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The Kaplan–Meier estimator, [1] [2] also known as the product limit estimator, is a non-parametric statistic used to estimate the survival function from lifetime data. In medical research, it is often used to measure the fraction of patients living for a certain amount of time after treatment.
Kaplan Meier Analysis of overall survival before starting a new line of therapy for patients with metastatic breast, colorectal and prostate cancer. Patients were divided into those with Favorable and Unfavorable CTC (Unfavorable: >5 CTC/7.5mL for breast and prostate, >3 CTC/7.5mL for colon) [29]
In complex diseases, such as cancer, researchers rely on statistical comparisons of disease-free survival (DFS) of patients against matched, healthy control groups. This logically rigorous approach essentially equates indefinite remission with cure. [6] The comparison is usually made through the Kaplan-Meier estimator approach. [7]
It can be thought of as the kaplan-meier survivor function for a particular year, divided by the expected survival rate in that particular year. That is typically known as the relative survival (RS). If five consecutive years are multiplied, the resulting figure would be known as cumulative relative survival (CRS). It is analogous to the five ...
Paul Meier (July 24, 1924 – August 7, 2011) [1] was a statistician who promoted the use of randomized trials in medicine. [2] [3]Meier is known for introducing, with Edward L. Kaplan, the Kaplan–Meier estimator, [4] [5] a method for measuring how many patients survive a medical treatment from one duration to another, taking into account that the sampled population changes over time.
Kaplan–Meier graph by treatment group in aml The null hypothesis for a log-rank test is that the groups have the same survival. The expected number of subjects surviving at each time point in each is adjusted for the number of subjects at risk in the groups at each event time.
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