End points in clinical trials in diffuse large B-cell lymphoma: time for more dialogue?

We observed lack of clarity and consistency in end point definitions of large randomized clinical trials in diffuse large B-cell lymphoma. These inconsistencies are such that trials might, in fact, address different clinical questions. They complicate interpretation of results, including comparisons across studies. Problems arise from different ways to account for events occurring after randomization including absence of improvement in disease status, treatment discontinuation or the initiation of new therapy. We call for more dialogue between stakeholders to define with clarity the questions of interest and corresponding end points. We illustrate that assessing different end point rules across a range of plausible patient journeys can be a powerful tool to facilitate such a discussion and contribute to better understanding of patient-relevant end points.

What is this article about? This article talks about the lack of clarity and consistency in the definitions of outcomes used in clinical trials that investigate new treatments for diffuse large B-cell lymphoma. This is mainly due to how these different outcome definitions handle events such as absence of improvement in disease status, treatment discontinuation or initiation of new treatment. The authors discuss how these inconsistencies make it hard to interpret the results of individual clinical trials and to compare results across clinical trials.Why is it important? Defining the above events and consequently defining outcomes affects what we can learn from the trials and can lead to different results. Some approaches may not reflect good and bad outcomes for patients appropriately. This makes it challenging for patients, physicians, health authorities and payors to understand the true benefit of treatments under investigation and which one is better.What are the key take-aways? This article serves as a call-to-action for more dialogue among all stakeholders involved in drug development and the decision-making process related to drug evaluations. There is an urgent need for clinical trials to be designed with more clarity and consistency on what is being measured so that relevant questions for patients and prescribing physicians are addressed. Understanding patient journeys will be key to successfully understand what truly matters to patients and how to measure the benefit of new treatments. Such discussions will contribute toward more clarity and consistency in the evaluation of new treatments.

Second-Line Tisagenlecleucel or Standard Care in Aggressive B-Cell Lymphoma.

BACKGROUND: Patient outcomes are poor for aggressive B-cell non-Hodgkin's lymphomas not responding to or progressing within 12 months after first-line therapy. Tisagenlecleucel is an anti-CD19 chimeric antigen receptor T-cell therapy approved for diffuse large B-cell lymphoma after at least two treatment lines. METHODS: We conducted an international phase 3 trial involving patients with aggressive lymphoma that was refractory to or progressing within 12 months after first-line therapy. Patients were randomly assigned to receive tisagenlecleucel with optional bridging therapy (tisagenlecleucel group) or salvage chemotherapy and autologous hematopoietic stem-cell transplantation (HSCT) (standard-care group). The primary end point was event-free survival, defined as the time from randomization to stable or progressive disease at or after the week 12 assessment or death. Crossover to receive tisagenlecleucel was allowed if a defined event occurred at or after the week 12 assessment. Other end points included response and safety. RESULTS: A total of 322 patients underwent randomization. At baseline, the percentage of patients with high-grade lymphomas was higher in the tisagenlecleucel group than in the standard-care group (24.1% vs. 16.9%), as was the percentage with an International Prognostic Index score (range, 0 to 5, with higher scores indicating a worse prognosis) of 2 or higher (65.4% vs. 57.5%). A total of 95.7% of the patients in the tisagenlecleucel group received tisagenlecleucel; 32.5% of the patients in the standard-care group received autologous HSCT. The median time from leukapheresis to tisagenlecleucel infusion was 52 days. A total of 25.9% of the patients in the tisagenlecleucel group had lymphoma progression at week 6, as compared with 13.8% of those in the standard-care group. The median event-free survival in both groups was 3.0 months (hazard ratio for event or death in the tisagenlecleucel group, 1.07; 95% confidence interval, 0.82 to 1.40; P = 0.61). A response occurred in 46.3% of the patients in the tisagenlecleucel group and in 42.5% in the standard-care group. Ten patients in the tisagenlecleucel group and 13 in the standard-care group died from adverse events. CONCLUSIONS: Tisagenlecleucel was not superior to standard salvage therapy in this trial. Additional studies are needed to assess which patients may obtain the most benefit from each approach. (Funded by Novartis; BELINDA ClinicalTrials.gov number, NCT03570892.).

Using Negative Control Outcomes and Difference-in-Differences Analysis to Estimate Treatment Effects in an Entirely Treated Cohort: The Effect of Ivacaftor in Cystic Fibrosis.

