ALBERT

Description: Background: MCL is a distinct lymphoma entity with improved outcome achieved by the introduction of rituximab, high dose Ara-C and autologous stem cell transplantation (ASCT) into the first line therapy. The outcome of the relapsed patients (pts) remain however poor and there is little data on the outcome after subsequent relapses and there is no information on secondary MIPI prognostic value. Aim: To analyze the outcome of the MCL patients after first line treatment failure and to evaluate the prognostic role of the sec MIPI which is MIPI calculated at the time of relapse/progression. Methods: This analysis is a part of the Lymphoma project in which consecutive lymphoma patients are registered since the year 1999. Altogether 519 newly diagnosed MCL patients were registered in 5 university centers and 9 regional departments between 1999 and 2011. Patients who were treated with rituximab as part of the first line treatment (n=388) were included into the analysis. The diagnoses were confirmed according to WHO classification in the reference pathology centers. The median follow up is 4.5 years. Results: The whole cohort consists of 261 males and 127 females (2.1:1) with median age 65 y (28-87), the majority of pts had advanced disease (CS IV in 81.6% pts), PS ECOG ≥ 2 in 23.6% pts, elevated LDH in 52.5% of pts. The MIPI risk profile was as follows: low risk 21.7%, intermediate risk 27.2% and high risk in 51.1%. All pts received rituximab as part of the induction, 48.7% pts received CHOP, 5.7% alternation of CHOP and HD Ara-C, 26.2% intensive induction with HD Ara-C, 10.3% CVP, 6.4% FC. High dose therapy with ASCT was performed in 23.9% of pts. The ORR was 89.0% with 63.8 CR/CRu, 6.3% had stable disease and 4.9% were primary progressive. The PFS and OS were 2.9 y and 5.5 y with significant impact of MIPI risk (p

Description: Background: The outcome of DLBCL patients is improving, it however seems to be very poor for those who are refractory to the therapy. We have decided to analyze this group of patients. Methodology: As part of an observational clinical study NiHiL (GovTrial No NCT03199066) we identified the patients treated in the first line by R-CHOP like immunochemotherapy who met at least one criterium: 1. refractory (stable disease - SD or progression) on 1st line therapy (1st l- R), 2. refractory (SD or progression) on salvage (platinum based regimen) (Salv-R), 3. refractory to or relapse/progression within 12 months after ASCT (ASCT-R/R). There were 210 patients diagnosed in the period 2001-2017 who fulfilled the criteria. Progression-free survival (PSF) and overall survival (OS) were estimated from the time of determination of a refractory disease. Results: The cohort consisted of 163 patients primarily resistant to the first-line therapy, 31 patients were resistant to the salvage therapy and 16 patients progressed within 12 months after ASCT . At the time of the diagnosis, the median age was 65 years (22-91) (the same as at the refractory disease), 54% were males, 74% had advanced clinical stage (III+IV), 68% had IPI 〉3, 77% had above-normal LDH, and 45% had a tumor mass 〉10cm. The OS from the time of determination of refractory disease was 0.53 years, median PFS was 0.29 years. Patients under 65 years had median survival 0.8 years compared to 0.4 years in the group of patients above 65 years of age. The median PFS for 1st l-R, Salv-R and ASCT-R/R resp. was 0.3, 0.26 and 0.35 years resp. and 5y survival 22%, 0% and 6% resp. The median OS for 1st l-R, Salv-R and ASCT-R/R resp. was 0.55, 0.39 and 0.65 y resp. and 5y survival was 28%, 0% and 13% resp. Our results demonstrate that resistant DLBCL has an extremely poor prognosis, clearly new effective therapeutic strategies such as CAR-based therapies or others are required. This work was supported by a research program Progres Q28-9. Disclosures Belada: Seattle Genetics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen-Cilag: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead Sciences: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding.

