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Objectives: The use of cost-effectiveness methods to support policy decisions has become well established, but difficulties can arise when evaluating a new treatment that is indicated to be used in combination with an established backbone treatment. If the latter has been priced close to the decision maker's willingness-to-pay threshold, this may mean that there is no headroom for the new treatment to demonstrate value, at any price, even if the combination is clinically effective. Without a mechanism for attributing value to component treatments within a combination therapy, the health system risks generating negative funding decisions for combinations of proven clinical benefit to patients. The aim of this work was to define a value attribution methodology, which could be used to allocate value between the components of any combination treatment., Methods: The framework is grounded in the standard decision rules of cost-effectiveness analysis and provides solutions according to key features of the problem: perfect/imperfect information about component treatment monotherapy effects and balanced/unbalanced market power between their manufacturers., Results: The share of incremental value varies depending on whether there is perfect/imperfect information and balance/imbalance of market power, with some scenarios requiring the manufacturers to negotiate a share of the incremental value within a range defined by the framework., Conclusions: It is possible to define a framework that is independent of price and focuses on benefits expressed as quality-adjusted life-year gains (and/or quality-adjusted life-year equivalents for cost savings), a standard metric used by many health technology assessment agencies to evaluate novel treatments., Competing Interests: Author Disclosures Author disclosure forms can be accessed below in the Supplemental Material section., (Copyright © 2025. Published by Elsevier Inc.)

Multiple myeloma (MM) is a heterogeneous and complex disease, both in mutational biology as well as in the clinical presentation of patients. While tailored and biomarker-targeted therapy remains the direct goal for patient-centric management, existing therapies in MM remain largely uniform. Translocation t(14;16) is a rare primary genetic event found in less than 5% of patients with newly diagnosed MM. Here, we present an overview of the biology of t(14;16), epidemiology, clinical presentation, prognostic impact, and discuss the future clinical and therapeutic strategies for targeting this rare yet high-risk group in MM to optimize patient outcomes., (© 2024 Wiley Periodicals LLC.)

This Good Practice Paper provides recommendations for the use of advanced imaging for earlier diagnosis and morbidity prevention in multiple myeloma. It describes how advanced imaging contributes to optimal healthcare resource utilisation by in newly diagnosed and relapsed myeloma, and provides a perspective on future directions of myeloma imaging, including machine learning assisted reporting., (© 2024 British Society for Haematology and John Wiley & Sons Ltd.)

This Good Practice Paper provides recommendations for the diagnosis and initial management of transplant-eligible high-risk myeloma patients. It describes recent updates to the genetic diagnostics of high-risk myeloma and provides recommendations for treatment on the basis of recent prospective clinical trial evidence., (© 2024 British Society for Haematology and John Wiley & Sons Ltd.)

Historical specimens from museum collections provide a valuable source of material also from remote areas or regions of conflict that are not easily accessible to scientists today. With this study, we are providing a taxon-complete phylogeny of snowfinches using historical DNA from whole skins of an endemic species from Afghanistan, the Afghan snowfinch, Pyrgilauda theresae. To resolve the strong conflict between previous phylogenetic hypotheses, we generated novel mitogenome sequences for selected taxa and genome-wide SNP data using ddRAD sequencing for all extant snowfinch species endemic to the Qinghai-Tibet Plateau (QTP) and for an extended intraspecific sampling of the sole Central and Western Palearctic snowfinch species (Montifringilla nivalis). Our phylogenetic reconstructions unanimously refuted the previously suggested paraphyly of genus Pyrgilauda. Misplacement of one species-level taxon (Onychostruthus tazcanowskii) in previous snowfinch phylogenies was undoubtedly inferred from chimeric mitogenomes that included heterospecific sequence information. Furthermore, comparison of novel and previously generated sequence data showed that the presumed sister-group relationship between M. nivalis and the QTP endemic M. henrici was suggested based on flawed taxonomy. Our phylogenetic reconstructions based on genome-wide SNP data and on mitogenomes were largely congruent and supported reciprocal monophyly of genera Montifringilla and Pyrgilauda with monotypic Onychostruthus being sister to the latter. The Afghan endemic P. theresae likely originated from a rather ancient Pliocene out-of-Tibet dispersal probably from a common ancestor with P. ruficollis. Our extended trans-Palearctic sampling for the white-winged snowfinch, M. nivalis, confirmed strong lineage divergence between an Asian and a European clade dated to 1.5 - 2.7 million years ago (mya). Genome-wide SNP data suggested subtle divergence among European samples from the Alps and from the Cantabrian mountains., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Multiple myeloma (MM) is an incurable malignancy of plasma cells. Epidemiological studies indicate a substantial heritable component, but the underlying mechanisms remain unclear. Here, in a genome-wide association study totaling 10,906 cases and 366,221 controls, we identify 35 MM risk loci, 12 of which are novel. Through functional fine-mapping and Mendelian randomization, we uncover two causal mechanisms for inherited MM risk: longer telomeres; and elevated levels of B-cell maturation antigen (BCMA) and interleukin-5 receptor alpha (IL5RA) in plasma. The largest increase in BCMA and IL5RA levels is mediated by the risk variant rs34562254-A at TNFRSF13B. While individuals with loss-of-function variants in TNFRSF13B develop B-cell immunodeficiency, rs34562254-A exerts a gain-of-function effect, increasing MM risk through amplified B-cell responses. Our results represent an analysis of genetic MM predisposition, highlighting causal mechanisms contributing to MM development., (© 2024. The Author(s).)

