Development of a myeloma case-finding approach for higher-risk patients: analysis of routine blood tests

Background Myeloma, a type of blood cancer, is one of the hardest cancers to diagnose.

It is relatively rare and the main presenting symptoms, including back pain, bone pain, tiredness and repeated infections, are non-specific and common to many non-cancer conditions that occur in the elderly.

Diagnosing myeloma early is important to prevent disease-related complications which can impact on quality of life and survival. Aims The project is aimed at improving the early diagnosis of myeloma. The specific aim is to develop a myeloma case-finding approach for higher-risk patients based on routine blood tests.

The rationale for this approach is that many myeloma patients will have numerous blood tests in the years before diagnosis (e.g. blood counts, renal and liver function, inflammatory markers), predominantly for reasons unrelated to myeloma, and that people at higher-risk of myeloma can be identified from these tests and their evolution over time.

Methods A nested case-control study will be conducted using de-identified data from Leeds Teaching Hospitals Trust including pathology, clinical and demographic data for myeloma patients and non-myeloma controls.

We will consider as a separate group, patients with the myeloma precursor monoclonal gammopathy of undetermined significance (MGUS).

We will compare and describe the number and type of blood test conducted in patients subsequently diagnosed with myeloma, MGUS and non-myeloma controls, as well as plotting trajectories of the blood test results in these three groups.

A risk prediction model will be developed and internally validated to identify people at high-risk of having myeloma based on these results and clinical data.

We will develop an early economic model to explore whether an automatic triage testing pathway for those at high risk of myeloma has the potential to be cost-effective.

How the results of this research will be used Following algorithm development, future funding would be sought to conduct a prospective multi-centre study aiming to implement the algorithm and reflex-test individuals identified at higher-risk of myeloma.

This would be with the aim of determining the impact on time to diagnosis, patient outcomes including quality of life and estimated costs to the NHS.

Assessment of overall benefits and harms of earlier diagnosis, including a potential increase in MGUS cases would also be performed.

If successful, there is clear line of sight to implementation within the clinical setting, capitalising on the existing healthcare infrastructure with the potential for a paradigm shift in the diagnostic pathway for myeloma.