Description: Background: Early events within 24 months (POD24) of initial immunochemotherapy (IC) were repeatedly confirmed to be associated with poor survival in follicular lymphoma (FL). Rituximab maintenance (RM) given to responding patients after IC is effective strategy to reduce relapse incidence and improve survival (Salles, Lancet 2011; Hill, BJH 2019). There is little known about the POD24 incidence pattern in chemosensitive patients, and the impact of subsequent RM application for POD24 reduction has not been studied yet. Aim: To (1) analyze the role of POD24 events in patients with responding FL and (2) describe whether post-induction RM changes the pattern of POD24 incidence and possibly post-POD24 outcome of the patients. Methods: The study comprised patients prospectively enrolled in the Czech Lymphoma Study Group network (ClinicalTrials.gov: NCT03199066) in 2000-2015, with grade 1-3A FL and treated with frontline R-CHOP/R-CHOP-like or R-bendamustine or R-CVP IC. Cases with previous WaW were not enrolled. No frontline stem cell (auto/allo) transplant was allowed. Only patients who achieved complete (CR/CRu) or partial remission (PR) at the end of induction (EOI) and were thus potential candidates for RM were included. Early event was defined as progression, relapse or death within 24 months after the date of EOI response assessment. Overall (OS) and progression-free survival (PFS) were calculated from the date of diagnosis and date of EOI response (OS-EOI). Patients who experienced an event before the median time to RM initiation were excluded from POD24 survival analyses to avoid overestimation of the RM group results. Results: A total of 1089 patients were identified, of whom 729 (67%) received RM (maintenance group) and 360 (33%) were followed without RM (observation group; OBS). When comparing both groups, we found no differences in age (median age 59 yrs for both; P=0.54), sex distribution (males 39% vs. 41% in OBS vs. RM, respectively; P=0.37) and ECOG 0-1 (90% vs. 93% in OBS vs. RM; P=0.10). There was a slightly lower proportion of advanced FL (Ann Arbor III-IV) in OBS (80%) as compared to RM (87%, P=0.01), which translated into a lower proportion of high FLIPI patients (46% vs. 52% in OBS vs. RM, respectively; P=0.003). The induction regimens were as follows: R-CHOP in 70% and 83%, R-COP in 18.6% and 10.7%, R-bendamustine 1% and 4%, R-fludarabine-based in 4% and 1% and others in 5% and 1% in RM and OBS, respectively. The EOI remission status was assessed 61 days (median) after the last IC dose with CR/CRu/PR rates of 65%/9%/26% and 65%/6%/29% in OBS and RM, respectively (P=0.14). The median time from EOI response to the first RM dose was 48 days (range 0-371 days), 89% of the pts have started RM within 120 days. The median number of RM doses given was 8 (range, 1-36), with 85% of patients receiving 8-12 doses of RM. After a median follow-up of 10.4 yrs (OBS) vs. 6.0 yrs (RM); P

