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Updated: May 8, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Reporting quality of survival analyses in medical journals still needs improvement. A minimal requirements proposal
Víctor Abraira1, Alfonso Muriel, José I Emparanza
1Unidad de Bioestadística Clínica, Hospital Universitario Ramón y Cajal, IRYCIS, Crta. Colmenar km 9.1, 28034 Madrid, Spain; CIBER de Epidemiología y Salud Pública (CIBERESP), Spain.
Objectives:
We reviewed publications with two main objectives: to describe how survival analyses are reported across medical journal specialties and to evaluate changes in reporting across periods and journal specialties.
Study Design And Setting:
Systematic review of clinical research articles published in 1991 and 2007, in 13 high-impact medical journals.
Results:
The number of articles performing survival analysis published in 1991 (104) and 2007 (240) doubled (17% vs. 33.5%; P = 0.000), although not uniformly across specialties. The percentage of studies using regression models and the number of patients included also increased. The presentation of results improved, although only the reporting of precision of effect estimates reached satisfactory levels (53.1% in 1991 vs. 94.2% in 2007; P = 0.000). Quality of reporting also varied across specialties; for example, cardiology articles were less likely than oncology ones to discuss sample size estimation (odds ratio = 0.12; 95% confidence interval: 0.05, 0.30). We also detected an interaction effect between period and specialty regarding the likelihood of reporting precision of curves and precision of effect estimates.
Conclusion:
The application of survival analysis to medical research data is increasing, whereas improvement in reporting quality is slow. We propose a list of minimum requirements for improved application and description of survival analysis.
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