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COVID19, Hočkinov limfom, Hronična limfocitna leukemija, Leukemije, Multipli mijelom, Nehočkinski limfom

FINDINGS FROM A RETROSPECTIVE CASE STUDY OF COVID-19 INFECTION IN CANCER PATIENTS IN WUHAN: AN EMPHASIS ON SEVERE EVENTS

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Analysis of risk factors associated with admission to an intensive care unit, the use of mechanical ventilation or deathDate:30 Mar 2020Topics:Cancer in Special Situations / Population A study team composed from clinicians from three hospitals in Wuhan, China, led by Dr Min Zhou of the Department of the Respiratory and Critical Care Medicine, Tongji Hospital, performed a retrospective case study of clinical features among 28 patients with cancer and COVID-19 infection. In particular, they analyzed the risk factors associated with admission to an intensive care unit, the use of mechanical ventilation or death. Their series was associated with poor outcomes. There was increased risk of developing severe events, especially if the last antitumour treatment was within 14 days of COVID-19 diagnosis. The findings are published on 23 March 2020 in the Annals of Oncology. Like the other coronaviruses, SARS-CoV-2 primarily causes respiratory tract infection. The study team wrote that data published in The Lancet Oncology on 18 patients with cancer diagnosis from a cohort of 2007 cases with COVID-19 disease in China represents a relatively small sample with limited clinical information and high heterogeneity of the course of the disease. Therefore, critical issues concerning treatment principles for cancer patients with COVID-19 infection are unclear. There is an urgent need to answer whether cancer patients with COVID-19 infection will have distinct clinical course and worse outcomes, such as death from the infection or severe pneumonia, and whether cancer patients should receive antitumour treatments as usual. The study team aimed to explore these issues by conducting a rapid retrospective case study on critical COVID-19-infected cancer patients. They analyzed cancer patients with laboratory confirmed COVID-19. The clinical data were collected from medical records from 13 January 2020 to 26 February 2020. In total, 28 cancer patients with COVID-19 infection were included. Of those, 17 patients (60.7%) were male. Median age was 65.0 years. Lung cancer was the most frequent cancer type in the cohort with 7 patients (25.0%), followed by oesophageal cancer in 4 patients (14.3%) and breast cancer in 3 patients (10.7%). Ten patients (35.7%) were diagnosed with stage IV cancer. Eight patients (28.6%) were suspected to be from hospital-associated transmission. All the patients had a history of antitumour therapy. Within 14 days of COVID-19 diagnosis, 6 patients (21.4%) were treated by at least one kind of antitumour therapy, such as chemotherapy in 3 patients (10.7%), targeted therapy in 2 patients (7.1%), radiotherapy in 1 patient (3.6%), immunotherapy in 1 patient (3.6%); one of them received treatment combining chemotherapy and immunotherapy. There were two main clusters of patients: 8 patients (28.6%) who developed COVID-19 undergoing antitumour therapy in hospitals and 20 patients (71.4%) in their communities. In addition to cancer, 11 patients (39.2%) had at least one or more comorbidities. The following clinical features were present in studied cohort: fever in 23 patients (82.1%), dry cough in 22 patients (81%) and dyspnoea in 14 patients (50.0%), along with lymphopaenia in 23 patients (82.1%), high level of high-sensitivity C-reactive protein in 23 patients (82.1%), anaemia in 21 patients (75.0%) and hypoproteinaemia in 25 patients (89.3%). The common chest CT findings were ground-glass opacity in 21 patients (75.0%) and patchy consolidation in 13 patients (46.3%). In total, 22 patients (78.6%) received oxygen therapy, 10 patients (35.7%) were put on invasive mechanical ventilation, with 2 patients (7.1%) requiring endotracheal intubation and invasive ventilation because of progressive hypoxia. Significantly more severe cases were subjected to mechanical ventilation (non-invasive: 53.3% vs 0%, p < 0.001; invasive: 13.3% vs 0%, p < 0.001) as compared to non-severe cases. The median period of mechanical ventilation for non-invasive and invasive ventilation was 2.5 days. None of the severe patients received extracorporeal membrane oxygenation. In the series, 20 patients (71.4%) were prescribed at least one antiviral agent, while 9 patients (32.1%) received combinations of antiviral agents. Empirical antibiotic therapy was given to 23 patients (82.1%). Systemic corticosteroids were given to 15 patients (53.6%). Administration of corticosteroids was more frequent in patients with severe events (12/15, 80%) than non-severe cases (3/13, 23.1%). Seven of 8 patients with acute respiratory distress syndrome (ARDS) received systemic corticosteroids. The dosage and period of corticosteroids in the severe cases was higher than in non-severe cases, but the difference was not significant. Moreover, intravenous immunoglobin was prescribed to 12 patients (35.7%). As of 26 February 2020, 15 patients (53.6%) developed severe clinical events, 6 patients (21.4%) were admitted to intensive care unit, 10 patients (35.7%) had life-threatening complications and 8 patients (28.6%) died. Of the 10 stage IV cancer patients, 7 patients (70%) had developed severe events, while 44.4% of the non-stage IV patients had such events. Among 6 cancer patients who received antitumor treatment within 14 days of COVID-19 disease diagnosis, 5 patients (83%) developed severe events. Additionally, 11 of 13 patients (84.6%) with patchy consolidation on CT on admission had developed severe events. The most common complication was ARDS in 8 patients (28.6%), followed by septic shock in 1 patient (3.6%), and acute myocardial infarction (AMI) in 1 patient (3.6%). Two patients (7.1%) were suspected to have pulmonary embolism. Ten of 28 patients (35.7%) had been discharged with a median hospital stay of 13.5 days; 10 patients (35.7%) were still inpatients with a median stay of 19.0 days. Of the 28 patients, 8 patients (28.6%) died, with a median time of 16.0 days from admission to death. The cause of death included ARDS in 5 patients (62.5%), followed by pulmonary embolism in 1 patient (12.5%), septic shock in 1 patient (12.5%) and AMI in 1 patient (12.5%). In univariate Cox proportional hazards model, cancer patients who received antitumour treatment within 14 days of COVID-19 diagnosis had a higher risk of developing severe events. Moreover, patchy consolidation on the first CT on admission suggested an elevated risk of developing severe events than those cases without consolidation. Similar results were observed in the multivariate-adjusted Cox proportional hazards model after being adjusted for age and gender. If the last antitumour treatment was within 14 days, it significantly increased the risk

