Survival analysis, more than meets the eye

The log-rank test is a cornerstone of phase III oncology clinical trials. However, there are at least three different mathematical procedures that can be named the log-rank test and two of them are widely used by commercial statistical programs. Consequently, different P values can be obtained. In the case of a borderline statistical significance, this can mean the difference between the evidence (significant P value) and merely an observation. Since all three methods can be reported under the same name, space for possible data manipulation occurs. This should be of a particular concern in a drug regulatory context. Randomized clinical trials with borderline significant results should perhaps be required to report P values calculated by all three methods, in order to properly evaluate drug efficacy. An interactive MS Excel spreadsheet that uses all three logrank test variants is prepared as a supplementary file accompanying this article. Association of high grade of bone marrow fibrosis with poor outcome in patients with myelofibrosis is used as an example

Use of biochemical parameters for non-invasive screening of oesophageal varices in comparison to elastography-based approach in patients with compensated advanced chronic liver disease

Oesophageal varices are routinely diagnosed by esophagogastroduodenoscopy (EGD), and their bleeding has high mortality. We aimed to evaluate diagnostic performance of biochemical tests in comparison to elastography-based approaches, as non-invasive alternatives to EGD, for ruling-out high risk oesophageal varices (HRV). Retrospective analysis of patients (N = 861) who underwent liver stiffness measurement (LSM) by transient elastography (TE) in a single centre over 5-year period, with available results of EGD (within 3 months from LSM). Only patients with suspicion of compensated advanced chronic liver disease (cACLD) defined by LSM ≥ 10 kPa were included comprising the final cohort of 73 subjects. Original and expanded Baveno VI criteria (B6C), controlled attenuation parameter (CAP), platelet count (PLT), aspartate aminotransferase to PLT ratio index (APRI), Fibrosis-4 index (FIB4), model for end stage liver disease (MELD) score were evaluated against the results of EGD that served as the reference method. Analysed patients had median age 62 years, 59/73 (0.81) were males, 54/73 (0.74) had alcoholic/non-alcoholic fatty liver disease, and 21/73 (0.29) had HRV. In multivariate logistic regression analysis only LSM and PLT were independently associated with HRV. The best performing tests for ruling-out HRV (% of spared EGD; % of missed HRV) were respectively: LSM 214x109/L (21.9%; 0%); FIB4 ≤ 1.8 (21.4%; 0%), APRI ≤ 0.34 (12.3%; 0%). CAP, MELD = 6 alone or combined with PLT > 150(x109/L) did not show acceptable performance. The best performing biochemical tests for ruling-out HRV in our cohort of patients were PLT and FIB-4, but they were still outperformed by elastography-based approaches

Survival analysis, more than meets the eye

The log-rank test is a cornerstone of phase III oncology clinical trials. However, there are at least three different mathematical procedures that can be named the log-rank test and two of them are widely used by commercial statistical programs. Consequently, different P values can be obtained. In the case of a borderline statistical significance, this can mean the difference between the evidence (significant P value) and merely an observation. Since all three methods can be reported under the same name, space for possible data manipulation occurs. This should be of a particular concern in a drug regulatory context. Randomized clinical trials with borderline significant results should perhaps be required to report P values calculated by all three methods, in order to properly evaluate drug efficacy. An interactive MS Excel spreadsheet that uses all three logrank test variants is prepared as a supplementary file accompanying this article. Association of high grade of bone marrow fibrosis with poor outcome in patients with myelofibrosis is used as an example

Analysis of censored data

Analyzing events over time is often complicated by incomplete, or censored, observations. Special non-parametric statistical methods were developed to overcome difficulties in summarizing and com-paring censored data. Life-table (actuarial) method and Kaplan-Meier method are described with an explanation of survival curves. For the didactic purpose authors prepared a workbook based on most widely used Kaplan-Meier method. It should help the reader understand how Kaplan-Meier method is conceptualized and how it can be used to obtain statistics and survival curves needed to completely describe a sample of patients. Log-rank test and hazard ratio are also discussed