What is survival analysis, and when should I use it?

Ferreira, Juliana Carvalho; Patino, Cecilia María

doi:10.1590/s1806-37562016000000013

Cited by 13 publications

(13 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The statistical analysis was performed in two phases and with different objectives. In the first one, with the objective of analyzing the survival time of patients and associated factors, we implemented the Cox proportional hazards regression model [20][21][22]. A descriptive analysis was carried out and the survival time was estimated for each factor under study, which were selected by statistical and clinical criteria.…”

Section: Methodsmentioning

confidence: 99%

Survival time among patients who were diagnosed with tuberculosis, the precocious deaths and associated factors in southern Brazil

et al. 2021

View full text Add to dashboard Cite

Background A diagnosis of tuberculosis (TB) does not mean that the disease will be treated successfully, since death may occur even among those who are known to the health services. Here, we aimed to analyze patient survival time from the diagnosis of TB to death, precocious deaths, and associated factors in southern Brazil. Methods We conducted a longitudinal study with patients who were diagnosed with TB and who died due to the disease between 2008 and 2015 in southern Brazil. The starting point for measuring survival time was the patient’s diagnosis date. Techniques for survival analysis were employed, including the Kaplan-Meier test and Cox’s regression. A mixed-effect model was applied for identifying the associated factors to precocious deaths. Hazard ratio (HR) and odds ratio (OR) with 95% confidence intervals (95% CI) were estimated. We defined p value <0.05 as statistically significant for all statistics applied. Results One hundred forty-six patients were included in the survival analysis, observing a median survival time of 23.5 days. We observed that alcoholism (HR=1.55, 95% CI=1.04-2.30) and being male (HR=6.49, 95% CI=1.03-2.68) were associated with death. The chance of precocious death within 60 days was 10.48 times greater than the chance of early death within 30 days. Conclusion Most of the deaths occurred within 2 months after the diagnosis, during the intensive phase of the treatment. The use of alcohol and gender were associated with death, revealing inequality between men and women. This study advanced knowledge regarding the vulnerability associated with mortality. These findings must be addressed to fill a gap in the care cascades for active TB and ensure equity in health.

show abstract

Section: Methodsmentioning

confidence: 99%

Survival time among patients who were diagnosed with tuberculosis, the precocious deaths and associated factors in southern Brazil

et al. 2021

View full text Add to dashboard Cite

show abstract

“…From massive time-event data from clinical trials, survival analysis identifies factors that are predictive to subjects' lifetime and estimates survival time for new subjects. Similar information cannot be retrieved from simple mortality comparison, which makes survival analysis necessary and irreplaceable [ 2 ].…”

Section: Introductionmentioning

confidence: 99%

Complete hazard ranking to analyze right-censored data: An ALS survival study

et al. 2017

View full text Add to dashboard Cite

Survival analysis represents an important outcome measure in clinical research and clinical trials; further, survival ranking may offer additional advantages in clinical trials. In this study, we developed GuanRank, a non-parametric ranking-based technique to transform patients' survival data into a linear space of hazard ranks. The transformation enables the utilization of machine learning base-learners including Gaussian process regression, Lasso, and random forest on survival data. The method was submitted to the DREAM Amyotrophic Lateral Sclerosis (ALS) Stratification Challenge. Ranked first place, the model gave more accurate ranking predictions on the PRO-ACT ALS dataset in comparison to Cox proportional hazard model. By utilizing right-censored data in its training process, the method demonstrated its state-of-the-art predictive power in ALS survival ranking. Its feature selection identified multiple important factors, some of which conflicts with previous studies.

show abstract

“…Os resultados estão apresentados através de proporções, medianas, quartis e médias, conforme a natureza destas variáveis. Os dados referentes à sobrevida global da doença estão apresentados na curva de Kaplan-Meier e teste de regressão de logrank 6,[15][16] . Através deste método, é possível estimar a probabilidade de sobrevida em vários intervalos de tempo e ilustrar graficamente a sobrevida ao longo do tempo.…”