Hronična limfocitna leukemija, Nehočkinski limfom

Implementation of CAR T-cell therapy in the real world – A round table discussion

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The Lymphoma Hub is pleased to report a summary of real-world experiences of chimeric antigen receptor (CAR) T-cell implementation as discussed at the 2nd European CAR T-Cell Meeting. Contributors included Stephan Mielke, Karolinska Institute, Stockholm, SE, Gilles Salles, South Lyon University Hospital, Lyon, FR, and Marcelo C. Pasquini, Medical College of Wisconsin, Wisconsin, US. To begin, Professor Stephan Mielke focused on the progression of CAR T implementation in Sweden. He explained that there are four CAR T-cell treatment centers, only two of which offer CAR T therapy as standard of care (SOC). The centers, Lund, Gothenburg, Stockholm and Uppsala, have formed the basis for Sweden’s CAR T-cell competence network (SWECARNET). SWECARNET stands as a cooperative network between academia, healthcare providers and the industry aiming to deliver education and quality assurance through meetings and lectures. Professor Mielke made it clear that access to CAR T-cell therapy is not equally distributed throughout Europe and hopes that SWECARNET will assist in overcoming the complexities of CAR T-cell implementation.1 We were also pleased to speak to the chair of our Lymphoma Hub, Professor Gilles Salles, who discussed real-world data from the French cohort study previously presented by Catherine Thieblemont at the 24th Congress of the European Hematology Association (EHA).2 The Lymphoma Hub interviewed Professor Thieblemont at EHA 2019 and the video is available here. French cohort study design2 Retrospective data from five centers across France: Lille, Lyon, Montpellier, Nantes and Paris (Saint-Louis), were collected from July 17th – December 31st, 2018 Patients with relapsed or refractory (R/R) diffuse large B cell lymphoma (DLBCL) were treated with axicabtagene ciloleucel (axi-cel) or tisagenlecleucel Objectives: Organization of CAR T-cell implementation in France Measure the outcome of CAR T-cell therapy in the real world Results Characteristics of patients receiving ‘real world’ CAR T therapy and those involved in the clinical trials, ZUMA 1 and JULIET, are compared in Table 1 Table 1. Patient characteristics from real world, ZUMA and JULIET studies Characteristics Real world, LYSA2 ZUMA 13 JULIET4 Median age(range), years 53 (18—77) 58 (23—76) 56 (22—76) Male, % 66 67 61 Histology: DLBCL, PMBCL/TFL, % 43/8/9 76/8/16 79/19/0 ECOG PS 0/1, %ECOG PS 2-4, % 937 42/58 55/45 IPI score 3/4, % 53 46 72 Disease stage III/IV, % 80 85 76 Median prior therapies (range), n 4 (2—8) 3 (1—10) 3 (2—6) Refractory to ≥2 lines of therapy, % 68 (primary refractory) 76 55 Relapse <1-year post-auto-SCT, % 30 21 49 Auto-SCT, autologous stem-cell transplantation; DLBCL, diffuse large B-cell lymphoma; ECOG PS, Eastern Cooperative Oncology Group performance status; IPI, International Prognostic Index; LYSA, The Lymphoma Study Association; PMBCL, primary mediastinal B-cell lymphoma; TFL, transformed follicular lymphoma At a three-month follow-up (n= 53): Progression free survival (PFS) was 53.7% (95% CI, 41.6—69.2) Overall survival (OS) was 82.2% (95% CI, 72.3—93.5) Prognostic factors found to have a significant impact on OS following CAR T infusion were: Number of prior lines of therapy, hazard ratio (HR)= 1.80 (95%CI, 1.26—2.58) p= 0.001 Eastern Cooperative Oncology Group performance status (ECOG