Description: INTRODUCTION: Peripheral T-cell lymphoma (PTCL) is a heterogeneous group of aggressive lymphomas with usually poor prognosis. Age was identified as the independent risk factors in many studies. Elderly patients suffer from comorbidities, impaired organ functions, and poor performance status resulting in worse tolerance of therapy and its efficacy. Data on outcome, prognosis and treatment efficacy for elderly patients with PTCLs are sparse. METHODS: We used data of 941 newly diagnosed PTCLs registered into CLSG database between January 1999 and March 2015 with last follow-up in February 2016. CLSG database covers approximately 85% of all newly diagnosed NonHodgkin´s lymphomas (NHLs) in Czech Republic. For the analysis, 208 patients with age 〉70 years at diagnosis were selected. RESULTS: Totally, PTCLs accounted for about 8.7% (454/5210) patients of all NHLs in population younger 60 years, but only about 5.8% (208/3561) NHL patients older 70 years. Median age was 76ys (71-91ys), 94 (45%) were women, lactate dehydrogenase (LDH) was elevated in 130/208 (62.5%) pts., ECOG ≥2 had 80 (38%) pts., and advanced clinical stage III-IV presented 132/208 (63.5%) pts. We identified following PTCL subtypes: PTCL-NOS (Peripheral T-cell lymphoma not otherwise specified) 89/208 (43%), Anaplastic large cell lymphoma (ALCL) 34/208 (16.3%), Cutaneous Anaplastic large cell lymphoma (C-ALCL) 10/208 (4.8%), Mycosis fungoides/ Sézary syndrome (MF/SS) together 29/208 (14%), NK/T nasal lymphoma (NK/T) 2/208 (1%), Angioimmunoblastic lymphoma (AITL) 17/208 (8.1%), Cutaneous CD30+ T lymphoproliferative disease 1/208 (0.5%), T-lymphoblastic lymphoma/leukemia (T-LBL) 3/208 (1.4%), T-cell lymphoma without specification (T-NHL) 17/208 (8.1%). Distribution of PTCL subtypes changed significantly with age. There was higher proportion of PTCL-NOS (43% vs. 34%; p.001) and MF/SS (14% vs. 4.8%; p70ys) compared to younger cohort (≤70ys; n=725). Contrary, percentage of ALCL (16.3% vs. 27%; p70ys vs. ≤70ys) according to PTCL subtype; PTCL-NOS 5 yr-OS 23% vs. 43% (p.00001), ALCL ALK+ 5-yr OS not reached vs. 79% (p.01), ALCL ALK- 5 yr-OS 24% vs. 50% (p.001). Patients with AITL or EATL showed no age-related survival differences. First-line chemotherapy was administered in majority of cases (67%); CHOP-like regimen was given in 78 (37%) pts., COP-like in 44 (21%) pts., and other chemotherapy in 18 (9%) cases. Local therapy (surgery, radiotherapy) was administered in first line in 17 (8%) pts., no or palliative therapy (corticoids) was given in 34 (17%) pts., initial therapy was unknown in 17 (8%) cases. We compared two subgroups of patients according to first line chemotherapy CHOP (n=75) vs. COP (n=41). Median age was 74ys (71-84) vs. 79ys (71-89), high IPI was presented in 29% vs. 50% of patients (p.001). Complete response (CR) was achieved in 35/75 (47%) CHOP treated patients, and in 7/41 (17%) patients managed with COP (p.001). Contrary, there were 12/75 (16%) progression in CHOP arm compared to 10/41 (24%) COP treated pts. Five-year OS was 28% vs. 15% better in CHOP group (p.029) and 5-yr PFS 25% vs. 10%, respectively. CONCLUSIONS: In population-based analysis of adult Caucasian PTCL patients, we identified mild decreasing incidence with age. There were significant age-related distribution differences of PTCL subtypes with shift to preponderance of PTCL-NOS, Mycosis fungoides, and NK/T nasal lymphoma in elderly. Worse survival in elderly PTCLs in comparison to younger patients was evident especially for PTCL-NOS and ALCL subtypes. Despite the baseline differences (COP managed pts. had higher IPI), there is tendency that anthracycline-based chemotherapy (CHOP) brings better results with higher proportion of CR and lower progression/relapse rate projected in longer survival. Disclosures Belada: Seattle Genetics: Research Funding. Mayer:AOP Orphan Pharmaceuticals: Research Funding; Novartis: Research Funding.

