Haematology patients and the risk of transfusion transmitted infection.

A 2014 study by NHS Blood and Transplant indicated that over one quarter of red cells were transfused to patients with haematological conditions. For platelet components, the figure is higher. Certain diagnostic groups, such as haemoglobinopathies, myelodysplastic syndromes and some haemato-oncology patients, receive multiple transfusion episodes, either over long periods, or more intensively over shorter periods. Haematology patients account for the majority of the multi-transfused population. The risk of transfusion-transmitted infection (TTI) increases with number of donor exposures, and the consequences of TTI are often more significant in immunosuppressed individuals. Historically, use of pooled plasma products in patients with clotting disorders resulted in widespread transmission of hepatitis B virus, hepatitis C virus and human immunodeficiency virus before effective screening and viral inactivation methods were introduced.

Adaptation of a multiple myeloma minimal residual disease multicolor flow cytometry assay for real-world practice.

BACKGROUND: Achieving minimal residual disease (MRD) negativity following treatment for multiple myeloma (MM) is associated with improved progression free and overall survival. In the UK, MRD assessments in MM are not incorporated into routine clinical use outside trials. Widely used in other haematological malignancies, there is a role for widening the availability of myeloma MRD assays to laboratories outside larger treating centers. METHODS: We set up and assessed concordance of a multicolor flow cytometry (MCF) assay for MM MRD in collaboration with a reference center including validity following delayed processing of samples using an optimized fixation step. We then conducted a real-world snapshot of MRD results in a cohort of newly diagnosed transplant-eligible patients treated with UK standard induction therapies at the time of analysis. RESULTS: 43 MCF MRD samples run in parallel with a reference center showed high correlation and minimal bias. 24 samples were split and processed in duplicate both fixed and fresh, with strong correlation, minimal bias, and no change in plasma cell phenotype by flow markers confirming a 6-day delay in processing did not affect assay performance. A real-world snapshot found 17% (10/58) of patients were MRD-negative post-bortezomib-based triplet induction therapy. CONCLUSIONS: We successfully adopted a reference MCF MM MRD method which was stable for up to 6 days following sample collection potentially allowing broader access of this assay to smaller laboratories which would facilitate further investigation of the prognostic value and clinical utility of MRD assessments outside the trial setting in real-world practice.

Impact of timing of stem cell return following high dose melphalan in multiple myeloma patients with renal impairment: a single center experience.

High dose melphalan (HDM) followed by autologous stem cell transplantation (ASCT) remains the standard consolidation in transplant eligible multiple myeloma (MM) patients. The timing between HDM administration and hematopoietic stem cell return (HSCR) varies among institutions, with a 'rest period' of 48 hours (h) employed by some for patients with renal impairment (RI). We investigated the differences in hematopoietic recovery and HDM toxicity between MM patients with RI who had HSCR after 24 vs 48 h from HDM. Fifty MM patients with RI (48 h group; n = 31 and 24 h group; n = 19) were included. No statistically significant differences were noted in surrogates for hematopoietic recovery and HDM toxicity between both groups. Only one death occurred in the 24 h group. No patients required renal replacement therapy. Therefore, a 24 h period between HDM and AHSC infusion appears safe for MM patients with RI.

Personalised progression prediction in patients with monoclonal gammopathy of undetermined significance or smouldering multiple myeloma (PANGEA): a retrospective, multicohort study.

BACKGROUND: Patients with precursors to multiple myeloma are dichotomised as having monoclonal gammopathy of undetermined significance or smouldering multiple myeloma on the basis of monoclonal protein concentrations or bone marrow plasma cell percentage. Current risk stratifications use laboratory measurements at diagnosis and do not incorporate time-varying biomarkers. Our goal was to develop a monoclonal gammopathy of undetermined significance and smouldering multiple myeloma stratification algorithm that utilised accessible, time-varying biomarkers to model risk of progression to multiple myeloma. METHODS: In this retrospective, multicohort study, we included patients who were 18 years or older with monoclonal gammopathy of undetermined significance or smouldering multiple myeloma. We evaluated several modelling approaches for predicting disease progression to multiple myeloma using a training cohort (with patients at Dana-Farber Cancer Institute, Boston, MA, USA; annotated from Nov, 13, 2019, to April, 13, 2022). We created the PANGEA models, which used data on biomarkers (monoclonal protein concentration, free light chain ratio, age, creatinine concentration, and bone marrow plasma cell percentage) and haemoglobin trajectories from medical records to predict progression from precursor disease to multiple myeloma. The models were validated in two independent validation cohorts from National and Kapodistrian University of Athens (Athens, Greece; from Jan 26, 2020, to Feb 7, 2022; validation cohort 1), University College London (London, UK; from June 9, 2020, to April 10, 2022; validation cohort 1), and Registry of Monoclonal Gammopathies (Czech Republic, Czech Republic; Jan 5, 2004, to March 10, 2022; validation cohort 2). We compared the PANGEA models (with bone marrow [BM] data and without bone marrow [no BM] data) to current criteria (International Myeloma Working Group [IMWG] monoclonal gammopathy of undetermined significance and 20/2/20 smouldering multiple myeloma risk criteria). FINDINGS: We included 6441 patients, 4931 (77%) with monoclonal gammopathy of undetermined significance and 1510 (23%) with smouldering multiple myeloma. 3430 (53%) of 6441 participants were female. The PANGEA model (BM) improved prediction of progression from smouldering multiple myeloma to multiple myeloma compared with the 20/2/20 model, with a C-statistic increase from 0·533 (0·480-0·709) to 0·756 (0·629-0·785) at patient visit 1 to the clinic, 0·613 (0·504-0·704) to 0·720 (0·592-0·775) at visit 2, and 0·637 (0·386-0·841) to 0·756 (0·547-0·830) at visit three in validation cohort 1. The PANGEA model (no BM) improved prediction of smouldering multiple myeloma progression to multiple myeloma compared with the 20/2/20 model with a C-statistic increase from 0·534 (0·501-0·672) to 0·692 (0·614-0·736) at visit 1, 0·573 (0·518-0·647) to 0·693 (0·605-0·734) at visit 2, and 0·560 (0·497-0·645) to 0·692 (0·570-0·708) at visit 3 in validation cohort 1. The PANGEA models improved prediction of monoclonal gammopathy of undetermined significance progression to multiple myeloma compared with the IMWG rolling model at visit 1 in validation cohort 2, with C-statistics increases from 0·640 (0·518-0·718) to 0·729 (0·643-0·941) for the PANGEA model (BM) and 0·670 (0·523-0·729) to 0·879 (0·586-0·938) for the PANGEA model (no BM). INTERPRETATION: Use of the PANGEA models in clinical practice will allow patients with precursor disease to receive more accurate measures of their risk of progression to multiple myeloma, thus prompting for more appropriate treatment strategies. FUNDING: SU2C Dream Team and Cancer Research UK.