Follicular Lymphoma Therapy Based on Biological Insights and Novel Concepts

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. SCI-7-SCI-7
Author(s):  
Sonali M. Smith
Keyword(s):  
High Risk ◽  
Follicular Lymphoma ◽  
Unmet Needs ◽  
The United States ◽  
Sales Force ◽  
New Drugs ◽  
Early Relapse ◽  
High Risk Patients ◽  
Risk Patients ◽  
The Impact

The majority of patients with follicular lymphoma experience a protracted course with survival estimates measured in decades. However, there are several critical unmet needs, including pre-emptive identification of high-risk patients, management of early relapse, and treatment of patients with multiply relapsed or rituximab-refractory disease. While exact numbers are not known, approximately 15-20% of patients will have early relapse and the bulk of patients will become rituximab-refractory with time; since there are 30,000 newly diagnosed patients with follicular lymphoma annually in The United States, this constitutes a substantial cancer and societal burden. Unfortunately, the overall possibility for widespread cure remains elusive. Clinical prognostic tools including the FLIPI and FLIPI-2 are difficult to apply at an individual level, and, to date, there are no prospectively validated biologic tools capable of identifying the highest risk groups. The M7-FLIPI, which integrates seven gene mutations (EZH2, ARID1A, MEF2B, EP300, FOXO1, CREBBP, CARD11) with performance status and the FLIPI, is prognostic in patients receiving chemoimmunotherapy, and merits further study. There are currently no pathobiologic predictors of outcome in patients treated with monoclonal antibodies or non-cytotoxic therapies. While prognostication in treatment-naïve patients remains elusive, there are now several time-to-event based observations following initial therapy that define a high-risk subset of patients with inferior survival; these include CR30 and EFS24 which will be further described. As discussed by the previous speakers, a provocative emerging theme is that many somatic mutations and epigenetic and genetic changes occur relatively early in the evolution of the disease and could potentially shape the subsequent clinical course. The possibility that early progression (as defined by EFS24, for example) is directly related to these events affords the exciting prospect of identifying high-risk patients before they receive standard treatment; furthermore, if confirmed, these aberrations are ripe targets for new agents. Moving from prognostication to prediction of response to individual agents or regimens is badly needed in this disease, particularly since there are a plethora of new drugs and new targets being identified. An important and poorly understood component of FL biology that is likely to impact clinical behavior is the tumor microenvironment. The non-malignant milieu of follicular lymphoma is comprised of several cell types, and their composition and interaction with the malignant compartment probably evolves with the disease course. The relationship between the microenvironment and the malignant cell is also a valid target, with both immunomodulatory agents and immunotherapy drugs actively being tested. Overall, the incorporation of biologic insights into treatment of follicular lymphoma will drive the next generation of clinical investigations and move to limit the impact of unmet needs in this disease. Disclosures Smith: Amgen: Other: Educational lecture to sales force; TGTX: Consultancy; Portola: Consultancy; Juno: Consultancy; AbbVie: Consultancy; Celgene: Consultancy; Genentech: Consultancy, Other: on a DSMB for two trials ; Pharmacyclics: Consultancy; Gilead: Consultancy.

scholarly journals Trial-in-Progress: Randomized Phase II Trial in Early Relapsing or Refractory Follicular Lymphoma (NCT#03269669): SWOG S1608

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 2425-2425
Author(s):  
Paul M. Barr ◽  
Hongli Li ◽  
Brian K. Link ◽  
Christopher R. Flowers ◽  
Richard Burack ◽  
...  
Keyword(s):  
High Risk ◽  
Follicular Lymphoma ◽  
Research Funding ◽  
Newly Diagnosed ◽  
Clinical Factors ◽  
High Risk Patients ◽  
Cytotoxic Treatment ◽  
Additional Chemotherapy ◽  
Risk Patients ◽  
The Impact

