| Title |
Prognostic value of the standardized uptake value maximum change calculated by dual-time-point 18F-fluorodeoxyglucose positron emission tomography imaging in patients with advanced non-small-cell lung cancer
|
|---|---|
| Published in |
OncoTargets and therapy, May 2016
|
| DOI | 10.2147/ott.s104919 |
| Pubmed ID | |
| Authors |
Feng Jin, Hui Zhu, Zheng Fu, Li Kong, Jinming Yu |
| Abstract |
The purpose of this study was to investigate the prognostic value of the standardized uptake value maximum (SUVmax) change calculated by dual-time-point (18)F-fluorodeoxyglucose positron emission tomography (PET) imaging in patients with advanced non-small-cell lung cancer (NSCLC). We conducted a retrospective review of 115 patients with advanced NSCLC who underwent pretreatment dual-time-point (18)F-fluorodeoxyglucose PET acquired at 1 and 2 hours after injection. The SUVmax from early images (SUVmax1) and SUVmax from delayed images (SUVmax2) were recorded and used to calculate the SUVmax changes, including the SUVmax increment (ΔSUVmax) and percent change of the SUVmax (%ΔSUVmax). Progression-free survival (PFS) and overall survival (OS) were determined by the Kaplan-Meier method and were compared with the studied PET parameters, and the clinicopathological prognostic factors in univariate analyses and multivariate analyses were constructed using Cox proportional hazards regression. One hundred and fifteen consecutive patients were reviewed, and the median follow-up time was 12.5 months. The estimated median PFS and OS were 3.8 and 9.6 months, respectively. In univariate analysis, SUVmax1, SUVmax2, ΔSUVmax, %ΔSUVmax, clinical stage, and Eastern Cooperative Oncology Group (ECOG) scores were significant prognostic factors for PFS. Similar results were significantly correlated with OS, except %ΔSUVmax. In multivariate analysis, ΔSUVmax and %ΔSUVmax were significant factors for PFS. On the other hand, ECOG scores were only identified as independent predictors of OS. Our results demonstrated the prognostic value of the SUVmax change in predicting the PFS of patients with advanced NSCLC. However, SUVmax change could not predict OS. |
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 9 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Other | 1 | 11% |
| Lecturer | 1 | 11% |
| Professor | 1 | 11% |
| Researcher | 1 | 11% |
| Professor > Associate Professor | 1 | 11% |
| Other | 0 | 0% |
| Unknown | 4 | 44% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 3 | 33% |
| Immunology and Microbiology | 1 | 11% |
| Biochemistry, Genetics and Molecular Biology | 1 | 11% |
| Unknown | 4 | 44% |
Attention Score in Context
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#22,759,802
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Outputs of similar age from OncoTargets and therapy
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