Clinical Trials

❘❙❚■ Chapter 21 | Analysis of Survival DataTable 4. Calculation of the log-rank statistic for the pancreatic cancer trial data.Time (months) Treatment A Treatment B Total Treatment Ad 1jn 1jd 2jn 2jd jn je 1jv 1j5 0 17 1 17 1 34 0.5000 0.25007 0 16 1 15 1 31 0.5161 0.24978 0 16 1 14 1 30 0.5333 0.248910 1 16 1 13 2 29 1.1034 0.477012 1 15 1 11 2 26 1.1538 0.468615 0 14 1 9 1 23 0.6087 0.238223 0 13 1 7 1 20 0.6500 0.227527 1 13 0 6 1 19 0.6842 0.216130 0 12 1 6 1 18 0.6667 0.222237 1 10 0 5 1 15 0.6667 0.222239 0 8 1 5 1 13 0.6154 0.236740 0 7 1 4 1 11 0.6364 0.231445 1 4 1 3 2 7 1.1429 0.4082Total 5 9.4776 3.6967A = new treatment; B = standard treatment.Limitations to the log-rank testThere are three major limitations to the log-rank test.• It does not provide a direct estimate of the magnitude of treatment effect.• It is mainly used to compare groups on the basis of a single variable,such as treatment.• It is more likely to detect a difference between groups when the riskof an event is consistently higher for one group than another, but itis unlikely to detect the difference when survival curves cross [1,2].KM survival curves should always be plotted before making group comparisons.In addition, all of the above shortcomings can be overcome by the application ofa hazards regression model, such as the Cox proportional hazards model,introduced in the next section [1,2].244