Tailored monitoring of patients with monoclonal gammopathy to improve early detection of myeloma and monoclonal gammopathy of clinical significance

Earlier detection is a high priority for patients and improves survival: 84% of people with myeloma survive for >5 years if diagnosed at the earliest stage, compared with only 26% if diagnosed at advanced stage. Myeloma is most frequently diagnosed late (>3-6 months post symptom presentation) and has the longest diagnostic delay of any cancer, with emergency presentations in >30% of newly diagnosed myeloma patients who have shortened survival, cancer arising from bone marrow, is the 20th most common cause of cancer deaths worldwide and remains incurable. Myeloma (MM) is often diagnosed at an advanced stage when it has multiple effects on patients' overall well-being, including bone disease, kidney disease, and a weakened immune system. Recent treatments have improved life expectancy and quality of life. The earlier that myeloma is diagnosed and treated, the more effectively symptoms are controlled, improving patient survival and reducing healthcare costs associated with treating late-stage myeloma and attendant co-morbidities. Every myeloma arises from a preceding, often symptomless and undiagnosed condition called Monoclonal Gammopathy of Undetermined Significance (MGUS), occurring in ~3% people aged 50 years and over. Screening >50s for MGUS and monitoring for progression using the existing inexpensive diagnostic blood test would enable myeloma early diagnosis but is unlikely to be cost-effective as most people with MGUS do not develop MM. Monoclonal gammopathy of clinical significance (MGCS) is a recently coined termed to capture a set of monoclonal gammopathy patients who have kidney impairment, nerve damage, bone fractures or skin lesions directly linked to the presence or deposition of the monoclonal protein. Lack of recognition of this clinical association leads to diagnostic delay and irreversible damage to organs involved. Therefore, we aim to specifically identify MGUS patients at high risk of progression to myeloma and / or MGCS.
Objective 1: Understanding the symptom burden, and additional clinical parameters driving the test request, which lands an incidental diagnosis of MGUS is key. Using access to Clinical practice research data link (CPRD) primary care records on patients coded as monoclonal gammopathy to generate this dataset. We will identify set of predictors for transformation from MGUS to MM. CPRD data will also enable identification of clinical associations recently described as MGCS conditions.
Objective 2: Oxford University Hospital, we have recently established the OxCom clinical service funded by Oxfordshire Clinical Commissioning Group to improve serial MGUS monitoring for patients in the Oxfordshire community. This funding has been allocated to address the lack of serial follow up of MGUS patients; patients are often lost to follow up, and GPs' are unable to address clinical concerns generated by MGUS patients in primary care. This OxCom infrastructure enables us to generate a prospective dataset with detailed clinical and laboratory data. Hypothesis generating observations generated from the CPRD datasets can be validate in this prospective MGUS database. We will validate the primary care prection model in the OxCom database.
Objective 3: Recent observations have shown that aberrant changes to light chains secrete dby MGUS patients can help predict who would develop MGCS, and/or potentially transform to myeloma. Working with Department of Chemistry at Oxford we can prospectively evaluate these preliminary observations in the surplus patient samples obtained from the OxCom service. These shared research-enabling resources will help drive improvements in early diagnosis and MGUS/myeloma care in the NHS.
My vision is to harness the multidisciplinary expertise in Oxford across big data analysis (primary care data), joined up secondary care clinical services and protein chemistry expertise to improve monitoring of MGUS patients, and enable early diagnosis of MGCS and myeloma.

Earlier detection is a high priority for patients and improves survival: 84% of people with myeloma survive for >5 years if diagnosed at the earliest stage, compared with only 26% if diagnosed at advanced stage. Myeloma is most frequently diagnosed late (>3-6 months post symptom presentation) and has the longest diagnostic delay of any cancer, with emergency presentations in >30% of newly diagnosed myeloma patients who have shortened survival. Because MGUS precedes all myelomas, an early diagnosis strategy of monitoring all MGUS patients for progression to myeloma, is impractical. Progression risk is ~1%/year in the MGUS population, with a prevalence of 3.2% in individuals >50 years. In addition, over the last few years, well defined clinical association of organ damage secondary to monoclonal protein in a MGUS setting has been described. This has been grouped under single diagnosis category of MGCS. Lack of optimal risk stratified monitoring for MGUS patients makes screening inefficient. Therefore, research is required to develop better monitoring/ tools. Exploring clinical characteristics of MGUS patient populations from primary care records (CPRD database) who remain in MGUS state versus those who transformed to myeloma will enable understanding of clinical predictors of disease progression. In addition, we will attempt to quantify the burden of undiagnosed MGCS patients in primary care. Oxfordshire CCG has funded an OxCom MGUS monitoring service to enable streamlined monitoring of MGUS patients in Oxfordshire. Prediction model from CPRD data will be validated in this database of 3000 MGUS patients with annual increment of 1000 patients per year. A recent observation that aberrant glycosylation of light chain drives MGUS to MGCS and/ or myeloma transition, has generated a new hypothesis. We can test this hypothesis using longitudinal excess diagnostic serum samples in a prospective MGUS to myeloma cohort vs controls, run alongside OxCoM MGUS patient pathway