Abstract While the majority of follicular lymphoma (FL) patients have an overall survival of nearly 2 decades, a subset of patients has a markedly inferior survival. Across randomized studies, 20% of patients will respond poorly to first-line chemoimmunotherapy and account largely for the early deaths in the larger FL population. This group represents the largest unmet need in FL, for which a precision approach to therapy must be developed. With the development of newer monoclonal antibodies, immunomodulatory agents, therapies targeting molecules downstream of the B-cell receptor and novel cellular strategies, non-cytotoxic treatment has the potential to improve outcomes for patients with early progressing FL. There are several validated clinical factors known to correlate with disease outcome in newly diagnosed FL including age, lactate dehydrogenase, β2-microglobulin and disease extent that have been incorporated in prognostic systems such as FLIPI and FLIPI2. More recently, genetic biomarkers have been identified, including MLL2, EZH2, IRF4, CREPPB, and EPHA7 which reflect the disease biology as well as the impact of the lymphoma microenvironment. The addition of these molecular aberrations to clinical factors has led to the development of the M7-FLIPI as well as a 23-gene score, improving risk prognostication for newly diagnosed FL patients. However, such systems have shown a limited ability to predict progression or relapse within 2 years of chemotherapy. As such, identification of these patients at diagnosis or prior to therapy is currently not possible. S1608 was developed to 1) enable identification of high-risk patients using clinical and molecular markers by validating the m7-FLIPI prognostic system and to 2) identify the novel therapeutic approaches most active in this population. This study is enrolling high-risk patients, refractory to chemoimmunotherapy, and in randomized fashion, comparing novel regimens against additional chemotherapy to identify the most active non-chemotherapeutic strategies for this population. Eligible patients must be 18 years or older with grade 1, 2 or 3a FL and have relapsed or progressed with 2 years of finishing their first course of chemoimmunotherapy. Previous chemotherapy must have been CHOP or bendamustine based. Patients are eligible regardless of anti-CD20 therapy used, whether radiation therapy had been administered and whether or not maintenance therapy was utilized. Note that patients are required to have evidence of progressive disease within 2 years but do not have to be registered within 2 years. These high-risk patients are randomized to 12 months of lenalidomide, umbralisib or additional chemotherapy (for 6 months), all combined with 12 months of obinutuzumab. The primary clinical endpoint is CR rate after 6 cycles, allowing responding patient to proceed with consolidative cellular therapies if desired by the treating physician. Biopsies from diagnosis and at the time of relapse as well as circulating tumor DNA are being collected to prospectively evaluate the m7-FLIPI and to identify additional predictive markers. S1608 is a collaborative effort amongst the SWOG, Alliance and ECOG-ACRIN cooperative groups. The study represents one of the only prospective efforts to characterize early progressing FL and the only randomized trial comparing treatment