Description: Background: Classical Hodgkin lymphoma (cHL) is the most common lymphoid malignancy under the age of 30. Despite the relatively high curability, about 20-30% of patients relapse after front-line therapy. Since the International Prognostic Factors Project score became obsolete in the era of dose-intensive regimens (BEACOPP), a clinically applicable tool for outcome prediction is lacking. Recent years have brought much novel information about close Hodgkin/Reed-Sternberg (HRS) microenvironment cross-talk promoting tumor growth. Many studies have tested the predictive value of microenvironment cells using immunohistochemistry but none have been concerned with HRS cell density. Aim: To assess the prognostic role of HRS cell density in lymph node biopsies using a novel automated system for scanning large tumor sample areas in cHL patients. Methods: Thirty-eight high-quality tissue samples obtained at time of cHL diagnosis were analyzed. The median age at diagnosis was 35 (17.5-93) years; the male-to-female ratio was 0.66:1. The lymphoma subtypes were nodular sclerosis (NS) in 25 (66%) and mixed cellularity (MC) in 13 (34%) patients. At the time of analysis, detailed baseline clinical information was available in 35 (92%) patients. Ann Arbor stages I through IV were observed in 2, 18, 9 and 6 patients, respectively. Systemic symptoms were present in 26 (75%) cases and large lymphoma mass (≥5 cm) was detected in 19 (56%) patients. German Hodgkin Study Group stages were: limited in 4 (12%), intermediate in 8 (23%) and advanced in 23 (66%) patients. Chemotherapy was given to 35 patients (92%): BEACOPP in 20 (57.1%), ABVD in 6 (17.1%), Stanford V in 4 (11.4%) and other (COPP, COPP/ABV) in 5 (14.3%) cases. Involved-field radiotherapy was applied in 11 (29%) cases. Tissue array analyses were performed using the TissueFAXS (TissueGnostics, Austria) system combining detailed morphologic information offered by microscopy with the scientific accuracy of multi-channel flow cytometry. Data were analyzed with TissueQuest software. Paraffin-embedded biopsies were prepared from pre-selected diagnostic samples stained with hematoxylin-eosin for morphology analyses and using CD30 (HRS) for cell density analyses. Each sample was previewed by the scanning software and only significant tumor tissue was manually gated by an experienced pathologist for further analyses. Fibrotic (≥10%), necrotic or residual lymphatic structures were excluded. Results: After treatment, 31 (82%) patients achieved complete remission, three partial remission, one stable disease and three patients progressed. After a median follow-up of 64.3 months, 9 (24%) patients relapsed or progressed and 7 (18%) of them died. Five-year overall survival (5-y OS) reached 81.0% (95%CI 0.68-0.94); 5-year progression survival (PFS) was 68.3% (95%CI 0.53-0.83). Tissue data: The mean scanned area covered 27.2±13.5 mm2 with the mean (median) total number of cells 461,504±286,491 (466,138). The mean (median) total cell density and CD30+ HRS cell density were 17,886±7,884 (16,557) and 279±232 (181) cells per mm2, respectively. Total cell density was 1.28-fold higher (p=0.14) and HRS cell density 1.44-fold (p=0.19) higher in MC compared to NS. HRS cell density did not correlate with sex (p=0.46), systemic symptoms (p=0.38), tumor bulk (p=0.34) or Ann Arbor stage (p=0.59). There was a trend for older age among low HRS cell density (below the median) patients (p=0.19). Low HRS cell density was associated with inferior 5-y PFS (44.4% vs 90.0%, p=0.0024) and OS (57.5% vs 100%, p=0.002). Multivariate Cox regression identified low HRS cell density as an unfavorable prognostic factor for PFS (p=0.037, HR=5.50) independent of age and lymphoma subtype. Conclusions: This is the first evidence about the possible predictive role of HRS cell density in cHL patients. Low density at diagnosis was associated with 5.5-fold higher risk of lymphoma progression or death. Automated image analysis is a new tool overcoming technical limitations caused by small (microarray) samples in lymphomas with high intra-tumor heterogeneity. Further analyses will define the role of HRS cell analysis in cHL in the context of risk-adapted and CD30-targeted therapies. Acknowledgment - Supported by: Palacky University Olomouc (IGA-LF-2015-001), Takeda Restricted Educational Grant and J. W. Fulbright Commission. Figure 1. Figure 1. Disclosures Prochazka: Takeda: Research Funding.