Purpose: Outcomes for patients with newly diagnosed multiple myeloma (NDMM) are heterogenous, with overall survival (OS) ranging from months to over 10 years., Methods: To decipher and predict the molecular and clinical heterogeneity of NDMM, we assembled a series of 1,933 patients with available clinical, genomic, and therapeutic data., Results: Leveraging a comprehensive catalog of genomic drivers, we identified 12 groups, expanding on previous gene expression-based molecular classifications. To build a model predicting individualized risk in NDMM (IRMMa), we integrated clinical, genomic, and treatment variables. To correct for time-dependent variables, including high-dose melphalan followed by autologous stem-cell transplantation (HDM-ASCT), and maintenance therapy, a multi-state model was designed. The IRMMa model accuracy was significantly higher than all comparator prognostic models, with a c-index for OS of 0.726, compared with International Staging System (ISS; 0.61), revised-ISS (0.572), and R2-ISS (0.625). Integral to model accuracy was 20 genomic features, including 1q21 gain/amp, del 1p, TP53 loss, NSD2 translocations, APOBEC mutational signatures, and copy-number signatures (reflecting the complex structural variant chromothripsis). IRMMa accuracy and superiority compared with other prognostic models were validated on 256 patients enrolled in the GMMG-HD6 (ClinicalTrials.gov identifier: NCT02495922) clinical trial. Individualized patient risks were significantly affected across the 12 genomic groups by different treatment strategies (ie, treatment variance), which was used to identify patients for whom HDM-ASCT is particularly effective versus patients for whom the impact is limited., Conclusion: Integrating clinical, demographic, genomic, and therapeutic data, to our knowledge, we have developed the first individualized risk-prediction model enabling personally tailored therapeutic decisions for patients with NDMM.

For many cancers there are only a few well-established risk factors. Here, we use summary data from genome-wide association studies (GWAS) in a Mendelian randomisation (MR) phenome-wide association study (PheWAS) to identify potentially causal relationships for over 3,000 traits. Our outcome datasets comprise 378,142 cases across breast, prostate, colorectal, lung, endometrial, oesophageal, renal, and ovarian cancers, as well as 485,715 controls. We complement this analysis by systematically mining the literature space for supporting evidence. In addition to providing supporting evidence for well-established risk factors (smoking, alcohol, obesity, lack of physical activity), we also find sex steroid hormones, plasma lipids, and telomere length as determinants of cancer risk. A number of the molecular factors we identify may prove to be potential biomarkers. Our analysis, which highlights aetiological similarities and differences in common cancers, should aid public health prevention strategies to reduce cancer burden. We provide a R/Shiny app to visualise findings., (© 2024. The Author(s).)

Objectives: MAchine Learning In MyelomA Response (MALIMAR) is an observational clinical study combining "real-world" and clinical trial data, both retrospective and prospective. Images were acquired on three MRI scanners over a 10-year window at two institutions, leading to a need for extensive curation., Methods: Curation involved image aggregation, pseudonymisation, allocation between project phases, data cleaning, upload to an XNAT repository visible from multiple sites, annotation, incorporation of machine learning research outputs and quality assurance using programmatic methods., Results: A total of 796 whole-body MR imaging sessions from 462 subjects were curated. A major change in scan protocol part way through the retrospective window meant that approximately 30% of available imaging sessions had properties that differed significantly from the remainder of the data. Issues were found with a vendor-supplied clinical algorithm for "composing" whole-body images from multiple imaging stations. Historic weaknesses in a digital video disk (DVD) research archive (already addressed by the mid-2010s) were highlighted by incomplete datasets, some of which could not be completely recovered. The final dataset contained 736 imaging sessions for 432 subjects. Software was written to clean and harmonise data. Implications for the subsequent machine learning activity are considered., Conclusions: MALIMAR exemplifies the vital role that curation plays in machine learning studies that use real-world data. A research repository such as XNAT facilitates day-to-day management, ensures robustness and consistency and enhances the value of the final dataset. The types of process described here will be vital for future large-scale multi-institutional and multi-national imaging projects., Critical Relevance Statement: This article showcases innovative data curation methods using a state-of-the-art image repository platform; such tools will be vital for managing the large multi-institutional datasets required to train and validate generalisable ML algorithms and future foundation models in medical imaging., Key Points: • Heterogeneous data in the MALIMAR study required the development of novel curation strategies. • Correction of multiple problems affecting the real-world data was successful, but implications for machine learning are still being evaluated. • Modern image repositories have rich application programming interfaces enabling data enrichment and programmatic QA, making them much more than simple "image marts"., (© 2024. The Author(s).)

