Oropharyngeal Cancer.

Fakhry Carole C Zhang Qiang Q Nguyen-Tân Phuc Felix PF Rosenthal David I DI Weber Randal S RS Lambert Louise L Trotti Andy M AM Barrett William L WL Thorstad Wade L WL Jones Christopher U CU Yom Sue S SS Wong Stuart J SJ Ridge John A JA Rao Shyam S D SSD Bonner James A JA Vigneault Eric E Raben David D Kudrimoti Mahesh R MR Harris Jonathan J Le Quynh-Thu QT Gillison Maura L ML

Journal of clinical oncology : official journal of the American Society of Clinical Oncology 20170804 36

Purpose Treatment of oropharyngeal squamous cell carcinoma (OPSCC) is evolving toward risk-based modification of therapeutic intensity, which requires patient-specific estimates of overall survival (OS) and progression-free survival (PFS). Methods To develop and validate nomograms for OS and PFS, we used a derivation cohort of 493 patients with OPSCC with known p16 tumor status (surrogate of human papillomavirus) and cigarette smoking history (pack-years) randomly assigned to clinical trials usi ...[more]

PMID: 28777690

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Project description:ObjectivesThis study aims to establish nomograms to accurately predict the overall survival (OS) and progression-free survival (PFS) in patients with non-small cell lung cancer (NSCLC) who received chemotherapy alone as the first-line treatment.Materials and methodsIn a training cohort of 121 NSCLC patients, radiomic features were extracted, selected from intra- and peri-tumoral regions, and used to build signatures (S1 and S2) using a Cox regression model. Deep learning features were obtained from three convolutional neural networks and utilized to build signatures (S3, S4, and S5) that were stratified into over- and under-expression subgroups for survival risk using X-tile. After univariate and multivariate Cox regression analyses, a nomogram incorporating the tumor, node, and metastasis (TNM) stages, radiomic signature, and deep learning signature was established to predict OS and PFS, respectively. The performance was validated using an independent cohort (61 patients).ResultsTNM stages, S2 and S3 were identified as the significant prognosis factors for both OS and PFS; S2 (OS: (HR (95%), 2.26 (1.40-3.67); PFS: (HR (95%), 2.23 (1.36-3.65)) demonstrated the best ability in discriminating patients with over- and under-expression. For the OS nomogram, the C-index (95% CI) was 0.74 (0.70-0.79) and 0.72 (0.67-0.78) in the training and validation cohorts, respectively; for the PFS nomogram, the C-index (95% CI) was 0.71 (0.68-0.81) and 0.72 (0.66-0.79). The calibration curves for the 3- and 5-year OS and PFS were in acceptable agreement between the predicted and observed survival. The established nomogram presented a higher overall net benefit than the TNM stage for predicting both OS and PFS.ConclusionBy integrating the TNM stage, CT radiomic signature, and deep learning signatures, the established nomograms can predict the individual prognosis of NSCLC patients who received chemotherapy. The integrated nomogram has the potential to improve the individualized treatment and precise management of NSCLC patients.

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Dataset Information

Development and Validation of Nomograms Predictive of Overall and Progression-Free Survival in Patients With Oropharyngeal Cancer.

Publications

Development and Validation of Nomograms Predictive of Overall and Progression-Free Survival in Patients With Oropharyngeal Cancer.

Similar Datasets

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