Methodology of a novel risk stratification algorithm for patients with multiple myeloma in the relapsed setting

Introduction Risk stratification tools provide valuable information to inform treatment decisions. Existing algorithms for patients with multiple myeloma (MM) were based on patients with newly diagnosed disease, and these have not been validated in the relapsed setting or in routine clinical practice. We developed a risk stratification algorithm (RSA) for patients with MM at initiation of second-line (2L) treatment, based on data from the Czech Registry of Monoclonal Gammopathies. Methods Predictors of overall survival (OS) at 2L treatment were identified using Cox proportional hazards models and backward selection. Risk scores were obtained by multiplying the hazard ratios for each predictor. The K-adaptive partitioning for survival (KAPS) algorithm defined four groups of stratification based on individual risk scores. Results Performance of the RSA was assessed using Nagelkerke’s R2 test and Harrell’s concordance index through Kaplan–Meier analysis of OS data. Prognostic groups were successfully defined based on real-world data. Use of a multiplicative score based on Cox modeling and KAPS to define cut-off values was effective. Conclusion Through innovative methods of risk assessment and collaboration between physicians and statisticians, the RSA was capable of stratifying patients at 2L treatment by survival expectations. This approach can be used to develop clinical decision-making tools in other disease areas to improve patient management

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

Innowacyjny program edukacyjny dotyczący wytwarzania biogazu realizowany na uniwersytetach w Hradec Králové (CZ) i Opolu (PL)

Recently, there is a growing pressure on a rapid construction of agricultural biogas plants, particularly in the Czech-Polish border region. It is an area with large expanses of agricultural land which can serve to supply biogas plants with biomass. This strategy should contribute to harmonize the common agricultural policy of the European Union. A need for qualified operators of these stations on this territory is also increasing. Therefore we first include a demonstration of an education program for students in the field of agricultural waste anaerobic fermentation and biogas production. We present here the first part of an innovative approach which we use in the teaching program “Physico-technical Measurements and Computer Technology” at the Faculty of Science at the University of Hradec Kralove and also in the education of internshipers from the Faculty of Natural Sciences and Technology at the University of Opole. There are requirements to fulfil labour market expectations and to make this subject more attractive for the students. Students’ theoretical and practical preparation constitutes a comprehensive source of knowledge and skills required in a real life job. Joined theoretical and practical knowledge gained by students, reinforced by the skills developed during task analysis followed by their solution, provides the future graduate higher quality abilities and better position in the labour market.W ostatnim czasie rośnie nacisk na budowę biogazowni rolniczych, szczególnie w czesko-polskim regionie przygranicznym. Jest to region, gdzie występują duże obszary gruntów rolnych mogących służyć do zasilania biogazowni. Strategia ta powinna przyczynić się do harmonizacji wspólnej polityki rolnej Unii Europejskiej. W związku z powyższym wzrasta również potrzeba wykształcenia wykwalifikowanych operatorów tych stacji. Pierwsza część pracy obejmuje prezentację akademickiego programu edukacyjnego w dziedzinie fermentacji beztlenowej odpadów i wytwarzania biogazu pochodzącego z produkcji rolnej. Zaprezentowano część innowacyjnego podejścia, które wykorzystywane jest w programie nauczania „Pomiary fizyko-techniczne oraz technologie komputerowe” na Wydziale Nauk Przyrodniczych Uniwersytetu Hradec Kralove, a także w edukacji studentów Wydziału Przyrodniczo-Technicznego Uniwersytetu Opolskiego. Wymagania te mają sprostać oczekiwaniom rynku pracy i uczynić kierunek studiów bardziej atrakcyjnym. Powiązanie przygotowania teoretycznego i praktycznego studentów tworzy kompleksowe źródło wiedzy i kształtuje umiejętności niezbędnych do pracy w biogazowniach. Zarówno wiedza teoretyczna, jak i umiejętności praktyczne zdobyte przez studentów, wzbogacone o umiejętności analizy zadań, a następnie ich rozwiązania, zapewnią przyszłym absolwentom większe możliwości i lepszą pozycję na rynku pracy

Hematogenous extramedullary relapse in multiple myeloma - a multicenter retrospective study in 127 patients