Description: Introduction: Medical care has recently been moving from wards to outpatient clinics due to a growing number of patients, convenient therapeutic approaches and rising emphasis on quality of life. There is an increased need for intensive monitoring of haemato-oncological patients undergoing long-lasting treatment especially when serious infectious complications are expected. Telemedicine is a great tool to keep an eye on patients spending most of their treatment at home, where reaction time plays an important role in reducing the impact of severe adverse events. Methods: We plan on enrolling 100 haemato-oncological patients undergoing treatment who are at high risk of febrile neutropenia and/or sepsis. In the comfort of their homes, selected patients will measure their body temperature, blood pressure and pulse regularly every morning, plus whenever they feel unwell. Contactless measuring is provided by a digital blood pressure monitor and an infrared thermometer. Both devices communicate via bluetooth with a mobile HUB (cell phone), which then encrypts the information and forwards it to the National Monitoring Center. Physicians have real-time access to the measured values through a web portal using any device with an internet connection. Importantly, values registered outside the individually set-up range are immediately sent by SMS to a designated physician, who can then promptly react. Results: In our pilot project, we enrolled 21 patients (33-80 y; median 60 y) including 9 treated for acute leukemia, 5 for multiple myeloma, 4 for chronic lymphocytic leukemia, 1 for myelodysplastic syndrome, 1 for malignant lymphoma and 1 for aplastic anemia. The median duration of monitoring was 6 months (1-16). One thousand, six hundred and twenty-three critical values of systolic (37.9°C) in 6 patients were registered, two cases with concomitant low blood pressure. After a telephone conversation with a physician, ambulatory care was recommended 12 times. Two cases of febrile neutropenia were detected, with the patients instantly hospitalized without progression into sepsis. Four cases of infectious complications (genital herpes, upper respiratory tract infection) with the need for anti-infective therapy and 6 cases of viral infections with only symptomatic treatment indicated were also addressed. Conclusion: Even in a small cohort of patients we demonstrated that the remote monitoring of body temperature, blood pressure and pulse at home enables the early detection of infections and prompt provision of adequate treatment. An evaluation of the financial savings on medical expenses might also be a useful aspect to revise. Disclosures Hajek: Celgene: Honoraria, Other: Consultant or advisory relationship, Research Funding; AbbVie: Other: Consultant or advisory relationship; Bristol-Myers Squibb: Honoraria, Other: Consultant or advisory relationship, Research Funding; Novartis: Other: Consultant or advisory relationship, Research Funding; PharmaMar: Honoraria, Other: Consultant or advisory relationship; Takeda: Honoraria, Other: Consultant or advisory relationship, Research Funding; Janssen: Honoraria, Other: Consultant or advisory relationship, Research Funding; Amgen: Honoraria, Other: Consultant or advisory relationship, Research Funding.

Description: Background: Twenty percent of patients (pts) with high-tumor burden follicular lymphoma (FL) develop progression/relapse of disease within 24 months of frontline immune-chemotherapy (POD24). Those ultra-high-risk cases are at 50% risk of dying within 5-years since the POD event. Unmet need is to identify such pts at the time of initial treatment. The traditional approach used for building predictive scores (such as FLIPI, PRIMA-PI) is multivariable logistic regression (LR). LR is the tool of choice in case of many predictors (continuous or categorical) and a single binary (yes/no) outcome. Bayesian network (BN) offer an alternative strategy which may overcome several drawbacks of LR (risk of overfitting, missing data handling, problems of odds ratio interpretation), brings more insight into the complex relations among the variables, and offer an individualized prediction. Aim: The goal was to build a model to predict the risk of POD24 from the parameters known at diagnosis and compare LR to BN approach. Methods: The study (ClinicalTrials.gov No NCT03199066) comprised 1394 FL (grade I-IIIA) patients from the Czech Lymphoma Study Group registry treated with frontline rituximab-containing regimen and diagnosed between 10. 