Elsevier

Clinical Lung Cancer

Volume 13, Issue 1, January 2012, Pages 52-58
Clinical Lung Cancer

Original study
Metabolic Tumor Volume is an Independent Prognostic Factor in Patients Treated Definitively for Non–Small-Cell Lung Cancer

Presented at: The 12th World Conference on Lung Cancer, Seoul, Korea, September 2-6, 2007; and the 50th Annual Meeting of the American Society for Therapeutic Radiology and Oncology, Boston, MA, September 22-25, 2008
https://doi.org/10.1016/j.cllc.2011.05.001Get rights and content

Abstract

Purpose

Fluorine-18 flurodeoxyglucose positron emission tomography (FDG-PET) imaging has rapidly become the standard of care for staging patients with lung cancer. We evaluated the prognostic value of metabolic tumor volume (MTV), a measure of tumor burden on FDG-PET imaging, in patients with non–small-cell lung cancer (NSCLC) treated definitively.

Methods and Materials

A retrospective review identified 61 patients with NSCLC who underwent FDG-PET imaging for pretreatment staging. Metabolically active tumor regions were segmented on the PET scans semiautomatically to calculate the total body MTV. We determined the relationship of overall survival (OS) and progression-free survival (PFS) with MTV in the entire cohort, and in the subgroup treated definitively.

Results

The estimated median PFS and OS for the entire cohort were 11.1 months and 18.9 months. Higher MTV was significantly associated with worse OS (P = 0.00075) and PFS (P = 0.00077). For definitively treated patients, when MTV was analyzed as a binary value above or below the median value, 2-year PFS was 60% versus 39.7% (median PFS 34.9 vs. 11.9 months) and 2-year OS was 79.7% versus 33.3% (median OS 41.9 vs. 18.9 months), respectively (log-rank P = 0.12 for PFS and P = 0.066 for OS). When MTV was analyzed as a continuous variable, multivariate Cox proportional hazards analysis demonstrated a trend to worse PFS (hazard ratio [HR] = 1.31; P = 0.12) and significantly worse OS (HR = 1.53; P = 0.018) with increasing MTV after controlling for known prognostic variables.

Conclusion

Tumor burden as assessed by MTV yields prognostic information on survival beyond that of established prognostic factors in patients with NSCLC treated definitively.

Introduction

Lung cancer is the leading cause of cancer death in both men and women in the United States1 and worldwide.2 While numerous prognostic factors have been identified including age, Karnofsky Performance Status (KPS), and weight loss,3 stage at presentation remains the most useful prognostic factor.4 As fluorine-18 fluorodeoxyglucose positron emission tomography (FDG-PET) imaging has become part of the standard of care for staging patients with lung cancer, metabolic imaging parameters have been studied as potential prognostic factors. Studies have found that tumor metabolic activity, as estimated by the standardized uptake value (SUV), is a prognostic factor in patients with non–small-cell lung cancer (NSCLC),5 but it has not been universally found independently prognostic compared to other factors such as stage and tumor size.6 A possible reason for this discrepancy is that SUV does not fully represent a patient's metabolic tumor burden. Recently, we showed that metabolic tumor volume (MTV), or the volume of tumor tissue demonstrating increased FDG uptake on PET, is a novel and independent adverse prognostic factor in a small, heterogeneous cohort of patients with lung cancer, including those with localized as well as metastatic disease.7

Nevertheless, the role of PET-MTV as a prognostic factor in patients with lung cancer remains to be clarified. For example, it is unknown to what degree MTV is prognostic in a more specific subpopulation of patients such as those with localized lung cancer who are treated with a curative or definitive intent. The objective of this study was to investigate the value of MTV as an independent prognostic factor in lung cancer for overall survival (OS) and progression-free survival (PFS) in a larger cohort of patients with lung cancer, as well as in the subset of patients treated with definitive intent.

Section snippets

Patient Selection

We conducted a retrospective review of the medical records of patients who underwent combined PET and computerized tomography (FDG-PET-CT) imaging at Stanford Hospital and Clinics. We conducted this study under the review and approval of the Stanford institutional review board. Between January 2003 and June 2005, 325 patients with NSCLC and small-cell lung cancer (SCLC) were evaluated with diagnostic PET-CT scans. Of the 325 patients, 66 had an initial staging scan before the initiation of

Patient Characteristics

Medical records of these 61 patients were reviewed for patient age, sex, tumor histology, date of initial PET-CT scan, American Joint Committee on Cancer (AJCC) stage (TNM), treatment type, treatment intent, date of treatment, radiation dose and target volume, date of local recurrence, date of distant progression, date of last follow-up, KPS, and weight loss. These characteristics are summarized in Table 1.

Among the 61 patients in this study, 39 were treated with definitive intent, while 22

Discussion

We based this study on the hypothesis that MTV is an independent prognostic factor for overall outcome in lung cancer after controlling for established variables such as clinical stage. Stage stratifies patients into only four categories of disease extent, within each of which there is a wide range of volumetric tumor burden and presumably prognosis.11 This was true in our cohort as well (Figure 3). CT-based gross tumor volume (GTV), as segmented manually for 3-dimensional conformal radiation

Disclosure

Conflict of interest: Percy Lee has received speaking honorarium from BrainLAB Medical Systems. Billy W. Loo, Jr, has received speaking honoraria from Varian Medical Systems, Accuray, and General Electric Medical Systems. None of the other authors have financial or personal conflicts of interest to disclose. The authors had full access to all of the data in the study and take complete responsibility for the integrity of the data and the accuracy of the data analysis.

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Percy Lee and Jose G. Bazan contributed equally to this work

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