Firstly, could you tell us what Tyrosinemia Type 1 is?

Tyrosinemia type 1 (TYR1) is a rare genetic disorder that is associated with liver, kidney, and neurological disease. Often symptoms begin within the first few months of life, and include fever, diarrhea, bloody stools, and vomiting.

Historically, the outcomes for individuals who have TYR1 have been poor, with death from liver failure and kidney disease common during childhood. Until the early 1990s the only management strategies for TYR1 were dietary restrictions and liver transplantation. In 1992 a new treatment, nitisinone, was introduced which has had a dramatic effect on the lives of people who have TYR1.

Should we screen for Tyrosinemia type 1?

Screening for TYR1 during the newborn period is carried out in many countries across the world. We decide whether to screen for most diseases using a trial which randomizes large numbers of people to be offered screening or not offered screening. This doesn’t work for very rare diseases because the sample sizes required would be too large. Instead we often assemble evidence along the screening pathway investigating how accurate the test is, and whether detecting the disease earlier at screening would improve survival or quality of life.

How accurate is the test?

Screening tests are not perfect; they give us an indication about a person’s risk but not a definitive answer about whether or not someone truly has the disease that is being searched for.

The test uses tandem mass spectrometry to measure the amount of succinylacetone (a toxic metabolite) that is present in dried blood spots. Succinylacetone is known to be higher in people who have TYR1. This new method of identification has facilitated earlier detection, with some studies suggesting it correctly identifies 100% of those with and without TYR1. However, this research has relied on the assumption that people who screened negative (i.e. elevated succinylacetone was not detected during screening) truly do not have the disease.

Screening tests are not perfect; they give us an indication about a person’s risk but not a definitive answer about whether or not someone truly has the disease that is being searched for. In some cases people who have tested positive will not have the disease (false positive) and, conversely, some people who screen negative will have the disease (false negative).

Without following up everyone who has screened negative, we cannot know how good a screening test really is. But to follow up everyone and expose them to further, often invasive, testing would be prohibitively expensive and practically unfeasible.

Is earlier treatment after screening better?

The current treatment strategy for TYR1 consists of a protein-restricted diet with medication (nitisinone). Nitisinone reduces the formation of toxic metabolites, and since it became available, dramatic improvements have been reported in mortality and morbidity.

There is some suggestion that outcomes for people who have TYR1 are better when the treatment with nitisinone is initiated before signs and symptoms present. We recently reviewed all of the published data and found that while there is consistent evidence that nitisinone is an effective, treatment the apparent ‘early initiation’ benefit might reflect biases in the studies rather than any genuine enhanced effect.

Why is rare disease research so difficult?

Our reviews have raised a number of important issues that are related to research with people who have rare diseases. For example, the numbers of participants are usually small and have diverse characteristics, and the studies lack control groups and comparator treatments. These types of problems are extremely challenging, and in some cases impossible, to address through the normal methods of including more participants and conducting randomized controlled trials.

There are other approaches, such as different study designs (cross-over and n-of-1 trials) and piecing together the test accuracy and benefits of earlier treatment as a replacement for a trial. These alternatives will always provide more biased estimates, and so decision-makers have greater uncertainty.