PS) at screening, HR= 3.69 (95%CI, 1.51—9.03) p= 0.004 Absence of infection, HR= 0.10 (95%CI, 0.01—0.89) p= 0.039 Professor Salles also presented data from studies reporting CAR T-cell therapy experiences in the UK, Spain and Germany (Tables 2 and 3). Table 2. Reported experience of tisagenlecleucel and axi-cel treatment in the UK   Tisagenlecleucel (n= 24) Axi-cel (n= 56) CR, % 17 24 PR, % 12 16 PD, % 71 59 Death, % 0 4 CR, complete response; PR, partial response; PD, progressive disease Table 3. Reported experience of tisagenlecleucel and axi-cel treatment in Spain and Germany   Spain5 Germany2 Study design 5 centersn= 36 infused Single center; Munichn= 21 infused Median age, years 51 60 Treatment Tisagenlecleucel (n= 36) Tisagenlecleucel (n= 9) or axi-cel (n= 12) CR*, % 26 25 Median PFS, months 3 – Axi-cel, axicabtagene ciloleucel; CR, complete response; PFS, progression free survival*CR is representative of patients receiving CAR T-cell infusion Aside from delivering valuable data from a number of European studies, the key message from Professor Salles was the urgent need for a uniformed system worldwide, particularly between Europe and the US. As shown by the studies presented, CAR T-cell data remain incomplete, with countries using different readout measures for clinical efficacy, prognosis and toxicities. Availability of patient data through collaboration is required to provide a greater picture regarding factors contributing to CAR T-cell therapy outcome. A summary of novel routine guidelines was presented by Ibrahim Yakoub-Agha, Lille University Hospital, Lille, FR, at the 2nd CAR T meeting and was recently covered by the Lymphoma Hub, see more here.  Finally, Professor Marcelo C. Pasquini emphasized the need for an efficient CAR T-cell registry (CT registry) to maximize the utilization and coordination of CAR T-cell therapy worldwide. Not only is the CT registry important in managing regulatory requirements, such as long-term follow-up and post approval safety studies (PASS), but also in developing a uniform grading system for CAR T-cell toxicities like cytokine release syndrome (CRS) and neurological events (NE). It has been extremely difficult to compare safety data across clinical trials due to the variations between toxicity grading systems. Professor Pasquini hopes that the CT registry and implementation of the novel American Society for Blood and Marrow Transplantation (ASTCT) consensus grading system will help to lower the incidences of serious toxicities through correct evaluation and treatment approach.6 The Lymphoma Hub covered toxicity grading systems reported during the 45th Meeting of the European Society for Blood and Marrow Transplantation (EBMT) in Frankfurt, DE, which can be accessed here. Professor Pasquini also highlighted how the rapid increase in CAR T-cell therapy is already impacting worldwide practices. Since 2016, 2058 patients have received CAR T-cell therapy across 123 CAR T centers worldwide, over half of which taking place in 2019. It was made very apparent that the level of hematopoietic cell transplantation (HCT) is declining in line with a rise in CAR T-cell therapy. To date, the primary indication for CAR T therapy in the US, comprising 71% of applications, is non-Hodgkin lymphoma (NHL), followed by acute lymphocytic leukemia (ALL; 22%) and multiple myeloma (MM; 6%).6 Take home message All three contributors highlighted the demand for European and worldwide collaboration to increase the availability, effectiveness and