The current study assesses the characteristics and outcomes of multiple myeloma (MM) patients, treated with novel agents for hematogenous extramedullary (HEMM) relapse. Consecutive patients diagnosed with HEMM between 2010-2018 were included. Patients' characteristics at diagnosis and at HEMM presentation, response to treatment, survival and factors predicting survival were recorded and analyzed. A group of 127 patients, all diagnosed with HEMM by imaging (87.3%) and/or biopsy (79%), were included. Of those, 44% were initially diagnosed with ISS3, 57% presented with plasmacytomas, and 30% had high-risk cytogenetics. Median time to HEMM was 32 months. In multivariate analysis, ISS3 and bone plasmacytoma predicted shorter time to HEMM (P =.005 and P =.008, respectively). Upfront autograft was associated with longer time to HEMM (P =.002). At HEMM, 32% of patients had no BM plasmacytosis, 20% had non-secretory disease and 43% had light-chain disease. Multiple HEMM sites were reported in 52% of patients, mostly involving soft tissue, skin (29%), and pleura/lung (25%). First treatment for HEMM included proteasome inhibitors (50%), immunomodulatory drugs (IMiDs) (39%), monoclonal antibodies (10%), and chemotherapy (53%). Overall response rate (ORR) was 57%. IMiDs were associated with higher ORR (HR 2.2, 95% CI 1.02-4.7, P =.04). Median survival from HEMM was 6 months (CI 95% 4.8-7.2). Failure to achieve ≥VGPR was the only significant factor for worse OS in multivariate analyses (HR = 9.87, CI 95% 2.35 - 39, P =.001). In conclusion, HEMM occurs within 3 years of initial myeloma diagnosis and is associated with dismal outcome. The IMiDs might provide a higher response rate, and achievement of ≥VGPR predicts longer survival

Outcome of a Salvage Third Autologous Stem Cell Transplantation in Multiple Myeloma

To evaluate the outcomes of salvage third autologous stem cell transplantation (ASCT) in patients with relapsed multiple myeloma. We analyzed 570 patients who had undergone a third ASCT between 1997 and 2010 (European Society for Blood and Marrow Transplantation data), of whom 482 patients underwent tandem ASCT and a third ASCT at first relapse (AARA group) and 88 patients underwent an upfront ASCT with second and third transplantations after subsequent relapses (ARARA group). With a median follow-up after salvage third ASCT of 61 months in the AARA group and 48 months in the ARARA group, the day +100 nonrelapse mortality in the 2 groups was 4% and 7%, the incidence of second primary malignancy was 6% and 7%, the median progression-free survival was 13 and 8 months, and median overall survival (OS) was 33 and 15 months. In the AARA group, according to the relapse-free interval (RFI) from the second ASCT, the median OS after the third ASCT was 17 months if the RFI was <18 months, 37 months if the RFI was between 18 and 36 months, and 64 months if the RFI was 6536 months (P <.001). In the ARARA group, the median OS after the third ASCT was 7 months if the RFI was <6 months, 13 months if the RFI was between 6 and 18 months, and 27 months if the RFI was 6518 months (P <.001). In a multivariate analysis of the AARA group, the favorable prognostic factor was an RFI after second ASCT of 6518 months. Progressive disease and a Karnofsky Performance Status score of <70 at third ASCT were unfavorable factors. A salvage third ASCT is of value for patients with relapsed myeloma, particularly for those with a long duration of response and chemosensitive disease at the time of transplantation

Different MAF translocations confer similar prognosis in newly diagnosed multiple myeloma patients

The MAF translocations, t(14;16) and t(14;20), are considered as adverse prognostic factors based on few studies with small sample sizes. We report on their prognostic impact in a large group of 254 patients–223 (87.8%) with t(14;16) and 31 (12.2%) with t(14;20). There were no intergroup differences in survival estimates. Median progression-free survival was 16.6 months for t(14;16) and 24.9 months for t(14;20) (p = 0.28). Median overall survival (OS) was 54.0 months and 49.0 months, respectively (p = 0.62). Median OS in patients who underwent double autologous stem cell transplantation (ASCT) was 107.0 months versus 60.0 months in patients who received single ASCT (p &lt; 0.001). ISS 3 was associated with shorter OS (HR = 1.89; 95% CI 1.24–3.19; p = 0.005) in Cox analysis. Our study suggests that t(14;20) should be considered as an adverse factor of equal prognostic implication to t(14;16)

A multicenter retrospective study of 223 patients with t(14;16) in multiple myeloma

The t(14;16) translocation, found in 3%-5% of newly diagnosed (ND) multiple myeloma (MM), has been associated with adverse outcomes. However, the studies establishing the characteristics of t(14;16) included solely small cohorts. The goal of the current international, multicenter (n = 25 centers), retrospective study was to describe the characteristics and outcomes of t(14;16) patients in a large, real-world cohort (n = 223). A substantial fraction of patients had renal impairment (24%) and hemoglobin &lt;10 g/dL (56%) on initial presentation. Combined therapy of both immunomodulatory drug and proteasome inhibitor (PI) in the first line was used in 35% of patients. Autologous stem cell transplantation was performed in 42% of patients. With a median follow up of 4.1 years (95% CI 3.7-18.7), the median progression-free survival (PFS) and overall survival (OS) from first line therapy were 2.1 years (95% CI 1.5-2.4) and 4.1 years (95% CI 3.3-5.5), respectively. Worse OS was predicted by age &gt; 60 years (HR = 1.65, 95% CI [1.05-2.58]), as well as revised International Scoring System (R-ISS) 3 (vs R-ISS 2; HR = 2.59, 95% CI [1.59-4.24]). In conclusion, based on the largest reported cohort of t(14;16) patients, quarter of this subset of MM patients initially presents with renal failure, while older age and the R-ISS 3 predict poor survival