Cancer Res Treat.  2018 Oct;50(4):1433-1443. 10.4143/crt.2017.223.

The NEAT Predictive Model for Survival in Patients with Advanced Cancer

• Zucker A
• Tsai CJ
• Loscalzo J
• Calves P
• Kao J

• KMID: 2424813
• DOI: http://doi.org/10.4143/crt.2017.223

Abstract

PURPOSE
We previously developed a model to more accurately predict life expectancy for stage IV cancer patients referred to radiation oncology. The goals of this study are to validate this model and to compare competing published models.
MATERIALS AND METHODS
From May 2012 to March 2015, 280 consecutive patientswith stage IV cancerwere prospectively evaluated by a single radiation oncologist. Patients were separated into training, validation and combined sets. TheNEAT model evaluated number of active tumors ("N"), Eastern Cooperative Oncology Group performance status ("E"), albumin ("A") and primary tumor site ("T"). The Odette Cancer Center model validated performance status, bone only metastases and primary tumor site. The Harvard TEACHH model investigated primary tumor type, performance status, age, prior chemotherapy courses, liver metastases, and hospitalization within 3 months. Cox multivariable analyses and logisticalregressionwere utilized to compare model performance.
RESULTS
Number of active tumors, performance status, albumin, primary tumor site, prior hospitalizationwithin the last 3 months, and liver metastases predicted overall survival on uinvariate and multivariable analysis (p < 0.05 for all). The NEAT model separated patients into four prognostic groups with median survivals of 24.9, 14.8, 4.0, and 1.2 months, respectively (p < 0.001). The NEAT model had a C-index of 0.76 with a Nagelkerke's R2 of 0.54 suggesting good discrimination, calibration and total performance compared to competing prognostic models.
CONCLUSION
The NEAT model warrants further investigation as a clinically useful approach to predict survival in patients with stage IV cancer.

Keyword

Life expectancy; Radiation oncology; Prognosis

MeSH Terms

Calibration
Discrimination (Psychology)
Drug Therapy
Hospitalization
Humans
Life Expectancy
Liver
Neoplasm Metastasis
Prognosis
Prospective Studies
Radiation Oncology

Figure

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  Fig. 1. Cumulative survival curve of the combined cohort.

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  Fig. 2. Survival probability based on groups according to the NEAT model (A), Odette Cancer Center model (B), and TEACHH model (C) developed from the training cohort. Survival probability based on groups according to the NEAT model (D), Odette Cancer Center model (E), and TEACHH model (F) developed from the validation cohort. Survival estimated using the Cox’s model (dashed lines) and the actual survival calculated by the Kaplan-Meier method (solid lines) are shown.

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  Fig. 3. Overall survival based on groups according to the NEAT model (A), Odette Cancer Center model (B), and TEACHH model (C) developed from the combined cohort.

Reference

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