Assessment of Outcomes After Stopping Tyrosine Kinase Inhibitors Among Patients With Chronic Myeloid Leukemia: A Nonrandomized Clinical Trial.

IMPORTANCE: Tyrosine kinase inhibitors (TKIs) have been associated with improved survival of patients with chronic myeloid leukemia (CML) but are also associated with adverse effects, especially fatigue and diarrhea. Discontinuation of TKIs is safe and is associated with the successful achievement of treatment-free remission (TFR) for some patients. OBJECTIVE: To evaluate molecular recurrence (MRec) and patient-reported outcomes (PROs) after TKI discontinuation for US patients with CML. DESIGN, SETTING, AND PARTICIPANTS: The Life After Stopping TKIs (LAST) study was a prospective single-group nonrandomized clinical trial that enrolled 172 patients from 14 US academic medical centers from December 18, 2014, to December 12, 2016, with a minimum follow-up of 3 years. Participants were adults with chronic-phase CML whose disease was well controlled with imatinib, dasatinib, nilotinib, or bosutinib. Statistical analysis was performed from August 13, 2019, to March 23, 2020. INTERVENTION: Discontinuation of TKIs. MAIN OUTCOMES AND MEASURES: Molecular recurrence, defined as loss of major molecular response (BCR-ABL1 International Scale ratio >0.1%) by central laboratory testing, and PROs (Patient-Reported Outcomes Measurement Information System computerized adaptive tests) were monitored. Droplet digital polymerase chain reaction (ddPCR) was performed on samples with undetectable BCR-ABL1 by standard real-time quantitative polymerase chain reaction (RQ-PCR). RESULTS: Of 172 patients, 89 were women (51.7%), and the median age was 60 years (range, 21-86 years). Of 171 patients evaluable for molecular analysis, 112 (65.5%) stayed in major molecular response, and 104 (60.8%) achieved TFR. Undetectable BCR-ABL1 by either ddPCR or RQ-PCR at the time of TKI discontinuation (hazard ratio, 3.60; 95% CI, 1.99-6.50; P < .001) and at 3 months (hazard ratio, 5.86; 95% CI, 3.07-11.1; P < .001) was independently associated with MRec. Molecular recurrence for patients with detectable BCR-ABL1 by RQ-PCR was 50.0% (14 of 28), undetectable BCR-ABL1 by RQ-PCR but detectable by ddPCR was 64.3% (36 of 56), and undetectable BCR-ABL1 by both ddPCR and RQ-PCR was 10.3% (9 of 87) (P ≤ .001). Of the 112 patients in TFR at 12 months, 90 (80.4%) had a clinically meaningful improvement in fatigue, 39 (34.8%) had a clinically meaningful improvement in depression, 98 (87.5%) had a clinically meaningful improvement in diarrhea, 24 (21.4%) had a clinically meaningful improvement in sleep disturbance, and 5 (4.5%) had a clinically meaningful improvement in pain interference. Restarting a TKI resulted in worsening of PROs. CONCLUSIONS AND RELEVANCE: In this study, TKI discontinuation was safe, and 60.8% of patients remained in TFR. Discontinuation of TKIs was associated with improvements in PROs. These findings should assist patients and physicians in their decision-making regarding discontinuation of TKIs. Detectable BCR-ABL1 by RQ-PCR or ddPCR at the time of TKI discontinuation was associated with higher risk of MRec; clinical application of this finding should be confirmed in other studies. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02269267.

Weighted comparison of two cumulative incidence functions with R-CIFsmry package.

In this paper we propose a class of flexible weight functions for use in comparison of two cumulative incidence functions. The proposed weights allow the users to focus their comparison on an early or a late time period post treatment or to treat all time points with equal emphasis. These weight functions can be used to compare two cumulative incidence functions via their risk difference, their relative risk, or their odds ratio. The proposed method has been implemented in the R-CIFsmry package which is readily available for download and is easy to use as illustrated in the example.

Asymptotic theory for the Cox semi-Markov illness-death model.

Irreversible illness-death models are used to model disease processes and in cancer studies to model disease recovery. In most applications, a Markov model is assumed for the multistate model. When there are covariates, a Cox (1972, J Roy Stat Soc Ser B 34:187-220) model is used to model the effect of covariates on each transition intensity. Andersen et al. (2000, Stat Med 19:587-599) proposed a Cox semi-Markov model for this problem. In this paper, we study the large sample theory for that model and provide the asymptotic variances of various probabilities of interest. A Monte Carlo study is conducted to investigate the robustness and efficiency of Markov/Semi-Markov estimators. A real data example from the PROVA (1991, Hepatology 14:1016-1024) trial is used to illustrate the theory.

A class of goodness of fit tests for a copula based on bivariate right-censored data.

The copula of a bivariate distribution, constructed by making marginal transformations of each component, captures all the information in the bivariate distribution about the dependence between two variables. For frailty models for bivariate data the choice of a family of distributions for the random frailty corresponds to the choice of a parametric family for the copula. A class of tests of the hypothesis that the copula is in a given parametric family, with unspecified association parameter, based on bivariate right censored data is proposed. These tests are based on first making marginal Kaplan-Meier transformations of the data and then comparing a non-parametric estimate of the copula to an estimate based on the assumed family of models. A number of options are available for choosing the scale and the distance measure for this comparison. Significance levels of the test are found by a modified bootstrap procedure. The procedure is used to check the appropriateness of a gamma or a positive stable frailty model in a set of survival data on Danish twins.