Background: The Myeloma Response Assessment and Diagnosis System (MY-RADS) guidelines establish a standardised acquisition and analysis pipeline for whole-body MRI (WB-MRI) in patients with myeloma. This is the first study to assess image quality in a multi-centre prospective trial using MY-RADS., Methods: The cohort consisted of 121 examinations acquired across ten sites with a range of prior WB-MRI experience, three scanner manufacturers and two field strengths. Image quality was evaluated qualitatively by a radiologist and quantitatively using a semi-automated pipeline to quantify common artefacts and image quality issues. The intra- and inter-rater repeatability of qualitative and quantitative scoring was also assessed., Results: Qualitative radiological scoring found that the image quality was generally good, with 94% of examinations rated as good or excellent and only one examination rated as non-diagnostic. There was a significant correlation between radiological and quantitative scoring for most measures, and intra- and inter-rater repeatability were generally good. When the quality of an overall examination was low, this was often due to low quality diffusion-weighted imaging (DWI), where signal to noise ratio (SNR), anterior thoracic signal loss and brain geometric distortion were found as significant predictors of examination quality., Conclusions: It is possible to successfully deliver a multi-centre WB-MRI study using the MY-RADS protocol involving scanners with a range of manufacturers, models and field strengths. Quantitative measures of image quality were developed and shown to be significantly correlated with radiological assessment. The SNR of DW images was identified as a significant factor affecting overall examination quality., Trial Registration: ClinicalTrials.gov, NCT03188172 , Registered on 15 June 2017., Critical Relevance Statement: Good overall image quality, assessed both qualitatively and quantitatively, can be achieved in a multi-centre whole-body MRI study using the MY-RADS guidelines., Key Points: • A prospective multi-centre WB-MRI study using MY-RADS can be successfully delivered. • Quantitative image quality metrics were developed and correlated with radiological assessment. • SNR in DWI was identified as a significant predictor of quality, allowing for rapid quality adjustment., (© 2023. European Society of Radiology (ESR).)

Objective: Traumatic hip dislocations are very rare in childhood and adolescence. The aim of this multi-centre study is to analyse the current epidemiology and injury morphology of a large number of traumatic hip dislocations in children. This can provide a better understanding of childhood hip dislocations and contribute to the development of a therapeutic approach in order to prevent long-term impacts., Methodology: This retrospective, anonymised multi-centre study included patients, aged up to 17 years, with acute traumatic hip dislocations and open growth plates. The patients came from 16 German hospitals. Exclusion criteria included insufficient data, a positive history of hip dysplasia, or an association with syndromal, neurological or connective tissue diseases predisposing to hip dislocation. An analysis was carried out on the patients' anthropometric data and scans (X-ray, MRI, CT), which were collected between 1979 and 2021. Gender, age at the time of dislocation, associated fractures, mechanism of injury, initial treatment including time between dislocation and reduction, method of reduction, treatment algorithm following reduction and all documented complications and concomitant injuries were evaluated., Results: Seventy-six patients met the inclusion criteria. There were two age peaks at 4-8 years and 11-15 years. There was an increased incidence of girls in the under-eight age group, who had mild trauma, and in the group of over-eights there were more boys, who had moderate and severe trauma. Dorsal dislocation occurred in 89.9% of cases. Mono-injuries dominated across all age groups. Concomitant injuries rarely occurred before the age of eight; however, they increased with increasing ossification of the acetabulum and appeared as avulsion injuries in 32% of 11-15-year-olds. Of the 76 patients, 4 underwent a spontaneous, 67 a closed and 5 a primary open reduction. A reduction was performed within 6 h on 84% of the children; however, in around 10% of cases a reduction was not performed until after 24 h. Concomitant injuries needing intervention were identified in 34 children following reduction. Complications included nerve irritation in the form of sensitivity disorders (n = 6) as well as avascular necrosis (AVN) of the femoral head in 15.8% of the patients (n = 12)., Conclusions: Traumatic hip dislocations are rare in childhood and adolescence and have high complication rates. The most severe complication, femoral head necrosis, occurred in 16% of cases. Minor injuries, especially in younger children, are enough to cause a dislocation. Posterior dislocation was more frequent and primarily occurred as a mono-injury; however, concomitant injuries must be considered with increasing age. Children continue to experience delayed reductions. The length of time until reduction, age and the severity of the concomitant injury play a role in the development of femoral head necrosis; however, this topic requires additional investigation., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany.)