strategies for this group of follicular lymphoma patients most in need of alternative therapies. Funding: NIH/NCI/NCTN grants U10CA180888, U10CA180819, U10CA180820, U10CA180821; and TG Therapeutics, Inc. Figure 1 Figure 1. Disclosures Barr: Genentech: Consultancy; AstraZeneca: Consultancy; Morphosys: Consultancy; TG Therapeutics: Consultancy; Beigene: Consultancy; Abbvie/Pharmacyclics: Consultancy; Bristol Meyers Squibb: Consultancy; Seattle Genetics: Consultancy; Janssen: Consultancy; Gilead: Consultancy. Link: Novartis, Jannsen: Research Funding; MEI: Consultancy; Genentech/Roche: Consultancy, Research Funding. Flowers: Cellectis: Research Funding; Nektar: Research Funding; Takeda: Research Funding; TG Therapeutics: Research Funding; BeiGene: Consultancy; 4D: Research Funding; Karyopharm: Consultancy; Morphosys: Research Funding; Guardant: Research Funding; Bayer: Consultancy, Research Funding; Genmab: Consultancy; Eastern Cooperative Oncology Group: Research Funding; SeaGen: Consultancy; Genentech/Roche: Consultancy, Research Funding; Pharmacyclics/Janssen: Consultancy; Burroughs Wellcome Fund: Research Funding; AbbVie: Consultancy, Research Funding; Adaptimmune: Research Funding; Janssen: Research Funding; Iovance: Research Funding; Acerta: Research Funding; Kite: Research Funding; Allogene: Research Funding; EMD: Research Funding; Amgen: Research Funding; Celgene: Consultancy, Research Funding; Ziopharm: Research Funding; Novartis: Research Funding; Pfizer: Research Funding; Sanofi: Research Funding; National Cancer Institute: Research Funding; Xencor: Research Funding; Spectrum: Consultancy; Gilead: Consultancy, Research Funding; Epizyme, Inc.: Consultancy; Biopharma: Consultancy; Denovo: Consultancy; Cancer Prevention and Research Institute of Texas: CPRIT Scholar in Cancer Research: Research Funding; Pharmacyclics: Research Funding. Weigert: Janssen: Speakers Bureau; Epizyme: Membership on an entity's Board of Directors or advisory committees; Roche: Research Funding. Herrera: ADC Therapeutics: Consultancy, Research Funding; Tubulis: Consultancy; Karyopharm: Consultancy; Kite, a Gilead Company: Research Funding; Bristol Myers Squibb: Consultancy, Research Funding; Gilead Sciences: Research Funding; Merck: Consultancy, Research Funding; Genentech: Consultancy, Research Funding; Takeda: Consultancy; Seagen: Consultancy, Research Funding; AstraZeneca: Consultancy, Research Funding. Weinstock: SecuraBio: Consultancy; ASELL: Consultancy; Bantam: Consultancy; Abcuro: Research Funding; Verastem: Research Funding; Daiichi Sankyo: Consultancy, Research Funding; AstraZeneca: Consultancy; Travera: Other: Founder/Equity; Ajax: Other: Founder/Equity. Leonard: ADC Therapeutics, AstraZeneca, Bayer, BMS/Celgene, Epizyme, Inc., Genmab, Gilead/Kite, Karyopharm, BMS/Celgene, Regeneron, MEI Pharma, Miltenyi, Roche/Genentech, Sutro: Consultancy; Roche/Genentech: Consultancy. Kahl: Abbvie, BeiGene, AstraZeneca, Acerta: Research Funding; Research to Practice: Speakers Bureau; Abbvie, ADCT, AstraZeneca, Beigene, Celgene, Teva, Janssen, MTEM, Bayer, InCyte, Adaptive, Genentech, Roche, MEI, KITE, TG Therapeutics, Epizyme, Takeda: Consultancy. Smith: Celgene, Genetech, AbbVie: Consultancy; Alexion, AstraZeneca Rare Disease: Other: Study investigator. Friedberg: Novartis: Other: DSMC ; Acerta: Other: DSMC ; Bayer: Other: DSMC .