When an entire cohort of patients receives a treatment, it is difficult to estimate the treatment effect in the treated because there are no directly comparable untreated patients. Attempts can be made to find a suitable control group (e.g., historical controls), but underlying differences between the treated and untreated can result in bias. Here we show how negative control outcomes combined with difference-in-differences analysis can be used to assess bias in treatment effect estimates and obtain unbiased estimates under certain assumptions. Causal diagrams and potential outcomes are used to explain the methods and assumptions. We apply the methods to UK Cystic Fibrosis Registry data to investigate the effect of ivacaftor, introduced in 2012 for a subset of the cystic fibrosis population with a particular genotype, on lung function and annual rate (days/year) of receiving intravenous (IV) antibiotics (i.e., IV days). We consider 2 negative control outcomes: outcomes measured in the pre-ivacaftor period and outcomes among persons ineligible for ivacaftor because of their genotype. Ivacaftor was found to improve lung function in year 1 (an approximately 6.5-percentage-point increase in ppFEV1), was associated with reduced lung function decline (an approximately 0.5-percentage-point decrease in annual ppFEV1 decline, though confidence intervals included 0), and reduced the annual rate of IV days (approximately 60% over 3 years).

Cardiovascular magnetic resonance predictors of heart failure in hypertrophic cardiomyopathy: the role of myocardial replacement fibrosis and the microcirculation.

INTRODUCTION: Heart failure (HF) in hypertrophic cardiomyopathy (HCM) is associated with high morbidity and mortality. Predictors of HF, in particular the role of myocardial fibrosis and microvascular ischemia remain unclear. We assessed the predictive value of cardiovascular magnetic resonance (CMR) for development of HF in HCM in an observational cohort study. METHODS: Serial patients with HCM underwent CMR, including adenosine first-pass perfusion, left atrial (LA) and left ventricular (LV) volumes indexed to body surface area (i) and late gadolinium enhancement (%LGE- as a % of total myocardial mass). We used a composite endpoint of HF death, cardiac transplantation, and progression to NYHA class III/IV. RESULTS: A total of 543 patients with HCM underwent CMR, of whom 94 met the composite endpoint at baseline. The remaining 449 patients were followed for a median of 5.6 years. Thirty nine patients (8.7%) reached the composite endpoint of HF death (n = 7), cardiac transplantation (n = 2) and progression to NYHA class III/IV (n = 20). The annual incidence of HF was 2.0 per 100 person-years, 95% CI (1.6-2.6). Age, previous non-sustained ventricular tachycardia, LV end-systolic volume indexed to body surface area (LVESVI), LA volume index ; LV ejection fraction, %LGE and presence of mitral regurgitation were significant univariable predictors of HF, with LVESVI (Hazard ratio (HR) 1.44, 95% confidence interval (95% CI) 1.16-1.78, p = 0.001), %LGE per 10% (HR 1.44, 95%CI 1.14-1.82, p = 0.002) age (HR 1.37, 95% CI 1.06-1.77, p = 0.02) and mitral regurgitation (HR 2.6, p = 0.02) remaining independently predictive on multivariable analysis. The presence or extent of inducible perfusion defect assessed using a visual score did not predict outcome (p = 0.16, p = 0.27 respectively). DISCUSSION: The annual incidence of HF in a contemporary ambulatory HCM population undergoing CMR is low. Myocardial fibrosis and LVESVI are strongly predictive of future HF, however CMR visual assessment of myocardial perfusion was not.

Microvascular Dysfunction in Dilated Cardiomyopathy: A Quantitative Stress Perfusion Cardiovascular Magnetic Resonance Study.

