ArticleBritish journal of cancer2022
Standardised survival probabilities: a useful and informative tool for reporting regression models for survival data.
Article in British journal of cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- Variation in chemotherapy use across healthcare regions in Sweden and its impact on prognosis in women with HR+/HER2- early breast cancer.Breast cancer research : BCR · 2026Article
- Menopausal hormone therapy after ovarian cancer: A 10-year survival analysis in premenopausal women.Acta obstetricia et gynecologica Scandinavica · 2026Article
- Survival impact of second primary cutaneous and non-cutaneous melanoma in melanoma survivors.Journal of the European Academy of Dermatology and Venereology : JEADV · 2026Article
- Multidimensional health poverty among diabetic adults in China: evidence from the China Kadoorie Biobank.Archives of public health = Archives belges de sante publique · 2026Article
- Standardized survival probabilities and contrasts between hierarchical units in multilevel survival models.BMC medical research methodology · 2026Article
- Variable Association of Neighborhood Deprivation and Race With Postoperative Survival After Coronary Artery Bypass Grafting.Journal of the American Heart Association · 2026Article
- Younger adults are not alright, but older adults are? Examining mortality disparities among the children of migrants aged 15-44 and 45-64 in Sweden, 1990-2023: a total-population cohort study.BMJ public health · 2026Article
- Impact of socioeconomics on recurrences and survival in non-metastasized colorectal cancer.British journal of cancer · 2025Article
- Long-term accrual of conditions following myocardial infarction: a study of disease trajectories in the Wales Multimorbidity e-Cohort.BMC medicine · 2025Article
- Comparison of Methods for Analyzing Environmental Mixtures Effects on Survival Outcomes.Current environmental health reports · 2025Review
- Day case hip and knee replacement in England: a population-based cohort study using linked National Joint Registry and Hospital Episode Statistics data.BMC medicine · 2025Article
- The association of a polygenic lifespan score with the risk of common age-related diseases and mortality.The journals of gerontology. Series A, Biological sciences and medical sciences · 2025Article
- Competing classes confront competing risks: unraveling mortality inequities with parametric g-computation.American journal of epidemiology · 2025Article
- Diabetes Risk After Treatment for Childhood and Young Adult Cancer.Diabetes care · 2025Article
- Analysis of temporal survival trends: considerations and best practice.BMC medical research methodology · 2025Article
- CDK4 inactivation inhibits apoptosis via mitochondria-ER contact remodeling in triple-negative breast cancer.Nature communications · 2025Article
- Cerebrolysin, hemorrhagic transformation, and anticoagulation timing after reperfusion therapy in stroke:Frontiers in pharmacology · 2025Article
- A population-based study on trajectories of HER2 status during neoadjuvant chemotherapy for early breast cancer and metastatic progression.British journal of cancer · 2024Article
- Article
- Sex Differences in the Survival of Patients with Neuroendocrine Neoplasms: A Comparative Study of Two National Databases.Cancers · 2024Article
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4 authors.
Funding
Abstract
backgroundWhen interested in studying the effect of a treatment (or other exposure) on a time-to-event outcome, the most popular approach is to estimate survival probabilities using the Kaplan-Meier estimator. In the presence of confounding, regression models are fitted, and results are often summarised as hazard ratios. However, despite their broad use, hazard ratios are frequently misinterpreted as relative risks instead of relative rates.
methodsWe discuss measures for summarising the analysis from a regression model that overcome some of the limitations associated with hazard ratios. Such measures are the standardised survival probabilities for treated and untreated: survival probabilities if everyone in the population received treatment and if everyone did not. The difference between treatment arms can be calculated to provide a measure for the treatment effect.
resultsUsing publicly available data on breast cancer, we demonstrated the usefulness of standardised survival probabilities for comparing the experience between treated and untreated after adjusting for confounding. We also showed that additional important research questions can be addressed by standardising among subgroups of the total population. DISCUSSION: Standardised survival probabilities are a useful way to report the treatment effect while adjusting for confounding and have an informative interpretation in terms of risk.
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