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Impact of t(11;14) as a sole and concomitant abnormality on outcomes in multiple myeloma

2021; Wiley; Volume: 195; Issue: 1 Linguagem: Inglês

10.1111/bjh.17627

1365-2141

Susan Bal, Smith Giri, Kelly Godby, Luciano J. Costa,

Protein Degradation and Inhibitors

Multiple Myeloma (MM) is a clonal plasma cell neoplasm that consistently arises from precursor monoclonal gammopathy of unknown significance (MGUS).1 Acquisition of certain genetic changes in normal plasma cells followed by the acquisition of chromosomal abnormalities over time drives disease progression and relapse.1 MM harbouring t(11;14) has several additional unique features such as lymphoplasmacytoid morphology and expression of CD20.2 Further, t(11;14) may be a predictive biomarker as these patients are more sensitive to the pro-apoptotic effects of the BCL2 inhibitor venetoclax.3 The prognostic significance of t(11;14) MM remains debatable. A better delineation of the natural history and prognosis of t(11;14) MM and understanding its behaviour in the presence of other cytogenetic abnormalities can serve as a benchmark for future therapies targeting this specific subset of patients. We used electronic health records from the Flatiron electronic health record derived database. Our primary study cohort included adults aged 18 years or older with a histologically confirmed diagnosis of MM between January 2011 and February 2020. Eligibility criteria for the study are summarized in supplemental Figure S1. We measured real-world-derived progression-free survival (dPFS) defined as the time from date of diagnosis until first progression or death. Overall survival (OS) was defined as the time from date of diagnosis to death. The primary variable of interest was the presence of t(11;14) by fluorescence in situ hybridization (FISH). We created mutually exclusive risk groups by placing patients in a hierarchical category dictated by the highest-risk cytogenetic abnormality present. Patients with del17p were allocated to their own group irrespective of other abnormalities. Patients with t(4;14), t(14;16) or t(14;20) were allocated to a high-risk (HRCA) translocations group, and patients with chromosome 1 abnormalities were placed in the Ch1a group. The remaining patients were placed into two groups based on the presence or absence of t(11;14). We described time-to-event end-points (OS and dPFS) using the method of Kaplan and Meier, using 90 days after the date of diagnosis as the index date. We compared OS and dPFS between groups using univariate Cox regression analysis. We explored patient, disease and treatment features influencing OS by performing Cox proportional-hazards model multivariable analysis. Additionally, we assessed the impact of t(11;14) as additional FISH abnormality in patients with del17p and in patients with Ch1a. We identified 5581 patients that met the inclusion criteria. The baseline characteristics are summarized in supplemental Table SI. The patients in the t(11;14)+ group had worse dPFS [median dPFS 36 months vs 40 months, P = 0·03; median follow up 37 months (95% confidence interval — CI — 35–38 months)] and a trend towards worse OS (median OS 73 months vs 78 months, P = 0·19; median follow up 35 months (95% CI 34–37 months)] compared to t(11;14)−, but better dPFS and OS than the other three high-risk groups (Ch1a, HRCA, del17p; Fig 1 A, B). The t(11;14)− group had superior dPFS compared to the t(11;14)+ group even after adjustment for sex, age, race/ethnicity, immunoglobulin isotype, stage, lactate dehydrogenase (LDH), renal function, and treatment received (adjusted HR = 0·87, 95% CI 0·77–0·98, P = 0·027; supplemental Table SII). There was no difference in OS between t(11;14)+ and t(11;14)− patients after adjustment for the aforementioned variables (adjusted HR = 0·90, 95% CI 0·77–1·06, P = 0·22; Fig 1, supplemental Table SII). We subsequently analyzed dPFS and OS for different cytogenetic groups according to first line of therapy and use of autologous haematopoietic cell transplantation (AHCT). Among patients who received proteasome inhibitor (PI)-based first line therapy, dPFS and OS were inferior for t(11;14)+ vs t(11;14)− patients [median dPFS 20 vs 31 months, P = 0·004; Supplemental Figure S2, panel A, median OS 41 vs 65 months, P < 0·001; hazard ratio (HR) 1·38, 95% CI 1·11–1·72, Supplemental Figure S3, panel A]. However, there was no difference of dPFS or OS between t(11;14)+ and t(11;14)− among patients who received immunomodulatory drug (IMiD) -based or triplet (PI + IMiD-based) therapy or AHCT (supplemental Figure S2 panels B, C and D and supplemental Figure S3, panels B, C, D). We subsequently analyzed the impact of the presence of IgH translocations on del17p and Ch1a. The presence of t(11;14) in addition to del17p resulted in worse OS compared to del 17p without IgH translocations including t(11;14) (median OS 34 vs 47 months, P < 0·01). Indeed, the impact of t(11;14) on del17p was comparable to the impact of t(4;14) (Fig 2A). There was no difference in survival with the concomitant presence of t(11;14) with Ch1a (Fig 2B). Over the past two decades, the prognostic significance of cytogenetic changes has evolved with the changing therapeutic landscape.4-8 The present study contains the largest cohort to date of patients with MM harbouring t(11;14). Because of our robust sample size, we were able to meaningfully compare the outcomes of t(11;14) MM with other standard-risk MM and show its adverse prognostic impact on dPFS. Such negative impact was maintained even after adjusting for other variables impacting outcomes. We aimed to study patients in mutually exclusive cytogenetic risk groups and combined them together based on the highest-risk abnormality present. Our decision to separate the Ch1a was based on increasing data supporting its unfavourable impact. The definition of high-risk myeloma has evolved over the years and the urgency to focus our efforts on this group with unmet need is clear. But what is unclear is a uniform definition of high-risk myeloma despite existing qualifiers [high-risk cytogenetics, bi-allelic TP53 mutations, amplification (≥4 copies) chr 1q, persistent minimal residual disease, double or triple hit myeloma] which portend a poor prognosis.9-11 Our study found that among patients who harbour del17p, the concomitant presence of t(11;14) was associated with worse survival (2·8 vs 3·7 years, P = 0·04). In fact, the impact of concomitant presence of t(11;14) is comparable to that of t(4;14) in this cohort. Our study has several limitations, such as shortcomings inherent to a retrospective study including derivation of information electronic health records. We noted a substantial burden of missing data and decided against multiple imputation. Chr1 abnormalities have been combined into one group without further categorization into those with 1p or 1q subsets. Information pertaining to the allelic burden of TP53 and deletion versus mutation status was not known.9, 12 Despite these limitations and with the help of robust multivariable analyses, we have shown the adverse impact of t(11;14) on dPFS, specifically when treated with proteasome inhibitor-based therapy. Additionally, when present together, t(11;14) with del17p identifies a subgroup of patients with high risk of early death and in need of additional therapeutic strategies to improve outcomes. Careful investigation of venetoclax combinations may provide benefit in this challenging subset. Presented in part at the Annual Society of Hematology Meeting 2020. No funding was received for this work. SB, SG, and LC conceptualized the study, the study design, and the methodology, curated, and analyzed the data, and performed the analyses, and SB, SG, KG, LC perform the investigation, wrote the original draft of the article, and reviewed and edited it. SB has received research funding from Amyloid Foundation. SG is supported in part by the Walter B. Frommeyer Fellowship in Investigative Medicine at the University of Alabama at Birmingham and reports receiving research funding from Carevive Systems and Pack Health. KG does not have any relevant disclosures. LJC receives honoraria from Amgen, Bristol-Myers Squibb, AbbVie, and Janssen, and grant/research support from Amgen, Bristol-Myers Squibb, AbbVie, and Janssen. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. 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