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Estimating the Survival of Patients With Lung Cancer: What Is the Best Statistical Model?
OBJECTIVES: Investigating the survival of patients with cancer is vitally necessary for controlling the disease and for assessing treatment methods. This study aimed to compare various statistical models of survival and to determine the survival rate and its related factors among patients suffering...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Korean Society for Preventive Medicine
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6459760/ https://www.ncbi.nlm.nih.gov/pubmed/30971081 http://dx.doi.org/10.3961/jpmph.17.090 |
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author | Abedi, Siavosh Janbabaei, Ghasem Afshari, Mahdi Moosazadeh, Mahmood Rashidi Alashti, Masoumeh Hedayatizadeh-Omran, Akbar Alizadeh-Navaei, Reza Abedini, Ehsan |
author_facet | Abedi, Siavosh Janbabaei, Ghasem Afshari, Mahdi Moosazadeh, Mahmood Rashidi Alashti, Masoumeh Hedayatizadeh-Omran, Akbar Alizadeh-Navaei, Reza Abedini, Ehsan |
author_sort | Abedi, Siavosh |
collection | PubMed |
description | OBJECTIVES: Investigating the survival of patients with cancer is vitally necessary for controlling the disease and for assessing treatment methods. This study aimed to compare various statistical models of survival and to determine the survival rate and its related factors among patients suffering from lung cancer. METHODS: In this retrospective cohort, the cumulative survival rate, median survival time, and factors associated with the survival of lung cancer patients were estimated using Cox, Weibull, exponential, and Gompertz regression models. Kaplan-Meier tables and the log-rank test were also used to analyze the survival of patients in different subgroups. RESULTS: Of 102 patients with lung cancer, 74.5% were male. During the follow-up period, 80.4% died. The incidence rate of death among patients was estimated as 3.9 (95% confidence [CI], 3.1 to 4.8) per 100 person-months. The 5-year survival rate for all patients, males, females, patients with non-small cell lung carcinoma (NSCLC), and patients with small cell lung carcinoma (SCLC) was 17%, 13%, 29%, 21%, and 0%, respectively. The median survival time for all patients, males, females, those with NSCLC, and those with SCLC was 12.7 months, 12.0 months, 16.0 months, 16.0 months, and 6.0 months, respectively. Multivariate analyses indicated that the hazard ratios (95% CIs) for male sex, age, and SCLC were 0.56 (0.33 to 0.93), 1.03 (1.01 to 1.05), and 2.91 (1.71 to 4.95), respectively. CONCLUSIONS: Our results showed that the exponential model was the most precise. This model identified age, sex, and type of cancer as factors that predicted survival in patients with lung cancer. |
format | Online Article Text |
id | pubmed-6459760 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Korean Society for Preventive Medicine |
record_format | MEDLINE/PubMed |
spelling | pubmed-64597602019-04-16 Estimating the Survival of Patients With Lung Cancer: What Is the Best Statistical Model? Abedi, Siavosh Janbabaei, Ghasem Afshari, Mahdi Moosazadeh, Mahmood Rashidi Alashti, Masoumeh Hedayatizadeh-Omran, Akbar Alizadeh-Navaei, Reza Abedini, Ehsan J Prev Med Public Health Brief Report OBJECTIVES: Investigating the survival of patients with cancer is vitally necessary for controlling the disease and for assessing treatment methods. This study aimed to compare various statistical models of survival and to determine the survival rate and its related factors among patients suffering from lung cancer. METHODS: In this retrospective cohort, the cumulative survival rate, median survival time, and factors associated with the survival of lung cancer patients were estimated using Cox, Weibull, exponential, and Gompertz regression models. Kaplan-Meier tables and the log-rank test were also used to analyze the survival of patients in different subgroups. RESULTS: Of 102 patients with lung cancer, 74.5% were male. During the follow-up period, 80.4% died. The incidence rate of death among patients was estimated as 3.9 (95% confidence [CI], 3.1 to 4.8) per 100 person-months. The 5-year survival rate for all patients, males, females, patients with non-small cell lung carcinoma (NSCLC), and patients with small cell lung carcinoma (SCLC) was 17%, 13%, 29%, 21%, and 0%, respectively. The median survival time for all patients, males, females, those with NSCLC, and those with SCLC was 12.7 months, 12.0 months, 16.0 months, 16.0 months, and 6.0 months, respectively. Multivariate analyses indicated that the hazard ratios (95% CIs) for male sex, age, and SCLC were 0.56 (0.33 to 0.93), 1.03 (1.01 to 1.05), and 2.91 (1.71 to 4.95), respectively. CONCLUSIONS: Our results showed that the exponential model was the most precise. This model identified age, sex, and type of cancer as factors that predicted survival in patients with lung cancer. Korean Society for Preventive Medicine 2019-03 2019-02-18 /pmc/articles/PMC6459760/ /pubmed/30971081 http://dx.doi.org/10.3961/jpmph.17.090 Text en Copyright © 2019 The Korean Society for Preventive Medicine This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Brief Report Abedi, Siavosh Janbabaei, Ghasem Afshari, Mahdi Moosazadeh, Mahmood Rashidi Alashti, Masoumeh Hedayatizadeh-Omran, Akbar Alizadeh-Navaei, Reza Abedini, Ehsan Estimating the Survival of Patients With Lung Cancer: What Is the Best Statistical Model? |
title | Estimating the Survival of Patients With Lung Cancer: What Is the Best Statistical Model? |
title_full | Estimating the Survival of Patients With Lung Cancer: What Is the Best Statistical Model? |
title_fullStr | Estimating the Survival of Patients With Lung Cancer: What Is the Best Statistical Model? |
title_full_unstemmed | Estimating the Survival of Patients With Lung Cancer: What Is the Best Statistical Model? |
title_short | Estimating the Survival of Patients With Lung Cancer: What Is the Best Statistical Model? |
title_sort | estimating the survival of patients with lung cancer: what is the best statistical model? |
topic | Brief Report |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6459760/ https://www.ncbi.nlm.nih.gov/pubmed/30971081 http://dx.doi.org/10.3961/jpmph.17.090 |
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