Inference for current leukemia free survival

Final report of TKI discontinuation trial with dasatinib for the second attempt of treatment-free remission after failing the first attempt with imatinib: Treatment-free Remission Accomplished by Dasatinib (TRAD) study

Multiple studies have reported a significant treatment-free remission (TFR) rate of 50%-60% in patients with chronic myeloid leukaemia (CML) who discontinue tyrosine kinase inhibitor (TKI) therapy. However, the remaining half of these patients still require re-initiation of TKI therapy for leukaemia control. It remains unclear if TKI drugs should be switched for re-therapy in patients who failed the first TFR (TFR1) attempt. Our study attempted to determine whether dasatinib therapy after TFR1 failure post-imatinib discontinuation could improve the likelihood of TFR2. Of 59 patients who lost molecular response after imatinib discontinuation for TFR1, 55 patients (93.2%) were treated with dasatinib, of whom 49 (89.1%) regained MR4.5 or deeper response, with a median time of 1.85 months to achieve MR4.5. Dasatinib was discontinued in 35 patients for TFR2 attempt, of whom 26 patients (74.28%) lost MMR and 6 (17.14%) MR4. Risk factor analysis for the TFR2 after dasatinib discontinuation suggested three significant factors: (1) doubling time of BCR::ABL1 transcript following TFR1 attempt, (2) rapid regaining of molecular response following dasatinib therapy and (3) undetectable BCR::ABL1 transcript prior to TFR2 attempt. The present study showed that dasatinib does not increase the TFR2 rate in general, but a selected group of patients could benefit from this approach.

The added value of multi-state modelling in a randomized controlled trial: The HOVON 102 study re-analyzed

Clofarabine is an active antileukemic drug for subgroups of patients with acute myeloid leukemia (AML). Multi-state models can provide additional insights to supplement the original intention-to-treat analysis of randomized controlled trials (RCT). We re-analyzed the HOVON102/SAKK30/09 phase III RCT for newly diagnosed AML patients, which randomized between standard induction chemotherapy with or without clofarabine. Using multi-state models, we evaluated the effects of induction chemotherapy outcomes (complete remission [CR], measurable residual disease [MRD]), and post-remission therapy with allogeneic stem cell transplantation [alloSCT] on relapse and death. Through the latter a consistent reduction in the hazard of relapse in the clofarabine arm compared to the standard arm was found, which occurred irrespective of MRD status or post-remission treatment with alloSCT, demonstrating a strong and persistent antileukemic effect of clofarabine. During the time period between achieving CR and possible post-remission treatment with alloSCT, non-relapse mortality was higher in patients receiving clofarabine. An overall net benefit of treatment with clofarabine was identified using the composite endpoint current leukemia-free survival (CLFS). In conclusion, these results enforce and extend the earlier reported beneficial effect of clofarabine in AML and show that multi-state models further detail the effect of treatment on competing and series of events.

The wild bootstrap for multivariate Nelson-Aalen estimators

We rigorously extend the widely used wild bootstrap resampling technique to the multivariate Nelson-Aalen estimator under Aalen's multiplicative intensity model. Aalen's model covers general Markovian multistate models including competing risks subject to independent left-truncation and right-censoring. This leads to various statistical applications such as asymptotically valid confidence bands or tests for equivalence and proportional hazards. This is exemplified in a data analysis examining the impact of ventilation on the duration of intensive care unit stay. The finite sample properties of the new procedures are investigated in a simulation study.

The time-dependent "cure-death" model investigating two equally important endpoints simultaneously in trials treating high-risk patients with resistant pathogens

A variety of primary endpoints are used in clinical trials treating patients with severe infectious diseases, and existing guidelines do not provide a consistent recommendation. We propose to study simultaneously two primary endpoints, cure and death, in a comprehensive multistate cure-death model as starting point for a treatment comparison. This technique enables us to study the temporal dynamic of the patient-relevant probability to be cured and alive. We describe and compare traditional and innovative methods suitable for a treatment comparison based on this model. Traditional analyses using risk differences focus on one prespecified timepoint only. A restricted logrank-based test of treatment effect is sensitive to ordered categories of responses and integrates information on duration of response. The pseudo-value regression provides a direct regression model for examination of treatment effect via difference in transition probabilities. Applied to a topical real data example and simulation scenarios, we demonstrate advantages and limitations and provide an insight into how these methods can handle different kinds of treatment imbalances. The cure-death model provides a suitable framework to gain a better understanding of how a new treatment influences the time-dynamic cure and death process. This might help the future planning of randomised clinical trials, sample size calculations, and data analyses.

Estimation of current cumulative incidence of leukaemia-free patients and current leukaemia-free survival in chronic myeloid leukaemia in the era of modern pharmacotherapy

BACKGROUND

The current situation in the treatment of chronic myeloid leukaemia (CML) presents a new challenge for attempts to measure the therapeutic results, as the CML patients can experience multiple leukaemia-free periods during the course of their treatment. Traditional measures of treatment efficacy such as leukaemia-free survival and cumulative incidence are unable to cope with multiple events in time, e.g. disease remissions or progressions, and as such are inappropriate for the efficacy assessment of the recent CML treatment.

METHODS

Standard nonparametric statistical methods are used for estimating two principal characteristics of the current CML treatment: the probability of being alive and leukaemia-free in time after CML therapy initiation, denoted as the current cumulative incidence of leukaemia-free patients; and the probability that a patient is alive and in any leukaemia-free period in time after achieving the first leukaemia-free period on the CML treatment, denoted as the current leukaemia-free survival. The validity of the proposed methods is further documented in the data of the Czech CML patients consecutively recorded between July 2003 and July 2009 as well as in simulated data.

RESULTS

The results have shown a difference between the estimates of the current cumulative incidence function and the common cumulative incidence of leukaemia-free patients, as well as between the estimates of the current leukaemia-free survival and the common leukaemia-free survival. Regarding the currently available follow-up period, both differences have reached the maximum (12.8% and 20.8%, respectively) at 3 years after the start of follow-up, i.e. after the CML therapy initiation in the former case and after the first achievement of the disease remission in the latter.

CONCLUSIONS

Two quantities for the evaluation of the efficacy of current CML therapy that may be estimated with standard nonparametric methods have been proposed in this paper. Both quantities reliably illustrate a patient's disease status in time because they account for the proportion of patients in the second and subsequent disease remissions. Moreover, the model is also applicable in the future, regardless of what the progress in the CML treatment will be and how many treatment options will be available, respectively.