Shirin Shafazand1, Michael K Gould. 1. Division of Pulmonary and Critical Care Medicine, University of Miami, Miller School of Medicine, Miami, Florida 33101, USA. sshafazand@med.miami.edu
Abstract
INTRODUCTION: Estimating the clinical probability of mediastinal metastasis in patients with non-small cell lung cancer (NSCLC) can facilitate the selection and interpretation of staging tests. PURPOSE: We sought to identify independent clinical predictors of mediastinal metastasis and to develop a prediction rule to estimate the pretest probability of nodal metastasis in patients with NSCLC. METHODS: We used data from a randomized controlled trial of selective versus routine mediastinoscopy to develop a clinical prediction model. RESULTS:Five hundred sixty-six patients were included, with a mean age of 65 +/- 9 years; 31% had positive lymph nodes. Independent predictors of positive nodes included adenocarcinoma or large cell histology (OR 2.6, 95% confidence interval [CI] = 1.8-3.9), apparent metastatic disease on chest radiography (OR 2.4, 95% CI = 1.2-4.7), central location of the primary tumor (OR 2.1, 95% CI = 1.4-3.3), symptoms from the primary tumor (OR 1.6, 95% CI = 1.1-2.4), tumor diameter > or =3.6 cm (OR 1.5, 95% CI = 1.0-2.3), and age less than 65 years (OR 1.5, 95% CI = 1.0-2.2). Model accuracy and calibration were good, with an area under the receiver operating characteristic curve of 0.70 (95% CI = 0.66-0.75) and good agreement between observed and predicted probabilities of mediastinal metastasis. CONCLUSIONS: Our prediction rule can be used to estimate the pretest probability of mediastinal metastasis in patients with NSCLC. Such estimates can facilitate clinical decision making when selecting and interpreting the results of noninvasive and invasive staging tests.
RCT Entities:
INTRODUCTION: Estimating the clinical probability of mediastinal metastasis in patients with non-small cell lung cancer (NSCLC) can facilitate the selection and interpretation of staging tests. PURPOSE: We sought to identify independent clinical predictors of mediastinal metastasis and to develop a prediction rule to estimate the pretest probability of nodal metastasis in patients with NSCLC. METHODS: We used data from a randomized controlled trial of selective versus routine mediastinoscopy to develop a clinical prediction model. RESULTS: Five hundred sixty-six patients were included, with a mean age of 65 +/- 9 years; 31% had positive lymph nodes. Independent predictors of positive nodes included adenocarcinoma or large cell histology (OR 2.6, 95% confidence interval [CI] = 1.8-3.9), apparent metastatic disease on chest radiography (OR 2.4, 95% CI = 1.2-4.7), central location of the primary tumor (OR 2.1, 95% CI = 1.4-3.3), symptoms from the primary tumor (OR 1.6, 95% CI = 1.1-2.4), tumor diameter > or =3.6 cm (OR 1.5, 95% CI = 1.0-2.3), and age less than 65 years (OR 1.5, 95% CI = 1.0-2.2). Model accuracy and calibration were good, with an area under the receiver operating characteristic curve of 0.70 (95% CI = 0.66-0.75) and good agreement between observed and predicted probabilities of mediastinal metastasis. CONCLUSIONS: Our prediction rule can be used to estimate the pretest probability of mediastinal metastasis in patients with NSCLC. Such estimates can facilitate clinical decision making when selecting and interpreting the results of noninvasive and invasive staging tests.
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