Survival of patients who had cancer diagnosed through an emergency hospital admission: A retrospective matched case-comparison study in Australia

  • 0Australian Institute of Health Innovation, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, Australia.

|

|

Summary

This summary is machine-generated.

Cancer patients admitted via emergency hospital stays face significantly higher mortality risks within 12 months. Key predictors of death include older age, specific cancer types, metastatic disease, mental disorders, and disadvantaged living areas.

Area Of Science

  • Oncology
  • Public Health
  • Epidemiology

Background

  • Emergency hospital admissions for cancer diagnosis are linked to poorer patient outcomes.
  • Identifying factors predicting mortality after emergency cancer diagnosis is crucial for improving survival rates.

Purpose Of The Study

  • To identify characteristics of cancer diagnosed through emergency hospital admission.
  • To examine predictors associated with 12-month mortality following an emergency cancer diagnosis.

Main Methods

  • A population-based retrospective case-comparison study was conducted in New South Wales, Australia (2013-2020).
  • Propensity-matched analysis (1:1) linked hospital, cancer registry, and mortality records.
  • Conditional logistic regression identified predictors of 12-month mortality.

Main Results

  • Individuals with emergency cancer admissions had a nearly fourfold increased likelihood of 12-month mortality (OR 3.93) compared to planned admissions.
  • Predictors of increased mortality included older age, lung and digestive organ cancers, metastatic disease, mental disorders, and living in rural or disadvantaged areas.
  • Females had a 13% lower likelihood of 12-month mortality compared to males.

Conclusions

  • While not all emergency cancer admissions are preventable, enhancing preventive screening and promoting early symptom help-seeking are vital.
  • These strategies can reduce emergency cancer admissions and improve overall cancer survival rates.

Related Concept Videos

Cancer Survival Analysis 01:21

343

Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...

Comparing the Survival Analysis of Two or More Groups 01:20

177

Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...

Kaplan-Meier Approach 01:24

132

The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...

Actuarial Approach 01:20

75

The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...

Introduction To Survival Analysis 01:18

220

Survival analysis is a statistical method used to study time-to-event data, where the "event" might represent outcomes like death, disease relapse, system failure, or recovery. A unique feature of survival data is censoring, which occurs when the event of interest has not been observed for some individuals during the study period. This requires specialized techniques to handle incomplete data effectively.
The primary goal of survival analysis is to estimate survival time—the time...

Adaptive Mechanisms in Cancer Cells 02:53

5.7K

Cancer cells accumulate genetic changes at an abnormally rapid rate due to the defects in the DNA repair mechanisms. From an evolutionary perspective, such genetic instability is advantageous for cancer development. Mutant cell lines accumulate a series of beneficial mutations that contribute to their progression into cancer.
Some of the advantages that cancer cells have on normal cells include - enhanced ability to divide without terminally differentiating, induce new blood vessel formation,...