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Multiple Testing, Cut-Point Optimization, and Signs of Publication Bias in Prognostic FDG–PET Imaging Studies of Head and Neck and Lung Cancer: A Review and Meta-Analysis
Positron emission tomography (PET) imaging with 2-deoxy-2-[(18)F]-fluorodeoxyglucose (FDG) was proposed as prognostic marker in radiotherapy. Various uptake metrics and cut points were used, potentially leading to inflated effect estimates. Here, we performed a meta-analysis and systematic review of...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7761090/ https://www.ncbi.nlm.nih.gov/pubmed/33271785 http://dx.doi.org/10.3390/diagnostics10121030 |
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author | Clausen, Malene M. Vogelius, Ivan R. Kjær, Andreas Bentzen, Søren M. |
author_facet | Clausen, Malene M. Vogelius, Ivan R. Kjær, Andreas Bentzen, Søren M. |
author_sort | Clausen, Malene M. |
collection | PubMed |
description | Positron emission tomography (PET) imaging with 2-deoxy-2-[(18)F]-fluorodeoxyglucose (FDG) was proposed as prognostic marker in radiotherapy. Various uptake metrics and cut points were used, potentially leading to inflated effect estimates. Here, we performed a meta-analysis and systematic review of the prognostic value of pretreatment FDG–PET in head and neck squamous cell carcinoma (HNSCC) and non-small cell lung cancer (NSCLC), with tests for publication bias. Hazard ratio (HR) for overall survival (OS), disease free survival (DFS), and local control was extracted or derived from the 57 studies included. Test for publication bias was performed, and the number of statistical tests and cut-point optimizations were registered. Eggers regression related to correlation of SUVmax with OS/DFS yielded p = 0.08/p = 0.02 for HNSCC and p < 0.001/p = 0.014 for NSCLC. No outcomes showed significant correlation with SUVmax, when adjusting for publication bias effect, whereas all four showed a correlation in the conventional meta-analysis. The number of statistical tests and cut points were high with no indication of improvement over time. Our analysis showed significant evidence of publication bias leading to inflated estimates of the prognostic value of SUVmax. We suggest that improved management of these complexities, including predefined statistical analysis plans, are critical for a reliable assessment of FDG–PET. |
format | Online Article Text |
id | pubmed-7761090 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-77610902020-12-26 Multiple Testing, Cut-Point Optimization, and Signs of Publication Bias in Prognostic FDG–PET Imaging Studies of Head and Neck and Lung Cancer: A Review and Meta-Analysis Clausen, Malene M. Vogelius, Ivan R. Kjær, Andreas Bentzen, Søren M. Diagnostics (Basel) Review Positron emission tomography (PET) imaging with 2-deoxy-2-[(18)F]-fluorodeoxyglucose (FDG) was proposed as prognostic marker in radiotherapy. Various uptake metrics and cut points were used, potentially leading to inflated effect estimates. Here, we performed a meta-analysis and systematic review of the prognostic value of pretreatment FDG–PET in head and neck squamous cell carcinoma (HNSCC) and non-small cell lung cancer (NSCLC), with tests for publication bias. Hazard ratio (HR) for overall survival (OS), disease free survival (DFS), and local control was extracted or derived from the 57 studies included. Test for publication bias was performed, and the number of statistical tests and cut-point optimizations were registered. Eggers regression related to correlation of SUVmax with OS/DFS yielded p = 0.08/p = 0.02 for HNSCC and p < 0.001/p = 0.014 for NSCLC. No outcomes showed significant correlation with SUVmax, when adjusting for publication bias effect, whereas all four showed a correlation in the conventional meta-analysis. The number of statistical tests and cut points were high with no indication of improvement over time. Our analysis showed significant evidence of publication bias leading to inflated estimates of the prognostic value of SUVmax. We suggest that improved management of these complexities, including predefined statistical analysis plans, are critical for a reliable assessment of FDG–PET. MDPI 2020-12-01 /pmc/articles/PMC7761090/ /pubmed/33271785 http://dx.doi.org/10.3390/diagnostics10121030 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Clausen, Malene M. Vogelius, Ivan R. Kjær, Andreas Bentzen, Søren M. Multiple Testing, Cut-Point Optimization, and Signs of Publication Bias in Prognostic FDG–PET Imaging Studies of Head and Neck and Lung Cancer: A Review and Meta-Analysis |
title | Multiple Testing, Cut-Point Optimization, and Signs of Publication Bias in Prognostic FDG–PET Imaging Studies of Head and Neck and Lung Cancer: A Review and Meta-Analysis |
title_full | Multiple Testing, Cut-Point Optimization, and Signs of Publication Bias in Prognostic FDG–PET Imaging Studies of Head and Neck and Lung Cancer: A Review and Meta-Analysis |
title_fullStr | Multiple Testing, Cut-Point Optimization, and Signs of Publication Bias in Prognostic FDG–PET Imaging Studies of Head and Neck and Lung Cancer: A Review and Meta-Analysis |
title_full_unstemmed | Multiple Testing, Cut-Point Optimization, and Signs of Publication Bias in Prognostic FDG–PET Imaging Studies of Head and Neck and Lung Cancer: A Review and Meta-Analysis |
title_short | Multiple Testing, Cut-Point Optimization, and Signs of Publication Bias in Prognostic FDG–PET Imaging Studies of Head and Neck and Lung Cancer: A Review and Meta-Analysis |
title_sort | multiple testing, cut-point optimization, and signs of publication bias in prognostic fdg–pet imaging studies of head and neck and lung cancer: a review and meta-analysis |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7761090/ https://www.ncbi.nlm.nih.gov/pubmed/33271785 http://dx.doi.org/10.3390/diagnostics10121030 |
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