Investigation of the affective factors on the survival rate of patients with laryngeal cancer using Cox proportional hazards and Lin -Ying’s additive hazards models

Zarei, Masoud; Mirzaee, Moghaddameh; Alizadeh, Hosniyeh; Jahani, Yunes

doi:10.47176/mjiri.35.16

Cited by 2 publications

(5 citation statements)

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“…The mean survival time for patients diagnosed with prostate cancer was 53.76 months, and the patients' 5-year survival rate was found to be 49.30%. In Iran, the patients' 5-year survival rate was 54.6%, which is almost coherent with the results of this study (2). It is while in the studies conducted outside of Iran, the 5-year survival rates were higher, 5-year survival rate was calculated in Italy, the US, and the UK as being 93.6%, 71%, and 56%, respectively (11,19,20).…”

Section: Discussionsupporting

confidence: 89%

“…old. In Iran, the mean age at diagnosis was 71.85 (2). Two studies conducted in the United States (US) reveal that the mean age at diagnosis was 66.19 and 66 yrs (15).…”

Section: Discussionmentioning

confidence: 99%

“…Cancer is a critical threat to individuals' health, which it bears an increasing and constant progression. It is the third global reason for death (1,2). About 18.1 million new cases and 9.6 million deaths were estimated worldwide in 2018 (3).…”

Section: Introductionmentioning

confidence: 99%

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The Evaluation of Survival Rate in Patients with Prostate Cancer by Bayesian Weibull Parametric Accelerated Failure-Time Model

Tajabadi¹,

Pakmanesh²,

Mirzaee³

et al. 2022

ijph

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Background: Prostate cancer is the most prevalent malignancy in men. This study was carried out to determine effective factors on the survival rate of patients diagnosed with prostate cancer in Kerman, Iran. Methods: The present study was conducted as a retrospective cohort of 238 patients diagnosed with prostate cancer from 2011 to 2019 in Kerman, Iran. First, the demographic and clinical information of patients were collected. Then, the information on patient survival up to June 2019 was tracked, and their latest statuses of death or survival were recorded. Kaplan-Meier method, log-rank test, and Bayesian Weibull parametric accelerated failure- time model were used for data analysis. Data analysis was carried out by Stata and SAS. Results: The mean age of patients in the diagnosis was 73.28±10.08 year. The patient’s 1, 2, 3 and 5-years of overall survival rates were equal to 78.54%, 65.97%, 56.64% and 49.30, respectively. Patients under surgical therapy relatively held longer survival times compared to the rest of the therapies. Patients under chemotherapy had shorter survival times. Age at diagnosis, occupation, chemotherapy, surgery, education, and smoking variables significantly affected patients’ survival (P<0.05). Conclusion: Patients' survival duration increases if the disease is diagnosed at younger ages and its preliminary development stages. Smoking cessation is strongly recommended after diagnosis, as it is associated with a lower survival rate. Patients who underwent radical prostatectomy surgery showed higher survival rates than radiotherapy, hormone ablation, or chemotherapy. Moreover, patients with higher education had more prolonged survival.

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Section: Discussionsupporting

confidence: 89%

“…old. In Iran, the mean age at diagnosis was 71.85 (2). Two studies conducted in the United States (US) reveal that the mean age at diagnosis was 66.19 and 66 yrs (15).…”

Section: Discussionmentioning

confidence: 99%

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The Evaluation of Survival Rate in Patients with Prostate Cancer by Bayesian Weibull Parametric Accelerated Failure-Time Model

Tajabadi¹,

Pakmanesh²,

Mirzaee³

et al. 2022

ijph

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“…The prognostic factors of laryngeal cancer include some demographic characteristics (i.e., age, race, sex, and marital status), disease characteristics (i.e., tumor size, histologic grade, the American Joint Committee on Cancer [AJCC] stage, and primary site), and treatment strategies (i.e., surgery, radiotherapy, and chemotherapy) 15,16 . However, as only a few cases of laryngeal cancer with synchronous or metachronous lung cancer (LCSMLC) have been reported, the exact prognostic factors for this condition have not been thoroughly defined 10,17,18 …”

