ReviewDer Urologe. Ausg. A2013
[Kaplan-Meier analysis in urological practice].
Review in Der Urologe. Ausg. A, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Prognostic impact of paraneoplastic syndromes on patients with non-metastatic renal cell carcinoma undergoing surgery: Results from Canadian Kidney Cancer information system.Canadian Urological Association journal = Journal de l'Association des urologues du Canada · 2021Article
- Impact of the Ki-67 labeling index and p53 expression status on disease-free survival in pT1 urothelial carcinoma of the bladder.Translational andrology and urology · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Kaplan-Meier curves and estimates of survival are the most common way to present survival data in medicine, especially for cohorts with different lengths of follow-up. Moreover, Kaplan-Meier curves present a frequently used general graphic approach to display time-to-event outcomes. A solid understanding of how Kaplan-Meier curves are generated and how they should be analyzed and interpreted is of great importance to appraise urological literature in daily clinical practice. This article describes the basic principles of Kaplan-Meier analysis, possible variants and pitfalls. Improved knowledge of Kaplan-Meier analysis can help to improve Evidence-based urology and its application in patient care.
Indexed as
Identifiers
23703691What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.