COVID19

COVID-19: WHY WE SHOULD ALL WEAR MASKS — THERE IS NEW SCIENTIFIC RATIONALE

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The official recommendation in the United States (and other Western countries) that the public should not wear face masks was motivated by the need to save respirator masks for health care workers. There is no scientific support for the statement that masks worn by non-professionals are “not effective”. In contrary, in view of the stated goal to “flatten the curve”, any additional, however partial reduction of transmission would be welcome — even that afforded by the simple surgical masks or home-made (DIY) masks (which would not exacerbate the supply problem). The latest biological findings on SARS-Cov-2 viral entry into human tissue and sneeze/cough-droplet ballistics suggest that the major transmission mechanism is not via the fine aerosols but large droplets, and thus, warrant the wearing of surgical masks by everyone. The surgeon general tweeted: “STOP BUYING MASK, they are not effective…”. The Center for Disease Controls (CDC) states that surgical masks offer far less protection than the N95 respirator masks (which also must be perfectly fitted and only professionals can do it). The CDC recommends that healthy persons should not wear masks at all, only the sick ones. These guidelines are not rooted in scientific rationales but were motivated by the need to save the valuable masks for health professionals in view of a shortage. But they may have had unintended consequences: stigmatizing those that wear masks in the public (you are a hoarder, or you are contagious!) Contrast this with the cultural habit, the encouragement, or even mandate to wear masks in Asian countries — which have now “flattened the curve” or even have had a flatter curve from the beginning. Sure, surgical masks, and improperly worn N95 respirator masks, do not offer perfect protection. But if the stated goal is to “flatten” the curve (as opposed to eradication of the virus), we have to abandon the black-and-white thinking, and embrace shades of grey. We cannot any longer claim that masks “are not effective”. We cannot allow the perfect to be the enemy of the good. What if a however partial protection afforded by leaky surgical or even self-made masks reduces transmission probability to an extent that is similar to that of the recommended (equally imperfect) distancing by more than 6 feet from each other or “not touching your face”? It could then double the impact of non-pharmacological intervention (NPI) on flattening the curve (FIG. 1). Since the CDC provides no scientific evidence for its statement that masks worn by the public “are not effective”, here we review the scientific support for protection conferred by surgical masks. We focus on mechanistic rationale (as opposed to epidemiological-phenomenological evidence). We conclude, by considering cough droplet ballistics and the latest research findings on the biology of transmission of the SARS-CoV2 virus (which causes COVID-19) that any physical barrier, as provided even by make-shift masks, may substantially reduce the spread of COVID 19. If we are soon to yield to the pressure to loosen lockdowns and allow limited social interactions to revive the economy, then public masks should have a role and could facilitate a middle-of-the-road approach. The official recommendation by CDC, FDA and others that masks worn by the non-health-care professionals are ineffective is incorrect at three levels: In the logic, in the mechanics of transmission, and in the biology of viral entry. I. THE LOGIC Of course no mask, be it the tight-fitting NIOSH approved N95 respirator mask or the loosely worn surgical mask, provide perfect (“100%”) protection. But imperfect protection does not mean “completely useless”, much as a glass not full need not be empty: I would gladly accept a glass of water filled to 60 % when I am thirsty. Absence of evidence (of protection) is not evidence of absence. But in our binary world, the official message that surgical masks are “not effective” may have sent the wrong message: that they are absolutely useless. Sadly, with the black-and-white picture painted by officials, the discussion about the effectiveness of masks has been stifled, and with it the possibility of incentivizing industry to ramp up production of these 75 cents-a-piece protective devices. But with the declared goal to “flatten the curve” (and not to totally eliminate the virus) we have a “relative” as opposed to absolute goal, which places the notion of “partial protection” in a new light. In principle, one could compute the extent Y of flattening of the curve given a partial protection by X % as conferred by mask. But for that we need to first understand the mechanics and biology of transmission in detail. II. THE MECHANICS How viruses that cause airborne diseases are carried by droplets from person to person is a complicated, understudied matter. Droplets can (for this discussion) be crudely divided in two large categories based on size (FIG. 2): (a) Droplets below a diameter of 10 um (micrometer), the upper size limit for the definition of ‘aerosol’ (particles so light as to be able to float in the air). For brevity, let us call this category across rooms. What makes N95 facial masks different from the surgical masks is that the former are designed (as per regulatory requirement) to stop aerosols: they have to filter out 95% of droplets smaller than 0.3 um. (b) Droplets larger than 10um (micrometer), reaching 100um or more. Let us call these large particles “spray droplets” here. (For a more detailed discussion, see Nicas and Jones, 2009). Of course, droplets can be even larger, up to a size visible to the naked eye in the spray generated by coughing or sneezing (0.1 um diameter to above). Calculations by Xie et al suggest that if exhaled, the >0.1 um droplets may evaporate or fall to a surface within 2m, depending on size, air humidity and temperature. But coughing or sneezing can shoot them like projectiles out of the mouth with a “muzzle velocity” of 50 meters/second (for sneezing) or 10 m/s (for coughing), and droplets can reach distances as far as 6m away. If so, then the much mentioned “safe distance” of 6 feet in social encounters may not suffice — except you wear a (simple) mask –more on that later. Here is the central