Section: Introductionmentioning

confidence: 99%

“…[8][9][10][11][12][13][14] The prognostic factors of laryngeal cancer include some demographic characteristics (i.e., age, race, sex, and marital status), disease characteristics (i.e., tumor size, histologic grade, the American Joint Committee on Cancer [AJCC] stage, and primary site), and treatment strategies (i.e., surgery, radiotherapy, and chemotherapy). 15,16 However, as only a few cases of laryngeal cancer with synchronous or metachronous lung cancer (LCSMLC) have been reported, the exact prognostic factors for this condition have not been thoroughly defined. 10,17,18 In the present study, we aimed to examine the independent prognostic factors of LCSMLC by employing the data from the Surveillance, Epidemiology, and End Results Program (SEER) database, which provides information on cancer statistics in the United States (https://seer.cancer.gov/).…”

mentioning

confidence: 99%

Development and validation of a prognostic nomogram for patients with laryngeal cancer with synchronous or metachronous lung cancer

Su,

Li,

Hou

et al. 2023

Head & Neck

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BackgroundThe objective of this study was to examine the independent prognostic factors of laryngeal cancer with synchronous or metachronous lung cancer (LCSMLC), and to generate and verify a clinical prediction model.MethodsIn this study, laryngeal cancer alone and LCSMLC were defined using the Surveillance, Epidemiology, and End Results (SEER) database. Risk factors of patients with LCSMLC were analyzed through univariate and multivariate logistic regression analysis. Independent prognostic factors were selected by Cox regression analyses, on the basis of which a nomogram was constructed using R code. Kaplan–Meier survival analyses were applied to test the application of a risk stratification system. Finally, we conducted a comparison of the American Joint Committee on Cancer (AJCC) staging system of laryngeal cancer with the new model of nomogram and risk stratification. For further validation of the nomogram, data from patients at two Chinese independent institutions were also analyzed.ResultsAccording to the eligibility criteria, 32 429 patients with laryngeal cancer alone and 641 patients with LCSMLC from the SEER database (the training cohort) and additional 61 patients from two Chinese independent institutions (the external validation cohort) were included for final analyses. Compared with patients with laryngeal cancer who did not have synchronous or metachronous lung cancer, age, sex, race, primary site of laryngeal cancer, grade, and stage were risk factors for LCSMLC, while marriage, surgery, radiation therapy, and chemotherapy are not their risk factors. Age, two cancers' interval, pathological type, stage, surgery, radiation, primary lung site, and primary throat site were independent prognostic predictors of LCSMLC. The risk stratification system of high‐, medium‐, and low‐risk groups significantly distinguished the prognosis in different patients with LCSMLC, regardless of the training cohort or the validation cohort. Compared with the 6th AJCC TNM stage of laryngeal cancer, the new model of nomogram and risk stratification showed an improved net benefit.ConclusionsAge, sex, race, primary site of laryngeal cancer, grade, and stage were risk factors for LCSMLC. An individualized clinical prognostic predictive model by nomogram was generated and validated, which showed superior prediction ability for LCSMLC.

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Investigation of the affective factors on the survival rate of patients with laryngeal cancer using Cox proportional hazards and Lin -Ying’s additive hazards models

Cited by 2 publications

References 25 publications

The Evaluation of Survival Rate in Patients with Prostate Cancer by Bayesian Weibull Parametric Accelerated Failure-Time Model

The Evaluation of Survival Rate in Patients with Prostate Cancer by Bayesian Weibull Parametric Accelerated Failure-Time Model

Development and validation of a prognostic nomogram for patients with laryngeal cancer with synchronous or metachronous lung cancer

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