Survival analysis: Log rank test

Crossing survival curves: alternatives to the log-rank test

Background It is not uncommon for clinical trials to present results on survival time as Kaplan-Meier survival curves that cross, indicating non-proportional hazards. A recent example was given in a pivotal trial in advanced nonsmall cell lung cancer (The ‘IPASS study’ [1]). Trials such as these present a hazard ratio and log-rank test for treatment comparison as this is their planned primary a...

A log-rank-type test to compare net survival distributions.

In population-based cancer studies, it is often interesting to compare cancer survival between different populations. However, in such studies, the exact causes of death are often unavailable or unreliable. Net survival methods were developed to overcome this difficulty. Net survival is the survival that would be observed if the disease under study was the only possible cause of death. The Poha...

Log-rank Test for Two Groups

Adjusted Kaplan-Meier estimator and log-rank test with inverse probability of treatment weighting for survival data.

Estimation and group comparison of survival curves are two very common issues in survival analysis. In practice, the Kaplan-Meier estimates of survival functions may be biased due to unbalanced distribution of confounders. Here we develop an adjusted Kaplan-Meier estimator (AKME) to reduce confounding effects using inverse probability of treatment weighting (IPTW). Each observation is weighted ...

survival analysis of transfusion dependent î²-thalassemia major patients

background: the classical supportive therapy for î² -thalassemia major consists of regular blood transfusion, iron-chelation therapy and specific treatment of the related complications. a balance between the maintenance of the highest possible level of haemoglobin and lowest possible level of iron accumulation in heart and liver give the best chance of survival and the best quality of life. met...