For many cancers there are few well-established risk factors. Summary data from genome-wide association studies (GWAS) can be used in a Mendelian randomisation (MR) phenome-wide association study (PheWAS) to identify causal relationships. We performed a MR-PheWAS of breast, prostate, colorectal, lung, endometrial, oesophageal, renal, and ovarian cancers, comprising 378,142 cases and 485,715 controls. To derive a more comprehensive insight into disease aetiology we systematically mined the literature space for supporting evidence. We evaluated causal relationships for over 3,000 potential risk factors. In addition to identifying well-established risk factors (smoking, alcohol, obesity, lack of physical activity), we provide evidence for specific factors, including dietary intake, sex steroid hormones, plasma lipids and telomere length as determinants of cancer risk. We also implicate molecular factors including plasma levels of IL-18, LAG-3, IGF-1, CT-1, and PRDX1 as risk factors. Our analyses highlight the importance of risk factors that are common to many cancer types but also reveal aetiological differences. A number of the molecular factors we identify have the potential to be biomarkers. Our findings should aid public health prevention strategies to reduce cancer burden. We provide a R/Shiny app (https://mrcancer.shinyapps.io/mrcan/) to visualise findings., Competing Interests: CONFLICT-OF-INTEREST DISCLOSURE The authors declare no competing financial interests.

Introduction: Multiple myeloma is a plasma cell malignancy that accounts for 1%-2% of newly diagnosed cancers.At diagnosis, approximately 20% of patients can be identified, using cytogenetics, to have inferior survival (high-risk). Additionally, standard-risk patients, with detectable disease (minimal residual disease (MRD)-positive) postautologus stem cell transplant (ASCT), fare worse compared with those who do not (MRD-negative). Research is required to determine whether a risk-adapted approach post-ASCT could further improve patient outcomes., Methods: RADAR is a UK, multicentre, risk-adapted, response-guided, open-label, randomised controlled trial for transplant-eligible newly diagnosed multiple myeloma patients, using combinations of lenalidomide (R), cyclophosphamide (Cy), bortezomib (Bor), dexamethasone (D) and isatuximab (Isa).Participants receive RCyBorD(x4) induction therapy, followed by high-dose melphalan and ASCT. Post-ASCT, there are three pathways as follows:A phase III discontinuation design to assess de-escalating therapy in standard-risk MRD-negative patients. Participants receive 12 cycles of Isa maintenance. Those who remain MRD-negative are randomised to either continue or stop treatment.A phase II/III multiarm multistage design to test treatment strategies for treatment escalation in standard-risk MRD-positive patients. Participants are randomised to either; R, RBorD(x4) +R, RIsa, or RBorIsaD(x4) + RIsa.A phase II design to assess the activity of intensive treatment strategies in high-risk patients. Participants are randomised to RBorD(x4) +R or RBorIsaD(x4) + RIsa.1400 participants will be registered to allow for 500, 450 and 172 participants in each pathway. Randomisations are equal and treatment is given until disease progression or intolerance., Ethics and Dissemination: Ethical approval was granted by the London-Central Research Ethics Committee (20/LO/0238) and capacity and capability confirmed by the appropriate local research and development department for each participating centre prior to opening recruitment. Participant informed consent is required before trial registration and reconfirmed post-ASCT. Results will be disseminated by conference presentations and peer-reviewed publications., Trial Registration Number: ISCRTN46841867., Competing Interests: Competing interests: ABC, KLR, DAC, AH, CO, LBai, LBar, AP and RL report grants and non-financial support from BMS/Celgene, grants and non-financial support from Merck Sharpe & Dohme, grants and non-financial support from Amgen, grants and non-financial support from Takeda, during the conduct of the trial. DAC also reports travel support from Celgene Corporation. KY, RDT, CB, GJ, GP, MC, BD, DM, GC, HA, KR,SA and AC have no conflicting interests to declare. MC declares, Bristol Myers Squibb- employee, Honoraria/travel support in the last 3 years from, Amgen, BMS/Celgene, Janssen, Takeda, Abbvie. CP declares BMS/Celgene Ad boards and speaker fees, Sanotif—Ad board, speaker fees, conference registration fees. JS reports Carrying out consultancy work (Advisory Board) for Sanofi. And an educational speaking engagement for Celgene/BMS RP declares; Honoraria—Jannsen, BMS, Abbvie, GSK. Consultancy: GSK, Janssen. Meeting support: Janssen, Takeda, BMS. RO declares- Janssen - advisory board, honoraria, Celegene— honoraria, Beigene - advisory board, honoraria, Astra Zeneca—honoraria. MK declares inter-relationships: AbbVie: consultancy; Amgen: honoraria; BMS/Celgene: consultancy, research funding (institution); GSK: consultancy; Janssen: consultancy, research funding (institution); Karyopharm: consultancy; Pfizer: consultancy; SeattleGenetics: consultancy; Takeda: consultancy; Sanofi: honoraria. MD reports owning stock in Abingdon Health. SQ is the founder and CSO of Achilles therapeutics a company developing T cell therapies for solid tumours., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ.)