4. 2000 and 28. 12. 2016. The following parameters were analyzed: gender, age at diagnosis, clinical stage, lymphoma grade, no. of LNs regions, bone marrow involvement, no. of extranodal localizations, longest tumor diameter, systemic symptoms, performance status, LDH, beta-2-microglobulin, hemoglobin, and leucocyte, lymphocyte, and thrombocyte counts, induction regime, radiotherapy, ASCT, maintenance application, response to treatment, and OS, PFS and POD24 as outcome parameters. POD24 was defined as relapse, progression, change of therapy for 24 months since the induction started. Only parameters known at diagnosis were used for the prediction of POD24. Results: The median age was 59 yrs (range 26-89 yrs) with female predominance (59.2%), advanced disease stage (III/IV) was seen in 85.9% of the cases and FLIPI risk groups distribution was as follows: low (18.8%), intermediate (30.9%) and high (50.3%). The most frequent regime used was R-CHOP (76.8%), followed by R-CVP (12.4%), R-bendamustine (4.7%), intensive protocols (3.3), and fludarabine-based (2.8%). Consolidative IF-radiotherapy was applied in 5.1% and up-front ASCT in 2.9% of the pts. Maintenance immunotherapy was given in 67.1% of the pts. Response to therapy was known in all but 28 pts (98%) with CR/CRu 67.9%, PR 26.6%, SD 1.8%, and PD in 3.2% of the cases. After a median follow-up of 7.64 yrs, 484 (34.7%) of the pts progressed or relapsed and 316 (22.6%) have died. POD24 was recorded in 266 (19.0%) of the pts. The 5-year OS reached 86.4% and 5-year PFS 64.2%. LR model (PFS) building strategy included testing for significance as this model performed better than the model with all parameters. Overfitting was prevented by splitting the data into training (75%) and testing (25%) set. The performance of the model was assessed using the AUC criterion computed on the ROC curve. The LR model reached AUC of 0.69, and at 80% specificity, it reached about 51% sensitivity. Next, the BN (Augmented Naïve Bayes Classifier) was trained. Links of all predictors to POD24 were forced and all links to age and gender were forbidden, otherwise the network structure was inferred from the data. The performance of the BN was similar to the LR - AUC of 0.67 and about 50% sensitivity at the specificity of 80%. Both these models were compared to the standard PRIMA-PI risk classifier and were found to better stratify the population into risk groups (Table 1). An example of a patient is presented who was low-risk according to PRIMA-PI but actually experienced the POD24 event. The BN estimated the probability of the event to 91% (Figure 1). Conclusion: Lymphoma-related death following POD24 remains the most frequent cause of mortality in FL patients. BN modelling is a non-inferior prognostic tool compared to LR in term of POD24 prediction. Unlike LR, it also allows visualisation of complex relations among the predictors and individualized prediction of the patient's POD24 risk, even if some of the predictors are unknown. Both "ad hoc" trained LR and BN were found to better stratify the population into risk groups with respect to POD24 event than the traditional PRIMA-PI score. Acknowledgement: MZ Czech Republic DRO grant (FNOL, 00098892). Disclosures Procházka: F. Hoffmann-La Roche AG: Consultancy, Honoraria; Takeda Pharmaceuticals, Inc: Consultancy, Research Funding. Belada:Roche: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel expenses, Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel expenses, Research Funding; Celgene: Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel expenses, Research Funding. Trněný:Janssen: Consultancy, Honoraria, Other: Travel Expenses; Gilead: Consultancy, Honoraria, Other: Travel Expenses; Takeda: Consultancy, Honoraria, Other: Travel Expenses; Bristol-Myers Squibb Company: Consultancy, Honoraria, Other: Travel Expenses; Amgen: Honoraria; Abbvie: Consultancy, Honoraria, Other: Travel Expenses; Roche: Consultancy, Honoraria, Other: Travel Expenses; MorphoSys: Consultancy, Honoraria; Incyte: Consultancy, Honoraria; Celgene: Consultancy.