scholarly journals Follicular lymphoma: are we ready for a risk-adapted approach?

Hematology ◽  
2017 ◽  
Vol 2017 (1) ◽  
pp. 358-364 ◽  
Author(s):  
Brad S. Kahl
Keyword(s):  
High Risk ◽  
Follicular Lymphoma ◽  
Randomized Clinical Trials ◽  
International Prognostic Index ◽  
Prognostic Index ◽  
Predictive Biomarkers ◽  
Western Hemisphere ◽  
Ongoing Research ◽  
High Risk Patients ◽  
Risk Patients

Abstract Follicular lymphoma is the most common indolent non-Hodgkin lymphoma in the Western hemisphere. The natural history of FL appears to have been favorably impacted by the introduction of rituximab after randomized clinical trials demonstrated that the addition of rituximab to standard chemotherapy induction has improved the overall survival. Yet, the disease is biologically and clinically heterogeneous with wide variations in outcomes for individual patients. The ability to accurately risk-stratify patients and then tailor therapy to the individual is an area of ongoing research. Historically, tumor grade, tumor burden, and the FL international prognostic index (version 1 and version 2) have been used to distinguish low-risk from high-risk patients. Biologic factors such as mutations in key genes can identify patients at high risk for poor outcomes to first-line therapy (mutational status of 7 genes [EZH2, ARID1A, MEF2B, EP300, FOX01, CREBBP, and CARD11] with Follicular Lymphoma International Prognostic Index). More recently, the quality of the response to initial therapy, as measured by either PET imaging or by remission duration, has been show to identify individuals at high risk. However, several unmet needs remain, including a better ability to identify high-risk patients at diagnosis, the development of predictive biomarkers for targeted agents, and strategies to reduce the risk of transformation.

scholarly journals The impact of the incorporation of a feasible postoperative mortality model at the Post-Anaesthestic Care Unit (PACU) on postoperative clinical deterioration: A pragmatic trial with 5,353 patients

PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0257941
Author(s):  
Claudia de Souza Gutierrez ◽  
Katia Bottega ◽  
Stela Maris de Jezus Castro ◽  
Gabriela Leal Gravina ◽  
Eduardo Kohls Toralles ◽  
...  
Keyword(s):  
Quality Improvement ◽  
High Risk ◽  
Clinical Deterioration ◽  
Surgical Patients ◽  
Predictive Tool ◽  
Postoperative Death ◽  
High Risk Patients ◽  
Death Probability ◽  
Risk Patients ◽  
The Impact

Background Practical use of risk predictive tools and the assessment of their impact on outcome reduction is still a challenge. This pragmatic study of quality improvement (QI) describes the preoperative adoption of a customised postoperative death probability model (SAMPE model) and the evaluation of the impact of a Postoperative Anaesthetic Care Unit (PACU) pathway on the clinical deterioration of high-risk surgical patients. Methods A prospective cohort of 2,533 surgical patients compared with 2,820 historical controls after the adoption of a quality improvement (QI) intervention. We carried out quick postoperative high-risk pathways at PACU when the probability of postoperative death exceeded 5%. As outcome measures, we used the number of rapid response team (RRT) calls within 7 and 30 postoperative days, in-hospital mortality, and non-planned Intensive Care Unit (ICU) admission. Results Not only did the QI succeed in the implementation of a customised risk stratification model, but it also diminished the postoperative deterioration evaluated by RRT calls on very high-risk patients within 30 postoperative days (from 23% before to 14% after the intervention, p = 0.05). We achieved no survival benefits or reduction of non-planned ICU. The small group of high-risk patients (13% of the total) accounted for the highest proportion of RRT calls and postoperative death. Conclusion Employing a risk predictive tool to guide immediate postoperative care may influence postoperative deterioration. It encouraged the design of pragmatic trials focused on feasible, low-technology, and long-term interventions that can be adapted to diverse health systems, especially those that demand more accurate decision making and ask for full engagement in the control of postoperative morbi-mortality.

Guidelines for the Management of Pediatric and Adult Tumor Lysis Syndrome: An Evidence-Based Review

2008 ◽  
Vol 26 (16) ◽  
pp. 2767-2778 ◽  
Author(s):  
Bertrand Coiffier ◽  
Arnold Altman ◽  
Ching-Hon Pui ◽  
Anas Younes ◽  
Mitchell S. Cairo
Keyword(s):  
At Risk ◽  
High Risk ◽  
Tumor Lysis Syndrome ◽  
The United States ◽  
Standards Of Care ◽  
Close Monitoring ◽  
Tumor Lysis ◽  
High Risk Patients ◽  
Patients At Risk ◽  
Risk Patients