Introduction: Multiple myeloma is a malignancy of plasma cells with around 6000 new cases per year in the UK. Cyclophosphamide plus prednisolone is considered a standard of care for disease and symptom control in the advanced relapsed or refractory myeloma setting within the UK NHS. The selective nuclear export inhibitor, selinexor, has been relatively well tolerated in previous clinical trials and offers promise when used in combination with a wide range of other anti-cancer treatments. Here, we investigate if the addition of selinexor can improve responses to cyclophosphamide plus prednisolone without adding prohibitive toxicity., Methods and Analysis: MUKtwelve is a UK-based, randomised, controlled, open, parallel group, multicentre phase II trial designed to evaluate clinical efficacy of selinexor in combination with cyclophosphamide and prednisolone (SCP) in patients with relapsed or refractory multiple myeloma. A calibration arm will receive cyclophosphamide and prednisolone alone (CP). Participants who experience disease progression on the CP arm may, if eligible, receive SCP.The MUK twelve trial results will be the first to assess clinical efficacy of selinexor with low-dose CP in relapsed/refractory multiple myeloma. It is widely accepted that the relapsing-remitting nature of the disease is accompanied by cellular changes that often result in the requirement for novel agents and drug combinations to regain disease control. Patients also often experience cumulative toxicities throughout their treatments, limiting the treatment intensity that can be given at relapse. Thus, there is a need for novel effective combination therapies with acceptable toxicity profiles., Ethics and Dissemination: Ethics approval is obtained. Results will be submitted for publication in a peer-reviewed journal., Trial Registration Number: ISRCTN15028850., Competing Interests: Competing interests: JK, AH, SR and SB declare they have no competing interests; MG has served as a consultant and received honoraria from Novartis; KB: honoraria and travel support from Celgene and Janssen; MK has served as a consultant and received honoraria from Celgene, Takeda, Amgen, Chugai, BMS, AbbVie and Janssen, and has received research funding from Celgene., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Introduction: Whole-body MRI (WB-MRI) is recommended by the National Institute of Clinical Excellence as the first-line imaging tool for diagnosis of multiple myeloma. Reporting WB-MRI scans requires expertise to interpret and can be challenging for radiologists who need to meet rapid turn-around requirements. Automated computational tools based on machine learning (ML) could assist the radiologist in terms of sensitivity and reading speed and would facilitate improved accuracy, productivity and cost-effectiveness. The MALIMAR study aims to develop and validate a ML algorithm to increase the diagnostic accuracy and reading speed of radiological interpretation of WB-MRI compared with standard methods., Methods and Analysis: This phase II/III imaging trial will perform retrospective analysis of previously obtained clinical radiology MRI scans and scans from healthy volunteers obtained prospectively to implement training and validation of an ML algorithm. The study will comprise three project phases using approximately 633 scans to (1) train the ML algorithm to identify active disease, (2) clinically validate the ML algorithm and (3) determine change in disease status following treatment via a quantification of burden of disease in patients with myeloma. Phase 1 will primarily train the ML algorithm to detect active myeloma against an expert assessment ('reference standard'). Phase 2 will use the ML output in the setting of radiology reader study to assess the difference in sensitivity when using ML-assisted reading or human-alone reading. Phase 3 will assess the agreement between experienced readers (with and without ML) and the reference standard in scoring both overall burden of disease before and after treatment, and response., Ethics and Dissemination: MALIMAR has ethical approval from South Central-Oxford C Research Ethics Committee (REC Reference: 17/SC/0630). IRAS Project ID: 233501. CPMS Portfolio adoption (CPMS ID: 36766). Participants gave informed consent to participate in the study before taking part. MALIMAR is funded by National Institute for Healthcare Research Efficacy and Mechanism Evaluation funding (NIHR EME Project ID: 16/68/34). Findings will be made available through peer-reviewed publications and conference dissemination., Trial Registration Number: NCT03574454., Competing Interests: Competing interests: AR receives honoraria for educational lecture at Garmisch International Symposium, has an unpaid role on the European Society of Radiology Board of Directors and receives travel cost support where necessary. BG receives grants from other entities; EU commission and UKRI London Medical Imaging & Artificial Intelligence Centre for Value Based Healthcare, is a Scientific advisor for Kheiron Medical Technologies (January 2018–September 2021) and receives stock options as part of standard employment packages from both Kheiron Medical Technologies and HeartFlow. EA has a patent pending for Machine Learning in Alzheimer’s disease and has a role on the scientific advisory board for Radiopharm Theranostics Limited. MK receives grants from both Myeloma UK and Celgene/BMS, and consulting fees or payments from AbbVie, BMS/Celgene, Janssen, GSK, Karyopharm, Takeda and Seagen. CM & DK receive additional funding as a co-investigator on a radiology NIHR study and is part of the joint venture Celescan with the Royal Marsden, The Institute of Cancer Research and Sopra Steria. TB receives additional funding from CRUK grant funding (NCITA) and NIHR (HTA) and receives honoraria from Bayer., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

