Literature DB >> 33402111

Competing risk analysis of cardiovascular/cerebrovascular death in T1/2 kidney cancer: a SEER database analysis.

Xiaofei Mo1,2, Mingge Zhou1,2, Hui Yan1,2, Xueqin Chen1,2, Yuetao Wang3,4.   

Abstract

BACKGROUND: Kidney cancer (KC) is associated with cardiovascular regulation disorder and easily leads to cardiovascular and cerebrovascular death (CCD), which is one of the major causes of death in patients with KC, especially those with T1/2 status. However, few studies have treated CCD as an independent outcome for analysis. We aimed to identify and evaluate the key factors associated with CCD in patients with T1/2 KC by competing risk analysis and compared these risk factors with those associated with kidney cancer-specific death (KCD) to offer some information for clinical management.
METHODS: A total of 45,117 patients diagnosed with first primary KC in T1/2 status were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. All patients were divided into the CCD group (n = 3087), KCD group (n = 3212), other events group (n = 6312) or alive group (n = 32,506). Patients' characteristics were estimated for their association with CCD or KCD by a competing risk model. Pearson's correlation coefficient and variance inflation factor (VIF) were used to detect collinearity between variables. Factors significantly correlated with CCD or KCD were used to create forest plots to compare their differences.
RESULTS: The competing risk analysis showed that age at diagnosis, race, AJCC T/N status, radiation therapy, chemotherapy and scope of lymph node represented different relationships to CCD than to KCD. In detail, age at diagnosis (over 74/1-50: HR = 9.525, 95% CI: 8.049-11.273), race (white/black: HR = 1.475, 95% CI: 1.334-1.632), AJCC T status (T2/T1: HR = 0.847, 95% CI: 0.758-0.946) and chemotherapy (received/unreceived: HR = 0.574, 95% CI: 0.347-0.949) were correlated significantly with CCD; age at diagnosis (over 74/1-50: HR = 3.205, 95% CI: 2.814-3.650), AJCC T/N status (T2/T1: HR = 2.259, 95% CI: 2.081-2.451 and N1/N0:HR = 3.347, 95% CI: 2.698-4.152), radiation therapy (received/unreceived: HR = 2.552, 95% CI: 1.946-3.346), chemotherapy (received/unreceived: HR = 2.896, 95% CI: 2.342-3.581) and scope of lymph nodes (1-3 regional lymph nodes removed/none: HR = 1.378, 95% CI: 1.206-1.575) were correlated significantly with KCD.
CONCLUSIONS: We found that age at diagnosis, race, AJCC T status and chemotherapy as the independent risk factors associated with CCD were different from those associated with KCD.

Entities:  

Keywords:  Competing risk analysis; Kidney cancer, Cardiovascular and cerebrovascular death; SEER database

Mesh:

Year:  2021        PMID: 33402111      PMCID: PMC7786899          DOI: 10.1186/s12885-020-07718-z

Source DB:  PubMed          Journal:  BMC Cancer        ISSN: 1471-2407            Impact factor:   4.430


  37 in total

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6.  Kidney cancer.

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Journal:  J Clin Oncol       Date:  2017-12-18       Impact factor: 50.717

8.  Predictors of early adulthood hypertension during adolescence: a population-based cohort study.

Authors:  Saeed Kalantari; Davood Khalili; Samaneh Asgari; Noushin Fahimfar; Farzad Hadaegh; Maryam Tohidi; Fereidoun Azizi
Journal:  BMC Public Health       Date:  2017-11-28       Impact factor: 3.295

9.  Establishment of predictive model for patients with kidney cancer bone metastasis: a study based on SEER database.

Authors:  Kun-Chi Hua; Yong-Cheng Hu
Journal:  Transl Androl Urol       Date:  2020-04

10.  Multicollinearity and misleading statistical results.

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Journal:  Korean J Anesthesiol       Date:  2019-07-15
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