PurposeTumor lysis syndrome (TLS) has recently been subclassified into either laboratory TLS or clinical TLS, and a grading system has been established. Standardized guidelines, however, are needed to aid in the stratification of patients according to risk and to establish prophylaxis and treatment recommendations for patients at risk or with established TLS.MethodsA panel of experts in pediatric and adult hematologic malignancies and TLS was assembled to develop recommendations and guidelines for TLS based on clinical evidence and standards of care. A review of relevant literature was also used.ResultsNew guidelines are presented regarding the prevention and management of patients at risk of developing TLS. The best management of TLS is prevention. Prevention strategies include hydration and prophylactic rasburicase in high-risk patients, hydration plus allopurinol or rasburicase for intermediate-risk patients, and close monitoring for low-risk patients. Primary management of established TLS involves similar recommendations, with the addition of aggressive hydration and diuresis, plus allopurinol or rasburicase for hyperuricemia. Alkalinization is not recommended. Although guidelines for rasburicase use in adults are provided, this agent is currently only approved for use in pediatric patients in the United States.ConclusionThe potential severity of complications resulting from TLS requires measures for prevention in high-risk patients and prompts treatment in the event that symptoms arise. Recognition of risk factors, monitoring of at-risk patients, and appropriate interventions are the key to preventing or managing TLS. These guidelines should assist in the prevention of TLS and improve the management of patients with established TLS.

The Impact of a Postmastectomy Chest Wall Scar Boost on Local Recurrence-free Survival in High-risk Patients

2019 ◽  
Vol 19 (5) ◽  
pp. 363-369
Author(s):  
Ashley Albert ◽  
Sophy Mangana ◽  
Mary R. Nittala ◽  
Toms Vengaloor Thomas ◽  
Lacey Weatherall ◽  
...  
Keyword(s):  
High Risk ◽  
Local Recurrence ◽  
Chest Wall ◽  
Recurrence Free Survival ◽  
Free Survival ◽  
High Risk Patients ◽  
Risk Patients ◽  
The Impact ◽  
Local Recurrence Free Survival

scholarly journals Impact of the Beta-Glucan Test on Management of Intensive Care Unit Patients at Risk for Invasive Candidiasis

2020 ◽  
Vol 58 (6) ◽  
Author(s):  
Antonios Kritikos ◽  
Julien Poissy ◽  
Antony Croxatto ◽  
Pierre-Yves Bochud ◽  
Jean-Luc Pagani ◽  
...  
Keyword(s):  
Intensive Care ◽  
High Risk ◽  
Invasive Candidiasis ◽  
Test Results ◽  
Beta Glucan ◽  
High Risk Patients ◽  
Therapeutic Decisions ◽  
Risk Patients ◽  
The Impact ◽  
Test Result

ABSTRACT The 1,3-beta-d-glucan (BDG) test is used for the diagnosis of invasive candidiasis (IC) in intensive care units (ICUs). However, its utility for patient management is unclear. This study assessed the impact of BDG test results on therapeutic decisions. This was a single-center observational study conducted in an ICU over two 6-month periods. All BDG test requests for the diagnosis of IC were analyzed. Before the second period, the ICU physicians received a pocket card instruction (algorithm) for targeted BDG testing in high-risk patients. The performance of the BDG test for IC diagnosis was assessed, as well as its impact on antifungal (AF) prescription. Overall, 72 patients had ≥1 BDG test, and 14 (19%) patients had an IC diagnosis. The BDG test results influenced therapeutic decisions in 41 (57%) cases. The impact of the BDG test was positive in 30 (73%) of them, as follows: AF abstention/interruption following a negative BDG result (n = 27), and AF initiation/continuation triggered by a positive BDG test result and subsequently confirmed IC (n = 3). In 10 (24%) cases, a positive BDG test result resulted in AF initiation/continuation with no further evidence of IC. A negative BDG result and AF abstention with subsequent IC diagnosis were observed in one case. The positive predictive value (PPV) of BDG was improved if testing was restricted to the algorithm’s indications (80% versus 36%, respectively). However, adherence to the algorithm was low (26%), and no benefit of the intervention was observed. The BDG result had an impact on therapeutic decisions in more than half of the cases, which consisted mainly of safe AF interruption/abstention. Targeted BDG testing in high-risk patients improves PPV but is difficult to achieve in ICU.