Section: Tratamento E Análise Dos Dadosunclassified

“…Através deste método, é possível estimar a probabilidade de sobrevida em vários intervalos de tempo e ilustrar graficamente a sobrevida ao longo do tempo. O teste de log-rank é um teste não paramétrico utilizado na comparação de curvas de sobrevida entre dois ou mais grupos 16 .…”

Section: Tratamento E Análise Dos Dadosunclassified

“…A taxa de sobrevida é uma variável utilizada como forma padrão para discutir o prognóstico de um paciente, utilizando a probabilidade de sobreviver no curso dos intervalos de tempo até um momento considerado (t), denominada probabilidade condicional. Assim, a taxa de sobrevida em 5 anos, por exemplo, se refere à porcentagem de pacientes que vivem pelo menos 5 anos após o diagnóstico de determinada doença [5][6][7] .…”

Section: Introductionunclassified

See 1 more Smart Citation

Sobrevida de pacientes com neoplasia maligna de colo conforme localização primária à direita ou esquerda

França¹,

Bertolazzi²

2019

ACS

View full text Add to dashboard Cite

Introdução. As neoplasias de colo possuem relevância epidemiológica mundial. Dada sua heterogeneidade molecular e clínica, o diagnóstico em estádios iniciais e tratamento precoce tornam-se essenciais para ganho de sobrevida. Outro fator determinante para a sobrevida e predição do desfecho dessas neoplasias diz respeito à localização primária da doença, destacando-se suas lateralidades. Objetivos. Investigar associação entre taxas de sobrevida e a localização à direita ou esquerda das neoplasias de colo. Métodos. Trata-se de estudo transversal com delineamento descritivo, abordagem quantitativa do tipo analítica, com correlação entre variáveis. Foram sujeitos do estudo pacientes atendidos em complexo hospitalar quaternário no interior de São Paulo entre 2010 e 2017. A coleta de dados aconteceu de forma retrospectiva e documental, a partir de fontes do Registro Hospitalar de Câncer e prontuários informatizados. Os dados sociodemográficos, clínico-patológicos e de sobrevida foram analisados pelo programa IBM SPSS Statistical Package v.25 (IBM Corporation) e apresentados em mediana, interquartis e curva de Kaplan Meier, conforme natureza dessas variáveis. Resultados. A amostra final de 691 pacientes teve maioria diagnosticada com neoplasias de colo esquerdo (n=392;56,7%), especialmente sigmoide (n=282;40,9%), com discreta predominância de homens (n=351;50,8%) e entre os estádios II (n=193;27,9%) e III (n=213;30,9%). Os adenocarcinomas tubulares foram o tipo morfológico mais frequente (n=477;69%). A idade variou de 14 a 97 (Mediana 63,7) anos. A maior parte dos pacientes se declararam brancos (n=623;90,2%) e proveniente das cidades do Departamento Regional de Saúde XV (n=408;59%). Ocorreram 296 (42,8%) óbitos no período, especialmente em portadores de neoplasia de colo à direita (n=149; 50,3%). O tempo de sobrevida global teve mediana de 807 dias (interquartil 25= 284; interquartil 75=1622), sendo de 866 dias para colo à esquerda e 675 dias para colo à direita. Conclusão. As neoplasias de colo direito podem ser vistas como possível preditor independente de óbito (sobrevida de 1,8 anos) quando comparadas com neoplasias de colo à esquerda (sobrevida de 2,4 anos).

show abstract

What is survival analysis, and when should I use it?

Cited by 13 publications

References 1 publication

Survival time among patients who were diagnosed with tuberculosis, the precocious deaths and associated factors in southern Brazil

Survival time among patients who were diagnosed with tuberculosis, the precocious deaths and associated factors in southern Brazil

Complete hazard ranking to analyze right-censored data: An ALS survival study

Sobrevida de pacientes com neoplasia maligna de colo conforme localização primária à direita ou esquerda

Contact Info

Product

Resources

About