Hočkinov limfom, Hronična limfocitna leukemija, Nehočkinski limfom

Body size and obesity during adulthood, and risk of lympho-haematopoietic cancers: an update of the WCRF-AICR systematic review of published prospective studies

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Overweight and obesity are a global health problem. During the last 40 years, the number of obese adults increased from 100 million in 1975 (69 million women, 31 million men) to 671 million in 2016 (390 million women, 281 million men) [1]. Excess weight and obesity have been linked to several chronic diseases including cardiovascular disease [2, 3], diabetes [3] and many types of cancers including lympho-haematopoietic cancers [4]. The age standardized incidence rates worldwide (per 100 000 inhabitants) were estimated of 1.0 for Hodgkin’s lymphoma (HL), 6.7 for non-Hodgkin’s lymphoma (NHL), 2.1 for multiple myeloma (MM) and 5.7 for leukaemia in 2018 [5]. Although, lympho-haematopoietic cancers are not as frequent as other cancers such as lung, breast, colorectal and prostate cancers, it is very important to investigate their association with overweight and obesity, which are the major public health issues. Consequently findings can add to the existing literature about the importance of lifestyle modification specifically weight management in prevention of haematological cancer incidence and mortality [4]. Previous meta-analyses published up to 2014, showed that greater body mass index (BMI) may increase the risk of HL [6], NHL [6], diffuse large beta-cell lymphoma (DLBCL) [7], myeloma [8] and leukaemia [9]. Since the publication of these metaanalysis, several additional large prospective studies with large number of cases have been published [10–16]. The accumulated evidence has greatly enhanced the investigation of how these modifiable risk factors influence the development of the many different types of lympho-haematopoietic cancers. Moreover, whether BMI in early adulthood (age 18–21 years), height and abdominal obesity increase the risk of lympho-haematopoietic cancers have not been summarized in a meta-analysis. Therefore, we conducted a systematic literature review and meta-analysis of prospective studies of BMI, BMI in early adulthood, height, weight, waist circumference (WC) and waist-to-hip ratio (WHR), and the risk of lymphoma, myeloma and leukaemia, and their main types to provide an up-to-date and comprehensive assessment of the existing evidence. We aimed to clarify the strength and shape of dose–response relationship between the general and abdominal adiposity and lympho-haematopoietic cancers and investigate any potential differences by sub-sites, sex, geographical locations, size of cohort, number of cases, years of follow-up, exposure assessment methods and adjustment for potential confounders. Search strategy and inclusion criteria The CUP team at Imperial College London searched in PubMed for studies on anthropometric measures including BMI, BMI in early adulthood (age 18–21 years), height, weight, WC and WHR, and lympho-haematopoietic cancer risk up to December 2017. The specific search criteria and the review protocol can be seen in supplementary materials, available at Annals of Oncology online. Study selection Our study selection was restricted to cohort (prospective, retrospective, case–cohort or nested case–control studies) studies which investigated the link between anthropometric measures and lympho-haematopoietic cancer risk and mortality, and reported estimates of the relative risk (RR) (e.g. hazard ratio, risk ratio or odds ratio) and 95% confidence intervals (CIs) for the exposures of interest [BMI, BMI in early adulthood (aged 18– 21 years), weight, WC and WHR]. In case of studies reporting only categorical results, number of cases and denominator data (person-years of follow-up or number of subjects) were required for inclusion in the meta-analysis. If there were multiple publications from the same study, the newest publication that included the largest number of cases was selected. Data extraction We extracted the following data from each study: authors, year of publication, country of origin, cancer type, length of study and loss of follow-up, sample size, numbers of cases and population at risk/controls, age, sex and other characteristics, anthropometric measures, RRs and 95% CIs or P-values for each exposure category and adjustment variables. A second reviewer checked at least 10% of the work. Statistical analysis We calculated the summary RRs and 95% CIs using random-effect models that takes into account heterogeneity between studies [17]. Q and I 2 statistics were used to determine heterogeneity [18], potential sources of which were explored in stratified analyses by sex, geographical location, exposure assessment methods, years of follow-up, number of cases, size of cohort and adjustments for confounders including alcohol consumption, smoking and physical activity. We used RR estimates and CIs for continuous increments directly from the articles if provided, and for studies that only reported categorical data, dose–response associations and 95% CIs were derived using generalized least-squares for trend estimation [19], which required the RRs and CIs associated with at least three categories of anthropometric measures, and the number of cases and non-cases or person-years of follow-up per category to be available. If only the total number of cases or person-years was reported in the articles, and the exposure was categorized in quantiles, the distribution of persons or person-years was calculated by dividing the total number of persons or person-years by the number of quantiles. We used the mean or median values per each anthropometric category if available in the articles, or the midpoint was calculated for studies that only reported a range by category. If the range of the highest or lowest category was open-ended, its width was assumed to be the same as the adjacent category. In case of close-ended lowest and highest categories with category widths substantially greater than those of the middle-categories (e.g. highest category of 35–60 kg/m2 of BMI), the Cheˆne and Thompson [20] method was used to estimate the midpoints. The Hamling method was used to recalculate the RR estimates when the first category was not used as reference [19]. If the results were reported for men and women separately, they were combined using a fixed effects meta-analysis before being pooled with other studies in linear, but not non-linear, analyses. We assessed small-study effects, such as publication bias, by using funnel plots and Egger’s test [21]. We assessed a potential nonlinear dose–response association between anthropometric measures and risk of lympho-haematopoietic cancers when we had 3 studies by calculating restricted cubic splines for each study, using three fixed knots at 10th, 50th and 90th percentiles of distribution of the exposure to account for a wider exposure range