OBJECTIVES: This study sought to quantify myocardial blood flow (MBF) and myocardial perfusion reserve (MPR) in dilated cardiomyopathy (DCM) and examine the relationship between myocardial perfusion and adverse left ventricular (LV) remodeling. BACKGROUND: Although regarded as a nonischemic condition, DCM has been associated with microvascular dysfunction, which is postulated to play a role in its pathogenesis. However, the relationship of the resulting perfusion abnormalities to myocardial fibrosis and the degree of LV remodeling is unclear. METHODS: A total of 65 patients and 35 healthy control subjects underwent adenosine (140 µg/kg/min) stress perfusion cardiovascular magnetic resonance with late gadolinium enhancement imaging. Stress and rest MBF and MPR were derived using a modified Fermi-constrained deconvolution algorithm. RESULTS: Patients had significantly higher global rest MBF compared with control subjects (1.73 ± 0.42 ml/g/min vs. 1.14 ± 0.42 ml/g/min; p < 0.001). In contrast, global stress MBF was significantly lower versus control subjects (3.07 ± 1.02 ml/g/min vs. 3.53 ± 0.79 ml/g/min; p = 0.02), resulting in impaired MPR in the DCM group (1.83 ± 0.58 vs. 3.50 ± 1.45; p < 0.001). Global stress MBF (2.70 ± 0.89 ml/g/min vs. 3.44 ± 1.03 ml/g/min; p = 0.017) and global MPR (1.67 ± 0.61 vs. 1.99 ± 0.50; p = 0.047) were significantly reduced in patients with DCM with LV ejection fraction ≤35% compared with those with LV ejection fraction >35%. Segments with fibrosis had lower rest MBF (mean difference: -0.12 ml/g/min; 95% confidence interval: -0.23 to -0.01 ml/g/min; p = 0.035) and lower stress MBF (mean difference: -0.15 ml/g/min; 95% confidence interval: -0.28 to -0.03 ml/g/min; p = 0.013). CONCLUSIONS: Patients with DCM exhibit microvascular dysfunction, the severity of which is associated with the degree of LV impairment. However, rest MBF is elevated rather than reduced in DCM. If microvascular dysfunction contributes to the pathogenesis of DCM, then the underlying mechanism is more likely to involve stress-induced repetitive stunning rather than chronic myocardial hypoperfusion.

Osteoprotegerin and Myocardial Fibrosis in Patients with Aortic Stenosis.

Left ventricular myocardial fibrosis in patients with aortic stenosis (AS) confers worse prognosis. Plasma osteoprotegerin (OPG), a cytokine from the TNF receptor family, correlates with the degree of valve calcification in AS, reflecting the activity of the tissue RANKL/RANK/OPG (receptor activator of nuclear factor κΒ ligand/RANK/osteoprotegerin) axis, and is associated with poorer outcomes in AS. Its association with myocardial fibrosis is unknown. We hypothesised that OPG levels would reflect the extent of myocardial fibrosis in AS. We included 110 consecutive patients with AS who had undergone late-gadolinium contrast enhanced cardiovascular magnetic resonance (LGE-CMR). Patients were characterised according to pattern of fibrosis (no fibrosis, midwall fibrosis, or chronic myocardial infarction fibrosis). Serum OPG was measured with ELISA and compared between groups defined by valve stenosis severity. Some 36 patients had no fibrosis, 38 had midwall fibrosis, and 36 had chronic infarction. Patients with midwall fibrosis did not have higher levels of OPG compared to those without fibrosis (6.78 vs. 5.25 pmol/L, p = 0.12). There was no difference between those with midwall or chronic myocardial infarction fibrosis (6.78 vs. 6.97 pmol/L, p = 0.27). However, OPG levels in patients with chronic myocardial infarction fibrosis were significantly higher than those without fibrosis (p = 0.005).

Estimating long-term treatment effects in observational data: A comparison of the performance of different methods under real-world uncertainty.

In the presence of time-dependent confounding, there are several methods available to estimate treatment effects. With correctly specified models and appropriate structural assumptions, any of these methods could provide consistent effect estimates, but with real-world data, all models will be misspecified and it is difficult to know if assumptions are violated. In this paper, we investigate five methods: inverse probability weighting of marginal structural models, history-adjusted marginal structural models, sequential conditional mean models, g-computation formula, and g-estimation of structural nested models. This work is motivated by an investigation of the effects of treatments in cystic fibrosis using the UK Cystic Fibrosis Registry data focussing on two outcomes: lung function (continuous outcome) and annual number of days receiving intravenous antibiotics (count outcome). We identified five features of this data that may affect the performance of the methods: misspecification of the causal null, long-term treatment effects, effect modification by time-varying covariates, misspecification of the direction of causal pathways, and censoring. In simulation studies, under ideal settings, all five methods provide consistent estimates of the treatment effect with little difference between methods. However, all methods performed poorly under some settings, highlighting the importance of using appropriate methods based on the data available. Furthermore, with the count outcome, the issue of non-collapsibility makes comparison between methods delivering marginal and conditional effects difficult. In many situations, we would recommend using more than one of the available methods for analysis, as if the effect estimates are very different, this would indicate potential issues with the analyses.