Real World Data as a control group, an ALS case study
Matteo Locatelli1, Alex Berger1, Alexander Sherman2
1MGH, 2Harvard Medical School
Objective:
Assess the effect of treatment with Real World Data (RWD) using Propensity Score Matching
Background:

In clinical research, the gold standard is to use a randomized controlled trial (RCT) to assess the effect of a treatment.

Thanks to the effort of many centers and institutes, the availability of retrospective data about Amyotrophic lateral sclerosis (ALS) is growing.

Since it’s a rare disease, enrolling patients for a study is always challenging, and providing the placebo to patients raises ethical questions.

Propensity score matching (PSM) aims to equate treatment groups concerning measured baseline covariates to achieve a comparison with reduced selection bias. It is a valuable statistical methodology mimics the RCT and may create an "apples to apples" comparison while reducing bias due to confounding.
Design/Methods:

Ceftriaxone injection treats certain infections caused by bacteria.

The ALS/MND Natural History consortium, comprising nine ALS clinics, collects real-world data on patients with ALS/MND, including medical history, medication, longitudinal outcomes, survival, and demographics. To extract causal inferences from this observational data set, PSM was used to create a dataset balanced on common factors known or believed to associate with ALS survival and progression and inclusion and exclusion criteria.

P-values were calculated using the Sharp Null Hypothesis and simulation rather than asymptotically.
Results:

First results show no differences in survival and ALSFRS-R functional between patients who received CEFTRIAXONE and matched patients from RWD. These results are the same as from the RCT.

Conclusions:
Thanks to the matching methodologies, RWD can be used as the control group avoiding the placebo.
10.1212/WNL.0000000000202294