Estimating the Causal Effect of Some Exposure From Nonrandomized Studies: The Example of Reduced Intensity Conditioning (RIC) in Hematological Diseases.
Authors: Resche-Rigon Matthieu , Robin Marie , Peffault de Latour Regis , Chevret Sylvie , Socie Gerard P 
Published: October 2019

Abstract 3365

Poster Board III-253

Introduction:

Although allogeneic SCT with RIC has now gained wide acceptance, its eventual benefit again non-transplant approach is largely unknown (outside the setting of large randomized trials). When evaluating the impact on survival of reduced intensity conditioning in malignant hematological diseases, standard estimations based on Cox regression from observational databases could be biased because they ignore covariates that confound treatment decision. In this setting, we applied and compared two different statistical methods that were developed to control for confounding in estimating exposure (or treatment) effect from epidemiological studies.

Patients and Methods:

The statistical challenge was that allograft tended to be given when a patient was in advanced phase of his/her hematological malignancy, so that treatment was confounded by performance indicators, which in turn lie on the causal pathway between treatment and outcome. Thus, comparison of outcome first used propensity score (PS) analyses that attempt to create a comparison group of non-treated patients that closely resembles the group of treated patients by matching for the likelihood that a given patient has received the treatment. Then, we used marginal structural models (MSMs) that consist in creating, by using inverse probability of treatment weights, a pseudo-population in which the probability of treatment does no longer depend on covariates, and the effect of treatment on outcome is the same as in the original population.

Result:

Reduced intensity conditioning allograft was performed in 82 patients with chemotherapy-sensitive patients relapsing after autologous transplantation. Patients with myeloma (MM, 23 pts), follicular lymphoma (FL, 28 pts) or Hodgkin disease (HD, 31 pts), were compared to 276 patients who relapsed after autologous transplantation but did not underwent allogeneic stem cell transplantation (142 MM, 115 FL and 19 HD). From original datasets, 21 (91%) matched pairs could be constituted from MM patients, as compared to 19 (68%) of the FL patients, down to 15 (48%) of the HD patients. Based on these PS-matched samples, a significant benefit of reduced intensity conditioning as compared with non allografted patients was observed in MM, with estimated hazard ratio (HR) of death at 0.34 (95% confidence interval, CI: 0.14-0.88), as well as in FL (HR= 0.78, 95%CI: 0.27;2.30) and in HD (HR= 0.24; 95%CI: 0.09-0.62). MSM-based analyses that applied to the reweighted populations confirmed these trends towards survival benefits in FL, though partially erased in MM and HD.

Conclusions:

We reported the application of marginal structural models, a new class of causal models to estimate the effect of nonrandomized treatments as an alternative to PS based approaches in small samples. We expect that an increasing number of physicians involved in clinical cohorts become familiar with these novel and appealing quantitative methods when assessing innovative treatment effects.

Disclosures:

No relevant conflicts of interest to declare.