A new study funded by the Lupus Nephritis Trials Network with support from the Lupus Research Alliance has proposed a set of standardized measures that promise to improve the way clinical trials in lupus nephritis (LN) are structured and how clinical researchers report their results. The findings will also help researchers in their search for new treatments for LN —inflammation of the kidneys.
In treating LN, the goal is to preserve kidney function as long as possible. But before researchers can test a new treatment, they need to know how and where to target it. Which early signs or symptoms are most important? Which ones are most likely to respond to treatment? And which are the best predictors of full-blown LN later in life?
Offering answers to these questions, Dr. Meggan Mackay and nearly 30 co-authors published their findings in the March 2019 issue of Arthritis & Rheumatology. They found effective, short-term measures that make sense in today’s clinical trials.
Many clinical trials last only one year or less. Researchers need to work within a very limited time frame to figure out precisely which signs or symptoms should be treated early in order to prevent future, more serious kidney disease, which can take years to develop. LN occurs in about 50 percent of people with lupus, so the issue of how to structure today’s shorter trials is a matter of some urgency.
The researchers looked at data collected during patient care in the first 12 months of treatment. They also analyzed data pertaining to race, age and gender. The investigators developed a statistical model that was able to predict with a relatively short period of time, 1 year of treatment, the risk for long-term kidney outcomes such as chronic kidney disease, severe kidney injury and need for kidney transplantation.
The team also noted the importance of the following risk factors for LN:
- proteinuria (an abnormal amount of protein in the urine)
- serum creatinine (abnormal levels of a waste product creatinine in the blood)
- black race
- younger age
Being able to predict during the clinical trial period the effects of the experimental treatment on the long-term kidney outcomes offers a great opportunity for enhancing drug development for LN and a great hope for improved prognosis and treatments for patients. However, before these predictive models can be used as surrogate markers—replacement for established clinical trial outcome measures—they will need to be tested and confirmed to hold true in further clinical studies.