Survival in Patients with Newly Diagnosed Myeloma Undergoing Therapy with Lenalidomide and Dexamethasone: Impact of High-Risk Cytogenetic Risk Status on Outcome

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 95-95 ◽  
Author(s):  
Prashant Kapoor ◽  
Shaji Kumar ◽  
Rafael Fonseca ◽  
Martha Q. Lacy ◽  
Thomas E Witzig ◽  
...  
Keyword(s):  
High Risk ◽  
Risk Stratification ◽  
Plasma Cell ◽  
Risk Groups ◽  
Newly Diagnosed ◽  
High Risk Patients ◽  
Risk Patients ◽  
The Impact ◽  
Standard Risk

Abstract Background: Multiple myeloma (MM) is a heterogeneous disease with very divergent outcomes that are dictated in a large part by specific cytogenetic abnormalities, as well as other prognostic factors such as the proliferative rate of marrow plasma cells. Prognostic systems incorporating these factors have shown clinical utility in identifying high-risk patients, and are increasingly being utilized for treatment decision-making. However, the prognostic relevance of these factors may change with the application of novel therapies. The objective of this study was to determine the impact of risk-stratification (incorporating plasma cell metaphase cytogenetics, interphase fluorescent in-situ hybridization (FISH) and the slide-based plasma cell labeling index (PCLI)) in a cohort of patients with newly diagnosed MM treated initially with lenalidomide + dexamethasone (Rev-Dex). Methods: From March 2004 to November 2007, 100 consecutive patients treated with Rev (25mg/day) on days 1 through 21 of a 4-week cycle in combination with dexamethasone as initial therapy for newly diagnosed myeloma, were identified. High-risk MM was defined as presence of any one or more of the following: hypodiploidy, monoallelic loss of chromosome 13 or its long arm (by metaphase cytogenetics only), deletion of p53 (locus 17p13) or PCLI ≥ 3% or immunoglobulin heavy chain (IgH) translocations, t(4;14) (p16.3;q32) or t(14;16)(q32;q23) on FISH. PFS and OS survival estimates were created using the Kaplan Meier method, and compared by log-rank tests. Results: The median estimated follow-up of the entire cohort (N=100) was 36 months. The median PFS was 31 months; the median OS has not been reached. The 2- and 3-year OS estimates were 93% and 83%, respectively. 16% patients were deemed high-risk by at least one of the 3 tests (cytogenetics, FISH or PCLI). Response rates (PR or better) were 81% versus 89% in the high-risk and standard risk groups, respectively, P=NS; corresponding values for CR plus VGPR rates were 38% and 45% respectively. The median PFS was 18.5 months in high-risk patients compared to 37 months in the standard-risk patients (n=84), P<0.001(Figure). Corresponding values for TTP were 18.5 months and 36.5 months, respectively, P=<0.001. OS was not statistically significant between the two groups; 92% 2-year OS was noted in both the groups. Overall, 95 patients had at least one of the 3 tests to determine risk, while 55 patients could be adequately stratified based on the availability of all the 3 tests, or at least one test result that led to their inclusion in the high-risk category. The significant difference in PFS persisted even when the analysis was restricted to the 55 patients classified using this stringent criterion; 18.5 months vs. 36.5 months in the high-risk and standard- risk groups respectively; P<0.001. In a separate analysis, patients who underwent SCT before the disease progression were censored on the date of SCT to negate its effect, and PFS was still inferior in the high-risk group (p=0.002). Conclusion: The TTP and PFS of high-risk MM patients are inferior to that of the standard-risk patients treated with Rev-Dex, indicating that the current genetic and proliferation-based risk-stratification model remains prognostic with novel therapy. However, the TTP, PFS, and OS obtained in high-risk patients treated with Rev-Dex in this study is comparable to overall results in all myeloma patients reported in recent phase III trials. In addition, no significant impact of high-risk features on OS is apparent so far. Longer follow-up is needed to determine the impact of risk stratification on the OS of patients treated with Rev-Dex. Figure Figure

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