Myeloma
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High-Risk Multiple Myeloma Written by Dr Roisin McAvera (Postdoctoral Researcher RCSI), Miss Niamh McAuley (PhD Student RCSI), Prof Ann Hopkins (Associate Professor RCSI), Prof Siobhan Glavey (Clinician-Scientist Beaumont Hospital/RCSI)
Introduction Multiple myeloma (MM) is a haematological malignancy characterised by the clonal expansion of malignant plasma cells in the bone marrow. MM manifests clinically as hypercalcaemia, renal failure, anaemia and bone lesions (known as CRAB features), with a median age of diagnosis of 71 in Ireland.1 MM affects around 384 people in Ireland each year1 and despite advancements in treatments remains incurable in 2024, as patients eventually relapse. At a genomic level MM is extremely heterogeneous, meaning patients present with a wide range of different genetic abnormalities. As a result, patient outcome and response to treatment also varies. Despite this, personalised treatment plans are still in their infancy relative to those in some of the more common solid cancers, with MM patients generally treated in a similar manner. Treatment of MM normally consists of a combination of two, three or even four drugs from different classes. Treatment approaches vary, depending on patient fitness, co-morbidities, disease features and eligibility for an autologous stem cell transplant (ASCT). Initial treatment in Ireland at present consists of one of the following National Cancer Control Programme (NCCP)-approved
regimens; RVD (bortezomib, lenalidomide, dexamethasone), VMP (bortezomib, melphalan, prednisone), CyBorD (cyclophosphamide, bortezomib, dexamethasone), Rd (lenalidomide, dexamethasone) or most recently D-VTD (daratumumab, bortezomib, thalidomide, dexamethasone). Notwithstanding significant improvements to patient prognosis as a result of these drug combinations, the median survival of MM patients is currently still low, at around 6 years.2 However, in reality patient outcome varies significantly. ‘High-risk’ MM patients tend to
Dr Roisin McAvera
Niamh McAuley
have a median survival of 2-3 years, whilst for ‘standard-risk’ patients this is 7-10 years.2 There are several methods to identify high-risk patients and, as a result, a major clinical challenge is the lack of standardisation. Ideally, a standardised approach to risk-stratification would aid with streamlined characterisation of patient response in different risk groups, and potentially enable risk-adapted treatment plans in the future. In this article, we will discuss some of the commonly employed methods to identify high-risk MM, with a focus on those related to our own research at the Royal College of Surgeons in Ireland (RCSI) University of Medicine and Health Sciences, Dublin.
Current Risk Classification Most current classification systems used for MM incorporate common cytogenetic abnormalities as detected by fluorescence in situ hybridisation (FISH). In 2005, the International Myeloma Working Group (IMWG) introduced the International Staging System (ISS) to stratify patients into three prognostic groups. ISS criteria are based on the clinical levels of serum β2 microglobulin and serum albumin. In 2015, this was revised (R-ISS) to include the level of lactate dehydrogenase (LDH) and several cytogenetic abnormalities, specifically high-risk cytogenetic abnormalities t(4;14), t(14;16) or del(17p).3 The R-ISS criteria are shown in Table 1.
Table 1. Revised International Staging System (R-ISS) for Risk Classification of MM
Stage I
All of the following: • Serum albumin ≥3.5 gm/dL • Serum beta-2-microglobulin <3.5 mg/L • No high-risk cytogenetics • Normal serum LDH level Stage II Not fitting Stage I or III Stage III Both of the following: • Serum beta-2-microglobulin >5.5 mg/L • High-risk cytogenetics [t(4;14), t(14;16), or del(17p)] or elevated serum lactate dehydrogenase level Table 1. Revised International Staging System (R-ISS) for Risk Classification of MM Additionally, the Mayo Stratification for Myeloma and Risk-adapted Therapy (mSMART) guidelines | HPN • FEBRUARY HOSPITALPROFESSIONALNEWS.IE 2024 use several more genetic factors to guide genetic risk, such as gain(1q), p53 mutation, and gene