Uncategorized

“Impressive” results of a new approach to relapsed or refractory Hodgkin lymphoma

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Phase 2 study finds that a new treatment combination may improve outcomes for people with relapsed or refractory Hodgkin lymphoma. A recent, phase 2 study in China has investigated a new treatment combination for classical Hodgkin lymphoma that has come back (relapsed) or not responded (refractory) after previous treatment. In this study, people with relapsed or refractory classical Hodgkin lymphoma who had had at least two previous treatments were given: camrelizumab on its own or cambrelizumab plus decitabine. Camrelizumab is a ‘checkpoint inhibitor’ that stops lymphoma cells hiding from your immune system. This allows your immune system to recognise and destroy the lymphoma cells. Some checkpoint inhibitors, such as nivolumab and pembrolizumab, are already available to treat certain people with relapsed or refractory Hodgkin lymphoma. Decitabine is a chemotherapy drug that works by turning on genes that stop cancer cells growing and dividing. Scientists think it might also boost your immune system’s response to treatment with checkpoint inhibitors. It is currently used to treat people with acute myeloid leukaemia who are not suitable for standard therapy. In this study, people who were treated with camrelizumab plus decitabine had a much higher response to treatment than people treated with camrelizumab on its own. The response also seemed to last longer in people who received camerlizumab plus decitabine, although longer-term results are needed to confirm this. These results show that drugs that alters gene activation in this way (called ‘epigenetic modulators’) have the potential to boost the anti-lymphoma response to checkpoint inhibitors. This is a promising new approach that could improve outcomes for people with relapsed or refractory Hodgkin lymphoma. The authors concluded that adding decitabine to camrelizumab was safe and had an ‘impressively high complete response rate’. Large-scale trials are planned to investigate the treatment further. To find out more about how clinical trials are used to study new treatments for lymphoma, or to search for a trial that might be suitable for you, visit LIPA clinical trials link.   Source: lymphoma-action.org.uk  

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