Dataset Information

Lung cancer prognostic index: a risk score to predict overall survival after the diagnosis of non-small-cell lung cancer.

ABSTRACT:

Introduction

Non-small-cell lung cancer outcomes are poor but heterogeneous, even within stage groups. To improve prognostic precision we aimed to develop and validate a simple prognostic model using patient and disease variables.

Methods

Prospective registry and study data were analysed using Cox proportional hazards regression to derive a prognostic model (hospital 1, n=695), which was subsequently tested (Harrell's c-statistic for discrimination and Cox-Snell residuals for calibration) in two independent validation cohorts (hospital 2, n=479 and hospital 3, n=284).

Results

The derived Lung Cancer Prognostic Index (LCPI) included stage, histology, mutation status, performance status, weight loss, smoking history, respiratory comorbidity, sex, and age. Two-year overall survival rates according to LCPI in the derivation and two validation cohorts, respectively, were 84, 77, and 68% (LCPI 1: score?9); 61, 61, and 42% (LCPI 2: score 10-13); 33, 32, and 14% (LCPI 3: score 14-16); 7, 16, and 5% (LCPI 4: score ?15). Discrimination (c-statistic) was 0.74 for the derivation cohort, 0.72 and 0.71 for the two validation cohorts.

Conclusions

The LCPI contributes additional prognostic information, which may be used to counsel patients, guide trial eligibility or design, or standardise mortality risk for epidemiological analyses.

SUBMITTER: Alexander M

PROVIDER: S-EPMC5572183 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

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Publications

Lung cancer prognostic index: a risk score to predict overall survival after the diagnosis of non-small-cell lung cancer.

Alexander Marliese M Wolfe Rory R Ball David D Conron Matthew M Stirling Robert G RG Solomon Benjamin B MacManus Michael M Officer Ann A Karnam Sameer S Burbury Kate K Evans Sue M SM

British journal of cancer 20170720 5

<h4>Introduction</h4>Non-small-cell lung cancer outcomes are poor but heterogeneous, even within stage groups. To improve prognostic precision we aimed to develop and validate a simple prognostic model using patient and disease variables.<h4>Methods</h4>Prospective registry and study data were analysed using Cox proportional hazards regression to derive a prognostic model (hospital 1, n=695), which was subsequently tested (Harrell's c-statistic for discrimination and Cox-Snell residuals for cali ...[more]

PMID: 28728168

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Dataset Information

Lung cancer prognostic index: a risk score to predict overall survival after the diagnosis of non-small-cell lung cancer.

Introduction

Methods

Results

Conclusions

Publications

Lung cancer prognostic index: a risk score to predict overall survival after the diagnosis of non-small-cell lung cancer.

Similar Datasets

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