In the primary analysis of the phase III COLUMBA study, daratumumab by subcutaneous administration (DARA SC) demonstrated non-inferiority to intravenous administration (DARA IV) for relapsed or refractory multiple myeloma (RRMM). Here, we report the final analysis of efficacy and safety from COLUMBA after a median of 29.3 months follow-up (additional 21.8 months after the primary analysis). In total, 522 patients were randomized (DARA SC, n=263; DARA IV, n=259). With longer follow-up, DARA SC and DARA IV continued to show consistent efficacy and maximum trough daratumumab concentration as compared with the primary analysis. The overall response rate was 43.7% for DARA SC and 39.8% for DARA IV. The maximum mean (standard deviation [SD]) trough concentration (cycle 3, day 1 pre-dose) of serum DARA was 581 (SD, 315) μg/mL for DARA SC and 496 (SD, 231) μg/mL for DARA IV. Median progression-free survival was 5.6 months for DARA SC and 6.1 months for DARA IV; median overall survival was 28.2 months and 25.6 months, respectively. Grade 3/4 treatment-emergent adverse events occurred in 50.8% of patients in the DARA SC group and 52.7% in the DARA IV group; the most common (≥10%) were thrombocytopenia (DARA SC, 14.2%; DARA IV, 13.6%), anemia (13.8%; 15.1%), and neutropenia (13.1%; 7.8%). The safety profile remained consistent with the primary analysis after longer follow-up. In summary, DARA SC and DARA IV continue to demonstrate similar efficacy and safety, with a low rate of infusion-related reactions (12.7% vs. 34.5%, respectively) and shorter administration time (3-5 minutes vs. 3-7 hours) supporting DARA SC as a preferable therapeutic choice. (Clinicaltrials gov. Identifier: NCT03277105.

Immunoglobulin D (IgD) myeloma is a subtype often considered to have adverse features and inferior survival, but there is a paucity of data from large clinical studies. We compare the clinical characteristics and outcomes of patients with IgD myeloma from UK phase 3 myeloma trials analyzed in 2 groups: old (1980-2002) and recent (2002-2016) clinical trials, based on the time of adoption of novel myeloma therapies. Patients with IgD myeloma comprised 44 of 2789 (1.6%) and 70 of 5773 (1.2%) of the old and recent trials, respectively. Overall, IgD myeloma was associated with male predominance, low-level paraproteinemia (<10g/L), and λ light chain preference. The frequency of ultra-high-risk cytogenetics was similar in IgD myeloma compared with other subtypes (4.3% vs 5.3%, P > .99). Despite the old trial series being a younger group (median age: 59 vs 63 years, P = .015), there was a higher frequency of bone lesions, advanced stage at diagnosis, worse performance status, and severe renal impairment compared with the recent trials. Furthermore, the early mortality rate was significantly higher for the old trial series (20% vs 4%, P = .01). The overall response rate following induction therapy was significantly higher in the recent trials (89% vs 43%, P < .0001), and this was consistent with improved median overall survival (48 months; 95% confidence interval [CI] 35-67 months vs 22 months; 95% CI, 16-29 months). Survival outcomes for IgD myeloma have significantly improved and are now comparable to other myeloma types because of earlier diagnosis, novel therapies, and improved supportive care. This trial was registered at clinicaltrials.gov as # NCT01554852., (© 2022 by The American Society of Hematology. Licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0), permitting only noncommercial, nonderivative use with attribution. All other rights reserved.)

