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Prognostic Factors for Survival in Multiple Primary Lung Adenocarcinomas: A Retrospective Analysis of 283 Patients
Purpose: In recent years, a rising number of multiple primary lung cancers have been detected with the advancement of imaging technology. No detailed study has assessed the prognosis of multiple primary lung adenocarcinomas based on computed tomography characteristics. The present study aimed to ana...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10327415/ https://www.ncbi.nlm.nih.gov/pubmed/37365877 http://dx.doi.org/10.1177/15330338231185278 |
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author | Zheng, Yuting Han, Xiaoyu Wu, Ying Jia, Xi Zhang, Kailu Fan, Jun Shi, Heshui |
author_facet | Zheng, Yuting Han, Xiaoyu Wu, Ying Jia, Xi Zhang, Kailu Fan, Jun Shi, Heshui |
author_sort | Zheng, Yuting |
collection | PubMed |
description | Purpose: In recent years, a rising number of multiple primary lung cancers have been detected with the advancement of imaging technology. No detailed study has assessed the prognosis of multiple primary lung adenocarcinomas based on computed tomography characteristics. The present study aimed to analyze outcomes and determine valuable factors for predicting the prognosis of multiple primary lung adenocarcinoma. Methods: This single-center retrospective study was performed from January 2013 to October 2021. All patients were divided into 3 groups based on tumor density as follows: multi-pure ground-glass nodules, at least one part-solid nodule without solid nodules, and at least one solid nodule. Clinicopathologic features, computed tomography signs, and survival outcomes were compared between these groups. The Kaplan-Meier method was used for survival analysis. The multivariable Cox proportional hazards regression model was used to identify independent predictors for recurrence-free survival and overall survival. Results: The sample included 283 patients with 623 lesions who met the inclusion criteria for multiple primary lung adenocarcinoma. Of these patients, 71 (25.1%) presented with multi-pure ground-glass nodules, 100 (35.3%) with at least one part-solid nodule without solid nodule, and 112 (39.6%) with at least one solid nodule. The 3 groups had distinguished clinicopathologic and radiological features of age, adjuvant therapy, types of tumor resection, TNM stage, pathological subtypes, pleural indentation, spicule, and vacuole (all P < .001). Multivariate analysis found that lesion number was an independent predictor for both recurrence-free survival (hazard ratio 2.41; 95% confidence interval 1.12-5.19; P = .025) and overall survival (hazard ratio 4.78; 95% confidence interval 1.88-12.18; P = .001), and the at least one solid nodule was an independent predictor for overall survival (hazard ratio 5.307; 95% confidence interval 1.16-24.31; P = .032). Stage III (hazard ratio 5.71; 95% confidence interval 1.94-16.81; P = .002) and adjuvant therapy (hazard ratio 2.52; 95% confidence interval 1.24-5.13; P = .011) influenced the recurrence-free survival. Conclusions: Survival of multiple primary lung adenocarcinoma patients is strongly correlated with the lesion number and the at least one solid nodule tumors in radiological. This information may be useful for predicting survival and making clinical decisions in future studies. |
format | Online Article Text |
id | pubmed-10327415 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-103274152023-07-08 Prognostic Factors for Survival in Multiple Primary Lung Adenocarcinomas: A Retrospective Analysis of 283 Patients Zheng, Yuting Han, Xiaoyu Wu, Ying Jia, Xi Zhang, Kailu Fan, Jun Shi, Heshui Technol Cancer Res Treat Original Article Purpose: In recent years, a rising number of multiple primary lung cancers have been detected with the advancement of imaging technology. No detailed study has assessed the prognosis of multiple primary lung adenocarcinomas based on computed tomography characteristics. The present study aimed to analyze outcomes and determine valuable factors for predicting the prognosis of multiple primary lung adenocarcinoma. Methods: This single-center retrospective study was performed from January 2013 to October 2021. All patients were divided into 3 groups based on tumor density as follows: multi-pure ground-glass nodules, at least one part-solid nodule without solid nodules, and at least one solid nodule. Clinicopathologic features, computed tomography signs, and survival outcomes were compared between these groups. The Kaplan-Meier method was used for survival analysis. The multivariable Cox proportional hazards regression model was used to identify independent predictors for recurrence-free survival and overall survival. Results: The sample included 283 patients with 623 lesions who met the inclusion criteria for multiple primary lung adenocarcinoma. Of these patients, 71 (25.1%) presented with multi-pure ground-glass nodules, 100 (35.3%) with at least one part-solid nodule without solid nodule, and 112 (39.6%) with at least one solid nodule. The 3 groups had distinguished clinicopathologic and radiological features of age, adjuvant therapy, types of tumor resection, TNM stage, pathological subtypes, pleural indentation, spicule, and vacuole (all P < .001). Multivariate analysis found that lesion number was an independent predictor for both recurrence-free survival (hazard ratio 2.41; 95% confidence interval 1.12-5.19; P = .025) and overall survival (hazard ratio 4.78; 95% confidence interval 1.88-12.18; P = .001), and the at least one solid nodule was an independent predictor for overall survival (hazard ratio 5.307; 95% confidence interval 1.16-24.31; P = .032). Stage III (hazard ratio 5.71; 95% confidence interval 1.94-16.81; P = .002) and adjuvant therapy (hazard ratio 2.52; 95% confidence interval 1.24-5.13; P = .011) influenced the recurrence-free survival. Conclusions: Survival of multiple primary lung adenocarcinoma patients is strongly correlated with the lesion number and the at least one solid nodule tumors in radiological. This information may be useful for predicting survival and making clinical decisions in future studies. SAGE Publications 2023-06-26 /pmc/articles/PMC10327415/ /pubmed/37365877 http://dx.doi.org/10.1177/15330338231185278 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Original Article Zheng, Yuting Han, Xiaoyu Wu, Ying Jia, Xi Zhang, Kailu Fan, Jun Shi, Heshui Prognostic Factors for Survival in Multiple Primary Lung Adenocarcinomas: A Retrospective Analysis of 283 Patients |
title | Prognostic Factors for Survival in Multiple Primary Lung Adenocarcinomas: A Retrospective Analysis of 283 Patients |
title_full | Prognostic Factors for Survival in Multiple Primary Lung Adenocarcinomas: A Retrospective Analysis of 283 Patients |
title_fullStr | Prognostic Factors for Survival in Multiple Primary Lung Adenocarcinomas: A Retrospective Analysis of 283 Patients |
title_full_unstemmed | Prognostic Factors for Survival in Multiple Primary Lung Adenocarcinomas: A Retrospective Analysis of 283 Patients |
title_short | Prognostic Factors for Survival in Multiple Primary Lung Adenocarcinomas: A Retrospective Analysis of 283 Patients |
title_sort | prognostic factors for survival in multiple primary lung adenocarcinomas: a retrospective analysis of 283 patients |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10327415/ https://www.ncbi.nlm.nih.gov/pubmed/37365877 http://dx.doi.org/10.1177/15330338231185278 |
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