Background: Whole-body (WB) MRI, which includes diffusion-weighted imaging (DWI) and T 1 -w Dixon, permits sensitive detection of marrow disease in addition to qualitative and quantitative measurements of disease and response to treatment of bone marrow. We report on the first study to embed standardised WB-MRI within a prospective, multi-centre myeloma clinical trial (IMAGIMM trial, sub-study of OPTIMUM/MUKnine) to explore the use of WB-MRI to detect minimal residual disease after treatment., Methods: The standardised MY-RADS WB-MRI protocol was set up on a local 1.5 T scanner. An imaging manual describing the MR protocol, quality assurance/control procedures and data transfer was produced and provided to sites. For non-identical scanners (different vendor or magnet strength), site visits from our physics team were organised to support protocol optimisation. The site qualification process included review of phantom and volunteer data acquired at each site and a teleconference to brief the multidisciplinary team. Image quality of initial patients at each site was assessed., Results: WB-MRI was successfully set up at 12 UK sites involving 3 vendor systems and two field strengths. Four main protocols (1.5 T Siemens, 3 T Siemens, 1.5 T Philips and 3 T GE scanners) were generated. Scanner limitations (hardware and software) and scanning time constraint required protocol modifications for 4 sites. Nevertheless, shared methodology and imaging protocols enabled other centres to obtain images suitable for qualitative and quantitative analysis., Conclusions: Standardised WB-MRI protocols can be implemented and supported in prospective multi-centre clinical trials. Trial registration NCT03188172 clinicaltrials.gov; registration date 15th June 2017 https://clinicaltrials.gov/ct2/show/study/NCT03188172., (© 2022. The Author(s).)

Introduction: Multiple myeloma is a bone marrow cancer, which predominantly affects older people. The incidence is increasing in an ageing population.Over the last 10 years, patient outcomes have improved. However, this is less apparent in older, less fit patients, who are ineligible for stem cell transplant. Research is required in this patient group, taking into account frailty and aiming to improve: treatment tolerability, clinical outcomes and quality of life., Methods and Analysis: Frailty-adjusted therapy in Transplant Non-Eligible patients with newly diagnosed Multiple Myeloma is a national, phase III, multicentre, randomised controlled trial comparing standard (reactive) and frailty-adjusted (adaptive) induction therapy delivery with ixazomib, lenalidomide and dexamethasone (IRD), and to compare maintenance lenalidomide to lenalidomide+ixazomib, in patients with newly diagnosed multiple myeloma not suitable for stem cell transplant. Overall, 740 participants will be registered into the trial to allow 720 and 478 to be randomised at induction and maintenance, respectively.All participants will receive IRD induction with the dosing strategy randomised (1:1) at trial entry. Patients randomised to the standard, reactive arm will commence at the full dose followed by toxicity dependent reactive modifications. Patients randomised to the adaptive arm will commence at a dose level determined by their International Myeloma Working Group frailty score. Following 12 cycles of induction treatment, participants alive and progression free will undergo a second (double-blind) randomisation on a 1:1 basis to maintenance treatment with lenalidomide+placebo versus lenalidomide+ixazomib until disease progression or intolerance., Ethics and Dissemination: Ethical approval has been obtained from the North East-Tyne & Wear South Research Ethics Committee (19/NE/0125) and capacity and capability confirmed by local research and development departments for each participating centre prior to opening to recruitment. Participants are required to provide written informed consent prior to trial registration. Trial results will be disseminated by conference presentations and peer-reviewed publications., Trial Registration Number: ISRCTN17973108, NCT03720041., Competing Interests: Competing interests: ABC, K-LR, DAC, AH, CO, RH and PB report grants and non-financial support from BMS/Celgene, grants and non-financial support from Merck Sharpe & Dohme, grants and non-financial support from Amgen, grants and non-financial support from Takeda, during the conduct of the trial. DAC also reports travel support from Celgene Corporation. CPawlyn reports receiving honoraria and/or travel support from Amgen, BMS/Celgene, Janssen, Sanofi and Takeda. MK consultancy: AbbVie, Amgen, BMS/Celgene, GSK, Janssen, Karyopharm, Seattle Genetics, Takeda; honoraria: BMS/Celgene, Janssen, Takeda; Research funding: BMS/Celgene; Travel/educational support: BMS/Celgene, Janssen, Takeda. SB reports receiving research funding from Takeda. KB—Advisory Boards Janssen: BMS/Celgene, Takeda, Novartis. Speaker Honoraria: Janssen, BMS/Celgene, Sanofi, Takeda. Support to attend educational meetings: Janssen, BMS/Celgene, Takeda, GSK. GJ reports research funding from Takeda, Onyx, MSD & BMS/Celgene with consultancy from Janssen, Takeda, Sanofi, Oncopeptides, Karyopharm, Pfizer, Roche & BMS/Celgene. GC reports research funding from Janssen, Takeda, Amgen & BMS/Celgene with consultancy from Janssen, Takeda, Sanofi, Oncopeptides, Karyopharm, Pfizer, Roche & BMS/Celgene. MD reports Stock held in Abingdon Health. JB, RdT, NR, JJ, CParrish, HG, DM, BD, RO, MJ and BK have no declared competing interests., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ.)

Introduction/background: Immunoparesis, or low polyclonal immunoglobulin levels, is commonly seen in multiple myeloma (MM), and is associated with poor clinical outcomes. MM can be divided into subgroups with distinct biology and outcomes based on etiologic cytogenetic abnormalities. These include hyperdiploidy and translocations of t(11;14), t(4;14), t(14;16), and t(14;20), with the latter 3 associated with high-risk disease. We hypothesized that the different etiologic cytogenetic abnormalities drive bone marrow microenvironmental changes, resulting in different degrees of immunoparesis, and subgroup-dependent effects on clinical outcomes., Materials and Methods: We performed a retrospective review of 985 newly diagnosed patients enrolled in the Myeloma IX and XI trials. Immunoglobulin levels, survival outcomes, and infection rates were evaluated for each cytogenetic subgroup., Results: A significant proportion of patients with high-risk t(4;14), t(14;16), or t(14;20) had suppressed polyclonal immunoglobulins compared to standard-risk patients with hyperdiploidy or t(11;14). The clinical impact of immunoparesis depended on the cytogenetic subgroup, with the degree of IgM suppression effecting progression-free and overall survival only in the hyperdiploid subgroup. There was no significant difference in infection rates amongst the etiologic subgroups., Conclusion: These findings demonstrate that the etiologic cytogenetic subgroup influences the degree and clinical impact of immunoparesis. This suggests that the underlying cytogenetic abnormality affects remodeling of the bone marrow plasma cell niche, resulting in suppressed normal plasma cell function, and low immunoglobulin levels., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Multiple myeloma is a blood cancer characterized by clonal proliferation of plasma cells in the bone marrow. In recent years, several new drugs have been added to the therapeutic landscape of multiple myeloma, which have contributed to increased survival rates. However, while the use of therapeutics has evolved, there is still a group of high-risk patients who do not benefit from current treatment strategies. Risk stratification and risk-adapted treatment are crucial to identify the group of patients with urgent need for novel therapies. Gene expression profiling has been introduced as a tool for risk stratification in multiple myeloma based on the genetic make-up of myeloma cells. In this review we discuss the challenge of defining the high-risk multiple myeloma patient. We focus on the standardized analysis of myeloma cancer cells by gene expression profiling and describe how gene expression profiling provides additional insights for optimal risk-adapted treatment of patients suffering from multiple myeloma., Competing Interests: AKS has received consulting fee from SkylineDx. SU and PS have received research funding and consulting fees from SkylineDx. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Cerchione, Usmani, Stewart, Kaiser, Rasche, Kortüm, Mateos, Spencer, Sonneveld and Anderson.)

Thousands of non-coding variants have been associated with increased risk of human diseases, yet the causal variants and their mechanisms-of-action remain obscure. In an integrative study combining massively parallel reporter assays (MPRA), expression analyses (eQTL, meQTL, PCHiC) and chromatin accessibility analyses in primary cells (caQTL), we investigate 1,039 variants associated with multiple myeloma (MM). We demonstrate that MM susceptibility is mediated by gene-regulatory changes in plasma cells and B-cells, and identify putative causal variants at six risk loci (SMARCD3, WAC, ELL2, CDCA7L, CEP120, and PREX1). Notably, three of these variants co-localize with significant plasma cell caQTLs, signaling the presence of causal activity at these precise genomic positions in an endogenous chromosomal context in vivo. Our results provide a systematic functional dissection of risk loci for a hematologic malignancy., (© 2022. The Author(s).)